Development ofa Decision Support
System for Individual Dairy Farms
in Mixed Irrigated Farming Systems
inthe Nile Delta
Ahmed Tabana
Promotor:
Dr. ir.S.Tamminga
Hoogleraar indeVeevoeding,innetbijzonderdevoeding van
herkauwers
Dr. ir.H.van Keulen
Hoogleraar bijdeleerstoelgroep Plantaardige Productiesystemen
Co-promotoren:
Dr. I.Gomaa
Senior research officer,Animal Production Research Institute,
Egypt
20/ 2210
Development of a Decision Support System for
Individual Dairy Farms in Mixed Irrigated Farming
Systems inthe Nile Delta
Ahmed Tabana
Proefschrift
terverkrijging vandegraadvandoctor
opgezagvande rector magnificus
vanWageningen Universiteit
dr. C. M. Karssen
innetopenbaarte verdedigen
opdinsdag 13June2000
des namiddagsomvier uur indeAula
(;YVA
< ^ C ^ 1 \ ^ \
Tabana,A. S.,2000
Development of a Decision Support System for Individual Dairy Farms inMixed
Irrigated Farming Systems inthe NileDelta.
Ph.D.ThesisWageningen University,Wageningen,The Netherlands
- with references
- withsummary in English,DutchandArabic
ISBN
90- 5808- 245- 8
Subject headings:animalproductionsystem inEgypt, implementationof improved
technologies, computerised model, maize silages madeon-farm,
feeding berseemwithmaizesilage,acceptability ofmaizesilageby
farmers
Abstract
The principal animalproduction system inEgypt isthemixedcrop-livestock production
systems with a semi-intensive/semi-commercial orientation. The development
strategies emphasized inthisstudy contributetothedevelopment and implementation
ofimproved technologies.
The role and placeofthe livestock sector anditscontributiontothe national economy,
as well as the development ofexternaltrade inmilkanddairyproducts inthe past10
years were studied. The potential for dairy improvement is discussed and it is
concluded that rapid population growth along withsocialandeconomic changeswill
further increasethedemandforanimalproducts.Thetraditional mixedfarming systems
were studied in detail.As partofthesestudies on-farmandon-stationexperiments on
animal nutrition andfeed utilisationwereconducted.Additionally acomputerised model
of the mixed crop-dairy farming systems was developedto helpdecision-makers at
farm level to obtain an optimal cropping plan and feeding system with maximum
income.
The farm management information system was developed inthecontext ofamixed
farming system in the northern part ofEgypt.An identification anddescription ofthe
management practices of both crop and dairy sub-systems resulted in a better
understanding of the dairy farming systems and established the boundaries ofthe
components that are used as the basefor modellingthewholefarmingsystem.The
constraints of the systems were also identified with special attentionforfeeds and
feeding. Finally, this information was usedtodesignandperform nutritionalstudies,
which alongwithother informationwaswas used todevelop adecision support system
for crop-dairy mixedfarms.
One hundred and fifty five samples ofmaizesilages madeon-farmweretakentobe
nutritionally chracterised through visual inspection aswellasonthe basisofchemical
composition. Good quality silageswereobtained,indicating adequate preservationfor
all silages. The highest qualities correspondedtowhole-plant maize (without removing
ears), ensiled atanaverage ageof 108days,after 17daysoffermentation, and,upto
a45daysoff-takefeeding period (after opening ofthesilo).Variety andtypeofchopper
used in this study, had no significant effectonsilagequality.Thefinalconclusion is
that, smallfarmers easily adoptedsilage-making asanintervention asindicated bythe
quality ofmaizesilage producedon-farm.
The quality of four feedstuffs: berseem (Trifolium alexandrinum), rice straw, a
concentrate mixture andmaizesilagewere investigated intwodirect andthree indirect
metabolism trialswithsheep. Undertheconditions prevailing inEgypt,the fermentation
process of maize silage reached anacceptable range(indicated bythefermentation
products) after 16 days of ensiling. Maize silage had neither negativenor positive
effects whenfedwith berseem. Feeding berseemwith maizesilage increasedtotalDM
intake and improved the energy/protein ratio (64%TDN and 12% CP)whichwould
allowamedium levelofmilkproduction.
Eleven different combinations (scenarios) of the four feedstuffs were designed to
assess the nutritional feasibility of 9 milk production levels.Thescenariosaimedto
satisfy the nutritional constraints and to minimize the feeding costs of the 9 milk
production levels. Sensitivity analyses of the effects of changes inmilkprice,land
rentalandlaborwages onthe marginoverfeeding costswereperformed.
With regardtotheacceptability ofmaizesilagebyfarmers,thestudy demonstrated the
easy introduction ofmaizesilage,thefarmers awareness andthe roleofextension,the
response to other new technologies with maizesilage,thefarmer's pointofview and
finally,theconstraintsofmakingmaizesilage inthestudyarea.
The financial analysis showedthatfeed mixtureswith maizesilagewould reducefeed
costs compared with mixtures without maizesilage.Thisconclusion notonly holdsat
present price levelsfor landrentalandlabor, butalsofor pricesthat aretill 100%above
presentlevels.
Farmers in the project area have quickly recognizedtheadvantage ofadding maize
silage to the dietoftheirdairyanimals.Theirobservations focusonhigher production
levels and lower production costs, which is in line with the step-wise analysis of
nutritional andfinancialaspects bytheresearchers.
Maize silage was well introduced by the extension staff and widely adopted once
farmers hadrecognised itsadvantages.
Keywords: farming systems,dairyfarming,Nile Delta,maizesilage,farmmodelling,
economic andnutritionalevaluation
Contents
1
Introduction,background ofthestudyand researchformulation
2
Animal production systems in Egypt: Their roles, classification, 18
description andpotentialcontributiontodevelopment
3
Development of adecision support systemfor individualdairyfarms in 34
mixed irrigated dairy farming systems: I Qualitative andquantitative
description ofthe mixed crop-dairyfarming systems inlower Egypt
4
Development ofadecisionsupport systemfor individualdairyfarms in
mixed irrigated dairyfarming systems: IIDescription and
implementation ofthe modelformixedcrop-dairyfarming systems in
lower Egypt
5
Factors influencingthefermentation characteristics ofmaizesilage onfarm
94
6
Introducing maizesilage intothe Egyptianfeeding systems: Ensiling
characteristics, digestibility andfeeding value,and interactionwith
berseem-based feeding systems
116
7
Financial,nutritional andacceptability assessment ofmaizesilagefor
smallandmediumscaledairyfarming
132
8
Generaldiscussion
156
9
Summary
162
10
Samenvatting
168
11 . Arabic summary
9
56
172
Acknowledgments
I sincerely wish to express mygratitudeto Professor SeerpTammingaand Professor
Herman van Keulen for their supervision andencouragement duringthiswork. Iam
also indebted to Professor Ismael Gomaa for his support andfortheopportunity to
conducttheexperiments atthedepartment ofBy-products.
I further wish to express my appreciation to Dr. Huug Boerfor hiskind assistance
during mystay inWageningen.
The constructive discussions andhelpfulcommentsformtheforeignstaffofthe Food
Sector Development Programme, especially Mr. Richard Donald, Mr. Gerard Van
Rootselaar, and Mr. Hans Bouman,were highlyappreciated.
Very special thanks to Professor MamdouhSharafel-DeenandMr.J.Taaksfortheir
great support andapprovaltofinancethefirst andsecond partofthisthesis.
I wish to express my sincerethankstothe laboratory staff andthemembers of Dairy
SystemsAnalysis Unit(DSAU).
Acknowledgments are also extended to Mr. Mohamed Ismael for hisassistanceto
maintain andoperatethemonitoring program efficiently.
Wageningen, May2000
N
M0)?^Ol,^l()
Propositions
1 Farmers are generally aiming at maximizing the utilization of their resources by
pursuing a set of multiple objectives, not only including economics but also social,
politicalandecologicalvalues(thisthesis).
2 New technologies can easily be rejectedfor reasons of unknown risks or expected
uneconomic performance or inappropriateness to their resource availability (this
thesis).
3 The adoption of a new technology in ruralareas is a perfect indicator of a relevant
technology design(thisthesis).
4 A decision-making process based on field observations/experiments and farmer
participation often leads to adequate mutual understanding, a prerequisite for the
collection of appropriate data needed to optimize acceptable farm plans (this
thesis).
5 The mentalityofnations isthe keyfordevelopment andcivilization.
6 Farmers allovertheworlddonotdodifferentthings,theydothings differently.
7 The best way to avoid critical conflicts between nations, cultures, civilizations or
religions istorespecteachother'svaluesandtraditions.
8 Democracy and human rights have no meaning with no education or an empty
stomach.
9 Globalization isahiddenaccesstothethirdworld resourcesandmarket.
10 Applying the sustainability concept will lead to a more unequal welfare between
nations.
11 The lifestyle ofa human results from allenvironmental events withwhich heor she
isconfronted sincebirth.
PropositionsassociatedwiththePh.D.ThesisofAhmed Tabana:
DevelopmentofaDecisionSupportSystem forIndividualDairyFarms in
MixedIrrigatedFarmingSystemsintheNileDelta.
Wageningen, May2000
Chapter1
Introduction,BackgroundoftheStudyandResearch
Formulation
-Introductionand Background-
Introduction
Dairy enterprises represent onlyonecomponentofanimalproduction,which isinturn
an integral part ofagriculturalproduction.Thusitcanbebestdevelopedaspartofan
integrated approach tothetotalsector.Animalswillcompetewithotherenterprisesfor
labor and perhaps for land, but it may parallelly benefit from other agricultural
developments (e.g., increased crop production giving rise to additional edible byproducts). Also,itcanoffer additional opportunitiesfor incomegenerationthrough local
processing, which can in turn stimulate further technological development and
employment inthearea.
The principal animalproduction system inEgyptisthemixed crop-livestock production
systems with a semi-intensive/semi-commercial orientation. The development
strategies should emphasize actionsthatsupportdevelopment and implementation of
improved technologies andthe useofmoreproduction inputs.Highpriority needstoto
be given to the development, through farming systems research, design and
implementation ofnewtechnologiestoenhancetheproductivity ofmixed crop-livestock
systems with different cropping patterns and production practices. Improved
technologies may include improved varieties of food and feed crops,forages,and
legumes; improved genetic stocks of indigenous buffaloes, sheep and goats; and
improved cropand livestock management systems. Improvedstrategiesfor technology
transfer andtheestablishment ofmoreeffective extension strategies areneeded.
Development strategies that aim at increasing the productivity ofaspecific system
must carefully consider thestageofdevelopment ofthetarget area/group inrelationto
the nature ofcrop-livestock interactions,availability ofspecifictechnologiesto improve
productivity, availability andcostsofinputs.Thespecifictechnology thatwill eventually
be required to reach the optimum level of resource use still must be developed.
Excellent possibilities exist for increasing production ofmilkthroughexpanded useof
improved technology and inputs. This requires that the traditional mixed farming
systems arestudied indetail,on-farmand/or on-station experiments onanimal nutrition
and feed utilisation are conducted, and models are developed that can help the
different levelsofdecision-makers.
To provide appropriate management decision support tothefarmer,thewholefarm
enterprise should bemodelled.Suchmodelsshould bebasedonanalysis ofthe mixed
farming system, taking into account the interactionsamongthe household,cropand
livestock subsystems. Model development can generally bebasedondata collected
through monitoring programs, observations and discussions with farmers on their
practices. The samples of farmstobeselected shouldcoverarangeof management
practices, thus enabling the use of comparative analysis methods to support the
11
Chapter1
modelling process.
Background of the study
Analysis of large ruminant production in Egypt reveals a general feed shortage
between the summer andwinter cultivation seasons.This isprimarily dueto shortage
of land to provide forage cropsallyear round.Inaddition,management limitationson
most of the small and medium scale mixed crop/livestock farms result in resources
being allocated sub-optimally.
Both, the quantity andquality ofthefeed play animportant role indairy production.In
Egypt this is especially true, as the animals' demand for nutrients ishighandthe
energy content ofthemostcommonly availableforage,clover (Trifolium alexandrinum),
is low. Increasing the quantity ofconcentrates fedatthistime,should result inhigher
availability of energy. Usingtheservices ofafeed millwhich hasfacilitiestoformulate
least cost rations, is a theoretical option. However, giventhe largevariations inthe
quality and availability ofraw materials, production ofconcentratefeedsofaconsistent
and stable nutritional quality isverydifficult.While lowquality roughagefrom cropbyproducts isavailable,the lowdigestibility ofthesematerials limitstheir useasasource
of energy, particularly for milking cows. Theuseofconservedforages does, however,
offer someopportunitiesforovercomingtheproblem.
The most common conservedforage crop usedbysmallfarmers inEgypt isberseem
hay. This isfed mainly during summer. Suppliesare normally inadequatetocoverthe
transition period from summer to winter, when the green feed maize (darawa) is
finished andthe newseason's berseem iseither notavailableorisoflow nutritive value
dueto itsearlystageofgrowth.
Many options have been proposed forsmallfarmerstoovercomethefeedshortage,
including "new" forage crops, chemical treatment of roughages and forage
conservation. These havemetwithvarying degrees ofsuccess. Maizesilage,which
has in recent years beenwidely adopted onlarge-scale dairyfarms inEgypt, hasalso
been promoted with smallfarmers inalimited numberofareas. The potential benefits
as indicated byon-station experiments,andthe initial positive on-farmresponsetothe
technology, suggestthat itcould beadopted morewidely.
Small farms inEgyptarecharacterised byrelatively complex production systems,often
involving cash crops and livestock alongwith considerable homeconsumption. The
introduction of innovations inoneareaofproductionwilltherefore normally havedirect
and indirect implications for other parts of the production system,farm incomeand
householdfood security.
12
-IntroductionandBackground-
The eventual success of"new"technology willbedetermined bythefarmers response
in relation to itsresource requirements, impactonprofitability and risk. This response
is, however, a long-term process, especially asfarmersare not inapositiontojudge
these issues inadvance,particularly intermsoftheproduction responsetonewfeeds
or feed combinations. Therefore, in the early stages ofdevelopment, considerable
benefit may beachieved byundertaking moreanalyses ofthefeed, its interactionwith
other components of the diet and itspotential impactoncropping patterns andfarm
income.
A better understanding ofthe lasttwo mightbeachievedthroughthedevelopment ofa
mathematical model. Initially, this should enable feed mix and cropping pattern
scenarios to be evaluated. Subsequently, withthe availability of improved technical
data on the production response to the feed, and the constraints, either real or
perceived, facedbysmallfarmers inadoptingthetechnology,the modelcouldbeused
as a direct aid toextensionstaffforassisting individualfarmers intheir crop/livestock
management decisions.
This study aimsat investigating variousfeeding strategiestomeetanimal requirements
and to examinetheir impactongrossandnetfarmincome. Itfocusesprimarilyonthe
inclusion of maize silage inthediet. The ultimateobjective is,however,to producea
tool, in the form of acomputer model,that canbeusedfor bothgeneral investigative
work and for specific farmsituations,topredictthe impactofchanges inthe livestock
feeding system onthe profitability ofmixeddairy/crop enterprises inEgypt.
The study can bedivided inthefourfollowing discrete,but inter-related components:
• the first part aims at producing a conceptualframework anddescriptionof DairyCrop Mixed Farming Systems in Egypt;this istobebased ontheanalysis oftime
series data collectedfromsmallandmediumscale mixedfarms overthreeyears;
• the second part involves nutritional studies on the impact ofintroducing various
levelsofmaizesilage intotheexistingfeedingsystem;
• the third part involves developing adescriptive mathematical modelofthefarming
system, based on the survey data and thedatafromthe nutritionalstudies. The
model will also includethefacilitytoassesstheimpact, innutritional andeconomic
terms, of introducing other forage crops and feed resources intothemixeddairy
farmingsystem;
• the fourth part involves refining the modeltoenable itsoperation atfarm level,by
advisory and management staff,asa"decision supporttool".
Thefollowing chart illustratestheoutlineofthestudy.
13
-Chapter 1-
^ ^ ^ ^ J ^ D a t a collection
J
Survey
^^^pMonitoring
Problem
Identification
i
^ ^ ^ ^ J
J
Description of
Farming Systems
''
Model
Development
r
Nutritional Studies
i
r
Extension Tool
Formulation of the research project
The first phase ofthe project isplanning,appraisal,anddesign.Therearethree basic
tasks inthis phase: 1)identification andformulation oftheproject,2)feasibility analysis
and appraisal of the project, and 3) design of the project (Louisand Ralph,1980).
Table 1.1 summarises thethree basictasksofthe proposed research projectthat isthe
subject ofthisthesis.
The first joint task (identification and formulation) involves the actual conception or
identification of the project, entitled "Development of a Decision Support System for
Individual Dairy Farms inMixedIrrigatedFarmingSystemsinEgypt".Formulationofthe
project involvesdevelopinganobjectivestatement inbroadterms"Promoteefficientdairy
farming", which expresses the objectives and also providesanestimateofthevarious
resources required to achieve the projectobjectives, i.e."farmingsystemresearchand
technology"throughresults/outputs.
The second task (feasibility and appraisal) was approached systematically by
identifying the professionalresearchteam,the limitsimposedbydecision makers,and
preliminary estimates ofthe resources required andtime.
The lasttask identifiestheactivitiesto becarriedout inoperationalform.Also,detailed
specifications oftheactivities aregiven.
14
-Introduction and Background-
o
o°
CO
b
. £ CL
(O to O =
<
r
h-
0.
3
CO
CO
d>
T3
CD
"O
CD > , . ! = C
e co
Li.
10
0)
CD - S i ,
^
2" | >
O O
"d<
181S •8 5
<
2><
oa
a.
a
co
UJ
Q S u-
<£
OLU
UJ >"
_
w
•IS
So
Ez
£-
a.
(0
CD
o
a.
a>
O
L_
ro
o
CD
0.
o
CO
"d
CD
£
CD
CD
"d
C
CD
i_
o
r
rCD
• a
CD
CD
SI
•2
1°
CD
.c
£-C
_ c>
CI)
CO
to
i
£0Q . CD|2
C CO
• ^ Q)
01
£°
O a)
co c
co
CO
if!
3 «>
Q . "-
q> o
t v Q-
3 2
• .Q
I CO
>.
>.
>,
"CI
Si
JZ
01
3
O ) CD
CO d)
O d)
q
a:
a co
o
CD
•c
> Q.
UJ 3
>
-I E
F CD
F b
a.
ro
o
co
_i O H UJ
UJ a.
(0
CD
T3
CO
CD
o o
co
m iC_D
o
c
k_
c
x:
p
o
E
a>
CO
a)
c
o CD
o • r4 ^
<D
i—
<
a>
CO
CO
W
4—
E
o
o
0
n
.2
2
•*-' s ;
-1
(0
£ °-o
_ro
a>
a.
"CI
C
o
01 01
c ai
"0
LL.
ai
CD
<D _
a>
c
3
-5
o
CD
CO
E
oo
oeg
s
a>
U- w g .£ ro
CD =H
Q..Q
Q->
"O
fc.2
a5c
;" .Q co p c
.2 3
>
CO
LL
2
<u
"d
O
-*—»
eg
CO
Is
^8
c £>
I — CD
CD
>>
i £1
— CO
co
CO
s
o
(D O
E
<
£°
c °>
c5 §
o
a.
<
CD
'* 2
ui
CD CD
CO
UJ
c
Q.
«J CD
DC
CO CO
3
si
a.
s
?2
CO
DC
O
I-
<
o
co
CD
to
CD
o:
Q
co S i ;
><^;
to u i
c 0.
co <
<
o»
SI
o
« o
o "55
_l
_l
DC
a.
<
3
<
<
<
SUJ
s ->m,„ UJ
>
a:
=>
fp.
woyj
o
C
^ i= 3
£> CD Q.
CD CD ^
CD C
CD CD
CO
Q.
it >
aj CD
U
If
nils
O
^
E
5
^ • 5
CD
<" £ ^>J
D> O - ^
•S= CO C
E CD ^ :
t to o
m p CD
15
CO
*•
O CD ro
•^
C
CD
•i °
a. co
ro "
E
a.
o
CD
>
•
CD T3
Q . CD ~
I
CO
ro>2S
C CN
to
JL t o
E
2 Sc
o t 3 ro
.><
CDC
E £ ®
§ | |
Q'ro £
i " a ro
roE
N
" E
CO
E
E
CO
3
CO • o
a>
o'co
CD
O CD
Q . CO
to
to
CD CD • £ • £
ro
co
c co
.2 co
£e So -^=§
"d
>>3? a)
CD to 0)
s E "S
a j to
T 3 CD
ro Q ;
CD t=
O) O
ro o
E co
3
Q.
j = CD
ls
< o o
o
2
S.5
o l E
5
5°
CO
5-o
SSI
c
*-> •*-»
to
CD
b c B |
Q-
«LU
T3
CD £ <£L
CO
3
Q.
T3
O "O CD
° S;
i
to
S ro o
>< 2
E"°
95^
coS^
III
Q. c
O CD
o -a
CD *£
O 2 a)
UJ £
1.
CD • = :
«s
LU Q .
a.
Q
CO
£••§
C
o
o
>>
^ t.£
. £ CD
co co
C
3
E a>
E-°
E co
c >
CO CO CD
i-
O ) CD
C <-
.£ «
3 CD
"O LL
o o
_. < "
0),0
£ ro
.2 ^
o ^
CD
co .*:
z
<
S
CO g s
o >
^ O
JBOCN
§ , C 0 CD
» C8 "c
CO LL
DC
I-
O
C CD
fc
•D
C
CD ••-»
><
(D
1°
co c
Q.Xco 33
?s
CO CD
CD —
=
o
CD "O
Q. C
CO CD
X
Si
O
:<e E
a.
o
O CD
i CO
16
- Develop adecision
- Identify problems and
constraints ofsmall and
medium scalemixed
farming.
- Qualitativeand
quantitative description
ofthe mixedcrop-dairy
farmingsystem.
individual dairyfarms
was developed,taking
into consideration the
intervention.
-Technical adoption of
the proposed
interventionwas
measured andthe
influencingfactorswere
identified.
- Detailed information
on maize silage and
interactions under local
conditions is provided.
- Nutritional feasibility,
economicprofitability
and farmer acceptability
ofthe intervention are
provided.
ACTIVITIES
- Studythe roleand
potential contribution of
mixed dairy farmingto
the agricultural sector.
SPECIFICATIONS
- Emphasis on aspects related tothe
development oflivestock sector, classification
and briefdescription ofthe animal production
systems in different agro-ecological conditions
involving differentsocio-economicgroups.
- Identification and description ofthe
management practices ofsmall and medium
scale farm households; establish hypothetical
boundaries ofthetwo inter-linkedsubsystems
(Crop-Dairy).
- Focus on management limitations that result in
sub-optimal resource uses, availability of
improved technology, outline procedureto
optimizefarm resource use and evaluating the
inclusion ofmaize silage as intervention.
- Maximizefarm profitabilityfrom both crop and
- Article on the implication ofmaize silage on
farm resources and farmers response
-Article on evaluation ofmaize silage isdrafted
and revised by March 2000
-Articles summarizing the on-station trials are
drafted and revised bythe end ofMarch 2000.
2000
Local official
statistics are
accessible.
Local funds are
available for
fieldwork and
monitoring.
Fund, vehicle,
official
authorization
and approvals
are provided to
interview
farmers in
different
districts.
Officefacilities
-Chapter1-
SZ
o
L_
CO
CD
IO
t_
fl)
o
E
o
i_
-Q
T3
<D
T3
Q.
>.
'>
O
•C iO CD
Q.T3
</>
a.
CD CO
-Introduction and Background-
•=> p 73
Q. co CD
F
S
o *:
73
10 o
o o >
co O
r
(l)
0)
ifc u
"D 01
ni
r <1>
>D
co C
tl)
S8
O 73
>».£ £
1^1
c
o
E D) <u
0)-^ ,g
CO
75 E
!=
Q.S
nj .2;
1 J!
E ro
O i=
* - CO
o *co -p
CD
CO
SStS E S
76 <» 5
E §>•
o.
o>
c
°£?
l!2is rss
2
(0
3
•:= en
<o c
- I E
•2J5 js
E £<73
to-gTo
> > _ o>
E CO
•C = • - c
O 73 - D C
(0 7 3 'J=
3 CD C
<3" != co
3e5
O m
o
co ,E E co
CD
> , CD
cr 1
D ) CO
7 3 CD
- N
TO £ .
7 3 « CD
C CD N
O CO - g
, o -5
CD
c
o
a> c c 73
N CD
3
c
o
>
'£
CO
X
CD
-
IT C
CD O
Hie
o o>
o c
~r co o-
73
CO
CD
CD
E >•
E D)
J2 3.
. o
co c•»-• r
8£
CD
E
O
CD
TO _^
3
C
73
CD
° > i TO
CO
CD
>
CO CO
Sis
iS
2, 75 io
O)
JS CO
CD
CD
TO-2
c
o
a
SI
1«
co ^
T
.O co 15
.si?
TO
O- > CD .22
g-73.^ »
C
73 J>
CD co u co
073
o . co
c
«tr co CO S>
o -c o .2
CO
" - r- 75 j f i S
0
— j 2 .c
I S "o
•2-D
Q. C
Q. O
73
O c re
o
co 2 CD
E
Q.
73 E
10
—
7:
0) —
£ ^
75 ~~
co . Q
55 o £
™ 7 = ' CD c
E CD £ c
E E <u . 2 | E
is CD 3
=>, m
C
O>'(0
ra
CD
a> = 7 3
e E o)
<u
2
_CD
"O
CD
—
Q-<
t3> CD
o o
o
•sa "to
| ! co
nj
OS
£
< " j° o
CO
-I
F
u 1—
r m
73
CD
73 _
w
£<*
£
q>? £
CD CO
(0
76 To .2 £
E |
78 5
S g
CD ">
c o
c
7 3
TO=
Q-.O
CD ra "- ~
D ) 2 CD 7 3
TO £ "2 S
to . £
3
o
•c
i; °u
3 CD
C
_
CO •&"
CO =
=! O
-Q =
CO c
CD 5
a.l>
CD C
U CD
<s
co .E
17
Chapter2
Animal ProductionSystems inEgypt:Their roles,classification,
description andpotentialcontributiontodevelopment
A.Tabana1,H.van Keulen2,S.Tamminga3andI.Gomaa1
1
AnimalProduction Research Institute. P.O. Box443,Dokki,Giza, Egypt
Agrosystems Department, Plant Research International,Wageningen-UR, P.O. Box
16, NL6700AAWageningen,The Netherlands
department ofAnimal Science,Wageningen Institute ofAnimalSciences,
Wageningen-UR, P.O. Box338,NL6700AHWageningen,The Netherlands
The Netherlands
2
(Submittedfor publication)
-Chapter2-
AnimalProductionSystems inEgypt:Their roles,classification,
descriptionandpotentialcontributiontodevelopment
Summary
This paper focuses on aspects related to thedevelopmentofthelivestocksectorin
Egypt, with emphasis on animal production systems. Based on studies of official
statistics, published articles, observations and experiences, theauthorswereableto
classify and describe the animal production systems in different agro-ecological
conditions involving different socio-economic groups. Two inter-linked criteria were
used to classify the animal production systems: a) degreeofcapitalintensification,
(intensive, semi-intensive orextensive); b)theeconomicobjectiveoftheholders. This
may be either of a subsistence, semi-subsistence, semi-commercial or entirely
commercialnature.
This paper demonstrates the role and place of the livestock sector andits
contribution to the national economy, aswellasthedevelopmentofexternaltradein
milk and dairy products in the past 10years.Thepotentialfordairyimprovementis
discussed and it is concluded that rapid population growth along with social and
economicchangeswillincrease thedemandforanimalproducts.
The vision recognises that as intensification evolves, the predominantly
traditional systems will change into systems that are more heavily dependent on
external inputsandimprovedtechnology. Thispaperisstronglyrecommendingthatthe
traditional mixedfarmingsystemswhich representover70% ofthelivestocksectorare
studied in detail, toenabledevelopingfarmmodelsthatcanhelpthe decision-makers
atfarmleveltomaintainhighproductivity.
Introduction
Historically, Egypt isknownasoneoftheoldest agricultural civilisations. Duringthe last
200 years, the economy has diversified andthe importance ofother, non-agricultural
sectors, increased. However, agriculture remains animportant sector ofthe Egyptian
economy, employing4.7 millionworkers,withanannualgrowth rateofabout 0.8%and
generating 20% of its GNP (Gross National Product).Theannualgrowth rateforthe
Gross Domestic Production (GDP) is 3.7% in year 1997/98. The country is selfsufficient in fruits andvegetables,butproduces only 30%ofitsrequirements inwheat
and 66%inmaize. Production increase,throughthecombined effect ofarea expansion
and yield increase,cannot keep upwithpopulationgrowth,sothat Egyptwill continue
20
-AnimalProductionSystemsinEgypt-
to depend on imports for a considerable proportion of itsfood supplies. Consumer
prices for bread are subsidised, but for meat, milk, vegetables and other food
commodities,they aredetermined inthefreemarket.
The totalcultivated areaduring 1997/1998was7.9 millionfeddans (6.3 irrigated
and around 1.5 rain-fed;afeddan is4200m2)includingthe newly reclaimed land,while
the harvested area was 14.2 million feddans. The agricultural sector is aimingat
increasing output by 4.1%per year. The government began to implement many
agricultural national projects in the field ofland reclamation andcultivationaimingat
increasing the cultivable area during the next twentyfiveyears bynearly 3.4 million
feddans ofwhich2.3 millionfeddans inthesouthernvalley and northSinai.
Average farm size isvery small,twotothreefeddan,but,under irrigation,each
year at least two crops, a winter crop andasummercrop,canbeharvested.Inthe
basin ofthe Nile Riverand itsdelta,aboutsevenmillionfeddanoflandareavailablefor
irrigated agriculture. Inaddition,around 1.5 millionfeddanofformer desert land hasin
recentdecades been brought underirrigation.
Although inthewinterseasonalargeproportionofthe landiscultivatedwiththe
forage cropberseem (Trifolium alexandrinum), ineconomicterms,animalproduction is
less important than arable farming.This ismainlyduetothegenerally mediumto low
level of production ( average estimated milkproductionper lactation in 1998 ranged
from 1946 to 2540 litres;forcross breed,1511to2190for buffaloes and950to 1228
for local breed)ofthe 3millioncattleand3millionbuffaloes heldonsmallfarms.Thus
far, agricultural extension anddevelopment havemainlyfocused oncerealsandcash
crops, leaving the cattle andbuffalowithoutmajortechnological innovations. Modern
dairy farming exists, but comprises only about 100,000 dairycows.As aresult,the
country istoasubstantialextentdependent onimportsforthesupply ofmeatandmilk.
The aim of this review is to describe the existing animalproductionsystems,their
relative importanceandthe potentialfordairy development.
The place of livestock
Agriculture is the dominant sector in the economy, where today 53percent ofthe
population lives in ruralareas.Outputoflivestock commodities meat,milk,eggs,wool
andskinsaccountedfor25percentofagriculturaldomesticproduction.
Livestock population development over the period 1976-1997 isindicated inTable1.
Cattle and buffaloes comprise over 70% ofthetotalpopulation,expressed inanimal
units (AU). The buffaloes (35.5%), and 26.4% of the cattle are considered dairy
animals, making the dairy sector themainanimalproduction activity.Thesizeofthe
population, the area for forage cultivation, and the availability of new technology
suggeststhatthere shouldbeanenormous potentialfor development.
21
Charter2
Table 1.Development of livestock* population (,000) inEgyptduring 1976-1997.
Buffaloes
Year
Cattle
Sheep
Goats
Camels Non-ruminants
2,226
1,878
1,349
1976
2,079
101
1,528
2,542
2,554
1,440
93
1978
2,587
1,685
2,009
2,488
1980
2,423
2,409
126
1,719
2,531
2,479
2,387
1984
2,782
146
2,239
2,864
1989
2,722
3,481
2,000
n.ab.
n.ab.
1991
2,719
3,165
3,148
2,442
147
1,587
1995
2,996
3,018
4,220
3,131
131
1,354
3,187
1997
3,118
3,096
4,260
136
1,475
a
3,095
852
478
284
AU**
3,117
885
35.5
9.8
5.5
AU%
35.8
3.3
10.1
Source: Central Department ofAgricultural Statistics, Ministry ofAgriculture and Land
Reclamation,Cairo,bi-annual seriesvolumesfrom 1976to 1997.
* Excluding poultry
** Animal Unit (AU) calculated as 1, 1.2, 0.2, 0.15, 1 and0.6forcattle,buffaloes,
sheep,goat, camelsand non-ruminant animals, respectively.
a
referringto 1997, b notavailable
Historically, the mostsignificant roleoflivestock hasbeen insupport ofarablefarming,
in both physical and socio-economic aspects.Animalmanureplayed acrucial rolein
soil fertility management, by restoring part of the nutrients that crops removed.
Additional nitrogen was supplied through fixation by the berseem. Untilonlyafew
decades ago, animals provided almostalldraft power. Throughtheir roleasacapital
asset (Bosman etal., 1997;Slingerlandetal., 1998),livestock significantly contributed
to the economic stability of farm enterprises, serving as 'living banks', providing
financial reserves for periods ofeconomic stressandabuffer againstsometimesnonremunerative crop prices. Animals thus provide a flexible source ofcash, enabling
farmers to purchase inputsandmeetother urgent needs. Furthermore,they providea
means toprofitably usefarmlabourduring periodswhen itisnot neededfor cultivating
or harvesting crops (Savadogo,2000).
External trade in milk and dairy products
Currently, as over the last 10years (Table2),Egypt importsdairy productstoavalue
of about 500,000,000 E annually (1 E = 0.34 US$), representing 43%ofitstotal
requirements (1996), mainly intheformofmilk powder (variousfat percentages), butter
oil and varioustypes ofcheese. Importstothatextent, may beexpectedto leadto low
domestic prices and disincentives to localproduction,especially whenexport ofdairy
products isstimulated bysubsidiesfromtheexporting countries (deJong,1996).
22
-AnimalProductionSystemsin Egypt-
Table 2.Value (000, E)aofexternaltrade inmilkanddairy products*
Exports
Year
Imports
Export:import ratio
5,968
1990
551,649
0.01
1991
405,739
16,248
0.04
1992
524,948
15,230
0.03
15,684
1993
503,239
0.03
1994
509,404
19,898
0.04
573,767
9,144
1995
0.02
659,821
14,711
1996
0.02
15,053
1997
505,560
0.03
505,569
12,116
1998
0.02
Source: Central Agency for Public Mobilisation and Statistics (CAPMAS) database,
September 1999
a
1 E = 0.341 U$
*CIF(cost, insurance andfreight)for imports, FOB(freeonboard)forexport.
Classification of animal production systems
Figure 1. Schematic representation of the classification of animal production
systems
AnimalProductionSystem
_L
Extensive
Semi-intensive
Intensive
i
Pastoralism
Agro-pastoral
MixedFarming
Systems
Perennialcrop/
livestock systems
Modern Farming
Prei-urban
productionsystem
Peri-urban
subsistence
production
23
-Chapter 2-
Classification criteria
From the many classifications ofanimalproductionsystems proposed,inthispapera
slightly modified version of the system described by Jahnke (1982) hasbeen used
(Figure 1, Table 3).Thisclassification system meetstwo requirements:a)thedegreeof
intensification in terms of capital investment (intensive,semi-intensive orextensive),
and b) the economic objective of the cattle owner (subsistence,semi-subsistence,
semi-commercial orentirely commercial).
Table3.Numberofanimalsandanimalunits(,000)intheclassifiedsystems
Baladi
Pure
Cross
Buffaloes
Goats
Sheep
Camels
Donkeys
Animal Units
Number
%
Pastoral
3
—
4
3
495
758
72
24
315
3
Agro-pastoral
60
—
31
20
83
63
967
16
134
1
Mixed
1603
—
533
2141
1526
2424
212
1036
Integrated
550
—
148
782
981
902
24
339
Peri-urban
78
—
8
149
103
113
7
62
Modern
—
100
—
—
—
—
—
—
8637
76
1925
17
265
2
120
1
The boundary betweenasemi-subsistence andsemi-commercial system issetto50%
sale of total production. The classification remains rather arbitrary though, as no
accurate statistical data are availableonsalesofEgyptianfarmers. Most commercial
producers specialise, focusing on cattle, while subsistence, semi-subsistence and
semi-commercial producers may utiliseseveraltypes ofdomestic livestock, depending
upon their economic-cultural system and environmental conditions. The dominant
animals in the pastoral system are sheep and goats, while camel isthedominant
animal intheagro-pastoral system.Intermsofanimalunits,76%ofthetotal population
is included inmixedfarming systems,followed byintegratedfarming (17%).The other
systems playonlyaminorrole.
Extensive systems
Subsistence
The primary purpose of subsistence-oriented production is to meetfamilyneeds.lt
involves little or nocommercial exchanges.
24
-AnimalProductionSystemsinEgypt-
Pastoralism
Pastoralism isofmarginal importance in Egypt,comprising about3%ofthetotalanimal
population. Pastoralists are concentrated in the northern part of Egypt (near the
Egyptian-Libyan border) and in the Sinai Peninsula, though small numbers of
pastoralist families arescatteredthroughout thedrierareas. Pastoralists keepcamels,
donkeys, sheep and goats. Their breeds can survive under arid and semi-arid
conditions, produce some milk, even if poorlyfed, andareveryfertile (reproductive)
under improved feeding conditions. In fact, most of the pastoral breeds aremore
suitableformeatproduction.
Most pastoral animals graze ingroups,belongingtoone holderoronefamily, moving
quickly over the pastures. They often browse during thedryseasonandgraze low
quality herbagewhenavailable.They maywalk considerable distancesduringtheday,
usually drinking only onceand,ifwater isscarcethey may notbeallowedtodrinkfor2
to 3 days. At night, the animals are kept in camps asonegroup orsub-divided in
severalgroupseach providedwith itsownenclosure.
The grazing land isacommunal resourcewhile livestock areowned individually orby
family units. Usually, water resources are also communally owned,though inafew
areas they belong to individuals or families. The numberoflivestock owned bythe
family istherefore notregulated bythecarrying capacity ofthegrazing land, but bythe
managerialskillsofthefamily unit.
Social and economic traditions that encourage andassistfamiliesto maximise herd
size have been retained, despiteoverstocking,notonlytoensureadequatefoodand
income butalsofamily survival intimesofdisaster.
Agro-pastoral systems
Agro-pastoralists are sedentary farmers that cultivatefood crops (mainly barley) both
for subsistence and for sale. These systemstypically occurwhere extensive rainfed
cropping is possible, i.e. in Egypt in some locations alongthe Mediterranean coast.
This system prefers indigenous cattle thatarealready utilized by pastoralists intheir
regions. At present, their cattlearetriple-purpose animals (meat, milk,andwork).The
owners herd their animals, camels, indigenous cattle breeds, sheep andgoats,on
communal land near their permanent cropping areas,onthefallowduringthewinter
season and throughouttheareaduringthesummerseasonafterthecrops havebeen
harvested. Indeed,inthese placessomefarmers keeppermanent plots under irrigation
(usingfossilwater resources) to beusedforcrop productionandtograze livestock.
25
-Chapter2-
The major technical objectives of this management aretomaintain andifpossibleto
reduce annual fluctuations in cattlenumbers andseasonalfluctuations inliveweight,
maximize reproductive performance and minimize mortality. All these managerial
practices tend to intensify production as a result ofincreases inherdsizeandthus
increased stocking rates.
Men usually herd mature cattle, while women and/or childrentendcalves andsick
animals.
Peri-urban subsistence production
Many urban families keep a few chickens, and/or two to three sheeporgoatsfor
occasional home consumption. Little or no investmentsaremadeintheirfeedingor
health care. The animals scavenge for a large part of their requiredfeed, butare
supplemented with available household and kitchenwaste.Performance istherefore
poor andmortality high.
Subsistence production isseasonal: dependent onvariations inthe household budget,
occasions inthe religious calendar andmore irregularly,eventstocelebrate,suchasa
wedding.
Semi-intensive systems
The main characteristic of these semi-intensive systems is the useof'intermediate
levels'ofexternal inputsalongwiththefollowingfeatures:
• Holdings of relatively smallsize.
• A mixture of subsistence, semi-subsistence and cash economies, though pure
subsistence economies havealmostdisappeared.
• Milk production as the main objective for livestock keeping,thoughalso draught
power continuesto play arole.
• Meatfromsheepandgoats playsaminor rolecomparedtocattle.
• Beef isonlya'by-product' originatingfromoldandculledmilkcows.
• Emphasis is on the use of agricultural and industrial by-products asfeed rather,
thanongrazing.
Mixed farming
The mixed crop-livestock system is the most important cattle production system,
representing over 70% of all cattlein 1997,togetherwith largenumbersof buffaloes
andsomesheepandgoats.
It is the predominant system inthe Nilebasin.Arablefarming,ofbothfoodand cash
crops is themainagricultural activity. Farmsize isusually small (1-5feddan)with high
26
-AnimalProductionSystemsinEgypt-
cropping intensity. Livestock servearablefarmingthrough utilisation ofcrop residues,
partly for the recycling of nutrients to maintain soil fertility andproviding additional
income intheformofmilk and/or meat (Savadogo,2000).Withinthissystem,buffaloes
are keptformilk production andcattlearebredfordouble purpose,togain bodyweight
and produce milk during their lifetime, being slaughtered when too old. In some
situations, cows are expected to provide draught power, if mechanisation is not
available.
The dominant animals arebuffaloes, baladicattleandcrossbreed cattlethatare locally
available. In areas such as Damietta (northern district of El-Delta), where milk
production is promoted by governmental and/orforeign aidprojects,andAl (artificial
insemination) orgenetically improvedbullswere usedforalmost 20years, crossbreeds
are primarily used inadditiontothebuffaloes. However, attempts arealso being made
by governmental and/or non-governmental organisation to establish purebreedand
high-grade herdsofEuropean breedsthrough importsandAl programs.
The majority of the farmers milk theircattletwiceaday- inthemorning (calves are
allowed to suckle before milking) beforethey leave homewherethey are keptat night,
and in the evening upon return from the shades where they are tethered during
daytime. These shades often are located attheedges ofcropfields,ifcutandcarry
systems are applied, restricted grazing systemscanalso befoundwhenshortageof
labourexists.
Feed quality strongly varies with season,withthe bestfeedavailable inwinter (fresh
berseem). In summer, onthecontrary,animals aremainlydependent on straw-based
rations, supplemented with small quantities of grown forage, mainly in theformof
densely sown maize, usedforfreshfeeding atanageof2months (calleddarawa).The
management of feed supply isfully adaptedtothis 'regular' pattern infeed availability.
The animals respond to the variation infeed supply byadjusting milk production and
fertility.
Results of surveys have indicatedthat about63percent ofthecalving occurred during
the colder season (El-Sheikh, 1987;Tabana, 1998).Mostageeretal. (1981) carriedout
a study on twogroups ofapproximately 200femaleseach,located inthesameestate
farm, fedberseem inwinter anddarawa insummer.Average milkyieldwas higher and
the lactation period longer in females calving duringthecolder seasonthan inthose
calving in the hotseason:1309versus 1147kgand233versus 200days.This agrees
with the findings reported by Tabana in 1998(withsignificantly higher levelsofmilk
production) onthe basisofanon-farmmonitoring programoveraperiod of4years.
The variation in feed availability between seasonswasmorepronounced inthe past
than at present. In particular before construction oftheAswan High Dam,seasonal
flooding of the Nile occurred.The localbreedsappeartobeusedtothesevariations,
and tolerate seasonaldeficiencies innutrition.However, longcalving intervals, delivery
preferably in winter and relatively low milk production was a normal performance
27
-Chapter2-
pattern. This inherited pattern of poor reproductive and productive performance
continues to limit productivity on traditional farmer holdings. As aresult,especially
among the smallholders, in winter seasons theremaybeasurplusofmilktosaleor
home processing, while in the summer a precarious balance hastobeestablished
between thecalves' intakeandtheoff-takeforhumans.
The major problem to achievesignificant development inthedairysector isthe small
size ofthe holdings,that isthe resultofthe inheritancesystem,alongwiththe pressure
of population on limited landresources.Thus,intensification ofagriculture suchasthe
production of fruit and vegetables iswidely practisedto increase cash incomeforthe
smallfarmer.
Similarly, milk production could be a very suitable activitytogenerate regular cash
income for small farmers, if collection, processing anddistribution could beproperly
organised. Before modern dairying techniques can be applied, systems of semiintensive and intensive herd management need to be adopted for regular, nonseasonal production. Anoptimumfeeding regimeofconcentrate rations and cultivated
green fodder is necessary throughout the year, and proper housingwouldalsobe
beneficial. Specialmanagerialarrangementswillhavetobemadetomeetthetechnical
demands ofintensive buffalofarming.
For meat production, three types offattening activities are practised,separately orin
sequence:
a) From birthtoweaning.Thistypeofvealproduction startswithaspecial calf-rearing
program. Initial birthweights arearound35-38 kgfor buffaloes and25-28 kgfor baladi
cattle. Farmers are aiming to reach 100-120 kg within a periodof90to 100days.
Calves are fed initially about 50%ofthe milk producedbytheir mothers,i.e.twoteats
until 45days,thenthreeteats untilthe75thday,followed bythefull uddertilltheendof
the fattening period. In addition,highquality concentrates (mainlywheat bran,cotton
seed cake andground maize) areusedtofeedthecalves atadaily rateof2%oftheir
body weight. Greenforage andgoodquality hayarefed invery restricted quantities,if
usedatall.
b) From weaning age to eight months.Thisstartsfromweaned calves,ina rangeof
100-120 kg body weight to reach 250-260 kg within 6 months post-weaning.The
feeding systems strongly vary among areas, depending on thetype ofconcentrate
feedstuff available and season. Berseem (clover) is the mainfodder offered during
winter and darawa (growing maize) insummer. Insomeareas,where maizesilage is
promoted such as Shanshor, Monofie governorate, maize silage along with home
manufactured or purchased concentrates are commonly used for growinganimals,
either with berseem in winter orbetweenthesummer andwinter seasons,whenever
greenforages are notavailable.
28
-AnimalProductionSystemsinEgypt-
c) From eight totwelve months.Thisstageoffattening isoriented by marketdemand.
When price of meat is high due tospecialoccasions suchasAed El-Adha,farmers
tend to increase the use ofgoodqualityconcentratestomaximisethegrowth rateof
the animals and decrease the use of greenforages.Theopposite occurswhenthe
demand for meat is low, farmers tend toincreasethefattening period by using less
concentrate andmoreforages.Thefinalweight isnormally over400kg.
Perennial crop-livestock integrated systems
An example of this system is the sugar cane-livestock system,prevalent inseveral
districts in Upper Egypt. Sugar cane provides three feed by-products: greentops,
molasses and bagasse, that are all threecommonly used inEgypt. Sugarcanetops
are used as fresh forage, and still rarely, assilage. Molasses aresupplemented by
urea as source of non-protein nitrogen (NPN), minerals and vitamins and are
distributed to farmers atsomelocations,but unfortunately notyet inthecane growing
areas. Themolasses mixture isalso usedtofeedfattening beefcattle. Bagasse isused
toa limitedextent asasourceofroughage infeedlots andother rations.
Intensive systems
Intensive dairy farming
Farmers practisingthis system use large proportions oralltheir landtocultivate fodder
crops for their dairy cattle and,inadditionthey usuallyfeed purchased concentrates.
They mayalso usepartoftheir landforfoodorcashcrops.Manure is usedfor growing
fodder and other crops;milk isamajorsourceoffarmincome. Intensive dairyfarming
is practised mainly bysmallfarmerswho usefamily labour, butit isalso undertakenby
largefarmerswhoemploy hired labour.
Peri-urban milk production
Peri-urban milk production has developed around citiesandtowns,inresponsetoa
high demandfor milk.Themainfeedsareagro-industrial by-products that are available
in the cities (e.g., brewery waste, oilseedcakes) andcultivatedfodder cropsorcrop
residues. Although dairy production cansometimes competewithvegetable production
for land, it can alsosupporttheproduction ofhorticultural cropsby providing manure.
Milk is often traded directly orthrough middlementotheconsumers inthecity andis
the major source of income forthefarmers. Family members are required mainlyfor
feedcollection and/ortofeedtheanimals.
29
-Chapter2-
Modern Production Systems
There are two major activitiesofthemodernsectorofcattleproduction,dairyfarming
(dairying) and intensive beef production. These systems adopted concepts and
management proceduresfromthewesternfarmmanagement styles.
Potential for dairying improvement
Mclntire et al. (1992) reported thataspopulation pressurescauseanimal production
systems tobecome more intensive,mixed crop-livestock becomes amoreefficient and
sustainable means of increasing off-take from a fixed land area than specialised
systems of crop and livestock production. These investigators foundthat under low
population densities and low disease stress,specialised herdingand crop cultivation
systems are moreefficient than integratedsystems.
The potential for improvement dependstoalargeextent ontheproductionsystem.In
the pastoralist and agro-pastoralist systems, productivity islowand highlyseasonal,
because of the rainfallpatternandtheassociatedfluctuations infeedavailability. Very
little external inputsareusedandlittleornocontrolexists overthefeed resourcesand
consequently few opportunities forcommercialisation.Collection ofmilkfor processing
is difficult due to the mobility of the producers in the pastoralist systemand/orthe
limited surpluses available after family subsistence requirements havebeenmet,in
additiontotheseasonalavailability ofmilk inbothsystems.
Inthe mixedfarming systems,feedavailability could beimprovedthroughfeedstorage,
crop residues andfodder cropcultivation.Thatwouldprovideopportunities to diversify
operations, tospread risksandgenerate aregular income. Production andsaleofmilk
may bestimulated bytheestablishment ofacollection/processing infrastructure andby
payment ofgood pricesfor milk.
Conclusion
The rapidly growing human population ofEgypt isdriving majordemographic, social
and economic changes thatwill leadtotransformation ofagriculturesystems. Inorder
to satisfy thegrowing demandforagricultural products,agriculturalsystemswillhaveto
be intensified. Thevision recognisesthat asintensification evolves,the predominantly
traditional systems will change into systems that are more heavily dependent on
external inputs and improved technology.Thespecifictechnology thatwill eventually
be required to reach the optimum levelofresource usestill mustbedeveloped.Itis
clear that livestock have an essential role to play in theagriculture ofthefuture in
Egypt.
30
-Animal Production Systems inEgypt-
There are excellent possibilities for increasing production offood and animals with the
most promising being (1) expansion of crop-livestock farming, (2) increased productivity
through expanded use oftechnology and inputs. This requires that the traditional mixed
farming systems be studied in detail and if possible simulated/modelled. If these
models are developed,they may help the decision-makers at farm level.
Bibliography
Abdel Hakim, T., and Abou-Mandour, M., 1993. The agricultural sector and its
prospects for the year 2000: Egypt. Montpellier Mediterranean Agronomic
Institute, France.
Abou Akkada, A.R., and A. M. Nour, 1999. Byproduct utilization in Egypt: A proposed
strategy for the development of animal feed resources. Department of Animal
Production. Faculty of Agriculture,Alexandria University, Egypt.
Abou-Mandour, M., 1992. The Egyptian agricultural labor force and itsfuture. Paper
presented at the Congress on "Agricultural Policies in Egypt". Co-organized
by FAO and the Ministry ofAgriculture (in Arabic).
American Embassy, 1992.Agricultural situation report. Annual Report EG2.14. Cairo.
Bosman, H.G., H.A.J. Moll & H.M.J. Udo, 1997. Measuring and interpreting the benefits
of goat keeping intropical farm systems. Agric. Syst. 53: 349-372.
Directorate General for international Co-operation (DGIS), Environmental Aspects of
Egypt-Netherlands Development Co-operation; mission report, November
1989.
Directorate-General for International Co-operation of the Netherlands Ministry of
Foreign Affairs: Policy plan for 1992-1995: Nile and Red Sea Region. The
Hague, 1992.
El-Sheikh, A.S. 1987. The reproductive performance of the buffalo in Egypt. Indian J.
Dairy Sci.,20: 89-95.
Institute for Resource Development and National Population Council of Egypt, 1995;
Egypt Demographic and Health Survey
Jahnke, H.E., 1982. Livestock production systems and livestock development in
tropical Africa. Kiel, Germany: Kieler Wissenschaftsverlag Vauk.
Jong, R. de, 1996. Dairy stock development and milk production with smallholders. Ph.
D. Thesis, Wageningen Agricultural University. 308 pp.
Ministry of Agriculture and Land Reclamation, 1997. Bulletin ofAgricultural Economic,
Cairo (in Arabic).
Ministry of Economic Affairs and Foreign Trade, 1998. Memorandum on imports and
exports in the next five years; Cairo (in Arabic).
Mostageer, A., Morsy, M.A. & Sadek, R.R. 1981.The production characteristics of a
herd of Egyptian buffaloes. Z. Tierziichtung & Zuchtungsbiol., 98: 220-236.
31
-Chspter2-
National BankofEgypt, 1997.Economic bulletin (inArabic).
Savadogo, M., 2000. Crop residuemanagement inrelationtosustainable land use.A
casestudy inBurkina Faso.Ph.D.Thesis,Wageningen University. 159pp.
Shafie, M.M., 1999. Environmental effects on water buffalo production.The author's
address is: Animal Production Department, Faculty of Agriculture, Cairo
University, Egypt.
Slingerland, M., T. van Rheenen &J.W. Nibbering, 1998.Animal production and rural
financing. The case of Zoundweogo Province, Burkina Faso.Quart.J.Int.
Agric. 37:180-200.
Smith, O.B. 1993.Feed resourcesfor intensive smallholder systems inthetropics:the
role of crop residues. In: Proceedings oftheXVII International Grassland
Congress. Palmerston North,NewZealand.February 8 - 2 1 ,1993.pp. 1969
-1976.
Tabana, A.S., 1998.Production andproductivity offiftyfarms(smalland mediumscale)
in lower Egypt. Technical report of the Dairy SystemAnalysis Unit, Food
Sector Development Program,Ministry ofAgriculture and LandReclamation,
Egypt.
Webster, C.C.&Wilson, P.N. 1980.Agriculture inthetropics,p. 390-400. London,UK,
Longman. (ELBS,2nded.)
World Bank, 1990;World Development Report(Poverty).
World Bank, February 1990; Arab Republic of Egypt, Land Reclamation Sub-sector
Review.
32
Chapter3
Development of a Decision Support System for Individual Dairy
Farms in Mixed Irrigated Farming Systems: I. Qualitative and
Quantitative Description oftheMixedCrop-Dairy FarmingSystems
inLowerEgypt
A. Tabana1, H.van Keulen2,S.Tamminga3and I. Gomaa1
1
Animal Production Research Institute. P.O. Box443, Dokki, Giza, Egypt
Agrosystems Department, Plant Research International,Wageningen-UR, P.O. Box
16, NL6700AAWageningen,The Netherlands
department ofAnimalScience,Wageningen Institute ofAnimalSciences,
Wageningen-UR, P.O. Box338,NL6700AHWageningen,The Netherlands
The Netherlands
2
(Submittedfor publication)
-Chspter3-
Development of a Decision Support System for Individual Dairy Farms in
Mixed Irrigated Farming Systems: I. Qualitative and Quantitative
Description of Mixed Crop-Dairy Farming Systems in Lower Egypt
Summary
This paper demonstrates a farm managementinformation systeminthecontextofa
mixed farmingsysteminthenorthernpartofEgypt.The managementissue considered
is divided into two inter-linked enterprises(Crop-Dairy). Itisbasedontheanalysisof
time series datacollectedfromsmallandmedium scalemixedfarmsoverthreeyears.
An identification and description of the management practices ofeachsub-system
resulted better understanding of the dairy farming systems and established the
boundaries of the components that are used as the base for modellingthewhole
farming system. The constraints of the systems were also identified with special
attention for feeds and feeding.Finally, theauthorsusedthisinformationtoconstruct
nutritional studies along with other information published in a scientific article to
developadecisionsupportsystemforcrop-dairymixedfarms.
Introduction
In Egypt, agriculture is concentrated inthe Nilevalleyanddelta.Theclimate andthe
availability of irrigation water permit cropping year-round. As illustrated in an
abundance of preserved picturesandsculpturesfromthe Pharaonicera(ondisplay in
the CairoAgricultural Museumand inthe Egyptian Museum), inthe Nilebasinamixed
farming system developed several millennia ago,withclover being used inwinter asa
forage crop. This mixedsystem hassurvived untiltoday. While inrecentdecadesthe
importance of animal draught power has sharply declined, dairy farming andmeat
production remain important activitiesformanyfarmers.
Crop-livestock farming systems are major components of agricultural production
systems (FAO, 1982). Dairyfarming isan important activityfor manyfarmers inEgypt,
where mixed crop-livestock farming is practicedtraditionally. Quantitative shortages,
and poor quality of feeds and fodder, as well as imbalanced diets affect the
performance of dairy animals through both under- andoverfeeding.These practices
have a negative effect on the economics ofmilkproduction,ashasthe competition
from annual staples and cash crops.Dairyfarming isabusinessandtheobjective is
maximising overall profit, ratherthanthefeedingofcowsto realisesome nationalyield
(Mainland, 1994). Decision-making aimingat profit maximisation inanenvironmentthat
involves multi purposes of the family and the farm is difficult. Computerized farm
records have failed to meet the needs of the 'average'farmerfor decision-making
support (Hardaker &Anderson, 1981).Thisproblemmustberesolved,sofarmers can
36
-Quantitativeandqualitativedescriptionofthedairyfarming-
respond to the increasing pressures tosubstitute inputsintheagriculture production
process (Sonka, 1985). To provide appropriate managementdecisionsupporttothe
farmer, the whole farm enterprise should bemodelled (Sitaramswamy &Jain, 1993).
Such models should be based onanalysis ofthemixeddairyfarmingsystem,taking
intoaccountthe interactions between household,cropandlivestock subsystems.
The objective of this paper is to identify and describe the management practices
applied ineachsubsystem,togainabetter understanding ofthedairyfarming systems
and to establish the boundariesofthecomponents asabasisfor modellingthewhole
farmingsystem.
Methodology
The information was obtained from datacollected insixareas (districts/sub-districts)
located in northern Egypt (1Menoufeia/Ashmoun,2 Dakahlia/Senbellewien, 3 Kafrel
Sheikh/Qallin, 4 Gharbia/Quttur, 5Alexandria/Nubaria,6 Damietta/Faraskor),asshown
in Figure 1.
Figurel. MapofEgyptwiththe location ofstudyareas.
32*NU
28° N-
LIBYA
24* NTropicof |
Cancer
37
-Chaster3-
A Rapid Rural Appraisal (RRA) technique was used intheselected sixstudyareas.
Seventy-two farmers were selected to identify the maincharacteristics oftheir dairy
farming system. Out of these, 36farmswereselected,usingspecialcriteriafordairy
farming e.g. 1) cultivated area; 2) number of adultdairycows;3)amountofmilksold
(Table 1). Basicdatacoveringthreeyears(1995-1997)werecollectedthroughindividual
monthly meetingswithfarmers.Sixfieldresearchofficers,andtwelveextensionists,under
the supervision of the Dairy Systems Analysis Unit (DSAU) of the Food Sector
Development Programme (FSDP) of the Animal Production Research Institute(APRI),
were involved in data collection. Frequent interviews with farmers, using a
questionnaire, were also carried out to collect additional quantitative data and
information related tocropand livestock production.Thesetofdatathatwas collected
tomeettheobjectives ofthestudyconsists of:
- Animaldata (herd:birth,mortality, sale;breeding:natural,Al;Animal production:milk,
meat).
- Cropdata (sowing and harvestingdates,yields,croparea,typeofforages: conserved
ortreated).
- Economic data (forage and feed purchases, milk marketed excluding home
consumption/processed milk,prices).
- Time allocationforthevariousfarmactivities.Samplesoffeedstuffsweretaken and
analyzed.
Table 1. Numberoffarmersandcriteriaused.
Item
Numberofselectedfarmersperarea
Criteria:
-Croparea (feddan*)
- Numberofadultanimals
-Quantityofmilksold(L/d)
*One hectareequals 2.4feddan
Smallscale
4
Mediumscale
8
<2
2-4
5-20
2-10
4-15
>20
Cropping subsystems
Egypt is known as one of the oldestagriculturalcivilisations (CIHEAM,1992).Total
land area is around 1 millionkm2,butonly2.61million haor2.6%ofthetotalareais
cultivable (FAO, 1992). Agriculture has beentransformedthroughthe introduction of
modern farming equipment andmanagement techniques. Multi-cropping systems are
common inallareasandfodder cropsandhorticulturalcropsare inter-cropped insome
38
—Quantitative andqualitative description ofthedairyfarming-
areas. Almost all the cultivated land uses surface irrigation systems. An exception is
the small horticultural area located in the newly reclaimed land (desert), where drip
irrigation systems are used. Because ofwater availability year-round andthe length of
the crop cycle, significant variations exist in sowing and harvesting dates within
geographical areas.
The main agricultural commodities typically belongto one ofthefollowing groups:
1) Annual staples:wheat, broad bean,maize,and rice
2) Fodder crops: berseem (Trifolium alexandhnum), darawa (vegetative maize), and
multi-cut summer forages, such as millet
3) Vegetables: tomato, potato/sweet potato, onions, andwatermelon or cucumber.
4) Cash crops: cotton,sugar cane, sugar beet
The common cropping patterns for the farmers were [fodder -food crop] inwinter and
[food crop/cash crop - fodder] in summer. Figure 2 represents the common cropping
calendars.
Figure 2. Cropping calendars ofthe main agricultural commodities.
Jul
Aug Sep Oct
Nov Dec Jan Feb Mar Apr
May
Jun
Berseem
Wheat
B. Bean
Maize
Cotton
Darawa
Rice
Berseem t*
Vegetables
* Berseem Tahreesh is mainly cultivated for short periods (1 or 2 cuts) before cotton for
soil fertility purposes.
The number of cultivated plots varied from farm to farm and was influenced by total
farm size, land ownership /inheritance system, policy, or household needs.
In the family-owned and -operated enterprises, with various levels of capital
investment, few alternative exist, under current infrastructure, water availability, soil
fertility and market conditions. The current crop rotations typically are: berseemrice/berseem-cotton/berseem-maize/wheat or broad bean-rice. Darawa or vegetables
can be cultivated instead of any other crop when the temperatures are suitable for
sowing and growth. The general quantitative pattern of crop area and rotation of the
monitored farms in each of the districts are shown in Figure 3.
39
-Chspter 3-
CD
c
CD
N
CD
2
<i>
CQ
o
O
3
2
2
c
5>
w
s
CD
C<u
O
c
o
O
is
(II
c
o
•o
o o
o
CO
CD
CQ
•a
g
(0
Q CD
13
CD
i
"5
o
53 cc
5 Q
w
ra
ie
f
10
t
S2
w
a
>.
a>
0)
£10
Q.
O)
c
CQ
* i _
TO
_Q
3
'a.
^ro
i
o
u
a>
_>
"•P
TO
Q.
X
0
<
re
*•<
o
TO
0)
'E
TO
a
'•&
c
re
3
a
CO
o
^
3
D)
O
CO
(uepp&f) eajv
40
-Quantitativeandqualitativedescriptionofthedairyfarming-
Livestock subsystems
Baladi (traditional cattle breed), Friesiancross Baladiand Buffaloes arethedominant
large ruminants inthestudyareas.Buffaloes arepreferredasmilkinganimalsfor home
consumption and tosupplythelocalmarketwith liquid milk.Crossbreedcattleaswell
as pure Friesians are preferred as milking animalsoncommercially orientedfarms.
Baladi cattle have been intensively usedfordraft purposes,butat presenttheir main
use is for meat production. Natural mating is predominant and hand milking is
performedtwicedaily, ifcalvesarenot present.
Small farmers and landless rural people mainly keep sheepandgoats.Oneortwo
productive female animals areusuallykeptforreproduction.Foryoung males,ashort
period of fattening is practised before slaughtering. This fattening isundertaken at
opportune periods, depending onthehousehold budgetsituation andonoccasions in
the religious calendar andmoreirregularly, oncelebrations ofamongothersweddings
or births. For instance, twoorthree months beforeAidelAdha (sacrificialfestival),at
which meat istraditionally eaten, somefamilies buylambsorsheepforfattening.
The herd structures found among the dairy farmers inthestudyareasareshownin
Table2.
Table 2. Average herd size and structure fordifferent geographical areasand
farmsizes2.
S.
M.
Men.
Sim.
Quail. Qut. Nub.
Lactating animals
Buffaloes
1.48
3.24
3.20
4.97
1.64
1.09
4.69
0.73
1.62
0.97
3.97
Cattle
4.48
3.76
3.65
2.21
4.82
5.94
Total Lactating
7.72
5.40
5.06
8.34
Young animals
Heifers
0.20
0.81
0.33
1.33
0.50
0.00
1.00
Fattening f.
0.17
1.42
0.50
1.00
0.00
0.00
0.67
Growing female
0.15
0.48
0.35
0.3
0.40
0.54
0.31
Growing male
0.15
0.53
0.65
0.46
0.33
0.19
0.43
Suckling calves
0.57
1.91
3.72
1.74
1.84
1.74
2.26
Totalyoung
1.24
5.15
5.55
3.83
3.40
3.43
4.38
Other animals
1.00
1.45
1.04
Donkeys
1.38
1.55
1.01
0.94
Sheep/goats
0.78
0.85
3.94
0.04
0.21
0.43
0.29
TotalAll 1
3.86
12.32 10.32 10.02
8.21
7.95 12.45
1
1AU= Cowproducing9litersofmilk/dwith500kgbodyweight.Buffalo=1.2AU,Heifer=0.8
All, Growinganimals= 0.6AU,Donkeysandcalvesupto7months= 0.4AU,sheepand goats
=0.2AU
2
S= smallfarms,M=mediumfarms,Sim=Senbellewienarea,Qut.=Qutturarea,Qall= Qallin
area,Nub=Nubariaarea,Men=Menoufeiaareaand Dam=Damiettaarea
41
Dam.
0.95
6.72
7.67
0.67
1.50
0.43
0.43
0.70
3.73
1.54
0.04
10.89
-Chapter3-
Thedatashowthat lactating animals represent morethan50%ofthetotalherdfor both
small and medium farmers.Also inallstudyareas,allfarmerstendtobreedtheirown
young stock as replacements orforfattening. Buffaloes arethedominantanimals inthe
areas located closeto urbancentres (e.g.Menoufeia,seefigure 1),where milktendsto
be sold asfresh milk (with7%fat).Milk ismainly usedforcheese making,andfor sale
asfresh milkthrough informalmarketingchannels.
With respectto herdsizeandstructure inthecourseoftheyear, itshould benotedthat
large modifications inthestructuredidtakeplace,with limitedchanges inthesize inall
areas. This implies that the drivingforceforchanges inherdsize isthe availability or
lack offeed resources alongwithother, lessimportantfactors,suchasanimal housing
facilities. Figures4 and5present herdsize bymonthandyear, respectively (expressed
in AU). The animal unit used,isbasedonstandard requirements of DryMatter(DM),
Total Digestible Nutrients (TDN)andCrude Protein (CP)ofacowproducing 9litersof
milk/day andalivebodyweight of500kg.
Ingeneral,animalsarekepteitherasmilkinganimals,whentheyareoldwhicharesold
for meat or as saving banks,soldwhenalargeamount ofcashisneeded..Foroldor
growing animals, sales are made mainly during the transitional period (between
summer and winter season), while productive adult animals aresoldwhentheyare
pregnant orwith calvesatfoot.
Examining herd dynamics over the three years (Fig.5), shows that on small-scale
farms, herd size graduallytendstodecreaseoverthestudy period.Formediumscale
farms, no clear trendemergesyet;moretime isneededtoestablishanytrendinherd
size, if present.
Figure4.Annual herdsizedynamicsforsmallandmediumfarms,averaged
overyearsandgeographicalareas.
14'
AU
124
10'
86-
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month(average 1995 - 1997)
Medium
Small
42
-Quantitativeandqualitativedescriptionofthedairyfarming-
Figure 5. Herdsize byyearoverthreeyearsforsmalland mediumfarms,
averaged overgeographicalareas.
AU
• Medium
• Small
Milk production
Estimates of milk production are based on monitoring at the sampled farms.This
included direct observations of the cows and discussions with each farmer onits
production, incombinationwith adapted recordingsofanimal performance.The sample
farms were selected insuchawayastocoverarangeofmanagement practices,thus
enabling the use of comparative analysis, as a basis for the modelling of milk
production. Table 3 represents average milk production per lactation and numberof
animals that completed lactation onthestudyfarms inthe period 1995to 1997inthe
six areas understudy.
Table.3Average milkproduction(M,inkg)perlactationandsamplesize(N),per
breedandstudyregion.
Breed
Region
Ashmoun
Senbellewien
Qallin
Quttur
Nubaria
Faraskor
Balad
M
1228
950
1050
980
1180
1060
N
15
1
6
4
3
1
Buffalo
M
N
2190
24
1865
48
1789
12
1511
7
1801
53
7
2109
43
Cross
M
N
2200 12
2120
7
1946 25
2356 42
2357 38
2540 45
-Chspter3-
The complete lactation period (over 75% of the animals haveamilkingperiodof10
months) has beenworkedoutforthethreeyearsofmonitoring. Relativelyfew animals
were monitored during a complete lactation period,becausesomeofthese animals
were sold or exchangedfor others.Moreover, milk recordingwasstartedwith animals
in different stagesoflactation. However,thedatacollectedfromthevariousfarms have
been sorted by month of lactation, and average milk production per month was
calculated. The overall averages obtained for such animals were then ordered
according to the month in the lactation period, to generate lactation curves. The
recorded data usedtoderivetotalmilk production per lactation andtomodelthe shape
of the lactation curveareshown inFig6.Thedatashow relatively lowmilk production
for Baladi, compared with the pure dairybreedssuchasFriesians.Therewereonly
smalldifferences inmilk production amongareas.
Figure6.Averagedaily milkproductionatdifferent lactation monthsofBuffaloes (B)
andcross (C)breeds inthestudyareas (1to6asinFigure 1).
B1
12
10 - L ^ - ^ ^ 8
Liter/day
.:
-._
4
2
0
4
5
6
Monthof lactation
10
B2
B3
B4
B5
B6
C1
C2
C3
C4
C5
C6
The predicted shapeofthe lactation curves (Figure7) hasbeenderived using animals
from different target (study) areas. Ittheoretically considers milkyieldunderfarmer
conditions as consequence modified by the effects ofseason (Coulonetal., 1995),
stage of pregnancy (Sharma et al., 1990), breed, parity number(Lescourretetal.,
1994), and the dryperiod.Thetheoreticalshapeofthelactationcurveisdescribedby
an equation that contains allabovefactors. Inpractice,thecurvecouldadequately be
described byapolynomial,based onlactationmonth:
Y Buffaloes= - 0.0088X4 +0.2007X3 - 1.64X2 +4.9917X +2.8097,
(R2 = 0.9841)
Ycattle =-0.0033X 4 +0.0823X 3 -0.7918X 2 +2.745X +6.1017, (R2 = 0.9843)
With,Y=milkyield(litres)andX=lactationmonth.
44
-Quantitative andqualitative description ofthe dairyfarming-
Figure 7. Averaged and derived lactation for buffaloes and cross breeds
1(U
987
6
5
4
3
2
1
0
I
2
3
4
5
6
7
Lactation month
8
10
11
Average observed milk productionfor buffaloes
Average observed milk productionfor cross breed cattle
Derived lactation curvefor cross breed cattle
Derived lactation curvesfor buffaloes
Fertility and animal health
All owners took advantage of the free vaccinations through national programs to control
epidemic diseases, except for some normal pathological diseases and internal
parasites. Artificial insemination (Al) is not widely implemented. However, special
holders keep bulls for natural insemination and charge 7-10 LE per insemination.
Age at first calving tended to be higher, and average calving interval longer (Table 4)
for buffaloes than for Baladi or crossbreeds, because their pregnancies are longer (310
days); silent heat occurs more often, calf rearing is poor, especially when milk prices
are high and finally the heifer may be kept under poor feeding conditions.
Table 4. Age at first calving, average calving interval and conception rate for
different breeds.
Breed
Baladi
Buffalo
Cross
Age atfirst calving
(months)
36.00
38.52
33.57
Calving interval
(days)
376
437
408
45
Conceptionrate
(serviceper insemination)
0.77
0.50
0.61
-Chapter3-
Timing of calving
It wasthoughtthatfarmerswouldtendtodelayinseminatinganimalstohavecalveswhen
good quality forages are available during thewinterseason.DatainTable5showthat
farmers are not planning calving in aparticularseason. Specialattentionwasgivento
this pointtocheckthevalidityofthisstatementmadeduringinterviewing bymanyfarmers
indifferentareas.
Table5.Calvingdistributionthroughouttheyear.
Winter season
Summer season
%
Y\M
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
1995
1996
1997
8
8
12
16
23
6
23
8
4
21
24
8
15
15
8
18
7
4
8
6
11
14
14
9
18
15
8
15
6
4
14
7
6
11
6
15
60.2 39.8
65.5 34.5
50.5 49.5
Tot.
36
45
35
53
38
29
25
36
41
25
27
32
58.7 41.3
W
S
Feeding systems
Five feeding periods/seasons have been distinguished (Figure 8)onthebasisofthe
composition ofthe rationandtypeoffeedstuffsfedtothe animals. Berseem isthe main
greenfodder and isavailable duringthewinter andspringseasons (5to7months).
Figure8.Commonfeedingcalendarforsmallandmediumfarmers.
Season
Months
Summer
Jul
Berseem
Darawa • • •
Hay
^ H
Aug Sep
Winter
Autumn
Oct
Nov
Dec
Jan Feb
Mar
Spring
Feeding
Apr May Jun months
^^^^^^^^^^^^^^^^^^^^^™
^ ^ • • • H
• •
H M
5.7
2-3
1-2
Straws M I ^ B H ^ ^ M i ^ i ^ B B M M H I • • • • • • • • • ^ ^ M 12
Cone1. • • • • • iHiMmM• • • • • • • • • • • • • • • • • • • ! m^m >3
Maize Silage
^^^m^m^mm
1
Concentratefeed mixture
• • • • • • •
Darawa isthemainfoddercrop inthesummerseasonandisavailablefor2-3months.In
the autumnandthetransitionalseasons,animalsrelyonberseemhay,conservedduring
late winter and/or spring. Straws include those of wheat, rice andbroadbeanare
offered twice daily (morning and night)year-round,andmixed,whenavailable,withfirst
46
2-5
-Quantitativeandqualitativedescriptionofthedairyfarming-
and/or second cut berseem at the time of feeding. In addition, smallquantities of
grains, cotton seed cakes (by-product ofcottonoilextraction) andwheat/rice branare
also fed (somefarmers alsobuycomplete concentratefeedwhich isavailablefromthe
market). Concentrates are mainly offered when green forages are notavailableor
during the summer season,toalleviatetheproteindeficiency inthe ration.Ingeneral,
concentrates areonlyfedtocowsproducingabove5litersofmilk perday.
Meat production
Farmers arepracticing meatproduction asaformof intensive useof inputs, implyinga
high investment rate per animalunit,suchasusing largeamountsofconcentrates to
realise highgrowth ratesovershorttimeintervals,combined with highanimaldensities
per unitarea.Threegrowthstages maybedistinguished inwhichfeeding practicesare
adapted to match the daily gains aimed for, and that are practiced separately or
sequentially:
Stage 1 (from birthtoweaning).Thistypeofveal production startswithaspecialcalfrearing program. The initialbirthweight isaround 35-38 kgfor buffaloes and25-28kg
for Baladi cattle. Farmers aim to reach 100-120 kgwithin aperiodof90to 100days.
Calves get initiallytwoteats until45days (50%ofthemilk produced bytheir mothers),
then three teatsfrom45to75days,followed bythefull uddertotheendofthisperiod.
High qualityconcentrates (mainlywheat bran,cottonseed cakeandground maize) are
used to feed thecalvesatadaily rateof2%oftheir bodyweight (around 1.5kginthe
morning and 1.5 kg in the evening) at theendofthefattening period.Ifusedatall,
greenforageandstrawsaresupplied inveryrestrictedquantities.
Stage 2 (fromweaningtoeightmonths).Atthisstage,farmers useweaned calves,on
average starting at 100-120kgbodyweighttoreach250-260 kgoveraperiodof6to8
months. The feeding systems vary stronglyamong regions,and inrelationtotypeof
feedstuff available and season.Berseem isthemainfodder offered duringwinter and
darawa in summer. In some areas,conservedfeeds,suchasmaizesilage areused,
either with berseem inwinter orinthetransitional period betweensummer andwinter
seasons,whengreenforages are notavailable.
Stage 3 (from 8 to 12 months). This stage of fattening isorientedtowards market
demand. High quality concentrates isthemainfeed used.Thefinalweight is normally
around400 kg.Thefeeding system ismoreorlessthesameasinstagetwo.
Feeds and Nutrition
Animal Unit (AU) was used to analyze thefeeding situation. Drymatter (DM),Total
Digestible Nutrients (TDN) andCrude Protein (CP) requirementswere calculated using
47
-Chapter3-
NRC (1988) tables.Thecalculatedfeeding requirements perAUwere 11.23,7.06 and
1.33kg,for DM,TDNandCP,respectively.Thefeedingvalues ofthefeedstuffs offered
were calculated usingthe Egyptianfeedanalysistables. Estimates offeed intakewere
based onquantities offeedstuffs offered minus 10%asfeeding losses.Also, quantities
of purchased feeds together with the production of area-cultivated fodder were
compared with the quantities offeredtotheanimals.Thedatawereanalysedtofigure
outthefeeding situation amongfarmsizes,areasandyears.
Figures 9, 10and 11present ageneraloverviewofthedaily DM,TDNandCP offered
and required per AU permonthforallfarms. Itisclearthat underthisfeedingsystem,
the rations on offerare unbalanced allyear round. Adeficiency inTDNmainly occurs
at the end of summer and the beginning of winter (September to February),when
berseem is cultivated and still growing or duringtheearlycutsof berseem.TheCP
offered tends to be close tothe requirements duringwinter,except attheendofthat
seasonwhenthe DMcontent ofthefresh berseem reaches itsmaximum.
With regardtothesizeofthefarms,Figures 12,13and 14presentaveragedaily nutrients
offered and required by sizeoffarmandmonth.Thefiguresshowthatthequalityofthe
feed offered onmedium-sizedfarmsisbetterthanthatonsmallfarms. Exceptatthetime
of cultivating berseem and during the first and second cuts (earlywinter),TDNwere
offered belowrequirementsonsmallfarms.Figures 15to20showthevariationinfeeding
situationamongareasandyears.
A general conclusion with respect to farm management on feeding is that farmers'
decisions on feeding were irrational or suboptimalinthebestcases,byeitherfeeding
above or belowtherequirements,whichnegativelyaffectsdairyproductionanddoesnot
allowanimalstoexpresstheirgeneticpotential.
Degree of commercialization and the interaction of crop-livestock activities
The degree of commercialization tends to be quite high, for bothcropand animal
production. Often, one major cash crop (e.g. cotton) or vegetables are grown in
combination with one or two food crops. When pricesforthecommercial cropsare
good, their area tends to expand, andwhen pricesdecrease,farmers switchtofood
crops (wheat-broad bean/winter and rice-maize/summer), there is some sale of
surpluses andsomepurchase ofexternalinputs.
Thesameapplies toanimalproduction.When highquality concentrates areavailable
at reasonable prices,farmerstendto increaseemphasis onfattening,comparedtomilk
production. Assoonaspriceschange intheoppositedirection (i.e.higher pricesfor
48
-Quantitative andqualitative description ofthe dairy farming
>
•
JK
/
/
•
• dr
\
\
\
• k;
\
\1
/
/
i
/
/
Q
1
.;
;/
i
5
A
•3
Q
1 . ii
/
•
\
a
$
.i
. /;
\
'
•
\
1
z
a
i.
v,
^
•> i
•
'
^
V
.
/
i
\
i
3
1
1
• •
i
•
^
IN k
1
6x
I
6x
6*
E
E
a
49
-Chspter3-
m
f
B»
>
XK\
iy^\ \
''k m -V
<D
I
1
IF
/ipi
z
•
D.
0)
O
I—
£-.
:
\t "< t*'
• \ i ; in
t
I A*/
a
t^y N
1
•
•fi Y'r-ii£c
^•j<«'V V
M
S
a
,,.fty
1
D
s
»
<'
JP^'
vf
—
rVj\
s ?
11
•
1 1\ 1
+V
W
* W\f
1/l\4|
•<.*»i
\
u\ .
i i Y 3k i.
1
nvMep/psjajjo6x
nvMep/pajs«o6x
o.
Q
<
£
flvMep/para«o 6>|
<
.E
Q
3
E
Q
(top) pajajjo 6x
d)
KV'I
Mlf
iV \
re
top/pai3«o 6>|
50
Xep/pajsyo 6>j
-Quantitativeandqualitativedescriptionofthedairyfarming-
concentrates), and fattening is commercially not attractive, farmers switch to milk
production,withsaleoftheyoung malecalves.
Switches between animal production and crop production alsooccur,when pricesof
animal products goup(or iftheyseemmoreprofitable),farmerstendto cultivate more
forage crops,attheexpenseofcashcrops.
Oneofthe importantfeatures ofthe Egyptian mixed crop-dairyfarming,isthatfarmers
can market/sell allquantities offoodcropsproduced onthefarm.Thatdoes not holdfor
milk production;partofthe milk isprocessed at hometomeetthefamily requirements
for butter orcheese,part isconsumed bycalves andthe remaining portiongoestothe
market. Data inTable6showthe proportionofmilkutilization.
Table 6. Proportion (%) ofmilk productionforvarious purposes inthe different
study region.
Home consumption
Buffalo milkfor sale
Cattle milkfor sale
Milkfor suckling
Processed athome
Ashmoun Senbellewien Qallin Quttur Nubaria Faraskor
16.2
8.1
8.9
11.8
2.8
3.6
57.9
66.5
26.7
11.5
39.9
15.9
13.9
44.1 69.8
46.0
13.9
68.1
5.6
11.2
10.4
6.6
7.5
12.1
5.0
0.1
8.9
1.2
5.5
0.3
A conceptual model of the farming system
One of the possibilities tostudyfarming systems istodevelop aconceptual modelof
the functioning of the system and to usethat modeltoexplorewaysto improvethe
system (Shaner et al., 1981). The firststageindevelopingsuchamodelistodefine
and representthe maincomponents ofthewhole mixedcrop-dairy farming system.Fig.
21 presentsthe maincomponents andboundaries distinguished inthisstudy.
Inthemixeddairyfarmingsystem,threemainsub-systemsaredistinguished:
• Thehouseholdsub-system
The household is the core ofthefarmunitthatmanagesresourcestoundertakean
integrated arrangement orpatternofcropand/orlivestockactivitiesandtheallocation
ofresourcestotheseactivities/enterprises.Theroleofthehouseholdistosetpriorities
amongthesuitablecropsandprovidetheinputsneeded,includingfamily labour,etc.
• Cropping sub-system
This sub-system comprises two main sub-enterprises, representing the common
fodder and cash crops; the main inputs come from outside the system, suchas
inorganic fertiliser, seeds (especially forhybrids),pesticidesandextensionservices.
51
-Chapter3-
The outputs identified are grain, fodder,economicyieldsofcashcropsandcropbyproducts.
• Dairysub-system
Dairying and meat/fattening arepractisedcombined,asoneenterprise.Themilkcan
be sold as fresh milk, mainly producedbybuffaloes,orprocessedathome,mainly
produced bycattle.Someofthemilk isprocessedathometomakebutterandcheese
for home consumption. Animals for fattening originatefromthecalvesbornatthe
farm,purchasedcalvesfromthemarketand/oroldanimals.
Market. Theboxes identified asinputs/outputs represent allpurchased inputsfor crops
and livestock,andtheproductssold.
Figure 21. Schematic presentationofthemixedcrop-dairy farmingsystem.
Feedstuff
Concentrates
Maize
Wheat bran
Rice bran
Mofeed
Linseed cake
Deriving a basis for development of a decision support system including the
contributionsofimprovedtechnologiesandintegrationofcropsandlivestock.
On the basis of the description of the relevant sub-systems, thefollowing specific
activities were identified as necessary components ofthemodelofthewholefarming
system:
• Constructing acropping plan,taking intoaccountthe land useconstraints.
52
-Quantitativeandqualitativedescriptionofthedairyfarming-
• Converting the availablefeedstuffs into DryMatter (DM),Total Digestible Nutrients
(TDN),Crude Protein (CP)and NetEnergyfor Lactation(NEL).
• Deciding on possiblefodder conservationandchemicaltreatment ofcrop residues,
taking into account climatic conditions, suitability, feed availability, and nutrient
requirements.
• Predicting animalproduction,milk production,bodyweightgain,calving.
• Estimating nutrient requirements, individuallyformilkinganimals,andbygroupsfor
other animalcategories.
• Estimating quantities offeedstobepurchasedtomeettotalanimal requirements.
• Formulating least cost ration
With regard tothe newtechnologies, itisclearthat introducing improved technologies
in the existing farming systems could improve the feeding situation year-round.
Introducing maize and berseem silagecouldfillthegapbetween cultivation seasons.
Also, introducingfodder beetaswinterfodder cropcould improvethebalance between
energy and protein inthegreenforageduring latewinter andthefollowing transitional
period.Ammonia andureatreatment could improvethepoorqualitystraws.
Some of these activities should be optimized on the basis of availability of new
technologies, or innovations inmanagement that canimprovethefarming systems and
allowfarmersto increase revenues,comparedtoexistingfarming practices.
References
CIHEAM (1992).Theagriculturesector and itsprospectsfortheyear2000, Egypt.
MediterraneanAgronomic Institute,Montpellier, France.
Coulon,J.B.,Perochon, L.&Lescourret, F.(1995).Modellingtheeffect ofthestageof
pregnancy ondairycows'milkyield.Animal Science60:401-408.
FAO(1982).Thestateof FoodandAgriculture 1982.World Review, Livestock
Production:AWorld Perspective. FAOAgriculture Series No. 15, FAO,Rome,
Italy.
FAO(1992)ThestateofFoodandAgriculture.World Review,Agrostat. FAO,Rome,
Italy.
Hardaker, J.B.&Anderson,J.R. (1981).Whyfarmrecording systems aredoomedto
failure. Review of Marketing andAgriculture Economics,49, 199-202.
Lescourret, F., Coulon,J.B., Perochon,L.&Faye,B.(1994).Modellingthe
interrelationships between mastitis andmilk production indairycows. Livestock
farming systems: research, development socio-economics and the land
manager. Proceeding of thethird internationalsymposium on livestock farming
systems. Aberdeen, Scotland, September 1-2,1994. EAAP Publication No.79,
1996.
53
-Chspter3-
Mainland, D.D. (1994).A Decision Support Systemfor Dairy Farmers andadvisors.
Agricultural Systems,45,217-231.
Shaner,W.W., Philipp,P.F., andSchmehl,W.R., 1981. FarmingSystems Research
and Development, Guidelinesfor Developing Countries.Westview Press/
Boulder, Colorado, USA.
Sharma,A.K.,Wilcox, C.J.,Martin,F.G. &Thatcher,W.W. (1990). Effectsofstageof
lactation on pregnancy and their interactions on milk yieldand constituents.
Journalof Dairy Science73:1586-1592.
Sitaramswamy,J.&Jain, D.K. (1993).The roleandtypeofmodels infarming system
research. Feeding of Ruminants on Fibrouscrop residues. Proceedings ofan
international workshop held at national Dairy Research Institute, Karnal
(Haryana,India).
Sonka,ST. (1985). Information management infarm production.Computer and
Electronics inAgriculture, 1,75-85.
54
Chapter4
DevelopmentofaDecisionSupportSystemforIndividualDairy
FarmsinMixedIrrigated FarmingSystems:IIDescriptionand
Implementation oftheModelforMixedCrop-Dairy Farming
Systems inLowerEgypt
A. Tabana 1 , H.van Keulen 2and S. Tamminga 3
1
Animal Production Research Institute. P.O. Box443,Dokki,Giza,Egypt
Agrosystems Department, PlantResearch International,Wageningen-UR, P.O. Box
16, NL6700AAWageningen,The Netherlands
department ofAnimal Science,Wageningen InstituteofAnimal Sciences,
Wageningen-UR, P.O. Box338,NL6700AHWageningen,The Netherlands
The Netherlands
2
(Submittedfor publication)
-Chapter4-
DevelopmentofaDecisionSupportSystemforIndividualDairy
Farms inMixedIrrigated FarmingSystems:IIDescriptionand
implementation oftheModelforMixedCrop-Dairy Farming
Systems intheNileDelta
Summary
ThispaperreportsonthedevelopmentofaMixedDairyFarmingModel(MDFM) that
hasbeendevelopedprimarilyforuseatfarm levelbyextension ormanagementstaff
in Lower Egypt.Itcanbeadaptedforotherregions.Theobjectiveofthemodelisto
analyze present activities of a mixed farm andtomaximizetheprofitofthe farm,
from both crop and dairy farming. It also allows the formulation and testingof
biological parameters and management strategies at farm leveltomeasuretheir
impactonprofit.
The model represents365daysdividedintoa 12(monthly) periods. Simultaneously
it predicts animal production levels, nuthent requirements and cropping pattern
basedonleastcostrationformulationandfarm revenues.
The authors conclude that MDFM can make more efficient use and or more
integration of the farm resources and improvethenutritionalandeconomicgains
significantly.
Introduction
The functioning of agricultural systems is affected by physical,biological,socioeconomic and policy factors. Livestock farming isinfactanactivity locatedatthe
"interface" between all of these factors andthe internal processesthat governthe
functioning ofagricultural systems,andplaysafundamental role intheequilibriumof
rural societies (Vissac, 1992).The inclusion ofsocialandeconomicfactors,derived
from survey data, intoproduction system analysis provides adifferent approachfrom
the simple integration of existing technical knowledge derived from animal
production sciences.
Modelling herd performance on thebasisofherdstatus,modifiedby management
practices, is necessary for characterizing systems andforquantitatively estimating
the effect of different technicalmeasuresaffectingthe herd(Beranger andVissac,
1992). Development of models for this purpose isgenerally basedon monitoring
sample farms, including explanatory observations and discussions with farmers
about their practicesandconcomitant appropriate recording ofanimal performance.
The sample of farms is selected tocoverawide rangeofmanagement practices,
58
-DescriptionoftheMixedCrop-Dairy FarmingModel(MDFM)-
thus allowing the use of comparative analysis methods to help inthe modelling
process.
This paper presents a description of a model, developed as adecision support
system for amixed crop-dairyfarming system,thatallowsforoptimalfarm resource
use, andassessment ofthe impact, innutritional andeconomicterms,of introducing
alternativeforage cropsandfeed resources intothesystem.
Model use
The Mixed Dairy Farming Model (MDFM) hasbeendeveloped primarilyfor useat
field/farm level, by extension or management staff. The modelcanbeusedasa
decision support toolbythefarmer, inconsultationwith hisfarmadvisor,to analyze
the consequences of different management strategieswith respecttoland useand
animal nutrition,onfarm profitability.
Model objectives and the objective function
The modelobjectives aretoanalysethepresentactivitiesofamixeddairyfarmfrom
a nutritional and economic point of view, and to identify improved systems by
including alternativefodder sources andfeeding strategies.
MDFM is an optimisation model that maximizes net margin fromfarmactivities,
comprising total revenues frommilk,animals andcropsminuscostsoffeeding and
other variable costs,suchaslabor, animalhealthcare,fertiliser, etc.Thenetmargin
takes into account the opportunity costs of the resources used indual-purpose
production (e.g.maizecanbeproducedascashorfoddercrop).
Model activities
MDFM represents 365days,divided into 12periods (months),startingfromtheday
ofthefarmvisit.Themodelsimultaneously defines and linksthefollowing activities:
- Constructing acropping plan,taking intoaccountthe land useconstraints.
- Converting the available feedstuffs into available Dry Matter (DM), Total
Digestible Nutrients (TDN), Crude Protein (CP) and Net Energyfor Lactation
(NEL).
- Allocating a current excess of available feed resourcestofodder conservation
and various feed treatments, taking into account climatic conditions, feed
availability andfeed requirements.
- Predicting animal performance,e.g.milk production,bodyweightgainandcalving
time.
- Estimating energy, protein,andmineral(calcium andphosphorus) requirements
per individual for lactating animals and per groupforother animalcategories.
59
-Chapter4-
- Estimating the amount and type of feeds tobepurchasedtosatisfy total herd
requirements.
- Formulating aleastcost ration
- Predicting farm revenues (gross or net) under the existingsituationandafter
optimization
Model limitations
MDFM can handle only a limited number of animals, i.e. 9milking cows,9milking
buffaloes, 5 cattle heifers and 5 buffalo heifers, andarestricted number oftypesof
concentrates and straws to formulate rations. The restrictions of the model are
summarised inTable1.
Table 1. Restrictions ofthemodel bytypeand category
Category
Type
Limitation
Numberof
animals
Dairy cattle
Dairy Buffaloes
Heifers
Growing/fattening animals
Max.9milking animals
Max.9milking animals
Max.5heiferseach (cattle/buffaloes)
3age-sex stages/groups, unlimited
animal number pergroup
Purchased
feeds
Commercial concentrates
Otherconcentratetypes
Straws
3typeswithdifferentfeeding values
Maize,molasses,wheat/rice bran
Wheat/rice/bean/maize
Crops
Traditionalfodder crops
Alternativefodder crops
Other crops
Berseem-darawa
Fodderbeet/maizefor silage
Wheat-broad bean-maize-rice-cotton
Output
Income
Salesofmilk &animals*pluscashcrop
revenues
*Value oftotal bodyweightgains
Model constraints
The levelof intensity oftheactivities inMDFMisbounded byconstraints imposedby
the environment, time and subsystems (Gorgensen, 1994). The activities and
60
—Description ofthe MixedCrop-DairyFarmingModel(MDFM)-
constraints can be varied in particular runs of the model, in accordance with
available resources and/or farmer decisions.Theconstrained operations andtheir
limitationsareshown inTable2.
Table 2Theconstraintsand boundaries ofthemain subsystems/operations.
Operation
Identified constraints
Land use
Cropping areaperyear
Cropping areaand
rotation
Fodder
conservation
Berseemsilage
Producedfrom DecembertoJune
Berseemhay
Fodder beetsilage
Maizesilage
ProducedfromApriltoJune
ProducedfromApriltoJune
ProducedfromSeptemberto
November
Roughage
treatment
Ammonia andurea
treatments
Adjusted byoperator or optimized
Feed availability
DM,TDN,CP
Equalorgreater than requirements
Ration formulation
Molasses
Straw
Wheator ricebran
Freshfodder(berseem,
fodder beet,darawa)
Maizesilage
Max 10%ofthetotal DMintake
Max25 %ofthetotal DMintake
Max25 %ofthetotal DMintake
Notexceeding availability
Wastedfeed
Limitations
Twotimes owned land
Winter =summer =owned land
Max.60%ofthetotal ration (DM)
Excessamount ofDMto Tobeadjusted byoperator (10%
beoffered
lossesasdefault)
Model development
Cropping system
The model was designed initially to describe specifically smallandmedium scale
mixed dairy production systems innorthern Egypt, butthegeneral structure allows
61
-Chapter4-
easy translation to other productionsystems.Themaincharacteristics ofthemixed
dairy production systems arethattheyarefamily-owned andoperated enterprises,
with various levelsofcapital investment.Thestandardized productionsystemallows
a limited numberofalternative landusetypes underthecurrentinfrastructure,water
availability, soil fertility and market conditions. These includethecurrent (wintersummer) crop rotations: berseem-rice/berseem-cotton/berseem-maize/wheat, broad
bean-rice/wheat orbroadbean-maize. Darawa (vegetative maize)orvegetables can
be cultivated instead of any othercropwhentemperatures aresuitablefor sowing
and/orgrowth.
Land useandfodder production:
Land area, crop rotation, farmer policy andenvironmental conditions arethe main
factors affecting thecropping pattern.Thesuitable (traditionalandalternative) crops
may be grown on one or two plots,toallowdifferences insowing and harvesting
dates, and also to differentiate productivity if different from the default/standard
values given inthemodel.
Fodder conservation andtreatments:
The model offers the possibility of making silagefrommaize,fodder beet, maize
stover and berseem, in addition to berseem hay. The modelalsopermits ureaor
ammonia treatment of straws from rice or wheat. The quantities of thevarious
feedstuffs allocated to conservation or chemicaltreatment, aredetermined bythe
farmer oroptimised inthemodelonthebasisofnutritionalandeconomic criteria.
Livestock system
The livestock system consists ofasmallmixedherd,comprising cattleofthe local
breed (Baladi), Friesian-Baladicrosses andbuffaloes,adultanimals and associated
young stock. In somecommercial/specialised enterprisese.g.'flying herds'system
(called Zarraba), male calves arenormally soldatweaning orafter afewdayswith
the mother; Inthemodel,this islefttothefarmer'sdecision.
Herdcomposition:
The following classification was constructed, based on information collected on
existing dairyfarms:
• milking cows (females overthreeyears oldand/orwithat leastone parturition);
• heifers 2-3 years (females overtwoyears oldandpregnant);
• heifers 1-2 years andmaleanimals 1-2years;
• female calves 3-12 months;
• malecalves 3-12 months;
• rearing calves (male andfemale) 0-3months.
62
-Descriptionofthe MixedCrop-DairyFarmingModel(MDFM)-
The number of animals kept onthefarmdepends onthefarmer's attitude andhis
objectives with respect to herdsize,definedasafunction oftimeoftheyear. Sales
and purchases of animals at certain ages are included to exogenously fix herd
dynamics.
Herddynamics(growth):
The herd consists of a numberofanimalsofeachofthedistinguished categories.
These numbers changewithtime-calvesare born,heifers becomecowsandcows
and heifers may be sold or may die. Changes inherdsizeand composition are
calculated twelvetimes annually (monthly). Biologicalevents such aspregnancy and
delivery are tracked, to monitorthestateofeach individual animalinthe herd.The
individual characteristics distinguished formilking animals andheifers areshownin
Table3.
Table 3. Statevariables andtheirdescriptionfor individual animals intheherd.
Statevariable
Current milk production
Description
Yieldonthedayofvisit (kg)
Milk production potential
Expected increase inkg*
Monthoflactation
Months post parturition
Pregnancy status
Pregnant ornotanddays post insemination
Bodyweight
Live bodyweight (kg)
Daily gain
Livebodyweight gain (g/d)
Fatpercentage
4%forcattleand7%for buffaloes
Parity number
Numberofcalving
Decision ofculling
Yesornoandtiming
*tobedecided byfarmersfor pregnant heifers
Herd productivity:
Milk production: Daily milk yield is predicted from an exogenously introduced
lactation curve, derived fromamonitoring program of36farmsforthreeyears.The
absolute level of production isdefined byspecifying themaximum attainablelevel,
thus allowing to take into account high yielding animals (breeding) or improved
environmental conditions such as housing, or offering better quality feedbythe
users.
Growth rate:The usercandefineatarget daily bodyweightgainforeach individual
milking animalorpercategory forgroupsofgrowinganimals.
63
-Cha*er4-
Nutrient requirements:
Daily nutrient requirements for milkinganimals arecalculated per individual,then
aggregated insubgroups (e.g.milkingcattle,milkingbuffaloesandpregnant heifers).
For growing animals, requirements arecalculatedforone representative animalfor
each category andthenmultiplied bythetotal number ineachcategory.The effects
of biological characteristics, such as pregnancy andparity number aretaken into
account when calculating requirements. Energy, proteinandmineral requirements
for milk production andgrowthwerederivedfromequationsgiven inNRC (1988).
Feeding plan,monthly/daily ration:
The feed requirements of each category of animals are matched with available
home-grown (fresh or conserved) and purchased feeds (Table 1). Feeding
constraints (Table2)andtiming offodder production (fromtheconstructed cropping
plan) aretaken intoaccount,andfinallytheeconomic/least costration isformulated.
Farm income:
MDFM takes into consideration two aspects: 1) The balance between cash
payments and earnings. The expenses attributedtothesub-systems (cropping or
dairy), including hired laborcosts,arecombined andare regarded asvariablecosts.
In this sense,theoverall cashbalance representsgross margin;2) Farmnetmargin,
excluding off-farm income. The forage costsarebasedontheopportunity costsof
alternative landuse.
Farm economic crop products and crop residues arevalued against exogenously
supplied farmgateprices.Themodelalsopermits sensitivity analysistoexaminethe
influence ofchanges inspecific elements onfarmincome.
Model structure/description
MDFM contains separate operational parts (modules), linkedtosimulatethewhole
farm.Thestructureofthe model,includingthe linkages,isshown inFig.1.
Cropping (sub-model)
In this sub-model,cropyields areestimated,leadingtoestimatesofavailability offresh
and conserved fodder year-round. Also, the quantities ofcashcrop by-products are
estimated inthissub-model.
Input data: A double-entry table (crop species, sowing date) was constructed,
comprising yields of the most common cash and fodder crops in the region. For
improved accuracy, default values for theproductivity tobeaccepted orvalidatedby
the individual farmer, aswellasawindow ofsowingtimes areprovided (seeAppendix
1). Productivity reference table: DatafromARC (Forage improvement project; Report
onwinterforage crops, November, 1989)were usedtodefinethe influenceofseason
64
Descriptionofthe MixedCrop-Dairy Farming Model (MDFM)-
i_
0
13
? 7
**
I
o
I
c 1=
0 n
ji
o a V
f» E
o
c-5
o
a)
2
3 ro
Z >
t
<u
a.
>S °
12
7
o LA
/
«l
"z U
v/
—
o en
•
°P
1
h
^(A_,
>
ro
3c!
roS?
i 5 HI
V
—
S CO
X
<A
o tS
a 0
ID
/
s
>.
•o
*-ro•
c
C
/ 6uiSS300Jd BJBQ
ro S
•a >
"S '"C < i
2
5
o 13
'•s.sl
• S I
> CO 3 1
CO
i
T
0 C •
ro
ro
^
1
1
0
o
c
<
O
O
--»
h
0
IL
1
c 1
4
c
1
a)
0)
LL
co to 1
r/ i
(^ 6 u i S S 3 0 0 J d
eien
/
§0 11
/
0
CO
S
u.
. H >
0• o
m.M/F
t
C
-Jit
"
J? ' ' r
a
3
<?
<N
3
filrf
•
en
a 1
"0
c
1
ro•••
-i
ro <s>
E "
<
(L
i^
>• 3
• o
5
>
l o
"|
0
IA
C
—>
in
•o
0
ro -=
.|S
= C 3
0
ro m
- a o)
•o
0
u
(0
.b 0)
ro 5
Q ro
O
>
0
0
O
r^T
8,2
1
\
c
CO
c
\
5.
£ o
o •
< I
£
CM
^
3
P r
a a
\ '5
1?
s
a>
CM
7
(0
owin
1 lilFs
rodu
3
*-»
U
3
Cr
£
'
1 £ t c : &
3-6
0-3 m. MS.
A.
3
Q.
65
/
/
/
/
O)
CD
0-
n
•
s 1r
II
D_
T3
c
CO
a)
to
E
a>
CO
0
o
n"
CO
-Chapter4Figure 2. Influence ofSeasononGrowth Rateof Berseem inthe Delt
KgDM/feddan/day
100i
.
90
80
70
60
50
40
30
20
10
30
Figures
61
121
91
152
182
212
242
.Influence ofSeasonon DM%of Berseem
Dry Matter
29%|
%
27%
25%|
23%
21%
19%
17%
15%
13%
11%
9%J
5%
-i
30
61
91
121
152
Date of cuttin
* Date of cutting expressed in number ofdays after 1 s t November.
66
182
212
Description ofthe MixedCrop-DairyFarmingModel(MDFM)on growth and dry matter content of berseem as shown inFigures 2and 3(FPM,
1998). This informationwascombinedwithdatafromthefarmtoderivethe productivity
coefficients used to generate a productivity table, that is used,incombination with
cultivated area,topredictthe productiononamonthlybasis.
Croppingplan:
The cropping plan, covering one year, starts from September1. For each month,
information is presented on cultivated area of all crops,their productionandfodder
conservation, if applicable. The land area and quantities of fodder conserved are
optimised, ifnot restricted bythefarmer.
Feedand nutrientavailability:
Fodder and straws produced on the farm, as well as different types of purchased
concentrates (as defined by the farmer) are allocated according to the time of
production. Availability can be a constraint incertain months.Chemical composition
and feeding values (e.g. TDN and CP) of some feedstuffs were derived from
experiments conducted by the authors; for other materialstheywere collectedfrom
literature.
Theenergy values offeedstuffswerecalculated accordingtothefollowing equations:
DE(Mcal/kg DM)
ME(Mcal/kg DM)
NEM(Mcal/kg DM)
NEG(Meal/kg DM)
NEL(Meal/kg DM)
= 0.441x TDN
(Cramptonetal., 1957)
= -0.45 + 1.01DE
(MoeandTyrrell, 1976)
= -1.12 + 1.37ME - 0.138 ME2 + 0.105 ME3 (Garrett, 1980)
= -1.65 + 1.42ME- 0.174 ME2 + 0.0122 ME3 (Garrett, 1980)
= 0.025x TDN
-0.12
(MoeandTyrrell, 1976)
Where, TDN = Total Digestible Nutrients (%); DE = Digestible Energy; ME =
Metabolizable Energy; NEM=Net Energyfor Maintenance; NEG=Net Energyfor Gain
and NEL=Net EnergyforLactation.
Animals
In theanimalsub-model,four characteristics arecalculated:animalproduction, nutrient
requirements for these animals, feedstuffs tobepurchased and leastcost rationsfor
eachcategory ofanimals inthe herd.
Inputdata:
For milking animals andpregnant heifers (buffaloes and/or cattle),tables areincluded,
containing information on individualanimals (Table3).Young andgrowing animals are
Theagriculturalyearstartsfrom September
67
Chepter4
classified inagegroups,as indicatedearlier.Thedatastored pergroup are:numberof
animals, livebodyweight anddailyweightgain. Sellingorbuyingofanimals atspecific
moments isentered inaccordancewithfarmer's anticipated decisions.
State variables: This part of the model contains the state variables (status),
characterizing the animals in the herd per month as the basis forestimating herd
nutritional requirements: Lengthofpregnancy, parity number, live bodyweight andmilk
production. Length of the gestation period isassumed280daysfrom conceptionfor
cattle and 310 for buffaloes. Potential milkyield increaseswith parity number: by 10%
shifting from 1 stto2ndparity orfrom2ndto 3rdparity,by3%whenshiftingfrom3rdto4th
parity, 2% from 4th to 5th parity; it decreases by2%whenshiftingfrom5thtothe6th
parity (Ragab andAskr, 1958).
Monthly live bodyweight iscalculatedas:
Y=X+ (G/1000)(T*30.42)
Where, Y= live bodyweight (kg),X=initial bodyweight atthestartofmodelrun(kg),G
= bodyweight gain (g/d),T=numberofmonthssincestartofthemodelrun.
Formilk production,theequationsare:
Y=-0.0088X4 +0.2007X3 - 1.64X2+4.9917X +2.8097 (for buffaloes);
Y=-0.0033X4 +0.0823X3 - 0.7918X2+2.745X +6.1017 (forcattle)
Where,Y= milk yield (liters) andX=numberofmonthssince parturition
Estimating nutrient requirements:
Nutrient requirements arecalculated using principles andequationsfrom NRC(1988),
with the necessary modification for use in a spreadsheet program. Theequations
applied to calculate energy and nutrient requirementsfor lactationareshown inTable
4, those for growth in Table 5. Table 6 gives the equations for predicting mineral
requirements (calcium and phosphorus)for bothgrowthandlactation.
The model calculates the requirements per individualanimal,taking intoaccount its
biological state,thenaggregates the nutrients requiredpercategory ofanimals ineach
month.
Nutritional/feeding balance
The assessment of feeding management practises is performed bysubtracting the
required nutrientsfromtheavailable nutrientsfromcultivatedfodder, crop by-products,
conserved fodder and purchasedfeedstuffs.The balance isoutlined inagraphasNE
andCP.
68
-Description oftheMixedCrop-DairyFarmingModel(MDFM)-
Economic assessment
This part of the model is designed to calculate on-farm income expressed as either
farm net margin or gross margin.
Farm net margin
Farm net income/earnings (Nl) is defined as the production value (Y) minus production
costs (X). The production costs include labor, land rent, etc. The equations used to
calculate farm net margin are :
Nl total
N l crops
Nl
animals
—
—
N l crops
' crops
= Y
animals
"*" N l animals
- X
- X
crops
animals
* \/
C
v
^ cropx
r milkx
Where,
P
V
L
FF
O
V milkx
+
cropx
V,LWcategoryx
L W G categoryx
v^l crop>
+ Lc
+ LR,
r"""croD*
* O,
+ PF
Productivity (ton/feddan)
C
Market price (LE)
LWG
Labour cost (LE/ton)
CI
Farm grown fodder (feddan) LR
Opportunity cost (LE/feddan) PF
V,
Cultivated area (feddan)
Live weight gain (kg)
Cultivation cost (LE)
Land rental (LE)
Purchased feed (ton)
Gross margin
MDFM also calculates the overall cash balance (i.e. gross margin), as the balance
between cash payments/expenses and cash earnings. The model takes into account
only the real cash outlays associated with the sub-systems (crops and dairy) and the
cash earnings from the sale of products. Inthis sense, fodder produced on-farm has
low costs and thus leads to a reduction in the feeding costs and increased gross
margin. The equations used to calculate farm gross margins are the same as for net
margin with cash outlays only.
69
-Chapter4-
3
in
a:
O
II
X!
c
o
=s
XI
Al
o
u
O
XI
•*-
CO
5?
i2
c
X
CM
CD
E
-Q
•ST
1*-
XI
• *
f-
o
o
<D
O
+
CM
CO
C)
O
•a
c
CO
3
CT
111
o
CJ)
.*:
ro
o
o
o
^-
•q-
•
X
CO
X
d
CM
+
-2.
E .
00
o
o
o
-
o
o
XI ._,
II II
TO
CI)
1^
5^
2
II
C
o
3
TJ
O
O
TITO
C
CJ
TJ
o
II
_l
X
CO
TJ
X
X
CN
O
CO
CN
CN
O
CN
LO
II
II
CO
ra
m
o
JO
_i
LU
_i
_i
LU
Z
o
o
c
co
c
TO
CL
(n
c
cu
CU
N
'(O
TJ
O
XI
O
O
XI
'5
c
g
ro
o
ro
Q
o
ro
ro
c
0
o
c
o
o
_l
LXJ
>
ro
CD
cu CU
t t EC
TO
CO
ai
c
cu
cu
z
0
ii
TJ
c
c
cu
o
c
o
o
_l
HI
c
g
ro
c
cu
o
c
o
o
Q
Z
D
H
CO.
cu
c
cu
X
ro
E
TJ
ro
c
0)
"c
CO
cu
o
c:
E
CO
c
TO aj
Z
Q
ai
CO
cu
cu
o
c
a)
ro TO h-cu
TJ
c
ai
TJ
CU
_i
LU
Z
g
5
5
s
Q
cu
o
c
ro
c=
JU
c
ro ro
E
o
ro ,2
E
CO
>>
TO
*L
Q."
Q."
_l
LU
Z
^^
5
Q
Z
Q
H
Z
c
o
c
g
^ Z oc Za >.
ro
o
t3
_*: a cTO H cco ro oro
H
c
TO TO
cu S_j
m a.
cz _c
2
6"
c
Q
a.
_j
CO
O)
'L_
cu
b
CU
3
TJ
CO
TO
L_
z
ro
E
"5
CO
g>
cu
c
cu
cu
c
cu
ro L U z
m
70
cu H
cu
ro
E
£•
Q
o
II
2
m
Q
'ro
E
cu
c
cu
£•
U
_i
LU
Z
CU
O
X
CU
g £ c
3
TJ
c
ro >^ ro
TO C) c
c
g
g
t3
ro
c
ro oc a . cg 'ro
t3 ro
g
ro
o
TO
ro
c
ro
JD
ro
£ 13
t3
o
TO
Z
ro
TO
ro £
z
a.
Q
aj
c
>>
Q
2
CO
cu H
cu
ro
o
cu
o
c
g>
cu
c=
O)
Z
Q
H
m
o
ro L U z
2ro z m
ro
o
O)
C
5
^—
Q
H
a>
c
cu
£
z
c
g
ro
o
ro
TO
c
'l_
3
TJ
C
CO
TO
c
o
ro
t3
ro
Q
cu
c=
LU
CO
c
ro
c
TO
2
CL
c
CU
E
2
CU
cu
ro z
m
c
LU
"O
3
CT
• —
TO
2
TJ
2>
ro ro
o o
z
cu
c
cu
o
Q
c
TO3o \-<a TOo
ai
cu
ro
c
c
TO"cu
cu
CU
10
CO
CD
TO
c
ro
o
TO Q_| ro
^:
LU
CN
5
_i
cj
c
o
O
a
I!
c
g
T3
ro
o
CO
ro £ z z
a)
E E
cu
I
o
o
+
E
+
T>
co
o
CO
T3
,,
CO
z 2
a.
O"
CO
X
1 ,
- j
TOTOTO
-* —
'
g
'£3
X
N-
Wi
r^
CN
CsT
o
ro ro o+
o
a>
c
a>
a>
c
c
o
X
a.
• *
E E -=:
>.
(0
XI
3
UJ
-S£
CO
CD
O
ro
"o
c
ro
TOTO
x : x:
TOTO
cu
* •S
>• >.
ro
CM
o
X
c
en
c?
o
o
£
<u
5
^S
CO
cu
ro z
m
E
H
cu
^
"aj
CO
3o
i
ro LU
Z
CD
-Description of the Mixed Crop-Dairy Farming Model (MDFM)-
o
o
o
O
O
o
C?
O
X
X
o
o
1
II
•o
co
C?
O
0
"co
E
CO
%
CD
X
c
E
'5
u
o
o
o
m
o
d
LO j t
CO CM
d
+
+
CM
CD
X
CO
CO
a)
X
O
t^
o
a: ^
O in
d
1
1
.O
CD
X
CM
-a
^ ^~
II
•^5 5;
TO
CM
in" d
T3 O CM
CD V CO
CD T3
s:
a> 5T
o o
•0;
O
CD
d X
1—
o
*~**
CD
1
CD in 1 ^
"co 1^- CM CO
1 E c\i
II
II d
II
CO
o
CO
CD
X
CM
CM
o
d d
a)
E
%
m
CD
oo
o
o
"to" CN
1
CO
X
in
CM
Al
O
T3 i n
oA
2
O)
i2
o"
in
c
1
a)
CM
E
in
CD
CO
CD
1^
to
S
o
CM
d•
^C—
O^
o
o
o
2,
CD
c
w
re
o
o
o
*J
o
o
00
_i
E
c
re
CD
o
^s.
in
d d
+
+ T3
+
2.
X
X
II
II
CO
^II~
II
CO
CD
co
Q
E
0
ID
a>
a>
.a
"co
i
CO
k.
"(0
o
<u
c
o
E
co
O)
co
o
0
o
c
n
u
o
CO
c
O
0
c
in
c
o
ill
LU
c
C
o
<D
£
U
TO
CO
CO
TO
TOTO
>.
>.
o f"
o 3
>* > .
TO T3
TO^TO
CD CD
in
0
CO CD
0 *~ui CD
.C
C
-a
™
&
c
0
•4—>
c
CO
.32
E
-Q
CO
N
a
2
0
T3
C
0
O
c
0
c
0
O) TO
0
0
co
0
re
TO
•a
re
o
c
o
o
>.
E>
T3
3
-1
re
- £ CD "(5 <D
-2 1
0
T> -a
rC0
-Q £>
re & . E
££
2
o
^ i
CD yj
2 Z
71
0 0
.> .>
TO O)
=£ 2
re ™
o o
o o
CD 0 0
>>
TO -- TO
re
>. >o o
Q
0
D) 0 Q g - ^ t i 0
"5 ^:
c
J? «0 J £
-Q
:= 0
CD C
5 -^ c +^
O 0 £iu 0
O
re
E
o
c
0
•S LU
c
™ 0
0
E
CO
ri
_ l
_i
c
2
CO
Q
co
E
LU
LU
0
F
CO
CO
O
Q
LU
LU
c
re
T3
.O
>.
•Q
T3
0 ^
0 «
"
E (D 0
> , «1 «1
C 1 CO CO
2 Q mm
X
X
rere
E E
Description ofthe Mixed Crop-Dairy Farming Model (MDFM)
Table 6.Equations forcalculation ofcalciumand phosphorus requirements for
growthand lactation
State
Equation
Calcium requirementsfor lactation(g/d)
Iflactation number = 1
=(1.2x0.0154x LW+1.22FCM+
0.0078 xTFG1)/0.38
Iflactation number =2
=(1.1 x0.0154x LW+1.22 FCM+
0.0078 xTFG)/0.38
Iflactation number =3
=(0.0154xLW+1.22FCM+0.0078x
TFG)/0.38
Phosphorus requirementsfor lactation (g/d)
Iflactation number =1
=(1.2x0.0143 x LW+0.99x FCM+
0.0047 xTFG)/0.5
Iflactation number =2
=(1.1x0.0143 xLW+0.99x FCM+
0.0047 xTFG)/0.5
Iflactation number =3
=(0.0143xLW+0.99xFCM+0.0047 x
TFG)/0.5
Calcium requirementsforgrowth (g/d)
If90<liveweight <250 kg
=8.00 +0.0367 x LW+0.00848 xLWG
If>250 liveweight <400 kg = 13.4+0.0184xLW+0.00717xLWG
Ifliveweight >400
=25.4 +0.00092 x LW+0.00361 xLWG
Phosphorus requirementsforgrowth (g/d)
If90<liveweight <250 kg
=0.884 +0.0500 xLW+0.00486 xLWG
If>250 liveweight <400 kg =7.27 +0.0215x LW+0.00602 xLWG
Ifliveweight>400
=13.5+0.00207 xLW+0.00829x LWG
1=totalfetalgain (g/d) ifpregnancyexceeds 210days, F= 1.23 LW
Model layout
Figure 4 illustrates the MDFM layout. The model was constructed using the basic
spreadsheet facilities of Lotus 1-2-3 Release 5 for Windows (Lotus Development
Corporation, 1997), in combination with an optimisation program"What's Best" (Lindo
System Inc., 1999).Themodelconsists oftwofiles(basic andoptimizationfile):Eachfile
contains a series of spreadsheets,eachsheetforoneormoreparticular activity(ies),as
given in the model activity description. The spreadsheets are linked, if relationships
between the data source sheets and calculation sheets areneededtorunthemodel.
72
-DescriptionoftheMixedCrop-Dairy FarmingModel (MDFM)Macros are extensively used to allocate and store calculateddataandforprintingthe
results.
Figure 4. MDFMlayout
Model calculations
The following example illustrates atypical runofMDFM.Theactivity definitions used
for the model runs have been presented earlier.Abriefexplanation ofthe activities
engaged inatthefarm,andincluded inthemodelcalculations isprovided below.
Landuse
Table 7 shows thecrop-input data requiredfor running MDFM. Theexisting structure
provides list of cashandfodder crops,allowsfarmerstoselectthesuitable cropsand
decide the sowing month. Default values for sowing months, crop area and
productivities are provided, and willbeselected,unlessspecified exogenously bythe
model user and/or the operator. Themodelalso allowscultivation ofonecropontwo
separate plots of landwithdifferent cultivation characteristics.
73
Chapter4Table7.Inputdatafor landuse
Crop 1
rseem (long term)
Broad bean (late)
Maize (for silage)
Rice
Crop selection andcultivation months
Sowing month
Default Limitation
September
November
May
June
Sep
Sep
Nov
Dec
Sep - Nov
Sep - Nov
Nov - Dec
Nov - Dec
Area
Prod.
2
3
Restricted Optimized
Default
No
0
40
No
0
14
No
0
20
No
0
6
1
A complete listofcropsisprovidedinAppendix 1
MDFM usercanselect anareaforeachcrop,otherwisethe modelwilloptimizethearea
3
Productivity (ton/feddan,asitis)
2
The herd
The herdconsists oftwobreed (buffaloes andcattle);theanimals per breedaredividedin
two groups (growing animals and lactating animals.Eachgroupofanimals isdividedin
different categories, on the basis of age: heifers 1-2 years; male animals 1-2years;
female calves 3-12 months; male calves 3-12 months; and rearing calves (maleand
female) 0-3 months.Thisclassification isbasedoninformationcollected infarmsurveys.
Farmers tend to distinguish thesecategories becausethey aimatdifferent growth rates
for each category, which may guide selection of the quality of feedstuffs offered to
animals.Table 8showsthe inputdata requiredperbreed andcategory ofanimals.
Table 8.Inputdatafor growinganimals (summary1)
No.
Heifer 1-2 years
Male 3-12 m.
Female 3-12 m.
Calves 0-3 m.
1
2
4
6
4
2
Cattle
B2 weight
(kg)
250
105
110
70
Buffaloes
Daily
gain (g)
150
400
700
500
No.
B2. weight
Daily gain
2
4
3
2
(kg)
300
160
140
90
(g)
120
650
320
200
Thedetailed inputdataforgrowing animalareprovided inAppendix 1
Bis live body, 3 misageofanimalpermonth
For dairy cowsand pregnant heifers,asetofdata isrequired per individualanimalper
breed as shown in Table 9. The numberofdairy animals isrestrictedtomaximum9
milking animals and 5 pregnant heifers per breed. In practice,this number ofdairy
animals isnotareal limitationofthemodel,consideringthesizeoffarmholdings (small
74
-DescriptionoftheMixedCrop-Dairy FarmingModel(MDFM)and medium) inEgypt.The inputdatatake intoconsideration biological changes inthe
animals that may affectthe nutritional requirements inthefuture.However,the above
data are necessary to predict actual nutritional requirements,that meetthe biological
needsoftheanimals.
Table 9. Inputdatafordairyanimals1
Daily Milk
production
(litre)
Cattle (cows)
Buffaloes (cows)
Heifers (cattle)
Heifers (buffaloes)
1
15
8.5
14.5
7.5
Lactation
month
3
5
1
1
Average per category, detailed data
Days
pregnant
35
95
260
285
Body
weight
(kg)
434
438
388
380
Daily
gain
(g)
17
42
51
100
Fat
(%)
Lactation
number
4
7
4
7
3
4
1
1
are provided inAppendix 1
Other input data
The feeding values of feedstuffs, market prices ofmilk,meat, cashcrops andamount of
concentrates that can be purchased by farmers should be provided endogenously or
exogenously as applying to the farm area under consideration. Table 10providesan
example ofthe requireddata.
Table 10.Inputdata offeedingvalues,market pricesand purchased concentrates1
Berseem
Wheat bran
Rice straw
Bean straw
Maize silage
Concentrate
Feeding values (%)
TDN 2
CP 3
17.4
58.7
16.3
68.0
5.2
42.9
7.5
51.0
9.3
69.9
16.8
69.3
Market price
(LE)
300
700
45
150
250
670
Purchased
amount (tons)
—
5
20
—
—
10
1
Exampleofthefeedstuff used inrationformulation only,acomplete list offeedstuffs is
provided inAppendix 1 , 2 Total Digestible Nutrients,3 Crude Protein
Model calculation/predicted output
Land use,crop production andfodder conservation
Table 11 illustrates the resultsofanMDFMmodel runfor optimalcropping areasthat
result in maximum incomefromthewholefarmenterprise. Model results suggestthat
75
Chapter4
the combination ofberseemlongterm(fodder crop) andbroad bean (cashcrop) isthe
optimal winter cropping pattern, followed by rice(cashcrop) andmaizeforsilageas
summer crops. Indeed, this pattern istypicalforthesituationwherewater availability
allows ricecultivation.
Table 11. MDFMoutputofland use,crop productionandfodder conservation
Area
Crop
(feddan)
Berseem (long-term) 25.4
Broadbean (late)
4.6
Maize (forsilage)
8.3
Rice (field 1)
21.7
pertonfresh matter
2
pertonfresh matter
Sowing
Month
September
November
May
June
Mainproduct1
93.28
5.49
—
129.99
Byproduct1
—
4.572
—
21.672
Conservation
Hay1 Silage1
70.84
—
33.34
—
Prediction ofmilk productionand bodyweight
MDFM predicts milk productionforeach individualanimalfor 365days (12periods) using
a standard lactation curve for each breed (Chapter4).Theshapeofthe lactation curve
was developed on the basisofresultsofon-farmmonitoringforthree consecutiveyears.
The actual lactation curves used,are influenced bypregnancy status and (exogenously
supplied) maximum daily milk production. For localbreeds,animals areset'dry' ifmilk
production drops below 2 litre perday; maximum lactation length issetto 10months,if
animals get pregnant. Milk production canbeextended upto 12months,ifanimalsare
not pregnant and still producing significant amounts of milk.Thesame rulesapplyfor
pregnant heifers. Forbodyweight changes,acomeulative bodyweightfunction isapplied,
containing month since monitoring, initial bodyweight anddailygain assupplied bythe
user farmer. A detailedtableofpredictedmilkproductionandbodyweight isprovidedin
Appendix1.
Prediction of nutrient requirements
The model calculates the requirements for an individual animal, according to its
biological state,thenaggregates thenutrients required percategory ofanimals ineach
month. Different equations are applied to calculate the nutrient requirements for
lactating andgrowing animals.The modelpredictsenergy, protein andmineral (calcium
and phosphorus) requirements indifferent unit'se.g.g/kg DM,Mealand/or proportions
in DM requirement. Table 12 compares the predicted nutritional requirements for
various biological status using MDFMwiththosegiven by NRC(1988).Thevalues are
76
-DescriptionoftheMixedCrop-Dairy FarmingModel(MDFM)in closeagreement,exceptfor CP,wherethedifferencewas+ 1% . The reason could
be that NRC has limitationsfor livebodyweight (minimum400kg) andfat percentage
(maximum 5.5%). In MDFM such limitations havenotbeen introduced,which means
that MDFM ismoresuitablefor buffaloes andbreedsofsmallsize.
Table 12.Nutritional requirementsforvarious biologicalstatusas predicted byNRC
(1988)and MDFM
Items
Values
NRC MDFM NRC MDFM NRC MDFM NRC MDFM NRC MDFM
Animal status
10
Milk production (litre)
5
5
10
15
2
3
2
3
4
Lactation month
60
30
30
60
90
Days pregnant
400
Body weight (kg)
400
400
400
420
200
150
Daily gain (g)
200
150
100
3.7
3.7
4
4
4
Fat (%)
1
2
1
2
3
Lactation number
Predicted nutrient requirements
9.26
11
11
12.5
9.26
DM (kg)
16
13.15 13.15
16
18.9
NEL (Meal)
1037 1203 1523 1549 1930
CP(g)
34.78 34.78 49.9 49.94 65.2
Ca(g)
23.18 23.18 32.4 32.38 41.7
P(9)
5.82
5.82
7.07
7.07
8.36
TDN (kg)
21.76 22.05 26.54 26.75 31.59
ME (Meal)
25.65 25.65 31.16 31.16 36.85
DE (Meal)
15
4
90
420
100
4
3
20
6
225
480
50
4
3
20
6
225
480
50
4
3
25
8
260
550
0
4
3
25
8
260
550
0
4
3
12.53 14.91 14.91 17.34 17.34
18.97 23.18 23.18 27.49 27.49
1867 2352 2283 2771 2879
83.7 102.6 102.6
65.2
83.7
41.7
53.3
53.3
65.2
65.2
10.19
10.19
8.36
12.07 12.07
31.59 38.68 38.75 45.94 45.94
36.85 44.93 44.94 53.21 53.21
Nutrient/feeding balance
Feeding management practises are assessed bysubtractingthe required nutrientsfrom
the nutrients availablefromcultivatedfodder, crop by-products,andconservedfodder and
purchased feedstuffs. Thepredictedfeeding situation ispresented inthe model ingraph,
indicating the deficiency of nutrient availability in certain month. As for nutrient
requirements, availability of nutrients is calculated permonth,becausetheuseoffeed
balances as annual aggregates is misleading, as seasonal peaks in demand and/or
supply cannot beaccommodated. Aggregation offeeds and requirements alsoexcludes
the possibility of selective consumption,i.e. instead oftryingto utiliseallfeeds,itmaybe
advantageous not to utilise part of the (low quality) feed resources. Moreover, an
aggregate feed balance may mask a proteinorenergy excess inoneanimal category,
withadeficiency inanother.
77
Chspter4
Least cost ration formulation
Model calculations aim at minimizing the feeding costs, while meeting the nutritional
requirements of each category of animals with feed available from the own farm (fresh or
conserved) and purchased feeds, taking into account the feeding constraints and time
pattern of fodder production. Table 13 provides an example of a least cost ration for one
category (dairy cows).
The prices of the forages are calculated as the direct costs offodder production, while for
concentrates and rice straw, the market prices were used. The nutritional constraints
require that optimal diets satisfy animal requirements for dry matter, energy and protein.
In addition, constraints specify a maximum proportion (in terms of dry matter) of specific
feedstuffs inthe formulated ration (see Table 2, Chapter 4).
Table 13. Calculated least cost ration for dairy cows 1
Sep. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May Jun. Jul. Aug.
Feedstuff (kg)
Berseem
— — 6322 6240 6443 6628 6495 5588 4810 1653 — —
Rice straw
— — — — — — — 523 888 397 —
Bean straw
— — — — — — — — — 277 — 1062
Maize Silage
4080 4261 1444 1471 1194 737 370 — — 2792 2390 2316
Concentrate 3
1530 3509 — — — — — — — — — 249
Corn
— — — — — — — — — — 1096 46
Wheat bran
1870 42 — —
— 896 574
Nutrient availability (kg)
DM 2
7479 7812 7766 7711 7636 7365 6865 6111 5697 5120 4382 4247
TDN 3
5183 5438 4720 4691 4616 4406 4071 3504 3204 3234 3156 2760
CP"
941 993 1234 1223 1232 1222 1165 999 883 589 461 434
1
Dairy cows only; resultsforthe other categories arepresented inAppendix 1
2
Dry Matter (including 10%feeding losses)
3
TotalDigestible Nutrients
4
Crude Protein
The formulated ration satisfies the nutrient requirements for each category of animals
plus 10 percent losses during feeding.The ration ingredients match with the temporal
pattern of fodder production and availability, e.g. berseem cultivation starts in
September and becomes available for feeding (first cut 45-60 days after sowing,
Chapter 3) in November. Similarly, bean and rice straws become available for feeding
after harvesting. Purchased feedstuffs, can befed any time of the year.
Table 14 represents the feeding costs per category offeeds and animals. The feeding
costs per category of feed represent the cash requirements at a certain time, when
78
-Description ofthe Mixed Crop-Dairy Farming Model (MDFM)referring to external inputs. The costs per category of animals indicate the relative costs
for each category, which allows farmers to compare costs and revenues per category
of animals.
Table 14. Feeding cost(LE) per feed component and animal category
Sep. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May Jun. Jul. Aug.
Feed component
Freshforage
0
0 1958 1994 2092 2182 2223 2082 1949 1375 0
0
Straws
36 126 8 10 13 18 23 52 75 104 157 326
Conserved forage
1138 1218 355 339 271 173 91 12 6 559 1172 1195
Concentrates
3370 3069 274 119 147 179 268 236 203 283 2826 2228
Animal Categories
Milking cows
3131 3212 1589 1577 1565 1514 1415 1178 1034 946 1751 1208
Heifers 1-2 years
317 303 197 200 203 206 209 215 221 227 448 480
Males 6-12 months
465 355 283 308 328 341 354 366 377 379 757 806
Females 6-12 months
210 150 116 124 131 138 146 151 155 159 283 294
Males 3-6 months
119 89 70 77 84 90 97 104 112 119 208 210
Females 3-6 months
50 54 43 47 51 55 60 64 67 70 119 129
Calves 0-3 months
252 249 296 128 162 207 325 303 268 421 591 620
Totalfeedingcosts
4544 4412 2595 2461 2523 2552 2606 2382 2233 2321 4155 3748
Farm economics
Table 15 presents the gross value of crop and animal production and their costs over
one year.
Table 15.Gross margin of the crop-dairy farm over one year
Cash crops
Broad bean
Rice
Subtotal
Animal products
Milk
Weight gain
Subtotal
Total
Production
cost
Production
values
Gross
margin
3204
19499
22703
3479
81245
84723
275
61746
62021
20165
16306
36471
59174
25112
54973
80086
164809
4948
38667
43615
105635
79
Chapter4
References
Beranger, C. and Vissac, B., 1992. A holistic approach to livestock farming systems:
theoretical and methodological aspects. The study of livestock farming systems in
research and development framework. Proceedings of the Second International
Symposium on Livestock Farming Systems. Saragossa, Spain, 1992
Crampton, E.W., Lloyd, L.E. and Macky, V.G., 1957. The caloric value of TDN. J.Anim.
Sci. 16:541.
FPM, 1998. Farm Planning Manual, Food Sector Development Programme, Animal
Production Research Institute. Ministry of Agriculture and Land Reclamation,
Egypt.
Garrett, W. N., 1980. Energy utilization of growing cattle as determined in seventy-two
comparative slaughter experiments. Energy Metabolism, L.E. Mount, ed. Eur.
Assoc. Anim. Prod. Publ. No. 26. London: Butterworth.
Gorgensen, S.E., 1994. Fundamentals of Ecological Modelling. 2nd edition, Langkaer
Vaenge 9, DK-3500 Vaerlose, Copenhagen, Denmark.
LINDO System Inc., 1999. Chicago, USA Optimisation software "What'sBest!",
Lotus Development Corporation, 1997. Lotus 1-2-3 Release 5for Windows, USA
Moe, P. W. and Tyrrell, H. F. 1976. Estimating metabolizable and net energy of feeds. Pp.
232-237 in Proc. 1st Intern. Symp. on Feed composition,Animal Nutrient
Requirements, and Computerization of Diets, P.V. Fonnesbeck, L. E. Harris, and L.
C. Kearl, eds. Logan: Utah State University
NRC, 1988. Nutrient requirements of dairy cattle. National Research Council, Washington
DC.
Ragab, M. T. and Askr, A.A., 1958. Milk Production from Cattle and Buffaloes (in Arabic),
Maktabit El-Nahda El-Masria, Adly-Cairo
Vissac B., 1992. Livestock farming systems: Research /Development/Action. From the
developed to the developing countries, 43rd Annual EAAP Meeting, Madrid 13-17
Sept. 1992, 20p.
80
-Appendix Chapter 4-
Appendix
Table 1. Input table for land use
Crop
Berseem(longterm)
Berseem (shortterm)
Wheat area1
Wheat area2
Broad bean early
Broad bean late
Darawa area 1
Darawa area2
Fodder beafl 1
Fodder beat22
Maize (duel purpose)
Maize (for silage)
Rice (field 1)
Rice (field2)
Cotton
Crop selection and cultivation
Area
Prod.
months
Default
*
Sowing month Defaul Limitation Restricted: Optimized
Month/default
Sep Sep- - Nov Yes/No Value/ 0
40
Month/default
Sep Sep- - Nov
Yes/No Value/0
14
Nov Nov- - Dec Yes/No Value/0
Month/default
15
Dec
Month/default
Nov- -Dec Yes/No Value/0
13
Nov Nov- - Dec Yes/No Value/0
Month/default
1.2
Month/default
Dec Nov- - Dec Yes/No Value/ 0
1.0
Mar Mar- -Sep Yes/No Value/ 0
Month/default
15
Apr Mar- -Sep Yes/No Value /0
Month/default
15
Month/default
Sep Sep- - Nov
Yes/No Value /0
50
Month/default
Dec Dec- -Feb Yes/No Value /0
40
May May • -Jul
Month/default
Yes/No Value /0
3
May May • -Jul
Month/default
Yes/No Value/0
20
Month/default
May Jun - Jul
Yes/No Value/ 0
6
Month/default
Jun Jun- Jul
Yes/No Value /0
6
Month/default
Mar Mar- -Apr
0.7
Yes/No Value/0
* Default values of productivity perton (fresh matterforfodder cropandairdryfor cash crop)
perfeddan [to beused ifconfirmed byfarmers, changed incase if itdiffersthan farmer
productivity].
1 Fodder beat cultivated by seeding
2 Fodder beat cultivated by transplanting
3 MDFM allow the usersto define area per cropwithout optimization
Table 2 Input data of the growing animals per category and breed
Number
Heifer (2-3 years)
Heifer (1-2 years)
Male calves 6-12 months
Female calves 6-12 months
Male calves 3-6 months
Female calves 3-6 months
Calves 0-3 months
2
4
4
3
2
1
2
Cattle
Body Daily
weight gain
350
150
250
400
200
800
120
500
110
650
100
500
70
500
81
Number
2
2
3
2
1
1
2
Buffaloes
Body
weight
350
300
200
180
120
100
90
Daily
gain
150
120
800
150
500
500
200
-AppendixChapter4-
Table3. Inputdata ofthedairy cows/heifersstatusattheday ofvisit
Milkpr- Lactation
Days
Body
oduction
month
pregnant weight
Cattle (cows)
Cowl
Cow2
Cow3
Cow4
Cow5
Cow6
Cow7
Cow8
Cow9
Buffaloes
(cows)
Cowl
Cow2
Cow3
Cow4
10
11
12
14
25
12.5
13.5
17
20
6
5
4
2
1
4
2
4
2
7
6
7
6
4
10
2
11
0
0
X
0
0
X
0
0
X
0
0
X
0
X
0
Dry cow, heifers pregnant (cattle)
1
Heifer 1
14
17
1
Heifer 1
1
Heifer2
12
1
Heifer3
15
0
0
Heifer4
0
0
X
Dry cow, heifers pregnant (buffaloes)
1
Heifer 1
8
7
1
Heifer 1
0
Heifer2
0
0
0
X
0
0
X
0
0
X
Daily
gain
Lactation
Fat
percentage number
120
90
90
15
0
0
0
0
0
550
400
420
520
400
400
450
350
420
1
50
50
1
50
1
1
1
1
4
4
4
4
4
4
4
4
4
3
2
1
4
4
4
4
4
3
180
120
70
10
0
0
0
0
0
420
480
400
450
0
0
0
0
0.
50
20
50
50
0
0
0
0
0
7
7
7
7
0
0
0
0
0
4
4
4
4
0
0
0
0
0
270
260
270
240
0
0
390
380
380
400
0
0
100
100
1
1
0
0
4
4
4
4
0
0
1
1
1
1
0
0
290
280
0
0
0
0
390
370
0
0
0
0
100
100
0
0
0
0
7
7
0
0
0
0
1
1
0
0
0
0
82
-AppendixChapter4-
Table4. Inputdataof product pricesand productioncost perfeddan
Cash crops
Wheat
Field bean
Maize
Rice
Cotton
Animal products
Milk (buffaloes)
Milk (cattle)
Standing weight (adult)
Standing weight (growing)
Unit
Farm gate price
Production cost
Ardab
Ardab
Ardab
Darepa
Qentar
80
95
65
250
400
500
700
800
900
800
liter
liter
kilo
kilo
1.2
1
6
8
Table 5. Inputdata offeeding values,market pricesand purchased feedstuff
Feedstuff
Berseem
Darawa
Fodder beat
Corn stalk
Wheat straw
Rice straw
Bean straw
Maize silage
Fodder b. Silage
Corn stover silage
Cloverhay
Ammoniated corn stalk
Ammoniated rice straw
Ureated corn stalk
Ureated rice straw
Concentrate 1
Concentrate 2
Concentrate 3
Corn
Wheat bran
Rice bran
Mofeed
Berseem silage
Feeding values
TDN
CP
17.4%
58.7%
4.7%
66.5%
9.7%
75.0%
35.0%
5.0%
32.0%
4.7%
5.2%
42.9%
7.5%
51.0%
69.9%
9.3%
70.0%
10.0%
55.0%
6.5%
52.0%
12.5%
62.0%
8.9%
7.1%
50.0%
11.0%
50.0%
8.7%
45.0%
60.0%
12.0%
65.0%
14.0%
69.3%
16.8%
80.0%
8.5%
68.0%
16.3%
63.2%
15.6%
80.0%
8.0%
55.0%
15.0%
83
Market
price
300
250
150
30
150
45
150
250
300
65
350
45
55
60
60
460
550
670
600
700
450
350
220
Purchased
Amount
—
—
—
0
0
20
0
—
—
—
—
—
—
—
—
0
0
10
5
5
0
0
—
-AppendixChapter4Table6. Model outputofcropping plan,production andfodder conservation
Crop
Berseem long
Berseem short
Wheat early
Wheat late
Broad bean early
Broad bean late
Darawa area 1
Darawa area 2
Fodder beat (by seeds
Fodder beat (with transplanting)
Maize (duel purpose)
Maize (for silage)
Rice (field 1)
Rice (field 2)
Cotton
Land use(2season)
Area
(feddan)
25.8
0
0
0
4.2
0
0
0
0
0
0
8.3
0
21.7
0
30
Sowing Main
By
month product product
Sep
94.6
0
0
0
0
0
0
0
0
0
0
Nov
5.1
4.2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
May
0
0
0
0
0
Jul
130.6
21.7
0
0
0
conservation
Hay silage
0
71.7
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
33.1
0
0
0
0
0
0
Table 7. Predicted Milk Production for cattle's and buffaloes
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Total Body weight
Milk initial final
Cattle (cows)
Cow 1 10 9.1
7.8 7.2 5.8 0.0 0.0 0.0 0.0 0.0 0.0 1196 550 550.3
Cow 2 11 10.2 10.0 9.1 7.8 7.2 5.8 0.0 0.0 0.0 0.0 1830 400 416.5
Cow 3 12 11.2 10.9 9.9 8.5 7.8 6.3 0.0 0.0 0.0 0.0 1996 420 436.5
Cow4 14 13.6 12.8 11.9 11.6 10.6 9.1 8.3 6.7 0.0 0.0 2957 520 520.3
Cow 5 25 29.4 28.4 26.9 25.0 24.4 22.2 19.1 17.5 14.1 0.0 6956 400 416.5
Cow6 12.5 11.6 11.3 10.3 8.9 8.1 6.5 0.0 0.0 14.1 0.0 2501 400 400.3
Cow 7 13.5 13.1 12.4 11.5 11.2 10.2 8.8 8.0 6.5 0.0 0.0 2852 450 450.3
Cow 8 17.0 15.8 15.4 14.0 12.1 11.1 8.9 0.0 0.0 0.0 0.0 2828 350 350.3
Cow 9 20.0 19.4 18.3 17.0 16.6 15.1 13.0 11.9 9.6 0.0 0.0 4225 420 420.3
Buffaloes (cows)
4.7 3.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 591 420.0 436.5
Cow 1 6.0 5.2
Cow 2 7.0 6.4
5.5 5.0 4.0 0.0 0.0 0.0 0.0 0.0 0.0 837 480.0 486.6
9.1 8.3 7.1 6.5 5.2 0.0 0.0 0.0 0.0 1664 400.0 416.5
Cow 3 10.0 9.3
Cow4 11.0 10.6 10.1 9.4 9.1 8.3 7.1 6.6 5.3 0.0 0.0 2324 450.0 466.5
0.0
0.0
Cow 5 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0
0.0
Cow 6 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0
0.0
Cow 7 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0
0.0
Cow 8 0.0 00
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0
0.0
Cow 9 0.0 0.0
84
Pregnantheifers(cattle)
Heif.1 14.016.5 18.7
20.1
Heif.2 17.020.022.7
24.4
Heif.3 12.014.1 16.0
17.2
Heif.4 0.015.0 17.6
20.0
Heif.5 0.00.00.0
0.0
Pregnantheifers(buffaloes)
Heif.1 0.08.09.4
10.7
Heif.2 0.07.08.2
9.4
Heif.3 0.00.00.0
0.0
0.0
Heif.4 0.00.00.0
Heif.5 0.00.00.0
0.0
20.1
24.4
17.2
21.6
19.6
23.8
16.8
21.6
17.4
21.1
14.9
21.0
13.3
16.1
11.4
18.6
9.3 5.2 0.0 0.0 390.0
11.3 6.3 0.0 0.0 380.0
8.0 4.5 0.0 0.0 380.0
14.2 10.0 5.6 0.0 400.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
11.5 11.5 11.2 9.9
10.1 10.1 9.8 8.7
7.6
6.6
0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0
5.3
4.6
0.0
0.0
0.0
3.0
2.6
0.0
0.0
0.0
0.0
423.0
413.0
380.3
400.3
0.0
0.0 390.0 423.0
0.0 370.0 403.0
0.0 0.0 0.0
0.0 0.0 0.0
0.0 0.0 0.0
Table8.Predicted nutrientrequirementsfordifferentcategories ofanimals
Jan Feb Mar Apr May Jun Jul Aug Sep
Dairycowsandpregnantheifers
DM
6799 7101
7060 7010 6942 6695 6241 5555
TDN 4441 4730
4720 4691 4616 4406 4071 3504
1050 1049 1034 978 892 759
CP
997 1061
Heifers(1-2years)
DM
926 960
995 1031 1068 1106 1144 1184
614 632 651 669 688 708
TDN
578 596
119 124 128 133 137 142
CP
111 115
Male(6-12 months)
DM
1046 1148
1251 1358 1467 1580 1697 1819
TDN
701 761
821 881 941 1003 1065 1128
CP
154 162
170 178 187 195 204 218
Female(6-12 months)
DM
456 486
517 547 578 610 643 676
TDN
307 325
343 361 379 398 416 434
76
78
CP
69 72
74
81
83
85
Male(3-6months)
DM
258 287
316 344 373 402 432 462
TDN
180 198
216 234 252 269 287 304
53
56
58
60
63
CP
46 49
51
Female(3-6months)
DM
158 175
193 210 228 245 264 282
TDN
109 120
131 141 152 162 173 183
37
32
33
34
36
CP
28 29
30
Calves(0-3months)
DM
505 560
614 266 340 458 755 741
TDN
354 393
430 186 237 317 519 506
115 49
61
CP
105 110
78 124 117
85
Oct
Nov Dec
5179 4654 3983 3861
3204 2803 2282 2159
687
589
461
434
1225 1267 1311 1355
727
147
747
152
768
157
789
163
1945 2077 2216 2361
1192 1258 1326 1396
233
249
266
283
709
452
88
744
471
90
780
489
94
816
508
98
492
321
65
523
339
67
555
356
70
588
374
72
301
193
39
321
204
40
341
215
41
361
226
43
668 1143 1210 1277
454 768 808 847
103 167 172 177
-AppendixChapter4-
Table9.1 leastcost rationformulation fordairy cows
Jan Feb
6443 6628
0.0
0.0
0.0
0.0
0.0
0.0
Corn stalk
0.0
0.0
Wheat straw
0.0
0.0
Rice straw
0.0
0.0
Bean straw
1194 737
Maize silage
0.0
0.0
F. beat silage
0.0
0.0
Stover silage
0.0
0.0
Berseem silage
0.0
0.0
Clover hay
0.0
0.0
Ammoniated stalk
0.0
Ammoniated straw 0.0
0.0
0.0
Ureated m. stalk
0.0
0.0
Ureated r. straw
0.0
0.0
Concentrate 1
0.0
0.0
Concentrate 2
0.0
0.0
Concentrate 3
0.0
0.0
Corn
0.0
0.0
Wheat bran
0.0
0.0
Rice bran
0.0
0.0
Mofeed
Nutrients availability (kg)
7636 7364
DM (+10%)
4616 4405
TDN
1232 1222
CP
Berseem
Darawa
Fodder beat
Mar Apr May Jun
Jul
Aug Sep Oct Nov Dec
6495 6111 5697 1704 0.0
0.0
0.0
0.0 6321 6240
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
622
0.0
0.0
0.0
0.0
0.0
0.0
7.9
0.0
0.0
0.0
1062 1529 0.0
0.0
0.0
0.0
0.0
369
0.0 2793 2390 2316 4079 4261 1444 1471
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
843 788.0 0.0 3177 0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0 1141 80.7
0.0
0.0
0.0
1869 374
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
6864 6111 5697 5119 4381
4071 3587 3344 3219 3171
1164 1063 991 588 461
86
4246
2771
434
7479 7811 7766 7711
4903 5434 4720 4691
798 991 1234 1222
-AppendixChapter4Table9.2 leastcost rationformulation for heifersaged 1-2 years
Berseem
Darawa
Fodder beat
Corn stalk
Jan
928
0
0
0
0
246
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Wheat straw
Rice straw
Bean straw
Maize silage
F. beat silage
Stover silage
Berseem silage
Clover hay
Ammoniated stalk
Ammoniated straw
Ureated m. stalk
Ureated r. straw
Concentrate 1
Concentrate 2
Concentrate 3
Corn
Wheat bran
Rice bran
Mofeed
Nutrients availability (kg)
1175
DM (+10%)
651
TDN
174
CP
Feb
934
0
0
0
0
282
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Mar
944
0
0
0
0
315
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Apr
977
0
0
0
0
326
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
May Jun
1011 1045
0
0
0
0
0
0
0
0
337 348
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
786
0
0
0
0
0
0
0
0
0
0
4
291
360
0
0
Aug
0
0
0
0
0
0
269
813
0
0
0
0
0
0
0
0
0
0
36
0
373
0
0
Sep
0
0
0
0
0
0
182
555
0
0
0
0
0
0
0
0
0
0
27
0
255
0
0
Oct
0
0
0
0
0
0
204
576
0
0
0
0
0
0
0
0
0
0
276
0
0
0
0
Nov
912
0
0
0
0
183
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Dec
921
0
0
0
0
213
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1216 1259 1302 1347 1394 1442
669 689 713 738 763 1030
187
157
177
181
193 200
1491
984
163
1018
672
111
1056 1095
698 614
115
168
1134
632
171
87
Jul
0
0
0
0
-AppendixChapter4-
Table9.3 leastcostrationformulationfor malecalvesaged6-12 months
Jan Feb Mar Apr May Jun
Jul
1614 1626 1813 1921 2031 1653
0
Berseem
0
0
0
0
0
0
0
Darawa
0
0
0
0
0
0
0
Fodder beat
0
0
0
0
0
0
0
Corn stalk
0
0
0
0
0
0
0
Wheat straw
0
0
0
571
0
0
113
Rice straw
439
0
0
0
0
0
0
Bean straw
0
0
0
61
1330
0
0
Maize silage
0
0
0
0
0
0
0
F. beat silage
0
0
0
0
0
0
0
Stover silage
0
0
0
0
0
0
0
Berseem silage
0
0
0
0
0
0
0
Clover hay
0
0
0
0
0
0
0
Ammoniated stalk
0
0
0
0
0
0
0
Ammoniated straw
0
0
0
0
0
0
0
Ureated m. stalk
0
0
0
0
0
0
0
Ureated r. straw
0
0
0
0
0
0
0
Concentrate 1
0
0
0
0
0
0
0
Concentrate 2
0
0
60
0
0
0
0
Concentrate 3
0
0
0
0
0
0
0
Corn
609
0
0
0
0
0
0
Wheat bran
0
0
0
0
0
0
0
Rice bran
0
0
0
0
0
0
0
Mofeed
Nutrients availability (kg)
1614 1738 1813 1921 2031 2285 2437
DM (+10%)
947 1003 1065 1128 1192 1258 1609
TDN
353 323 266
281 289
316 334
CP
88
Aug
0
0
0
0
0
0
0
1417
0
0
0
0
0
0
0
0
0
0
617
563
0
0
0
Sep
0
0
0
0
0
0
0
527
0
0
0
0
0
0
0
0
0
0
624
0
0
0
0
2597
1869
283
1151 1262 1377
801 875 821
154
162 230
Oct
0
0
0
0
0
0
0
662
0
0
26
0
0
0
0
0
0
0
574
0
0
0
0
Nov Dec
1260 1455
0
0
0
0
0
0
0
0
0
0
0
0
39
116
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1494
881
257
-AppendixChapter4-
Table9.4 leastcost rationformulation forfemale calvesaged6-12 months
Berseem
Jan
583
0
0
0
0
0
0
53
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Feb
640
0
0
0
0
0
0
31
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Mar
700
0
0
0
0
0
0
7
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Apr
728
0
0
0
0
15
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
May
780
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Jun
818
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Jul
0
0
0
0
0
0
147
468
0
0
0
0
0
0
0
0
0
0
28
0
214
0
0
Aug
0
0
0
0
0
0
0
490
0
0
0
0
0
0
0
0
0
0
8
176
224
0
0
Sep
0
0
0
0
0
0
0
201
0
0
0
0
0
0
0
0
0
0
301
0
0
0
0
Oct
0
0
0
0
0
0
0
233
0
0
45
0
0
0
0
0
0
0
256
0
0
0
0
Nov
481
0
0
0
0
0
0
88
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Dec
530
0
0
0
0
0
0
72
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
106
671
398
114
707
416
122
743
434
127
780
458
136
818
480
142
858
567
94
898
641
98
502
349
69
535
366
72
568
343
92
602
361
99
Darawa
Fodder beat
Corn stalk
Wheat straw
Rice straw
Bean straw
Maize silage
F. beat silage
Stover silage
Berseem silage
Clover hay
Ammoniated stalk
Ammoniated straw
Ureated m. stalk
Ureated r. straw
Concentrate 1
Concentrate 2
Concentrate 3
Corn
Wheat bran
Rice bran
Mofeed
Nutrients availability (kg)
DM (+10%)
636
TDN
379
CP
89
-AppendixChapter4-
Table9.5 leastcost rationformulationfor malecalvesaged3-6 months
Berseem
Darawa
Fodder beat
Corn stalk
Wheat straw
Rice straw
Bean straw
Maize silage
F. beat silage
Stover silage
Berseem silage
Clover hay
Ammoniated stalk
Ammoniated straw
Ureated m. stalk
Ureated r. straw
Jan
313
0
0
0
0
0
0
97
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Concentrate 1
Concentrate 2
Concentrate 3
Corn
Wheat bran
Rice bran
Mofeed
Nutrients availability (kg)
DM (+10%)
410
TDN
252
CP
64
Feb
357
0
0
0
0
0
0
85
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Mar
405
0
0
0
0
0
443
269
70
0
70
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Apr
455
0
0
0
0
0
0
53
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
May
509
0
0
0
0
0
0
32
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Jun
567
0
0
0
0
0
0
8
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Jul
0
0
0
0
0
0
0
333
0
0
0
0
0
0
0
0
0
0
0
189
89
0
0
Aug
0
0
0
0
0
0
98
353
0
0
0
0
0
0
0
0
0
0
35
0
162
0
0
Sep
0
0
0
0
0
0
0
155
0
0
0
0
0
0
0
0
0
0
0
58
71
0
0
Oct
0
0
0
0
0
0
65
172
0
0
0
0
0
0
0
0
0
0
0
0
79
0
0
Nov
234
0
0
0
0
0
0
113
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Dec
272
0
0
0
0
0
0
107
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
475
287
77
508
304
84
541
576
339
99
611
444
62
646
430
72
284
203
31
316
207
34
347
216
51
379
234
57
321
92
90
—AppendixChapter4-
Table9.6 leastcost rationformulation forfemale calvesaged3-6 months
Jan Feb Mar Apr May Jun
Berseem
208 237 269 303 331 353
Darawa
0
0
0
0
0
0
Fodder beat
0
0
0
0
0
0
Corn stalk
0
0
0
0
0
0
Wheat straw
0
0
0
0
0
0
Rice straw
0
0
0
0
0
0
Beanstraw
0
0
0
0
0
0
Maize silage
42
21
7
0
32
0
F. beat silage
0
0
0
0
0
0
Stover silage
0
0
0
0
0
0
Berseem silage
0
0
0
0
0
0
Clover hay
0
0
0
0
0
0
Ammoniatedstalk
0
0
0
0
0
0
Ammoniatedstraw
0
0
0
0
0
0
Ureated m. stalk
0
0
0
0
0
0
Ureatedr.straw
0
0
0
0
0
0
Concentrate1
0
0
0
0
0
0
Concentrate2
0
0
0
0
0
0
Concentrate3
0
0
0
0
0
0
Corn
0
0
0
0
0
0
Wheat bran
0
0
0
0
0
0
Rice bran
0
0
0
0
0
0
Mofeed
0
0
0
0
0
0
Nutrients availability(kg)
DM (+10%)
250 270 290 310 331 353
TDN
152 162 173 183 194 207
CP
53
58
40
44
49
61
91
Jul
0
0
0
0
0
0
63
204
0
0
0
0
0
0
0
0
0
0
14
0
94
0
0
Aug
0
0
0
0
0
0
72
217
0
0
0
0
0
0
0
0
0
0
10
0
99
0
0
Sep
0
0
0
0
0
0
36
95
0
0
0
0
0
0
0
0
0
0
0
0
43
0
0
Oct
0
0
0
0
0
0
48
105
0
0
0
0
0
0
0
0
0
0
0
0
39
0
0
Nov
155
0
0
0
0
0
0
57
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Dec
181
0
0
0
0
0
0
50
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
375
248
41
397
262
43
174
114
19
193
125
20
212
131
32
231
141
36
-AppendixChapter4-
Table9.7 leastcostrationformulation for calvesaged0-3 months
Jan
Berseem
69
Darawa
0
Fodder beat
0
Corn stalk
0
Wheat straw
0
Ricestraw
0
Beanstraw
0
Maize silage
0
F. beat silage
0
Stover silage
0
Berseem silage
0
Clover hay
0
Ammoniatedstalk
0
Ammoniatedstraw
0
Ureatedm. stalk
0
Ureatedr. straw
0
Concentrate1
0
Concentrate2
0
Concentrate3
0
Corn
246
Wheat bran
0
Rice bran
0
Mofeed
0
Milk (fresh)
500
Nutrients availability(kg)
DM(+10%)
375
TDN
237
CP
33
Apr
624
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
95
0
0
0
800
Feb
134
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
298
0
0
0
600
Mar
699
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
24
0
0
0
900
May
51
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
520
80
0
0
0
700
504
317
49
830 815 734 12581331 1405 555
429 442 454 768 842 893 354
124 117 103 167 172 177 38
92
Jun Jul Aug Sep
525
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
418 511 41
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
282 793 730
406
331
0
0
44
0
0
0
0
0
0
0
0
0
0
0
10001000 1000 900
Oct Nov Dec
0
111 47
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
140
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
369 456 198
0
0
0
0
0
0
0
0
0
900 900 400
616 675
393 430
44
58
293
186
25
-AppendixChapter4-
Table 10.Feedingcostpercategory offeedsandanimals
Jan
Feedcategories
Forage
Straws
Conservedforage
Treated straws
Concentrates
AnimalCategories
Milkingcows
Heifer 1-2 years
Male6-12 months
Female6-12 months
Male 3-6 months
Female 3-6 months
Calves0-3 months
Overall
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Dec
1904 1978 2122 2084 1951 1249
0
0
0
0
1776
11
14
18
15
15
69
99
225 262
48
8
111
330 211
14
8
681 1411 1455 1345 1479 432
0
0
0
0
0
0
0
0
0
0
0
147
179
14
57
396 388 3096 2613 2483 3435 274
1808
10
414
0
119
1491 1417 1305 1145 1068 1012 1819 1287 2509 3404 1528 1519
191 198 205 212 617 519 355 352
185
188
179
182
302 310 340 360 381 350 849 1089 543
548 264 282
122
127
133
137
153 302 384 249 237
116
146
111
82
87
93
98
108 255 235
106
76
103
122
71
46
49
52
55
59
62
66
138
58
60
43
133
127
160 204
145
174 406 486 631 642 254 254 294
2392 2386 2262 2170 2370 2387 4605 4293 4090 4962 2490 2349
Table 11. Farmeconomics
Production
value
cost
Crop
Wheat
Broadbean
Maize
Rice
Cotton
Subtotal
Animalproducts
Milk
Bodygain
subtotal
Total
Nov
Gross
margin
0
2955
0
19553
0
22508
0
3208
0
81471
0
84678
0
253
0
61918
0
62171
19505
17251
36756
59264
25112
54973
80086
164764
5608
37722
43330
105501
93
Chapter5
Factors Influencingthe FermentationCharacteristics ofMaizeSilages
On-farm
A.Tabana1,S.Tamminga2,H.vanKeulen3andI.Gomaa1
1
Animal Production Research Institute.P.O. Box443,Dokki,Giza,Egypt
department ofAnimal Science,Wageningen InstituteofAnimalSciences,
Wageningen-UR, P.O. Box338,NL6700AHWageningen,The Netherlands
The Netherlands
3
Agrosystems Department, Plant Research International,Wageningen-UR, P.O. Box
16, NL6700AAWageningen,The Netherlands
(Submittedfor publication)
-Chspter5-
Factors Influencing the Fermentation Characteristics of Maize Silages O n Farm
Summary
One hundred and fifty five samples of maize silages made on-farm were taken during
the filling of silos or after a certain time of ensiling. Silage quality was determined
through visual inspection and on the basis of chemical composition, and related to: 1)
Length of chopped materials that resulted from four different types of choppers; 2)
variety, three maize varieties were included; 3) stage of maturity, age varying from 60
to 137 days at harvesting; 4)proportion of ears remaining with the stalks in tenns ofO,
25, 33, 50, 66, 75 and 100% of the total grain yield; 5) length of ensiling period from 0
to 90 days.; 6) length of the period since opening of the silo, from 0 to 60 days. The
impact of each individual factor was identified quantitatively and regression equations
were formulated. Good quality silages were obtained, indicating adequate preservation
for all silages. The highest qualities corresponded to whole-plant maize (without
removing ears), ensiled at an average age of 108 days, after 17days of fermentation,
and, up to 45 days off-take feeding period (opening of the silo). Variety and type of
chopper used in this study, had no significant effect on silage quality. The measured
fermentation characteristic pH, lactic, acetic, propionic, butyric, iso-butyric, valeric, isovaleric, total volatile fatty acid and NHj/total N incorporated agreed well with the visual
characteristics.
(Key words: maize silage, quality, fermentation characteristics)
Introduction
Animal feed resources in Egypt are a major limiting factor in exploiting the genetic
potential of improved livestock. The type of feed resources that are conventionally
available (primarily crop residues and other poor quality roughages) are of insufficient
quality to meet their nutritional requirements. Most of these materials are low in protein
and highly fibrous.
Many options have been presented to smallholder farmers to overcome the quantity
and quality limitations of conventional feeds, such as the use of hybrid forage crops,
chemical treatment of roughages and forage conservation. They have been introduced
with varying degrees of success. Maize silage, which has in recent years been widely
adopted on large-scale dairy farms in Egypt, has on a limited scale also been promoted
with smallholder farmers.
The potential benefits as indicated by on-station
experiments, and the initially positive on-farm response to the technology, suggests
that it could be adopted more widely.
96
-Thefermentationcharacteristicsofmaizesilagesonfarm-
It isunfortunatethat muchofthe knowledge onfeed utilization has not reachedfarmers
for extensive adoption, sothatthetechnologiesthat aretransferredtothefarmers are
often notadopted inthemostoptimalway.
To ensure that on-station technicalfeasibility studies arerelevant, moreaccurateonfarm information is neededonthequality offeedresources andthetreatmentsapplied.
Even iftheoriginal materialwasofgoodquality, itmayhave been poorlyconserved.
The aim of this studywastoevaluatethequality ofmaizesilage prepared byfarmers,
in comparison to on station prepared silage, and to quantitatively identify factors
influencingthequality ofthesilageon-farm.
Materials and Methods
The quality ofon-farm maizesilagewasassessed incomparisonwithcharacteristics of
on-station maizesilage,prepared understandard conditions.Theon-farmsilageswere
represented byone hundredandfiftyfivesamplescollectedfromdifferent locations.
On-station silage making (control)
Whole white maize plants (hybrid, Giza 310) were harvested at different stages,
chopped andconserved ina"threewall"concrete silo.The innersurface ofthesiloand
the top of the chopped material were covered with plastic sheets. Thesilagewas
sampledfor analysis after 90days.
On-farm silage making/sample collection
Sampling. In an earlier survey1, 994 farmers hadbeen identifiedthat had prepared
silage. Hence, the sample (155) represents 16.4% of the total population. The
respondents arespreadover 13villages inAshmondistrict, situated inthe Governorate
of Monofia; in each village, silage of 12 different farmers was sampled. The
respondents were randomly selectedfromthevillages. Semi-structured interviews with
questionnaire were used to collect relevant data for identifying and classifying the
collected samples. Table 1 summarizes thefactors influencing silagequality andthe
number ofsamples identifiedforeachfactor inthevariousvillages.
'The cooperative authorities inAshmon and Monofiagovernorate identified atotalof
994smallholder farmers having prepared maizesilage.
97
-Chapter 5-
Sampling and chemical analysis
Representative samplesweretakenduringthefillingofsilosand/or after acertaintime
of ensiling. The sampleswere stored inanicebox,transferredtothe laboratory, dried
in an oven at 60°Cforabout48 hours,groundtopassasieveof 1mm,for proximate
chemical analysis, following the conventional methodsofA.O.A.C (1984). Silagedry
matter (DM) contentwasdeterminedfollowing oven
Table 1.Factors influencingsilagequality anddescription ofvariation
Factor
Typeofmachine used1
Description
Twotypesofimportedchoppersandtwotypesoflocal
choppers
Varieties
Whitemaize(hybrid),Yellow maize(hybrid) and
traditional variety
Stage ofmaturity
60to 137daysafter sowing
Fraction ofgrain used
0,25,33,50,66,75and 100%ofthetotalgrainyield*
Ensiling duration2
1 to90days
Off-takefeeding period3 0to60daysopenattimeofsampling
1
lengthofchopped material,2timebetweenensiling andopening,3timefrom opening
to sampling
drying at 105°C for 24 hours. The fresh silage samples were analyzed in water
extracts, prepared byextracting 100gofhomogenizedwet materialwith200 mlof99%
water +1% ortho-phosphoric acid (v/v). The homogenate was filtered throughtwolayers of cheese cloth and used for pHdetermination. Forvolatilefatty acids (VFA)
analysis, 20 mlofthefiltrated homogenate plus20mldiethyletherweretransferredto
a separationfunnel andafter shaking,the upper layerwascollected inatesttube.The
procedure of adding diethyl ether was repeatedthreetimes untiltheether remained
colorless.Alletherwas banded/collected inonetesttube. Halfamlofde-ionized water
was added, andthetesttubewasshaken using avortex mixer. Thesolutionwasthen
transferred toafreezer untilthe lower layer becamefrozen,allowingthe upper layerto
be removed easily. The aqueous fraction remaining in the test tube was usedto
analyzeforVFA by HPLC underthefollowing conditions:
Columns:
Wavelength:
Mobile phase:
Flowrate:
Injectionvolume:
Rezex organic acid30x4.6mm(Phynomenix, USA)
210nm
1%ortho-phosphoric acid inwater
0.5ml/min
20ul
98
-Thefermentation characteristics ofmaize silages onfarm-
Chemical and visual evaluation
Silage quality was estimated visually by examining the external characteristics of the
material. Properties, such as color, odor and general appearance are useful indicators
of expected overall silage quality. Visual evaluation will not provide accurate
information on nutrient content of silage; that can only be estimated accurately through
chemical analysis. However, in combination with chemical analysis of the ensiled
materials and the fermentation characteristics, it can lead to accurate evaluation of the
silage quality. Table 2 presents the set of visual and chemical characteristics used to
evaluate the maize silages. These suggestions originate from the cited references or
from direct observation by the authors.
Table 2. Preservation quality and characteristics of maize silages 1
Characteristic Good
Visual
Color
Light green
Smell
Intermediate
Poor
Yellowish green
Brown to
Yellow to
brown
black
Butyric acid
Strong butyric
and strong
acid, odor
ammonia smell rancid
Soft tissues
Compost
easily rubbed
from fibre
Fermented
fruits/slight old
cheese smell
Firm, with soft
material not
easily rubbed
from fibre
Acetic acid/slight
butyric acid/slight
ammonia
Soft materials can
be separated from
fibre
Chemical
Moisture
65 to 70 %
Tends to be below
65%
pH
Lactic acid 2
Total VFA 2
Acetic acid 2
Propionic acid2
Butyric acid 2
Ammonia 3
3.9to 4.2
25 to 80
Below 60
Below 40
Less than 5
Below 5
Below 10
4.0 to 4.6
20 to 60
60-100
40-55
5-10
5-15
10-15
Texture
1
Tends to be
above 70 or
below 50%
4.8 to 5.2
Below 25
100-140
55-75
•7-15
15to 20
15-20
Very poor
Tends to be
above 70% or
below 50%
5.0 to 5.7
Below 25
Exceeding 140
Exceeding 75
Exceeding 15
Exceeding 20
Exceeding 20
ModifiedfromTabana, 1994;van Osand Dulphy, 1996;Langstone et al., 1992; McDonald,
1981; McDonald et al., 1991.2 Acetic, Propionic, Butyric andTotalVolatile FattyAcids are
measured ing/kg dry matter.3 NH3-N :Total-N in g/kg
99
-Chapter5-
Classification ofchopped materials
Representative samples (250 g each)offreshorensiledmaterialwereclassified into
four categories according tothe lengthofchoppedmaterials (Table3)
Table 3.Classification ofchopped materials
Class
Length (cm)
Fine
Small
Medium
Coarse
0-0.6
0.6-3.5
1-4
>4
Main materials within classes
All fine stuff, including the grain
Leaves, stems and cobs
Pith
Mainly leaves and tops
Results and discussion
Many factors affectthechemicalcomposition offorages andconsequently theirsilages.
Six major factors affect the fermentation characteristics andquality ofsilage, ranked
according totheir impact onsilagequality: 1)variety,2)proportion ofgrains leftwiththe
stover before ensiling, determining the content ofsoluble carbohydrates, 3)stageof
maturity or stage of growth in terms of plant development, acommonmeasurefor
describing forage quality, and plant age (lengthofperiodfromsowingtocutting has
been used for thesamepurpose) (VanSoest, 1994),4) lengthofensilingtime,5)offtakefeeding period,6)lengthofchopped materials.
Results indicatedthat nosignificant differences inCF,NFEandashcontentwerefound
in the silages ofthedifferent varieties (Table4).CPand EEcontentwere significantly
higher insilagesfromyellow maizethan inthosefromtheothervarieties.
Table4. Chemical composition ofensiledvarieties ofmaize.
No.* * of %of Av. age Av. Av. Days CP
Variety samples ears
of days of left at g/kg
maize fermen- sampling
(day) tation
EE
g/kg
CF
g/kg
NFE
g/kg
Hybrid
130
84
103
36
12 74.6 b 18.3b 286a 525.8a 94.7 a
Yellow
9
100
93
58
23 84.7a 23.0a 268a 527.1a 96.9 a
Baladi
16
87
98
43
16 72.3b 18.8b 271 a 543.8a 93.5 a
Control
1
100 100
30
30 76.7b 21.2b 279a 526.5a 96.3 a
*a/b Means inthesamecolumn havingdissimilar superscripts differ significantly
(P<0.05).
** Each sample representsonefarmer.
100
Ash
g/kg
-Thefermentationcharacteristicsofmaizesilagesonfarm-
These differences may berelatedtointrinsic properties ofthevariety and/orthey may
be associated with other factors, such as the fractionofears included inthe silage
and/or theageofthe maize.This isillustrated inTable5,wherethepercentageofears
or yield of grains removed beforeensiling isgiven.Thesedatashowthat CPandEE
markedly decreased with the percentage of earsremovedforensiling.Theopposite
trend holdsfor CFcontent.
The linear regressions between percentage ofears inthesilageand nutrient contents
are shown in Figure 1 for CP, Figure2for EE,Figure3forCFand Figure4forNFE.
Thecorresponding equationsare:
YCP=48.226+0.3118X
YEE =12.855+0.0679X
Y C F = 321.25-0.4354X
YNFE =522.9 +0.0543X
(R2=0.4022)
(R2=0.1409)
(R2=0.1928)
(R2=0.0029)
WhereX= percentage ofears removed beforeensiling
Fig.1
400
350
300
5 250-
s
a.
O 40
a
I200
o
150
101
Chapter5
Table 5. Percentage of maize ears removed before ensiling and proximate
chemical composition of silages.
% ofears
removed
100
75
66
50
33
25
0
Noof Av. ageof
.
samples maize
(day)
3
2
8
21
3
4
114
Av d a
- y s Av. Days
offermen- . ~ .
.
leftat
sampling
117
105
103
103
102
98
101
27
30
39
33
30
46
39
17
13
10
10
13
13
14
CP
EE
g/kg
g/kg
CF
g/kg
NFE
g/kg
56.9 9.9 329.3 504.8
59.4 7.9 306.7 541.8
54.8 15.7 297.3 538.4
62 18 300.3 524
73.9 15.3 311.1 510.7
76 17.4 293 519.9
79.5 19.6 277.4 528.6
Moreover, the age of maize plants (or rather their phenological stage) at ensiling affects
nutrient availability before and after fermentation (Table 6). The data indicate that CP
and NFE decrease as age increases. This decline is related to the fact that at an early
age mostly cell content is produced, and with increasing age more and more cell walls
(Argillier et al., 1995; Bal et al., 1997).While CF and EE increase with age, the fibre
content declines at early stages of maturity, because the proportion of grain in the
silage increases. At later stages of maturity, the increase infibre inthe stalks offsets
any increase inthe proportion of grain (Bal et al., 1997). Similar trends for fibre content
have been reported by Flachowsky et al., 1993;Wiersma etal., 1993 and Xu etal.,
1995. These relationships are presented in Figures. 5, 6, 7 and 8for CP, EE, CF and
NFE, respectively. The associated regression equations are:
Y CP = 90.808-0.1559 X
Y EE = 15.1507 + 0.0311 X
Y C F = 196.67 + 0.8581 X
Y NFE = 598.79 - 0.6999 X
(FT = 0.0384)
(R2 = 0.0112)
(R2 = 0.2855)
(R2 = 0.1848)
Where, X= age of maize (d) at ensiling.
I i1 ' t - j
90
100
110
120
130
Age(day)
102
Ash
g/kg
99.1
84.2
93.8
95.7
89
93.7
94.9
-Thefermentationcharacteristicsofmaizesilagesonfarm-
700>
600
500
H S:»ii*:\ fr*i |
° 400
I 3o
nr °
Z
200.
With regard to theeffect ofensilingtime length (indays),after20daysofensiling,the
chemical composition of maize silages tends to stabilise. The data that shown in
Appendix 1indicatedthat lengthofensiling hasarelatively smalleffect.
Table6. Proximate chemical composition ofmaizesilageasafunction ofageat
ensiling.
Av. age
of maize
(day)
60-70
71-80
81-90
91-100
101-110
111-120
121-130
130-140
No.of
samples
5
14
35
26
24
46
3
2
Av. Av. Days
% Av. age
days of
ears
of
leftat
fermenmaize tation sampling
—
27
68
10
33
13
95
78
90
89
40
17
14
82
98
37
78
108
34
11
86
119
40
12
34
4
83
128
46
7
100
136
CP EE
(g/kg) (g/kg)
(g/kg) (g/kg) (g/kg)
72.1
81.1
79.8
72.1
72.5
73.0
70.1
70.5
255.3
255.0
273.9
287.9
288.9
296.8
309.1
294.5
18.4
17.5
18.7
17.5
18.1
20.1
15.8
18.8
CF
NFE
Ash
554.3 99.9
551.2 95.2
531.0 96.6
533.3 89.2
524.4 96.1
515.5 94.6
509.6 95.4
514.3 101.9
Fermentation characteristics
The fermentation quality of silages can be characterized by their fermentation
characteristics (vanOs, 1997),organicacids,volatilefatty acidsandammonia (NH3).
Variety
Very large differences in fermentation quality among silagesfromdifferent varieties
were expected. The protein (CP) and lipid contents (EE) (Table4) inyellow maize
were higher than those in hybrid and Baladi. However, these differences in
103
-Charter 5-
fermentation quality were not found, This might be due to other factors such as 1)
significant quantity of grain that may increase slightly with maturity, as grain content
increases inthe plant, 2) insect pests that can reduce forage quality, particularly if they
cause significant leaf loss, 3) plant diseases can affect quality when they result in a
shift in the varieties present in the field and when they accelerate leaf senescence.
Insect pests and diseases generally have their strongest impact on yield and
persistence of forages.
Fermentation characteristics of silages of the different varieties tend to be within the
range associated with good quality silage (Appendix 2).
Percentage of ears remaining inthe stover
One of the main factors that influences silage quality isthe rate of pH decline in the
early stages of fermentation (Heron et al., 1989; Merry etal., 1993; Williams etal.,
1992). This pH decline is related to the rate of lactic acid production,which, in turn, is
determined by the activity of the natural lactic acid bacterial population and the content
and composition of water soluble carbohydrate (WSC) in the forage (Davies etal.,
1998). The WSC concentration inthe forages is strongly correlated with the percentage
of ears remaining with the stover. Table 7 and Figures 9 and 10 show the relationship
between fermentation characteristics and percentage of ears. It was expected that
silage quality would increase with an increased proportion of grains: Lactic acid content
markedly increased with increased ear contribution, pH and other fermentation
characteristics, however, markedly decreased. Protein degradation, indicated by the
ratio of ammonia nitrogen to total nitrogen content, increased with decreased ear
contribution, as at higher pH,deamination is carried out largely by Clostridia bacteria
(Ohshima and McDonald, 1978; Makoni et al., 1997). The level of lactic acid was
negatively correlated to the other fermentation characteristics.
Y pH
= 5 . 1 6 - 1 . 8 3 3 X +0.8722 X 2
(R2 = 0.2141)
YLacticadd
Y Total VFA
= 59.8 - 2 9 . 8 7 2 X
Y N H S - N : total-N
= 236.18 - 102.29 X
YAceticacid
Y Propionicacid
(R 2 = 0.1723)
= 6.29 + 37.466 X
(R 2 = 0.1257)
(R 2 = 0.4929)
= 80.971 - 132.3 X + 80.126 X
= 4 . 8 2 4 - 7.8908 X + 4 . 7 4 8 5 X
= 1.5168 - 2.5659 X + 1.3896 X
Y isobutyricadd
= 0.4 - 0.7962 X + 0.4241 X 2
Y isovalericacid
(R 2 = 0.2094)
2
(R 2 = 0.2372)
(R 2 = 0.2355)
= 0.1999 - 0.3594 X + 0.1988 X
= 0.1225 - 0.2697 X + 0.164 X
(R 2 = 0.1745)
2
Y Butyricacid
Yvaiericacid
2
2
2
(R 2 = 0.1849)
(R 2 = 0.1274)
Where, Y = concentration of certain fermentation product (g/kg) and X = percentage of
ears remaining with the maize stover before ensiling.
104
-Thefermentationcharacteristicsofmaizesilagesonfarm-
Table 7. Effect of percentage ofears remainingwiththestover onfermentation
characteristics (g/kgdry matter, exceptfor pHand L/A)
Characteristic
0
3
5.05
10.17
72.55
4.64
1.4
0.38
0.18
0.11
0.14
79.3
89.4
223
Numberofsamples
PH
Lactic acid
Acetic acid
Propionicacid
Butyric acid
Iso-butyricacid
Valeric acid
Isovaleric acid
Lactic :Acetic ratio (L/A)
TotalVolatile FattyAcids
TotalAcids (TA)
NH3-N
%ears •emainingwith stover
33
50
66
75
100
8
21
4
3
114
4.75 4.41 4.48 4.13 4.12
13.34 27.53 20.83 41.35 43.66
53.03 32.32 33.81 17.13 28.98
2.9
2
1.88 1.34 1.69
0.92 0.54 0.57 0.22 0.34
0.27 0.13 0.13
0
0.07
0.12 0.06 0.06 0.02 0.04
0.06 0.03 0.02
0
0.02
0.27 1.47 0.66 2.46 2.53
57.3 35.1 36.5 18.7 31.1
70.6 62.6 57.3 60.1 74.8
226
181
152
136
135
25
2
4.89
11.65
65.43
3.42
1.13
0.33
0.15
0.09
0.18
70.5
82.2
206
Fig. 9
Fig. 10
10
Lactic
300 1
• Acettc(g/100g)
Propionic
i
9.
8.
250.
TVFA
Butyric
7.
200.
Isobutyric
I
^'"T"'--
NH3N:total N
| =•
oi 4 .
100.
50.
•
0.25
i
0.5
3.
Linear
(NH3N:total N
- Linear
'
1
^
2.
1 ^ ^
• Valyric
!"•
* Isovalync
1.
- - - Poly.
0-
0.75
(Acetic(g/100g)
0.25
%ofears
0.5
0.75
%ofears
Age (stage of maturity/phenoloy)
Silage pHwas lowerforsilagefrommaize harvested at 90to 110daysthanfor silages
harvested earlier and later.This isassociatedwiththe higherconcentrations ofwatersoluble carbohydrates and a more intensive fermentation (Fisher and Burns,1987;
McDonald et al., 1981). The sametrendswerefoundfortheconcentrations ofTVFA
and the NH3-N/total-N ratio.The lacticacidconcentrations andpHvalues varied littlein
silages from maize harvested over 90days. However, higher pHcoincided with lower
lactateconcentration (Baletal., 1997).
105
(Acetic(g/100g)
-Chapter5-
Table 8 and Figures 11 and 12 show non-linear relationships between age at
harvesting and fermentation characteristics. Lacticacidcontentreached itsmaximum
atanaverage ageof98to 108days.
Fig. 12
Acetic(g/10
9)
Propionic
pH-20
Butyric
Lactic
Isobutyric
TVFA
>. ' •
• ":i
Valyric
Isovalyric
.
•
..
i
• • :
;•:•.
•
.1
NH3-N:total
N
•'
- Poly. (NH3N:total N)
'
Poly.
(Acetic(g/10
• Poly.
(Lactic)
100
• Poly. (TVFA
120
)
Age (days)
-Poly.
Table 8. Effect of maizeageatharvestonfermentation characteristics (g/kgdry
matter, exceptfor pHandL/A)ofthesilage
Ageofmaize(d)
60-70
68
Range
Average
Number of samples
5
4.55
pH
20.88
Lactic acid
38.44
Acetic acid
Propionic acid
2.23
0.64
Butyric acid
0.17
Iso-butyric acid
0.08
Valeric acid
Iso-valeric acid
0.03
Lactic :Acetic ratio
0.82
Total Volatile Fatty Ac. 41.6
Total Acids (TA)
62.5
NH3-N :total N
166
71-80
78
81-90 91-100 101-110 111-120 121-130 130-140
89
98
108
119
128
136
14
35
26
4.14
4.31
4.35
31.82 37.12 44.32
25.41 32.87 30.82
1.65
2.16
1.66
0.35
0.38
0.53
0.07
0.06
0.12
0.07
0.04
0.04
0.02
0.01
0.04
2.95
1.88
2.32
27.6
35.8
33
77.3
59.4
72.9
139
157
135
24
4.15
44.69
28.72
1.53
0.3
0.06
0.03
0.01
2.47
30.6
75.3
148
46
4.32
35.12
33.43
1.89
0.44
0.09
0.05
0.02
1.61
35.9
71
153
3
4.19
49.03
30.41
1.67
0.34
0.09
0.04
0.02
2.15
32.6
81.6
153
2
4.52
53.6
53.62
3.77
0.96
0.29
0.15
0.14
2.93
58.9
112.5
160
The regressionequationsthat representtheabove relationshipare:
"pH
' Lacticacid
= 7.5414-0.0652X+0.0003X 2
=-133.95+3.3815X-0.0162X 2
106
(R 2 =0.0501)
(R2=0.0436)
-Thefermentationcharacteristicsofmaizesilagesonfarm-
Y TotalVFA
Y N H 3 - N :total- N
' Aceticacid
' Propionicacid
• Butyricacid
• Isobutyricacid
| Valericacid
i Isovalericacid
(R2= 0.0105)
(R2= 0.0205)
(R2= 0.0184)
(R2= 0.0350)
(R2= 0.0393)
(R2= 0.0408)
(R2= 0.0372)
(R2= 0.0307)
=129.71-2.0288X+0.0105X 2
=245.03-2.2551X+0.0125X 2
=114.83-1.7758X+0.0092X 2
=9.4168-0.1545X+0.0008X 2
=3.53-0.0626X+0.0003X 2
=1.1026-0.0205X+0.0001X 2
=0.508-0.0093X+0.00005X 2
=0.3251-0.0062X+0.00003X 2
Where, Y =concentration ofcertainfermentation product ing/kg andX=ageofmaize
(d)
Days of ensiling
The fermentation characteristics as a function ofthe lengthoftheensiling periodare
presented inFigures 13and 14andAppendix 3.
Fig. (14)
pH"20
Acetic(g/100g)
Propionic
Lactic
Butyric
TVFA
"--y-r.ii:i-.--.-j-
NH3NtotalN
• Linear
(IMH3-
TT
Isobutyric
A •
Valyric
S 3
Isovalyric
Q
- Linear
(Af!«f<9'1°0g»
^ifcJ-.x-'r.-v-
— —Linear(Butyric)
_i
Fermentationperiod(days)
— - Linear
(TVFA)
"—"Linear
100 — —Linear
(Lactic)
20
40
60
80
Fermentationperiod(days)
The results showthatforallsilages allfermentation characteristics remainstable after
17 days offermentation. Subsequently, changes inthe proportions ofthemajorvolatile
fatty acids (acetic, propionic andbutyric) werevery limited.The pHvalues ofallsilages
slightly increase, probably due toasecondaryfermentation andbecause butyric acid
was only detected inlowconcentrations insomesilages. Clostridia, thatferment lactic
acid, cannot beinvolved (Davies etal., 1998). However, increased production of acetic
acid from lactic acid is alikelyexplanation,becauseoftwopossible reasons. Firstly,
fermentation oflacticacidtoacetic acidbylacticacidbacteria hasbeenshowntooccur
under sugar-limiting conditions (ChenandMcFeeters, 1986;Jonesand Mangan,1976;
Rooke et al., 1990), which provides indirect support for theshiftfrom lactic acidto
acetic acid. Moreover, a similar rise in pH took place in the silages. Secondly,
fermentative lactic acid bacteria, which are often present duringthe laterstagesof
107
lli^vlW)
Linear
(Isovalyric)
-Chester5-
ensiling, are moretolerantto acidic conditions (Mangan, 1982)and produce aceticacid
inadditionto lacticacid.
Comparing the fermentation characteristics (FP)at8dayswiththeir average overthe
period 17 - 1 0 0 days, ((FP8days - FPaverage 17-100 days)/ FP8days) shows a remarkable
reduction in pH, acetic, propionic, butyric, isobutyric, valeric, isovaleric,total volatile
fatty acids and in the NH3-N/total N ratio by7,24,41, 49,50,48,57,24and16%,
respectively. The effect of the length of the ensiling period on fermentation
characteristics wascalculatedas:
YpH
'Lactic acid
Y TotalVFA
Y NH3-N:total- N
' Aceticacid
' Propionicacid
• Butyricacid
' Isobutyricacid
• Valericacid
• Isovalericacid
= 4.4162
= 31.604
= 34.96 = 160.31
= 31.867
= 2.2657
= 0.5879
= 0.1361
= 0.0688
= 0.0345
(R2= 0.0160)
(R2= 0.0122)
(R2= 0.0002)
(R2= 0.0140)
(R2= 0.0193)
(R2= 0.0186)
(R2= 0.0195)
(R2= 0.0137)
(R2=0.0118)
(R2= 0.0087)
- 0.0037X
+0.1856X
0.0199X
- 0.3209X
- 0.0252X
-0.011 X
- 0.0043X
- 0.0012X
- 0.0005X
- 0.0003X
Where, Y =concentration ofacertainfermentation products (g/kg)andX=days since
thestartoffermentation.
Length offeeding periodafter opening
After opening the siloforfeeding,thefront ofthesilage iscontinuously exposedtoair
and that cannot bepreventedfromentering.Atthisstage,largedifferences inresponse
among silages have been recorded.Some remainapparently unaffectedfor morethan
one week, whereas extremely susceptible silages start deteriorating almost
immediately after opening (Spoelstra, 1994). Fermentationcharacteristics asafunction
of time after openingthesiloaregiven inTable 9and Figures 15and 16.Thevaluesof
pH and TVFA slightly increase,while lactic acidandthe NH3-N/total Nratiodecrease
(Figure15). The individual VFAs, especially acetic acid markedly increasewithtime
(Figure 16). This could bethe resultoftheentrance ofoxygenthroughthe fermented
mass, which causes a shift fromlacticacidtoaceticacid,throughtheactionoflactic
acid bacteria (Pahlow, 1982; Condon, 1987; Spoelstra, 1994) and of acetic acid
bacteria oxidizing ethanoltoaceticacid(Spoelstraetal., 1988).The relations between
the length ofthefeeding period and fermentation characteristicswere calculatedas:
YPH
Y La ctic acid
=4.3117-0.0037 X+0.0000006X2
= 36.795 + 0.2413 X - 0.0043 X
2
108
(R2= 0.0032)
2
(R = 0.0052)
-Thefermentationcharacteristicsofmaizesilagesonfarm-
(R2= 0.0026)
(R2= 0.0197)
(R2= 0.0031)
(R2= 0.0021)
(R2= 0.0026)
(R2=0.0039)
(R2= 0.0009)
(R2= 0.0010)
=34.21-0.052X+0.0019X 2
=147.17+0.431X-0.0112X 2
=31.649-0.0419X+0.0018X 2
=1.9194-0.0047X+0.000002X 2
=0.4603-0.0036X+0.000005X 2
=0.1041-0.0014X+0.000002X 2
=0.0529-0.0003X+0.0000004X 2
=0.0246-0.0002X+0.0000002X 2
Y Total VFA
Y NH3-N :total - N
• Acetic acid
Y Propionic acid
' Butyric acid
• Isobutyric acid
• Valeric acid
' Isovaleric acid
Where, Y = concentration of certain fermentation products (g/kg)andX=numberof
daysthesilo hasbeenopenforfeeding.
Acetic(g/10
og)
Propionic
Butyric
Isobutyric
Valyric
Isovalyric
• - Poly.
(Acetic(g/10
(Propionic)
FiitiU• i
10 20
120
° 100
5
"S>
80
60
40
20
0
• f e f e f a . "
Daysopen
'
...
.
j
NH3N:total N
-Poty.
(pH*20)
wir*
15
30 40 50 60 70
!
-Poty.
(Lactic)
30
45
60
Days open
Length of chopped materials
The length of thechopped materials isoneofthemaincriteriadetermining the quality
of a chopper. Obviously, all choppers produce different lengths at thesametime,
however, the proportions ofthesedifferent lengths playasignificant role inevaluating
the choppers.These proportions alsoplay anindirect rolethroughtheir influence onthe
effectiveness of compaction ofthematerials andsealing ofthesilos.Choppers,when
compared with other types of forage harvesters appear only usefulforwet materials
with relatively low DMcontent (Pickert etal., 1998). Thechopped materials have been
classified intocategories asshown inTable3.
The percentage of each category was identified and relativeweightsweregivento
these categories. Table 10 shows the percentage of each length of the chopped
materials andtheweightsgiven.Theoverallweight (calculated bymultiplying the
109
-Charter 5o
a>
^1 a>
."a.mcMin_incMi-cMco
T —
^ C O O O C M ^ O C O . C O C M C M
CM O
CO
o
cp
CD
CD
in
m
LO
^co
c
o
CO
CO o
CD CO
CM
o
CM
—
,
CM
•<!-
CO
CM
• *
o o
CM
a> CD a>
T_
a.
CO
*L_
CO
O O
CM
CM ("~ CO
^ . T - CM
o
CM CO 0 0
o d d
00
in
CM
CM CD CO CM
CM
• *
O
o
o
d d d
CM
CO CD
i n a)
CO CO
CO CO CO
CM CM d
m CM 00
m
o o CM
d
d d c\i
d
o
• *
00
in
CO
D)
c in
a) ^ K
1
•a
c
„rt^
• * -
CM
T -
(D
re
TOo
X
a
X
£
o
a.
CO
CD
in
x
a
T-CMCOOOmCMCDI^O
^ ( D r O O C O ^ u j f :
f^co in
C M ' d d d d x - ' ^ - i ^ ' ' ^ co cb
c
^ co co o T c
i > f \ I S ? TJt o^ o^ no ?cq0 CM
i9
CM CM •*
d
d
d
d
CM
COCM
_ CMroto
s ; co ^ 5£ . ^ - : ° . q ^ d c M ^
~ CMCO
CM°0000'>a-CD''-
in
in
•<j-
-*
CM °> °?
CO
CO
00 S R c o c M c o c o c O T - T r c M i n o o
^ ^ i n c o q q q r ^ ^ ^ j ^ CM
O O O O CM CM h-
CM
CM
0)
u
to
i"
re
E
. * a)
o>.E
*-' TJ
<D
0) a)
U <*=
w o
z *a> »
b
'
C3)CM CD
in c M ^ J 9 i n o q q o CO a>
CM
o d o d CM CMi^
T3
OT
re
£ ! •>- <3> CM CM
o
i n co
m
c
C M ^ ^ C D O O O O O O S J
CO 2
a>
o
O O Tf CD
<* £CO£CO- d o d d ^ <°
• *
• * -
O
CO CO
i - CM O) OO K)
in TJ-in^>
o ^ i ^ T f
CO i n c o q q oo c co
COCM T - d o o d T - c M m ' -
• * CO
-
-
CM 05 CO CMCM
CO
CO CM O O o
00
CD _ 00 •^°°. ° | 00 co
CM
in ^
•^ d d d
a>
^ ° ° ^ ^ d ° d d c M c o h :
w
re W
0)
re
£
£
U
^-*
O)
<
c
o
'& 'E
IS Q>
Q.
c
a o
E
0)
re
o>
2.
0)
A
re
H-
-g
4=
LL.
•D
O
'C
0)
a.
o >*
JU
as UTO
o
4—'
a) a>
o TO•g
' + J
-a
a>
c
CO
a) a)
C
O JD
1 _
E
> 3
< z
0)
co ! 2
2
CO co
o
o
o a)
a JTO< PD
.o-| 8. y
0
-g
o
co
ro
o
•&• o J)
5 .2
a > - Q o)
2 3 Q TO
110
U.
•g
o
<
o
O
o
> <
"C "TO
O o 5
•4—'
- C Q * > ^ J TO
l - l - Z
-Thefermentationcharacteristicsofmaizesilageson farmcategory weight by itspercentage) was usedtojudgethechoppers performance
regarding lengths of chopped materials. No significant differences were
observed among the choppers. All choppers performed non- homogeneous
lengths of chopped materials ormixoflengths.Theeffects ofchoppertype on
fermentation characteristics of the silages, presented inAppendix 4,showno
significant differences (P>0.05) among silages. The low pH, TVFA, NH3-N,
butyric acid and the high lactic acid concentration are all indicationsthatall
silageswerewellpreserved.
Table 10.Weightsandpercentages ofchoppedmaterials percategory and
pertype ofchopper
Category ofchopped
materials
Number ofsamples
Fine
Small
Medium
Coarse
Overallweight
Rank
Percentage
of
Baladi
weight
45
30
15
10
89
35.41
29.89
7.37
27.33
2874a
3
Typeof Machine (chopper)
Emagro
PZ
Claas
Weightof categories
22
19
33.48
37.44
31.4
29.7
5.42
2.07
29.7
30.79
2821 a
2915a
4
2
25
44.97
23.68
4.06
27.29
3068a
1
Conclusion
Small farmers adopted silage-making intervention as indicated bythequality of
maize silage producedon-farm.
The highest qualities corresponded to whole-plant maize (without removing
ears), ensiled atanaverage ageof 108days,after 17daysoffermentation,and,
up to 45 days off-take feeding period (opening ofthesilo).Variety andtypeof
chopper used inthis study, had nosignificanteffectonsilagequality.
111
-Chapter5References
Argillier, O.,Y. Herbert,andY. Bbarriere, 1985.Relationships between biomass
yield, grain production, lodging susceptibility andfeeding value insilage
maize. Maydica40:125.
Bal, M.A., J.G.Coors,and R.D. Shaver, 1997.Impactofthe maturity ofcornfor
use as silage in the diets of dairy cows onintake,digestion,andmilk
production.J.Dairy Sci.80:2497-2503.
Chen, K.H., and R.F. McFeeters, 1986.Utilizationofelectron-acceptors for
anaerobic metabolism by Lactobacillus planetarium, enzymes and
intermediates inthe utilization ofcitrate. Food Microbial.3:83-92.
Condon, S., 1987.Responses oflacticacid bacteriatooxygen.FEMS
Microbiology Reviews46:269-280.
Fisher, D.S., andJ.C. Burns, 1987.Quality analysis ofsummer-annualforages.
II. Effects of forage carbohydrate constituents on silage fermentation.
Agron.J.79:242.
Flachowsky, G.,W. Peyker,A. Schneider, and K. Henkel, 1993. Fibreanalysis in
sacco degradability of plant fractions of twocornvarieties harvested at
various time.Anim. FeedSci.&Tech. 43:41.
Heron, S.J.E., R.A. Edwards,and P. Phillips, 1989.Effect ofpHontheactivity of
ryegrass Loliummultiflorumprotease.J.Sci.FoodAgric.46:267-277.
Jones,W.T., andJ.L. Mangan.1976.Largescale isolation offraction 1leaf
protein (18s) from Lucerne (Medicago sativa L.). J.Agric. Sci.(Camb.)
86:495-501.
Langston, CM.,Wiseman,H.G., Gordon,C.H.,Jacobson,W.C.,Melin,C.G.,
Moor, L.A. and U. H. McCalomont, 1962.Chemical and bacteriological
changes ingrasssilageduringtheearlystagesoffermentation. I.J.Dairy
Sci.45:369-382.
Makoni, N.F., G.A., Broderick and R.E. Muck, 1997.Effect ofmodified
atmospheres on proteolysis and fermentation ofensiled alfalfa.J.Dairy
Sci., 80:912-920
Mangan, J.L. 1982.The nitrogenous constituents offreshforage. Pages25-40in
Forage Protein in Ruminant Animal Production, B. Soc. Anim. Prod.
Occas. Publ. No.6. D.J.Thompson, D.E. Beever, and R.G.Gunn,ed Br.
Soc.Anim.Prod.,London,UnitedKingdom.
McDonald,A.G., 1981. Thebiochemistry ofsilage.6thed.,McGraw-Hill,Book
Co. NewYork.
McDonald, P., R. Henderson,andS.J.E. Heron. 1991.Thebiochemistry of
silage. 2nded.Chalcombe Publ.,Marlow, UnitedKingdom.
Merry, R.J., R.F. Cussen-Mackenna,A.P.Williams,andJ.K.S.Tweed, 1993.The
effect of different inoculates onfermentation andproteolysis insilages of
different perennial ryegrass andwhiteclover content. Page 83-84 inProc.
10th Int.Conf. Silage Res. Sep. 6, 1993. Dublin,Ireland.P.O'Kiely,M.
O'Connell,andJ.Murphy,ed.City Univ., Dublin,Ireland.
Ohshima, M.,and P. McDonald, 1978.A reviewofthechanges in nitrogen
compounds ofherbageduringensilage.J.Sci.FoodAgric. 29:497
112
-ThefermentationcharacteristicsofmaizesilagesonfarmPahlow,G., 1982.Verbesserung deraeroben Stabilitatvon Silage durch
Impfpraparate. DasWirtschaftseigene Futter,28.107-122.
Rooke,J.A.,A.J.Bormanand D.G.Armstrong, 1990.Theeffect of inoculation
with Lactobacillus planetarium on fermentation in laboratory silos of
herbage low in water-soluble carbohydrate. Grass Forage Sci.45:143152.
Spoelstra, S.F., 1994.Influencesofaironsilage preservation and aerobic
stability. Grassland and Society, Proceeding ofthe 15thgeneral meeting
ofthe European Grassland Federation,June6-9.
Spoelstra, S.F., M.G.Courtinand H.van Beers., 1988.Acetic acid bacteria can
initiate aerobic determination of whole crop maizesilage.J.Agric.Sci.,
Cambridge 111: 127-132.
Tabana,A.S., 1994.Utilization ofcornandsunflower plant residues in ruminant
nutrition. M.Sc. in Agric. Sci., Anim. Nut., Faculty ofAgriculture, Cairo
University, Egypt.
Van Os,M., 1997.Roleofammonia andbiogenic amines inintakeofgrass
silage by ruminants. Ph.D.Thesis,WAU,Wageningen,The Netherlands.
Van Soest, P.J.,1994. Nutritional ecology ofthe ruminant.2nded.Cornell Univ.
NewYork, USA
VanOs,M.and Dulphy, M., 1996.Voluntary intakeand intakecontrolofgrass
silages by ruminants. Repr. Nutr. Develop.,36:113-135.,
Wiersma, D.W., P.R. Carter, K.A. Albert,andJ.P.Coors, 1993.Kernel milkmen
stage andcornforageyield,quality anddry matter content.J.Prod.Agric.
6:94.
Williams,A.P.,R.J. Merry,J.K.S.Tweed,and D.K. Leemans, 1992.Theeffect of
different additives on proteolysis during ensiling of perennial ryegrass.
Anim. Prod.54:487.
Xu, S.,J.H. Harrison,W.Kezar, N.Entrikin, K.A. Lony,and R.E. Riley, 1995.
Evaluation of yield, quality, andplantcomposition ofearly-maturing corn
hybrids harvested atthreestages ofmaturity. Prod.Anim.Sci.11:157.
113
Chapter5Appendix 1.Proximate chemicalcomposition ofsilages inrelationtothe
lengthofensilingtime.
Daysfrom
ensilingto
opening
<10
11-20
21-30
31-40
41-50
51-60
>60
No. of % ears Av. age Av. Av. Days
daysof
samp- remaof
leftat
fermenining
maize tation sampling
les
67
104
8
6
3
89
102
17
8
13
85
99
11
47
28
86
37
14
56
101
71
104
46
18
16
106
58
15
13
100
96
16
7
109
100
CP
EE
CF
g/kg
g/kg
69.1
72.5
74.7
75.5
71.9
79.2
78.7
12.4
18.6
18.4
18.7
16.9
21.2
22
g/kg
NFE
G/kg
g/kg
278.1
289
284.3
284.8
287.8
273.3
280.1
546.2
522.1
528.9
525
531.2
532.2
525.4
94.2
97.8
93.7
96.0
92.2
94.1
93.8
Appendix 2.Fermentation characteristics (g/kgdry matter, exceptforpH
and L/A) ofsilagesfromdifferentvarieties.
PH
Lactic acid
Acetic acid
Propionic acid
Butyric acid
Iso-butyric acid
Valeric acid
Isovaleric acid
Lactic :Acetic ratio(L/A)
Total Volatile Fatty Acids (TVFA)
Total Acids(TA)
NH 3 -N
Hybrid
4.27
39.54
32.15
1.86
0.43
0.09
0.05
0.02
2.22
34.6
74.1
149
114
Yellow
4.33
30.83
27.24
1.74
0.42
0.09
0.05
0.02
1.73
29.5
60.4
131
Baladi
4.36
32.83
31.3
1.96
0.48
0.11
0.06
0.03
1.83
33.9
66.8
154
Ash
-Thefermentationcharacteristicsofmaizesilageson farmAppendix 3. Effectoflength (day)oftheensiling period onfermentation
characteristics (g/kgdry matter, exceptfor pHandL/A).
Length (d)ofensi ling period
Range
Average
Number of samples
PH
Lactic acid
Acetic acid
Propionic acid
Butyric acid
Iso-butyric acid
Valeric acid
Isovaleric acid
Lactic :Acetic ratio(L/A)
Total Volatile Fatty Acid (TVFA)
Total Acids(TA)
NH 3 -N :total N
<10
8
11-20 21-30 31-40 41-50 51-60
17
28
37
46
58
>60
100
47
13
56
16
13
7
3
4.32 4.33 4.23 4.33 4.17
4.6
4.3
23.38 37.59 34.11 43.39 33.57 44.92 33.01
41.97 31.33 30.39 30.86 38.45 31.74 29.69
3.08 2.02
1.98
1.73
1.87
1.72
1.65
0.48
0.48
0.38
0.47
0.33
0.38
0.83
0.18
0.11
0.1
0.08
0.11
0.06
0.08
0.06
0.06
0.04 0.06
0.04 0.05
0.1
0.03
0.02
0.05
0.03
0.02
0.02
0.01
2.17 2.33
1.03
2.8
1.2
2.65
1.19
34
46.2
33
33.1
41
33.9
31.8
69.6 71.6 67.1 76.5
74.5
78.8 64.9
157
150
145
160
135
136
176
Appendix 4. Effect of type of chopper, maize characteristics andsilage
characteristics on fermentation characteristics (all in g/kg dry matter,
exceptfor pHand L/A).
Type of chopper
Item
Claas
PZ
Emagro Baladi
% of ears
Average ageofmaize(d)
Average length ofensiling period(d)
Average length ofperiod after opening(d)
0.91
101
38
22
4.26
41.21
33.06
1.79
0.39
0.08
0.05
0.02
1.85
35.4
76.6
144
PH
Lactic acid
Acetic acid
Propionic acid
Butyric acid
Iso-butyric acid
Valeric acid
Isovaleric acid
Lactic :Acetic ratio(L/A)
Total Volatile Fatty Acid (TVFA)
Total Acids(TA)
NH3-N :total N
115
0.83
98
36
12
4.27
37.08
27.57
1.68
0.39
0.08
0.04
0.01
2.21
29.8
66.8
147
0.84
102
41
9
4.29
38.29
34.2
2.04
0.47
0.11
0.05
0.03
2.17
36.9
75.2
145
0.85
103
37
12
4.29
37.83
31.71
1.88
0.44
0.1
0.05
0.02
2.22
34.2
72
151
Chapter6
Introducing MaizeSilage intotheEgyptian FeedingSystems:Ensiling
Characteristics, Digestibility andFeedingValue,andInteractionswith
Berseem-basedFeedingSystems
A. Tabana 1 , S. Tamminga 2 , and H. van Keulen 3
1
Animal Production Research Institute. P.O. Box443, Dokki,Egypt
department ofAnimal Science,Wageningen-UR, The Netherlands
3
Agrosystems Department, Plant Research International,Wageningen-UR, The Netherlands
(Submitted for publication)
-Chapter6-
Introducing MaizeSilage intothe Egyptian Feeding Systems: Ensiling
Characteristics, Digestibility and FeedingValue,and Interactions with
Berseem-basedFeeding Systems
Summary
Four feedstuffs: berseem (Trifolium alexandrinum) rice straw, concentrate mixture and
maize silage were used in two direct and three indirect metabolism trials with sheep. In
trials 1 and 5, berseem (B) and maize silage (M) were fed alone. In trials 2, 3 and 4, a
restricted quantity of wilted berseem (approximately 250 g DM) was fed, to cover 30 to
40% of total DM intake, the remainder being covered partly by concentrates (C), rice
straw (R), or maize silage (M) in trials 3, 4 and 5, respectively.
The silage was well preserved, as indicated by its low (35.35 g/kg DM) content of total
volatile fatty acids (VFA). Except for acetic and propionic acid, the silage was free from
undesirable VFA's (less than 1g/kg DM). Ammonia-N concentration was generally low
(1.7 g/kg DM), reflecting a relatively rapid rate of lactic acid production and limited
proteolysis. However, a high lactic acid content (63.6 g/kg DM) and a low pH (3.84)
were found. The efficiency of fermentation was favorable, as indicated by the ratio of
lactate to acetate (2.17).
To study the development of the fermentation, small-scale ensiling experiments were
carried out: they showed a rapid drop in pH during the first 8 days (from 6.6 to 4.85), up
to 16 days (during the second week) the changes were moderate (from 4.85 to 4.6),
and subsequently, up to 96 days, the values remained within narrow limits (3.87+0.06).
BR showed the lowest digestibilities for all components; M the highest DM (69.9 vs.
59.3) and OM (74.6 vs. 57.3) digestibilities. Feeding M with B increased DM digestibility
by 1.7 unit and decreased the OM digestibilities by 3.2 units compared to feeding M
alone.
There was no significant difference (P<0.05) between B and M in digestibility of any
fiber fraction, except for NDF. Berseem, being a legume, tends to have lower
digestibility than maize silage, belonging to the graminae. On the other hand, significant
differences (P>0.05) were found for C,R and Mi (maize silage calculated by difference)
for all fractions, except for NDF between C and Mi.
For hemicellulose and cellulose, digestibilities were almost identical for B and M, while
for Mi it was 6 units lower than for M.Comparison of the fiber fractions for C,R and Mi
(calculated by difference) showed that for hemicellulose, digestibility of Mi was highest,
that for R lowest, the inverse trend was found for cellulose digestion. The same trend
was found for BC, BR and BM, which can be ranked according to the digestibility
coefficient as BM>BC>BR and BR>BC>BM for hemicellulose and cellulose,
respectively.
118
-Ensilingcharacteristics,digestibilityandfeedingvalue-
DM intake of M was higherthanofB, indicatingthatBintakemaybemorerelatedto
therumenfillanddigestibility. IntakeofBMwashigherthanofBRandlowerthan of
BC. TDN and DCPvalues areinagreementwiththedataintheregion,indescending
order, C>M>B>R for TDNandB>C>M>RforDCP.
(key words: berseem, maize silage, rice straw, digestibility,fermentation, nutritive
value)
Introduction
In dairy production, both thequantity andquality ofthefeed play an important role.In
Egypt, this is an especially pressing problem,asanimaldemandfor nutrients ishigh
and the energy content of the most commonly available forage, clover (Trifolium
alexandrinum) islow.
Diets composed oflowquality roughages onlyareusually notadequatetosustain high
milk production, and need to be supplemented to increase the available energy
(Tamminga andJansman, 1997). Usingtheservices ofafeedmill,that hasfacilitiesto
formulate least cost rations, is a theoretical option. However,thequality ofamixed
concentrate, composed ofawidevariety ofingredients isnotalways guaranteed. Low
quality roughages in the form of crop by-products are widely available, butthelow
digestibility of these materials limits their use as asourceofenergy, particularly for
milking cows. Homegrown conservedforages mayoffer analternativefor overcoming
theproblem.
Maize silage, in recent yearswidely adoptedonlarge-scale dairyfarms in Egypt, has
also been promoted with smallholder farmers in a limited number of areas. The
potential benefits asindicated byon-stationexperiments, incombinationwiththe initial
positive on-farm response to the technology, suggeststhat itmight beadopted more
widely.
Although the on-farm fermentation characteristics of maize silage is fairly well
established (Tabana et al., 2000), little information isavailableon its interactionwith
other dietary ingredients.
The aim of this study was a detailed analysis oftheconservation process ofmaize
silage under conditions prevailing in Egypt, andtoestablish its interactionwith other
components of a diet common (in winter) for dairy cows at low and mediummilk
production.
Materials and Methods
Feedstuffs
Fourfeedstuffs were investigated inthisstudy: ricestraw, maizesilage, berseem clover
119
-Chapter6-
(Trifolium alexandrinum) andconcentratemixture.
Rice straw: Strawfromahybridvarietywas used.Tolimit lossesduringfeeding,the
strawswere chopped intopiecesof 15centimeter.
Maize silage:Wholewhite maize plants(hybrid,Giza 310)were harvested atthe hard
dent stage of maturity (100 days),chopped andconserved ina"threewall" concrete
silo. The inner surface of the silo andthetopofthechopped materialwere covered
withplastic sheets. After 90days ofensiling,thesilowasopenedforanalysis.
To study the development of silage quality, ten polyethylene bags werefilledwith
chopped maize,sealedand placed inaclosed/dark cupboardforanalysis after different
lengthsoftheensilingperiod.
Berseem: Athird cutofberseem(Meskawy, improvedvariety) was harvested byhand
after 35 days re-growth and a length of approximately 60 cm. Pre-wilting was
performed inashaded placefor24 hoursbeforefeeding.
Concentrate mixture: The composition ofthecommercialconcentrate mixture,as
specified by the manufacturer, was: Yellow maize (65%), cotton seedcake(10%),
wheat bran (15%), rice bran(5%),molasses (2.5%),limestone (1.5%),salt(1%),anda
mixture oftraceelements andvitaminpremix.
Metabolism trials
Two direct and three indirect metabolism trials were carried out, each with four
castrated two-year-old Ossimy rams. To avoid sourcesofvariability among different
individuals, the sameanimalswere used inthedirect andindirecttrials.An adaptation
period of 21 days preceded each trial. The fecal collection period was 7 days.
Metabolic cages were used,asdescribed by Loosli(1969),slightly modifiedfor better
ventilation andeasiercollection.
Sampling and chemical analyses
Composition of the fresh silage sampleswasanalysed inwater extracts, preparedby
extracting 100 g homogenised wet material with 200mlliquid,consisting ofof99%
water +1% ortho-phosphoric acid (v/v). The homogenate was filtered throughtwolayered cheese cloth, then used for silage quality determination.Volatilefatty acids
(VFA) were determined using KENAUER High Performance Liquid Chromatography
(HPLC). The device and separation conditions were columns: Rezex organic acid
30x4.6 mm (phynomenix, USA), detection wavelength: 210 nm., mobilephase:1%
120
-Ensilingcharacteristics,digestibilityandfeeding value-
ortho-phosphoric acid inwater,flow rate:0.5 ml/min., injection volume:20 ul.
Feedstuffs were sampled regularly andrepresentative samples offaecesweretaken
daily from the animals during the experimental period, as described byvanSoest
(1994). The sampleswerestoredfrozen,dried inanovenat60°Cforabout48 hours,
thoroughly ground in a wily-mill to pass a sieve of 1 mm, for proximate chemical
analysis, following theconventional methods ofA.O.A.C (1985). Silageandfaecesdry
matter (DM) contents were determined after oven drying at 105 °C for 24hours.
Neutral-detergent fiber (NDF), acid-detergent fiber (ADF) and acid-detergent lignin
(ADL) were measured according toGoering andVan Soest (1970). Hemicellulosewas
calculated as NDF-ADF,andcellulose asADF-ADL.
Experimental procedures
To avoidfeed losses and/or refusal,feed intakeweremeasured duringthe preparatory
period andaproximate quantities ofthemeasured intakeweredivided intotwo portions
and offered to the animals at8a.m.and5p.m.Thequantities offeedwere adjusted
daily to guarantee adlibitumfeedingwithminimum refusals (100g/day). Berseem and
rice straw were cut/chopped into pieces,oflength20centimeters (approximately), and
mixed beforefeeding.Also,concentrates andmaizesilagewere mixed beforefeeding.
In trials 1 and 5, berseem (B) andmaizesilage (M), respectively werefedassingle
feed. Intrials 2,3and4,arestrictedquantity ofberseem (approximately 250 g/head/d)
was fed, covering 30 to 40% of thetotal DMintake.The remainderwascovered by
concentrates (C),straw (R)andmaizesilage(M) intrial2,3and4, respectively.
Results and Discussion
Silage characteristics
Fermentation characteristics of the silage are given inTable 1.Thesilagewaswell
preserved asindicated bythe low (35.35g/kg DM)contentoftotalvolatilefattyacids.
Except for acetic and propionic acid,thesilagewasfreefromundesirableVFAs(less
than 1 g/kg DM). Also, silage pH and lactic acid concentration was indicativeof
adequate preservation (McDonald etal., 1991).The low pHand high lactic acidcontent
are due tothe highconcentrations ofwater-soluble carbohydrates and moreextensive
fermentation (Flachowsky etal., 1993).Ammonia-N concentrations weregenerally low
(1.7 g/kg DM), representing 11%of the total nitrogen (110 g/kg). This reflects a
relatively high rate oflacticacid production and limited proteolysis (Heronet al., 1989;
Williams et al., 1992), while the high lacticacidcontentand low pHinhibit activity of
aerobic organisms suchas Clostridia. Theefficiency offermentation wasfavourable,as
indicated by the ratio of lactate to acetate (Luther, 1986; Cleale et al., 1990).
121
-Chapter6-
Table 1.Fermentation characteristics (allvalues ing/kg dry matter, exceptfor pH,
L/A and NH3-N:total N)Nofmaizesilage
Characteristic
Value
3.84
63.66
29.22
5.69
0.31
0.09
0.04
0.002
2.17
35.35
99.0
1.7
0.11
pH
Lactic acid
Acetic acid
Propionic acid
Butyric acid
Iso-butyric acid
Valeric acid
Isovaleric acid
Lactic :Acetic ratio (L/A)
Total Volatile Fatty Acids (TVFA)
Total Acids (TA)
NH3-N
NH3-N: total N
Fermentation development
The results of the simulated ensiling experiment (Table 2), showafastdrop inpH
values duringthefirst 8days (from6.6to4.6),while upto 16days (duringthe second
Table 2.Development offermentation characteristics (all ing/kg dry matter) in
'simulated' maizesilage.
Time(days)
0
1
2
4
8
16
32
48
64
80
96
pH
6.6
5.3
5.01
4.85
4.6
3.74
3.89
3.83
3.95
3.79
3.91
Lactic
TVFA
ND*
36.3
45.2
47.9
49.4
52.4
61.3
64.1
61.6
62.6
60.7
ND*
5.6
11.5
15.0
18.8
29.1
30.7
37.8
36.4
36.9
35.8
Acetic
ND*
5.2
10.7
13.3
14.1
14.5
15.3
18.9
18.2
18.4
17.9
*Not determined
122
Propionic
ND*
0.2
0.5
1.1
2.3
4.8
5.1
6.3
6.0
6.1
5.9
Butyric
ND*
0.096
0.19
0.5
2.3
9.7
10.2
12.6
12.1
12.3
11.9
NH 3 -N
137.8
130.3
126.1
119.6
97.2
101.1
99.6
102.7
98.5
101.7
101.6
-Ensilingcharacteristics,digestibilityandfeedingvalue-
week) the changes were moderate (3.74), and up to 96 days pHremainedwithin
narrow limits (3.87+0.06). Lactic acid concentration showed the inverse trend: it
increased markedly duringthefirst 8days.The rateofdecline inpHintheearly stages
of fermentation (Heron et al., 1989; Merry et al., 1993; Williams et al., 1992) isa
reflection of the rate of lactic acid production, which, in turn, isdetermined bythe
activity ofthe natural lacticacid bacterial population andthecontentandcomposition of
water soluble carbohydrate (WSC) intheforage (Davies etal., 1998).Thenumber of
lactic acid bacteria remains high after 10 daysoffermentation (van Osetal., 1996)
which explainsthe limitedchanges inpHand lacticacidduringthe periodfrom 16to96
days.
Chemical composition
The chemical composition of the feedstuffs, presented inTable 3,shows substantial
variation among individualfeedstuffs.Thevariation reflectsthedifferences inquality.
Table 3.Proximate chemical composition andfiberfractionforfeedstuffs and
rations
Feed mixtures'"
Ingredient ratios
Proximate analysis (g/kg DM)
DM
CP
EE
CF
NFE
Ash
Fiber fractions (g/kg)
NDF
ADF
Hemicellulose
ADL
Cellulose
Exp.1 Exp.2 H Exp.3" Exp.4 H Exp.5
B
BC
BR
BM
M
100 2 8 : 7 2 3 9 : 6 1 3 4 : 6 6
100
171
174
14
207
461
144
—
—
—
170
28
149
530
122
100
10
307
433
151
414
352
62
79
274
368
210
159
46
164
585
417
168
79
337
1
Exp.6 1 Exp.7
R
C
100
100
120
20
263
489
108
352
93
23
292
503
89
915
168
34
127
556
114
926
52
7
372
413
155
433
286
147
53
233
442
251
191
39
212
351
155
196
34
122
696
458
237
79
379
iCalculated bythedifference methodfromexperiments 1,2and3.
ii Estimates based onresultsofexp. 1,5,6and7,byapplying suchcombination atthe
same ratioof DMintake.
iii B= Berseem, BC= Berseem + Concentrate, BR= Berseem + Rice straw, BM=
Berseem+Maizesilage, M=Maizesilage,C=Concentrate and R=Ricestraw.
123
-Chapter6-
Low (52g/kg DM)andmoderate (93g/kg) CP(crudeprotein) contentwasfound inrice
straw and maize silage, respectively. The concentrate mixture was highest inNFE
(Nitrogen Free Extract) and EE(Ether Extract),followed bymaizesilage,berseemand
rice straw. In experiments 2, 3 and4,berseemwascombinedwith concentrate, rice
straw and maize silage in proportions of 28, 39 and 34% on a dry matter basis,
respectively. This resulted in relatively high, moderate and low CP, EE and NFE
contents for the mixtures containing concentrates, maize silage and rice straw,
respectively. Rice straw had the highest crudefiber content,comparedwith berseem
and maize silage. These results were confirmed byfiberfractionanalysis (Table3),
which indicated that rice straw containedthe highest proportions ofallfiberfractions,
except hemicellulose. When berseem was mixed with 6 1 % straw (DMbasis) NDF,
ADF, hemicellulose andcellulosecontents increased.Themixture ofberseemwith rice
straw containedthe highest hemicellulose content.
Feed intake
DM intake of M was appreciably higher than of B(Table4),which indicatesthatB
intake may be more related to rumenfilland/ordigestibility (Bosch etal., 1991;Van
Soest, 1994). Intakeof BMwas higherthanofBRand lowerthanof BC.Higher silage
intake has been reported when animals were fed fiber-based, rather than starchy
supplements (Thomas et al., 1986; Phipps et al., 1987), though sometimes the
differences were small (Castle et al., 1981; Mayne and Gordon, 1984;Huthanen,
1987).
Table4. Intakeandfeedingvaluesoftheexperimentalfeeds
B
Intake (g/d)
DM
CP
NDF
Hemicellulose
ADL
Cellulose
Substitution rate
448
78
263
158
28
35
—
BC
910
154
335
145
42
142
0.30
BR
623
62
365
105
49
204
0.54
BM
747
90
323
110
39
167
0.40
M
634
59
354
159
121
25
—
C
659
110
231
129
22
80
—
R
378
20
263
90
30
143
—
Mi
494
46
218
94
19
105
—
Because intakewasalmostadlib,fromthefigures intable4substitution rates (SR=kg
DM of berseem substituted per kg DMofsupplement) canbecalculated.Theywere
0,54, 0.40 and 0.30 for rice straw, maizesilageandconcentrates respectively. The
124
-Ensilingcharacteristics,digestibilityandfeedingvalue-
figures for rice straw and Maizesilagearesurprisingly low. Because oftheir bulkiness
one wouldexpectfiguresclosetoorevenhigherthan 1.0.Thereasonwhythey arefar
below 1.0 must be because berseem hasasurplus ofrumendegradable Nofwhich
ricestraw and maizesilage haveashortage.
Therefore, DMintakeofmaizesilagewas higherthanofberseem (634vs.448g/d) and
higher when mixedwith berseem (747vs.634g/d).A positive effect onintakewas also
observed when berseemwas mixedwith ricestraw. Proteinsupplements (Egan,1977)
have been suggestedtoincrease intakethrough improved proteinsupply, andthrough
changes in the protein/energy ratio that lead to improved nutritional status ofthe
animals. Accordingly, high protein intake inthe BC,BM,and BSrations (154,90and
62g/d) appears to have ledto relatively high DMintake (910,747and623g/d).
Correlation between intakeandchemical composition
With respect tochemical composition,feeding values,andfeed intake,data inTable5
indicate that DM intake ispositively correlatedwithTDNand negativelywiththefiber
fractions. Dietary NDFconcentration isnegatively correlatedwith hemicelluloseintake.
Table 5.Correlation coefficients between intakevaluesand chemical
composition
DM, NDFi ADFi
1
DM,
NDFi
0.66
1
ADFi
0.31 0.83
1
Herrii
0.76 0.63 0.10
ADLi
0.41 0.73 0.91
Cell,
0.26 0.86 0.98
TDN% 0.54 -0.13 -0.43
NDFC -0.56 0.22 0.44
ADF C -0.59 0.14 0.56
Hem c -0.09 0.20 -0.15
ADL C -0.48 0.09 0.56
Cell c
-0.57 0.21 0.56
Herrii ADLi
Celli TDN% NDFc ADFc Hem c ADL C Cell c
1
1
0.03
0.17 0.82
1
0.37 -0.34 -0.46
1
-0.22 0.22 0.53 -0.87
-0.53 0.43 0.57 -0.89
0.57 -0.39 0.01 -0.18
-0.63 0.59 0.51 -0.81
-0.41 0.37 0.61 -0.89
1
0.90
0.45
0.70
0.96
1
0.01
1
0.92 -0.29
0.98 0.17
*The subscript lettercmeanchemical composition and Imean intake
Digestibility
Thedigestibility ofboththetotalandthefractionalfiber components ofthefeedstuffs
andthe mixtures arepresented inTable6.Theeffects ondigestibilities ofcombining
berseemwith maizesilagewerecalculatedas:
125
1
0.84
1
-Chepter6-
Effect on nutrientX (CP, EE,etc) =Mix -Mx
Where, Mix is the digestion coefficientformaizesilagecalculatedfromthe difference
between trials 1(B) and4 (BM),andMxisthedigestion coefficient calculatedfromthe
direct trial 5(M).Thedigestioncoefficients of BM,MandM a s wellasthe combination
effects onnutrientdigestibilities arepresented inFigure1.
Figure 1.Thedigestion coefficients ofmaizesilagesestimateddirectly (M),by
difference (Mi)andthedifferences betweenthetwomeasurements.
Digestibility (%)
-15
DM OM CP EE
CF NFE NDF ADF HEM ADL CELL
B M 1 Mi fj M-i
The digestibilities ofallfractions distinguished intheproximate analysis (Table6)ofthe
two forages fed individually (BandM),weresignificantly different (P>0.05),exceptfor
the EE fraction. The values for BC, BR and BM were also significantly different
(P>0.05) forall proximatefractions,exceptforCFbetween BCand BR.BRshowedthe
lowest values for allcomponents, i.e.for DMandOM59.3%and57.3%,respectively.
M showedthe highestdigestibilitiesfor DM(69.9%) andOM(74.6 %).
Mixing B with M decreased both DMandOMdigestibility by 1.0 (N.S),and3.2 units,
respectively, comparedtofeeding Malone.Bhadthe highest (73.8 %)CPdigestibility,
followed by BM (68.2 %) and M(64.5 %), R(15.9 %)the lowest. This isassociated
with the properties oftheprotein (VanSoest, 1994). Infreshforage (B) halfofthetrue
protein is inwater-solubleform,while maizesilagealso hasarelatively high NPN(nonprotein nitrogen)-content comparedtoconcentrate orstraw.
EE digestibility didnotdiffer significantly (P>0.05) among B,BM,MandMior between
BC and C. This may beduetothequality andquantity ofthe EEintakealongwiththe
interaction withtheother nutrients. However,thevaluesfor BRand Rwere significantly
different from thatfor B.TheEEdigestibilities decreased intheorder C(80),M(69.5),
B (66.9) and R(17.2).Thecombination ofBwithC,RorMleadsto EEdigestibilities as
predictedfromtheweighted averagesforthesinglefeeds.
The digestion coefficients ofcrudefiber (CF)weresignificantly different (P>0.05) for all
diets,exceptfor BCand BRandfor Cand R.These relativedifferences indigestibility
126
-Ensilingcharacteristics,digestibilityandfeedingvalue-
probably reflect differences in fiber quality (Colucci et al., 1982;Uden, 1984a,b)in
berseem, concentrate, ricestrawandmaizesilage.Theresults indicatethat combining
M with B has no effect on CF digestibility, asMand Miarevirtually equal(71.7vs.
71.8). However, Jaakkola (1992) has reported that dilution offoragefiberwith less
digestible fiber (such as from concentrate or straw) maysometimescause reduced
digestibility. Thedepression infiberdigestibility mightbegreaterfor highquality forage
(such as berseem) than for low quality forage, due to a higher content ofsoluble
carbohydrates (Vadivelooand Holmes, 1979;Jaakkola and Huthanen, 1990).Thismay
have been the reason that C and R had the same CF digestion coefficient, as
calculated bythedifference method,when mixedwithB.
Table 6. Digestion coefficients (%)* ofthefeedstuffs andthe rations
Exp.1 ' Exp.2 Exp.3 Exp.4 Exp.51 Exp.6n Exp.7H Exp.8H
BR
M
Feedstuff"
B
BC
BM
R
Mi
C
Proximate analysis
DM
63.7a 64.6a 59.3b 68.9° 69.9° 64.9 a 56.5d 71.6C
b
57.3c 69.6 d 74.6e 75.0 b 51.6f 71.4b
OM
65.9 a 72.6
CP
73.8 a 63.3 b 55.6c 68.2d 64.5b 59.1 e 15.9f 62.8b
b
45.2° 65.9a 69.5a 80.0b 17.2e 65.6a
EE
66.9 a 78.3
b
a
48.2 47.3b 67.7c 71.7d 43.2e 44.0e 71.8 d
CF
56.3
a
NFE
69.8
82.1 b 65.0° 71.2a 78.4b 86.0 d 61.6 e 71.8'
Fiberfractions (%)
ab 49 be
2
NDF
43.8 a 46.2
46.7 b 48.9bc 47.3 b 51.3C 48.2b
ac
ad
b
b
ADF
40.6
43.6
53.6
40.8 a 38.1° 46.2d 60.0
41.2'
a
b
a
b
a
38.4° 58.0
Hemicellulose 62.2
49.7
63.2
48.2
34.5C 57.2a
ADL
21.6a 20.1 a 25.8ab 31.4ab 27.0ab 18.7ad 28.5ab 41.1 c
c
Cellulose
40.4 a 48.0b 55.8
40.7 a 40.2 a 53.9c 62.3d 41.2"
' a, b,c,.. Means inthesame rowwithdifferent superscripts aresignificantly different.
Direct metabolism trials
i Calculated bydifference methodfromexperiments 1,2,3,4and5
ii B= Berseem, BC= Berseem + Concentrates, BR= Berseem + Rice straw, BM=
Berseem +Maizesilage,M=Maizesilage,C=Concentrate and R=Ricestraw.
Digestibilities of fiber fractions
There was nosignificant difference (P<0.05) between Band Mindigestibility ofanyof
the fiberfractions,exceptfor NDF,with berseem havingthe lowervalue. Ingeneral,the
values for legumes,such asberseemare lowerthanfor grasses,suchasmaize (Van
127
M-Mi
1.7
-3.2
-1.7
-3.9
0.1
-6.6
-0.7
3.1
-6
14.1
1
-Chepter6-
Soest, 1994). Digestibilities of the fiber fractions of C, R and Mi (by difference
calculations) were significantly different (P>0.05),exceptfor NDFbetween CandMi.
For the mixtures, NDFandADLdigestibilities were notsignificantly differentfor BC,BR
and BM,whilethoseforcelluloseandhemicellulosewere. NDFisindeed knowntobe
more closely associated with intake than withdigestibility, because itrepresents the
total insoluble matrixoffiber (vanSoest, 1994).
Uden (1984b)andJaakkola (1992) have reported larger reductions in NDFdigestibility
of forage with increasing levels ofconcentrate inhay-fedthan insilage-fedcows.On
the other hand, when supplementing with high levels of straw, anincrease inNDF
digestibility was observed (Silva and Orskov, 1988; Nellovu and Buchanan-Smith,
1985; Prasad et al., 1993). Indeed in the presenttrials,NDFdigestibility of BRwas
higherthanofBCorBM.
ForADF, Mhadthe lowest (38.1%)and Rthehighest (60%)digestion coefficient, with
C intermediate (46.2 %).Thiscouldpartly beexplained inrelationtothe corresponding
ADF content (Table 3)and intake (Table4)ofM,RandC. The highestADF content,
of which the degradable part is mainly cellulose (Bosch et al.,1991)seemsto be
associated withthe highestADFdigestibility forthe individualforages.Thesametrend
was found in BR, BC and BM, with ADF digestibilities of 53.6, 43.8 and40.8%,
respectively. Digestibility ofADF inMincreased (41.2vs.38.1 %),whenmixedwith B.
This may have resulted from the more favorable energy/protein ratioforthe rumen
microorganisms.
Hemicellulose and cellulose digestibilities werealmost identicalfor BandM,whilefor
Mi it was 6 units lowerthanfor M.ComparingthedataforC, Rand Mi,calculated by
difference, shows that thedigestibility ofhemicellulose was highestfor Mi,and lowest
for R. For cellulosedigestibility,thevaluefor Rwashighestandfor Milowest. Forthe
mixtures, the digestibilities are ranked BM>BC>BR and BR>BC>BMfor hemicellulose
and cellulose, respectively.
For ADL, digestibility increased remarkably (14.1units)whenmaizesilagewas mixed
with berseem (41%). For the mixtures, BM showed the highest value and BCthe
lowest. It was expected to find a lowerADLdigestion associatedwithahigherADL
content, because lignin isboundtothecellulose-hemicellulosefraction ofthecellwall,
and acts as a barrier for enzymatic degradation by rumenmicroorganisms (Engels,
1987). Therefore, degradation of the cellwallfractiondecreases (Bosch etal., 1991)
with increasedADLcontent.
Feeding values
TDN and DCPvalues (Table7)are inagreementwiththedata inthe region,andwere
in descending order C>M>B>R for TDN and B>C>M>R for DCP. When feeding
berseem mixed with Ctotalfeed intake increasedfor berseemwithconcentrates (BC),
128
-Ensilingcharacteristics,digestibilityandfeedingvalue-
but forage intakedecreased (Jaakkola, 1992;Mould,1988). Thismay berelatedtothe
density oftheconcentrates and itsNDFcontentwhichwasnegatively correlated (r=0.56) with DM intake.Theobserved lower intakeof BRmayberelatedtothe reduced
rate of digestion andpassage (Colucciet al., 1992;1990),bothfactorsthatgovernthe
extent ofrumenfill.
Table 7. Feeding valuesoftheexperimental feeds
TDN
DCP
B
58.77
12.87
BC
BR
BM M
C
R
66.42 49.15 63.76 69.96 69.32 42.94
10.74 5.57 8.2
5.97 9.93 0.83
Mi
61.69
6.62
Conclusion
Under the prevailing conditions in Egypt, the fermentation process ofmaize silage
reaches an acceptable range (indicated bythefermentation products) after 16daysof
ensiling. Maizesilage hasneither negative norpositive effects whenfedwith berseem.
Feeding berseem with maize silage increase total DM intake and improve the
energy/protein ratio (64%TDN and 12% CP) which allows medium level of milk
production.
References
Bosch, M.W., S.TammingaandG.Post, 1991.Influence ofstageofmaturity ofgrass
silages on digestion processes in dairy cows: 1. Composition, nylon bag
degradation rates, digestibility and intake. Ph.D. Thesis. Wageningen
Agricultural University, The Netherlands.
Castle, M.E., M.S. GillandJ.N.Watson, 1981. Silageandmilk production:a
comparison between barley and dried sugar beet pulp assilage supplement.
Grass and Forage Sci.36:319-324.
Cleale, R. M.,J.L,Firkins, F.vander Beek,J.H.Clark, E.H.Jaster, G.C. Mccoy, and
T.H. Klusmeyer, 1990. Effect of inoculation of whole plant corn foragewith
Pediococcus acidilacticiandLactobacillusxylosusonpreservation ofsilageand
heifergrowth.J.Dairy Sci.73:711-718.
Colucci, P. E., E. L.Chaseand P.J.Van Soest, 1982.Feed intake, apparent
digestibilityand rateofparticulate passage indairycattle.J.Dairy Sci.65: 14451456.
Colucci, P.E., G. K. Macleod,W.L.,Grovum, I.McMillan and D.J.Barkey, 1990.
Digesta kinetics insheepandcattlefeddietswithdifferentforageto concentrate
ratiosat highand low intakes.J.Dairy Sci.73:2143-2156.
129
-Chapter6-
Egan,A.R. 1977.Nutritional statues andintake regulation insheep.VIMRelationship
betweenthevoluntary intakeofherbage bysheepandtheprotein/energy ratioin
thedigestionproducts.Austr. J.Agric. Res.28:907-915.
Engels, F.M., 1987.Changes inthephysical/chemical structuresofcellwallsduring
growth and degradation. In:Degradation oflignocellulosics inruminants andin
industrial processes. ElsevierApplied Science Publishers.LTD.
Flachowsky, G.,W. Peyker,A. Schneider, andK. Henkel,1993.Fibreanalysisand in
sacco degradability of plantfractionsoftwocornvarieties harvested atvarious
times.Anim. FeedSci.Technol.43:41.
Goering, H.K. and P.J.Van Soest, 1970.Foragefiber analysis.Agricultural Handbook
No379.ARS, USDA,Washington, DC,USA.
Heron, S.J.E., R.A. Edwards,and P. Phillips, 1989.Effect ofpHontheactivity of
ryegrass Loliummultiflorumprotease.J.Sci.FoodAgric.46:267-277.
Huthanen, P., 1992.Theeffects ofbarleyvs.barleyfibrewithorwithout distillers
soluble on site and extentofnutrientdigestion incattlefed grass-silage-based
diet.Anim.FeedSci.&Tech.36:319-337.
Jaakkola, S., 1992.Silagefermentation inrelationtothefeeding valuewithspecial
reference to enzyme-treated grasssilage. Ph.D.Thesis,Department ofAnimal
Science, University of Helsinki,Finland.
Jaakkola, S.,and P. Huthanen, 1990. Responsetocellulosetreatment ofsilageand
replacement of barley by sugar beet pulp in thedietsofgrowing cattle.Acta
Agric. Scand.40:415-426.
Luther, R.M., 1986. Effectofmicrobial inoculation ofwhole plantcornsilageon
chemical characteristics, preservation and utilization by steers. J.Anim.Sci.
63:1329.
Mayne, C.S. and F.J. Gordon, 1984.Theeffect oftypeofconcentrate and levelof
concentrate feeding onmilk production.Anim.Prod.39:65-76.
McDonald, P.,A. R. Henderson,andS.J.E. Heron, 1991.The Biochemistry ofSilage.
2nded.Chalcombe Publ., Marlow, UnitedKingdom.
Merry, R.J., R.F. Cussen-Mackenna,A.P.Williams,andJ.K.S.Tweed. 1993.The effect
of different inoculates on fermentation and proteolysis in silages of different
perennial ryegrass andwhite clovercontent. Page 83-84 inProc. 10th Int.Conf.
Silage Res. Sep. 6, 1993. Dublin, Ireland. P. O'Kiely, M. O'Connell, andJ.
Murphy, ed.City Univ., Dublin,Ireland.
Mould, F. L., 1988.Associative effects offeeds. In: Orskov, E.R. (ed)WorldAnimal
Science B4,FeedScience,pp.279-292.Amsterdam: Elsevier.
Nellovu, L.R., and Buchanan-Smith,J.G., 1985.Utilization ofpoorquality roughage by
sheep: effect of alfalfa supplementation onruminalparameters,fiber digestion
and rateofpassagefromthe rumen.CanadianJ.ofAnim. Sci.65:693-703.
Phipps, R.H.,J.D.Sutton.,R.F.WellerandJ.A. Bines., 1987.Theeffect ofconcentrate
130
-Ensilingcharacteristics,digestibilityandfeedingvalue-
composition and method of silage feeding on intake and performance of
lactating dairy cows.J.Agric.Sci.,Camb. 109:337-343.
Prasad, C.S., K.T. Sampath, M.T. ShivaramaiahandT.K.Walli, 1992. Dry matter
intake, digestibility and supplementation of slender and coarse straw.
Proceedings of an international workshop on Feedingofruminantsonfibrous
crop residueswork. February 4 - 8 , 1991,Karnal,Haryana,India.
Silva,A. T.,andOrskove, E.R., 1988.Theeffect offivedifferent supplements onthe
degradation of straw in sheepgiven untreated barleystraw.Anim. Feed Sci.&
Tech. 19:289-298.
Tamminga, S.andA.J.M. Jansman, 1997.Animal Nutrition.Department ofAnimal
Nutrition,WageningenAgric. Univ.The Netherlands
Thomas, C, K.Aston,S.R. DaleyandJ.Bass,1986.Milk productionfromsilage.4.The
effect ofthecomposition ofthesupplement.Anim.Prod.42:315-325.
Uden, P., 1984a.Theeffect ofintakeand hay:concentrate ratio upondigestibility and
digesta passage.Anim.FeedSci.&Tech. 11: 167-179.
Uden, P., 1984b. Digestibility anddigesta retentiontime indairycows receiving hayor
silage atvarying concentrate levels.Anim.FeedSci.&Technology, 11, 279-281.
Vadiveloo,J.andW. Holmes, 1979.Theeffectofforagedigestibility and concentrate
supplementation on the nutritive valueofthedietand performance offinishing
cattle.Anim.Prod.29:121-129.
Van Os,M., P.G.vanWikselaarand S.F. Spoelstra, 1996.Formation ofbiogenic
amines inwell-fermented grasssilages.J.of Agric. Sci. 127:97-107.
Van Soest, P.J.,1994. Nutritionalecology ofthe ruminant.2nded.Cornell Univ. New
York, USA.
Williams,A.P.,R.J. Merry,J.K.S.Tweed,and D.K. Leemans, 1992.Theeffectof
different additives on proteolysis during ensilage ofperennial ryegrass.Anim.
Prod.54:487.
131
Chapter7
Financial, Nutritional,andAcceptability Assessment ofMaizeSilage
forSmallandMediumScaleDairy Farming
A.Tabana1,H.A.J.Moll2,H.van Keulen3andS.Tamminga4
1
Animal Production Research Institute.P.O. Box443,Dokki,Giza,Egypt
department ofSocialScience, Development Economics Group,Wageningen-UR,
Hollandseweg 1,NL 6706 KNWageningen,The Netherlands
3
Agrosystems Department, Plant Research International,Wageningen-UR, P.O. Box
16,NL6700AAWageningen,The Netherlands
4
DepartmentofAnimalScience,Wageningen InstituteofAnimalSciences,
Wageningen-UR, P.O. Box338,NL6700AHWageningen,The Netherlands
(Submittedfor publication)
Chapter7
Financial, nutritional,and acceptability assessment of maize silage for
small and medium scale dairy farming
Summary
This paper is one of a series ofstudiestoevaluatemaizesilageasoneofthe most
promising new technologies/interventionsintroduced and applied by the Egyptian
farmers. The overallgoalistoevaluatethemaizesilagetechnically, economicallyand
itsacceptabilitybythefarmers.
The methodology implemented incorporate results of on-station experiments with
animals andinterviewsofonehundredandfifty-fivefarmers, spreadover 13villagesto
collect data,aswellasusingMDFM(MixedDairyFarmingModel)whichdevelopedby
the authors topredicttheannualmilkproductionandthenutritionalrequirements. The
costs and returns of cultivatingBerseem (B)(Trifolium alexandrinum) asmainforage
andMaizeforsilage(M)werecalculatedusingthedataobtainedfromadditionalsurvey
(17 respondents) conducted in the same villages. While for Rice straw (R) and
concentrates(C),themarketpriceswere used.
Eleven different combinations (scenarios) of the four feedstuffs weredevelopedto
assess the nutritionalfeasibilityof9milkproductionlevels.The scenariosaimssatisfy
the nutritional constraints and tominimizethefeedingcostofthe9production levels.
Sensitivity analyses with regard totheeffectofchangesinmilkprice,landrentaland
laborwages onthemarginoverfeeding costswereperformed.
For the acceptability of the maize silage by farmers, the study demonstrated the
introduction ofmaizesilage,farmersawareness andtheroleofextension, responseto
other new technologies with maize silage, farmer's point of view and finally, the
constraintsofmakingmaizesilageinthestudyarea.
The authorswereabletoconcludethatthisstudysupportthehypothesisthatnutritional
factors represent a major limitation to increase systemproductivityandprofitunder
conditions in many similar districts in Egypt. In addition the studyshowedthatthe
farmers'reaction/response towardnewtechnologiesisverypositive.
Introduction
Mixed farming with livestock complementary to crops is widely practiced inEgypt.
Quality and availability of feedstuffs pose problems for themore intensivetypesof
livestock production. Concentratefeeds havenoconsistentandstable nutrientquality,
and whereas low quality roughage suchasricestraw isavailable, its lowdigestibility
limits the useasasourceofenergy,particularlyformilkingcows.Thewishto increase
livestock productivity and farmers' income hasledtothe introduction andadoptionof
new technologies in dairy production. Whole maize silage has been one ofthese
134
-Financial,nutritionalandacceptabilityassessment•
innovations that has been introduced to improvequalityandavailability offorages all
yearround.
Dairy farming is a commercial enterprise andtheobjectiveoffarmers isoverall profit
rather thanacontributiontonational production (Mainland, 1994).Twoobjectives from
the national viewpoint however, increasing ruralincomesandsupplyingthe nationwith
a balanced diet, runparallelwiththefarmers'objectives andjustify stateparticipation in
research andextension.
Animal nutrition research and extension require methods toassessthefeasibility of
technical innovations (Schiere and De Wit, 1995)beforetheir application underfarm
conditions. The challenge fortheevaluation ofnewtechnology istoaccurately predict
the consequences for environmental, biological and economic characteristics
(Congleton, 1984) under a range of physicalandmarket conditions (Bowman etal.,
1989; Moll, 1993). The eventual success of the introduction of an innovation is
determined by farmers' response, primarily based onthe resource requirements,the
impact on risk, and on profitability. This response is however alongtermprocess,
especially when farmers are not inapositiontojudgethe relevant issues inadvance,
particularly the production response to new feeds or feed combinations and their
impact oncosts.Therefore, intheearlystages ofdevelopment and introduction ofnew
technology such as maize silage, considerable benefit could be achieved by
undertaking more detailed analysis of the production, its interaction with other
components of the diet and its potential impact on the feeding costs andthuson
income.
This study provides atwo-fold assessment ofthe inclusion ofmaizesilage inthedietof
dairy cows. First, a combination of on-station and on-farm research leads to an
assessment of the nutritional and feeding cost aspects at various levels of milk
production.Second,the responsesofagroupoffarmerswhogainedaccesstothenew
technology through a development project such as the Food Sector Development
Programme (FSDP) provide insight intheacceptability undernormalfarmconditions.
Methodology
A semi-structured interviewwith 155farmers provideddata ontheactual productionof
maize silageand berseemin 1997.Thesefarmerswere pre-selectedthrough stratified
sampling over 13 villages. The selection of individual farmers was based on the
following criteria: 1)milk production,farmers should haveatleast2adultdairy animals;
2) silage making, farmers had made silageat leastonce. Inthe interviews,the input
and output quantities for the two fodder cropswere recordedtogether with pricesof
land, labour, and other feedstuffs such asricestrawandconcentrates. Additionally,
questions were asked regarding various aspects relatedtotheacceptability of maize
silage.
135
-Chapter 7-
On-station experiments were carried out to establish thechemicalcompositionand
feeding values, as well as the relationship betweenvariousfeedcompositions,that
used inthis study.
Data on the production and feeding cost of maize silage,berseem, ricestraw and
concentrates are combined with the relationship betweenvariousfeed compositions
and milk production, to analyse the relationships betweenoptimalfeedcomposition,
cost of various rations and feeding, and milk yield levels. Sensitivity analysiswith
regard to pricesof landand labour iscarried outtoarriveattheleastcost combinations
offeed compositions andfeeding,atvarious levelsofmilkyield.
The analysis ofthefarmers' responsetothevarious aspects relatedtothe acceptability
of maize silage provides direct insight inthe possibilities and limitations accordingto
farmers' experience inthe production andfeeding ofmaizesilage.
Feed composition and milk production
The production of maize silage and berseem
Farmers are generally aimingatmaximizingtheutilityoftheir resourcesbypursuinga
set of multiple objectives.Theseobjectives areconditioned byavailability of resources
and technology. Utility maximization implies that farmers are likely to adopt new
technologies whentheyenhancethechanceofobtaininganacceptable returnfromthe
available resources. Under current farming systems, farmers have the choice to
produce maize for cash or to make silage to feed their animals, insteadof using
purchased concentrates. Maizeforsilagehasimplicationsfor land resources, laboruse
and capital requirements. To assess and comparethefarm resources relatedtothe
production ofberseem (B) andmaizesilage (M),datawereanalyzed asshown inTable
1.
The data indicate that M needs moreexternal inputsthan B;the basicexternal input
needed for M cultivation was almost double that of B (1.9 vs. 1). Adding the
conservation costs increasedthe ratiobetweenMandBto2.7 :1 .
To estimate labor requirements, ,thecurrentfeeding systems isassumed acut-andcarry system. However, Bneeds labortocut-and-carry forages over longdistancesto
feedthe animals,while, maizesilage isalwaysstoredclosertotheanimalhouse.
For land, B occupies the land for7months comparedto5months occupation byM.
Under irrigatedsystems,where2crops peryeararecultivated,thecalculation inTable
1 takes into account the length ofcropping period inthefield. However, relatively,B
needs28%more landthanM.
The total costs of production,includingfeeding,indicate minordifferences betweenB
andM.
136
-Financial,nutritionalandacceptabilityassessment-
Table 1.Productionandfeeding offodder crops (units perfeddan).
Unit
Berseem Maizesilage
Production
DM
Ton
5.5
5.6
External inputs
Fertilizer
Seed
Tractor hire (land preparation)
Chopper hire (maizesilage)
Materials (plasticformaizesilage)
Machineryfor balingandtransport
Subtotal
£E
£E
£E
£E
£E
£E
£E
179
74
93
0
0
0
346
350
150
142
120
58
0
820
Manday
Manday
8
75
18
—
Manday
Manday
—
—
83
4
36
58
Month
eddan/year
7
0.58
5
0.42
£E
£E
£E
£E
370
664
875
1909
861
464
625
1950
Labor
Cultivation
Harvesting includes feeding
(berseem)
Silage making (maizeonly)
Feeding (silage)
Subtotal
Land
Season length
Relative land occupation
r
Costfor productionandfeeding
Cash, including 1% interest/month
Labor,at£E 8permanday
Land,at£E 1500perfeddanyear
Total
Financial comparison offeedstuffs
The choice between producing home-grownfeeds orpurchasefeedsfromoutside,is
determined by financial and practicalconsiderations. Practically, maizesilagecanbe
produced under localcircumstances. However,farmers canrejecta newtechnology for
reasons ofunknown risksor uneconomic performance or inappropriatenesstotheir
137
-Chapter 7-
resource availability. A simple methodcomparesthe unitcostofnutrients asdoneby
Kearl (1982), and Schiere and Nell (1993). This methodofcost per unitof nutritive
value is simple, but inadequate because itvaluestheenergy andprotein separately
and does not take intoaccountdrymatter intakelimitations.Comparingthe resources
required for 1000£Eworthoffeedproductiontopurchasing concentratesfor 1000£E,
and applyingthe sameconceptforfeedingvaluesandfeeding limitation,would provide
a more realisticevaluation.Table2representsquantitative andqualitative comparison
of producing 1000 £E worthfromon-farmproducedfodder (BandM)andpurchased
feedstuffs (RandC).
Table 2.Comparison offodder production1,4and purchasedfeedstuff for 1000L£
worth.
Unit
Berseem
Maize
silage
Resources required
Cash
Labor1
Manday
Feddanyear
Land
194
43
0.31
421
30
0.21
654
39
0.00
1000
p.m.
0.00
Feeding values
Dry Matter
TDN2
CP3
Cost perkg
2.88
1.69
0.50
0.347
2.87
2.01
0.27
0.348
13.07
5.61
0.68
0.077
1.48
1.02
0.25
0.677
Ton
Ton
Ton
Maximum proportion infeedstuff mixture
Lowand medium production levels
0.80
0.65
High production level
0.80
0.65
Constraintfor highmilk
Lowenergy Highenergy
yield
Highprotein Lowprotein
Medium
Potentialfor highmilk
production level
includingthe required labourtofeedtheanimals
2
Total Digestible Nutrients,3Crude Protein
4
Pricesof landand labour areprovided inTable1
138
Medium
Ricestraw
Concentrates
0.40
0.70
0.00
0.70
Highbulking Highenergy
Lowenergy Highprotein
Low protein Lowbulking
Low
High
-Financial,nutritionalandacceptabilityassessment•
Data indicate thatfarmers haveto match resource availability withquality andquantity
ofproduction asfollows:
• A relative abundance of land and labor and somecashisrequiredfor berseem
production. The levelofmilk production islimited bytheenergy content ofberseem,
and only lowand medium levels ofproduction arepossible.
• Less land and laborcombinedwithmorecashisrequiredtoproduce maizesilage.
The level of milk production is limited by the protein content,andonly lowand
medium levelsofproduction areattainable.
• No land, but cash andlabouronlyarerequiredforfeeding ricestraw, butonly low
milk production levels arepossible.
• No landand (hardly) labour, butcashonly isrequiredtofeed concentrates. Medium
and high levelsofmilk production areattainablewiththequality ofconcentrates as
thedetermining factor.
Nutrition and Milk production
The feeding values, constraints andpotentialsfor highmilk production suggestthata
combination ofthefourfeedstuffs would leadtoabalanceddietfrom anutritional point
ofview (energy andprotein) andeconomic rationformulation.
Calculation ofsuchcombinations aimsat minimisingthefeeding costatdifferent levels
ofmilk production.The prices oftheforageswerecalculatedfromthedirect costsof
Table 3. MDFM1 predictions ofannualmilk production and nutrient requirements.
Milk production
Annual
Daily
4
1113
1670
6
2226
8
10
2783
3339
12
14
3896
16
4452
18
5009
5565
20
2
Nutritional requirements (annual)
TDN 3
DM 3
CP 3
2704
1674
353.3
1855
402.4
2993
2036
450.8
3274
496.2
3525
2215
534.8
3713
2363
3939
2542
573.9
615.7
4156
2719
2897
656.6
4366
3074
696.7
4569
1
The state variables in MDFM (Mixed Dairy Farming Model) are: 1)number ofdays
pregnant attheendtheyear is220;2) Bodyweight is450 kg,with nogain; 3)animalin
thethird parity
2
Daily milk production (kg,at4%fat) atfirst monthof lactation
3
DM=dry matter;TDN=totaldigestible nutrients andCP=crudeprotein.
139
-Chapter 7-
fodder production, whileforconcentrates and ricestraw,themarket priceswereused.
The nutritive values applied here,havebeendetermined earlier (Chapter 6,thisthesis)
by conducting in vivotrials.The nutritional constraints requirethatoptimaldiets satisfy
animal requirements fordry matter, energyand protein.Inaddition,constraints specify
a maximum proportion of each individualfeedstuff intheformulated diet.Thefeeding
values andthe constraints usedareshown inTable2.
Total annualmilk productionand nutrient requirementswere predicted usingtheMDFM
model (Chapter4).Thestatevariablewassettofixedvaluesfortheanimals,exceptfor
milk production in the first month of lactation. Predicted milk production,aswellas
nutrient requirements areshown inTable3.
Nutritional assessment of the feed mixtures
Feeding scenarios
A number ofdifferent combinations ofthefourfeedstuffs weredeveloped toassessthe
nutritional feasibility at a certain production level (9 levels) as well as the costof
feeding. The nutritional assessment ofthe 11possiblecombinations (scenarios) forthe
9 milk production levelaresummarized inTable4,andthedetailed proportions ofthe
diets, aswellasthefeeding costsareoutlined inAppendix 1.
Table 4.Summary ofthefeedingsituation ofdifferentfeedstuff combinations and
their feedingcosts.
Feedstuff
Feedingsituation
Scenario 1
B+C+R+M Allfeeding requirement andconstraints satisfied
Scenario2
B+C+R
Up to 5000 litre,DMandTDNaresatisfied,asurplus isprovidedof15%
above thetotalprotein required.Above 5000 litre,thesamewithasurplus
of2%intotal DMrequirements.
Scenario3
C+R+M
For a low production level (1100 litre) all feeding requirements and
constraints aresatisfied.Above 1100litre,DMandCParesatisfied,anda
surplus is provided of 5% over total TDN requirements.Tosatisfy CP
requirements, concentrates exceed themaximum proportion allowedto
maintain healthy condition, being 74, 77 and 79% of DM for animals
producing4450,5000and5560 litre/annum,respectively.
140
-Financial, nutritional andacceptability assessment•
Scenario 4
B+R+M
Up to 2800 litres, all nutritional requirements are satisfied.At 3300 litre, a
small deficiency inTDN occurs, above that level no feasible solution due
to high dry matter content
Scenario 5
B+C
All feeding requirements and constraints are satisfied,with 2% surplus in
total TDN requirements. At high production levels (5000 and 5560 litre),
concentrates contributed 72 and 8 1 % of the total DM requirements.
Scenario 6
B+M
Up to 2780 litre, all feeding requirements and constraints are satisfied,
with a total TDN supply 10% above requirements. For more than 2780
litre, CP and TDN are satisfied, but DM is 4 % higher than the total
requirements.
Scenario 7
B+R
No feasible formulation, using this mixture. Up to 4450 litre, CP was hardly
satisfying the requirements, but TDN is less than the requirements at all
production levels. The deficiencies ranged from 11 to 17%of the total
TDN required. For 5000 and 5560 litre, neither TDN nor CP are satisfied.
Scenario 8
C+R
Up to 2220 litre,the formulated rations were feasible with small surpluses
of DM, TDN and CP of 4, 2 and 1 % , respectively. While, no feasible
formulation at higher production levels, the deficiencies range from 2 to
9% of the TDN requirements and from 5to 15% of the CP requirements,
for cows producing 2780 up to 5560 litre per lactation.
Scenario 9
C+M
Feasible formulation occurred with this mixture with a remarkable reverse
trend for TDN surplus and milk production level.
Scenario 10
R+M
No feasible solution for any production level, only DM requirements are
covered, while TDN and CP are not satisfied at any production levels.
Scenario 11
B+C+M
Feasible solutions at all production levels, with surplus of CP for milk
production up to 2800 litre.
Optimizing feeding (financial assessment)
The gross returns of milk and the feeding costs of scenarios 1and 2 are presented in
Figure 1.It is clear that scenario 1(S1) is profitable at all production levels, while S2
141
-Chapter 7-
becomes profitable whenmilk production exceeds 2000 litreperyear. Moreover, S1is
associated with lowercosts,evenathighproduction levels.
Figure1 Feedingcosts andmilkreturn(gross)ofdifferentmilkproductionlevels
4.5
a Return
oS1(BCRM)
* S2(BCR)
2.2
2.8
3.3
3.9
4.5
Mlkproduction (000,liters)
For the other scenarios, S7, S8andS10wereignored,becausetheycannotsatisfy
the nutritional requirements of the animals. S4andS6arefeasible at lower levelsof
milk production (upto2800 litre).The otherscenarios are nutritionally feasible butvary
incosts.
In general, S1 and S11, which both contain B and M, arethebestscenarios with
respect to the costs andthe potentialsfor highmilk production levels. However, itcan
beconcludedthat supplementation ofthe localforage (berseem) byconcentrates atthe
current milk price (0.8 LE/litre) isunprofitable atlowlevelsofmilk production. Useof
maizesilage isprofitableat anyproductionlevel.
Sensitivity analysis
Two scenarios were selectedto perform sensitivity analysiswith regardtochanges in
milk price,land rental rateand labourwages onthecostoffeedproduction,milk return
and feeding costs. The first scenario (S1) representsthe improvedfeedingsystem,
including maizesilagewithberseem,ricestrawandconcentrates.Thesecondscenario
(S2) representsthetraditionalfeeding system,including B, RandConly.The changes
inprices leadtochanges inrationcostandmilk revenueonly, nottochanges inthe
142
-Financial,nutritionalandacceptabilityassessment•
ration composition. Hence, in both scenarios the same quantities are used as
formulated inAppendix 1.
Response offeed production coststochanges inresource prices
To examine the effect of increasing farm resources pricese.g.land rentalrateand
labour wages on production costs (includingfeeding) of BandM,sensitivity analyses
were performed byincreasing landrental rateandlabourwages by25,50and 100%of
thecurrent prices.Thevalues ofthe resources andthe response areshown inTable5.
Table 5. Responseoffeedstuff coststochanges inresource prices
Land
%
Value
increase
LE
0
1500
—
1500
25
1875
50
2250
—
1500
100
3000
—
1500
25
1875
50
2250
100
3000
Labour
Value
%
LE
increase
8
10
8
8
12
8
16
10
12
16
0
25
—
—
50
—
100
25
50
100
Feedstuff (LE/Ton)
B
C
R
M
347
377
387
427
407
506
468
417
487
627
677
677
677
677
677
677
677
677
677
677
77
83
77
77
89
77
101
83
89
101
348
369
376
404
390
460
431
397
445
543
Results indicate that B production is more sensitive than Mtochanges inresource
prices. When price of land rental increases by25, 50and 100%thetotal production
costs increases by8, 16and32%formaizecomparedto 12,23and46%for berseem.
The same trends hold for labourwages:totalproduction costs increase by6, 12and
24% for maize compared to 9, 17and35%for berseem. Increasingthe priceofboth
land and labour increasesthe production costs by 14,28,and56for Mand20,40and
80% for Bwhenprices increase by25,50and 100%,respectively.
Responsetochange inmilk price
The responseofmarginoverfeeding coststochanges inmilk pricewasexamined by
increasing milk priceby20and50%comparedtothecurrent price (Figure2).
143
-Chapter7-
Figure 2.Effect ofincreasing milk priceon themargin overfeeding costs
4.25
Thousands
Margin overfeeding cost(LE)
5.25
3.25
2.25
1.25
0.25
-0.75
•?•
1.1
i
1.7
2.2
2.8
3.3
3.9
4.5
Milkproduction (000, liters)
5
i
5.6
a Scenario 1atcurrent price
± Scenario 1plus 50% increases
a Scenario 2atcurrent price
o Scenario 2plus 50% increases
At the current price of milk, net margin is negative, whenmilk production islow,(477LE); when milk production increases to 2000 litre the marginbecomeszero.A
positive margin is realised only when milkproductionexceeds 2000 litreperannum,
which represents the economic levelofproductionatcurrent pricesofmilkandfeeds.
The same trends are found formilk price increasesof25and50%,theimpact being
that the economic level of milk production decreases to 1500 and 1100 litre,
respectively. Forthe improvedfeeding system (S1),increased milk prices haveadirect
positive impact onthemargin overfeedingcosts.
Responsetochangesinland price/rental rate
The responses of net margintoincreases inlandrentalrateandlabourwages by25,
50and 100%,comparedtothecurrent pricesarepresented inFigures3and 4.
At current prices, S1 is the only profitable scenario at a milk production of 1100
litre/annum. When the price of land increases by 25, 50 and 100%,profitable milk
production level shift to 1700litre.Inthetraditionalfeedingsystem(S2)the profitable
level is 2200 litre, when prices increase by 25 and50%and2800when land price
increasesby100%
Similar trendswerefoundwhen labourwageswereincreased.
144
-Financial, nutritional andacceptability assessment•
Figure 3.Response tochanges inland rental rate
5
r
4 .
3
-i-»
a)
1—
•D
C
CO
x:
CO
m
O
to
•o
c
-B-Milk return
3
8
*-S1
o
.c o
H
-A-S2
1 .
1.1 1.7 2.2 2.8 3.3 3.9 4.5
5
5.6
Milk production
Figure 4.Response tochanges inlabour wages
5 r-
c/>
c
-B-Milkreturn
3 -S 3
OJ
C
-G-S1
•£• Si
2 F 2
*S2
<3
_i_
1.1
1.7
2.2
2.8 3.3 3.9 4.5
Milkproduction,000)
145
J
5
L.
5.6
-Chapter 7-
Farmers'perspective onmaizesilage
The measure of acceptance of maize silage by the farmers isan indicationforthe
feasibility of the new technology under normalfarmconditions.Ontheone handthe
response of farmers to maizesilagecanbeconsidered asatooltocheckwhetherthe
new technologies are suitable for farmers. On the other hand, itcan beusedasa
criterion to judge the extension performance/methodologies from different pointsof
view. Bothviewpoints arepursued below.
Introduction and acceptance
At the beginning of 1992,FSDP (FoodSector Development Program,aprojectfunded
by ECandthe Egyptiangovernment) introduced maizesilagemaking,alongwith other
innovations. Some inputsweresubsidized. Beforethistimemaizesilagewas unknown
to most of the farmers. Adoption by farmersofmaizesilagefrom 1992to 1997,as
recorded bythearea manager ofAshmoundistrict isshown inTable6.
Table 6. Number offarmers making maizesilageannually.
Item
1992 1993 1994 1995 1996 1997
No. of farmers identified byarea 7
41
55
159 682 944
manager
Estimated*
2166
No.offarmers receiving support
7
0
0
0
0
20
Source:DSAU,areamanager reports
*Estimated is based ontheassumptionthatthenumberoffarmersthat canbeserved
byonechopper is38(Tabana, 1998)
The data show that the number offarmerswho madesilage increased substantially
over the periodfrom 1992to 1997.TheArea Manager's estimatesareconsideredtobe
conservative, as theyonly refertofarmers knowntotheareamanager and hisstaff. It
is estimated that an additional 1222 farmeralsomademaizesilage in 1997givinga
total of 2166. The sample (155 respondents) represents 16.4%ofthefarmersthat
identified/reported by thearea manager, and7.2%oftheestimated number offarmers
that mademaizesilage.
Extension and awareness
To determinetheeffectiveness oftheextensionmethodology andtheway inwhichthe
farmers becameawareofmaizesilage making,theywereaskedwhentheyfirst heard
146
-Financial,nutritionalandacceptabilityassessment•
about the silage and who supportedthem inmakingsilage.Table 7givesthe annual
breakdown of the number of farmers that became aware of maize silageandthe
number actually involved insilagemaking.
Table 7. Number offarmersandawareness (timeof hearing)andapplying maize
silage makingfor 155random respondents
Year
83
87
90
91
92
93
94
95
96
97
Number of
farmers that
heard about
maize silage
for the first
time
1
1
3
4
17
38
36
30
22
3
Cumulative
number of
farmers that
heard about
maize silage
Number of
farmers that
made maize
silage for first
time
1
2
5
9
26
64
100
130
152
155
0
0
2
2
2
19
31
20
36
43
Cumulative
number of
farmers that had
made maize
silage at least
once
0
0
2
4
6
25
56
76
112
All respondents*
*Selection of respondents based onmaking silage in1997
Before 1992,veryfewfarmers (9) had heardaboutsilageand hardlyany (4) hadmade
it. Thefarmersthat hadmadesilagewereoften alsolivestocktraders,and hadseenit
being made in different areas where other projects had helddemonstrations. They
rented locally madechoppersfrom otherareasto makesilage.
With respect to the contribution of theextension staff inspreadingthetechnology of
making maize silage, the data inTable8summarizethesourceof informationtothe
farmers and the relativecontribution oftheextension staff inspreading informationon
maize silage. Hence, a relatively large number (108 respondents out of 155,
representing 69.7% of the sample) of farmers startedlearning aboutthe innovation
from theextension staff of FSDP.Neighbours (12.9%)orlargefarmers (11.6%) played
a minor role as source of spreading the maizesilage package,while other sources
such as television programs and projects located inotherareas played an insignificant
role.
147
-Chapter 7-
Table8.Source ofinformationwith respecttosilagemaking.
Extension staff
Neighbour
Innovator (large farmer)
Others
Total
No. of farmers
%
108
20
18
9
155
69.7
12.9
11.6
5.8
100
Introduction and responsetoother packages
Along with maize silage, other innovations were introduced tothefarmers.Table9
shows the other packages introduced by FSDPextensionstaff andthenumber and
percentage of farmers interested in applying these innovations. Three extension
packages are ranked with a relatively high priority, e.g. mufeed (molasses
supplemented by urea, minerals and vitamins; 29%), mixing feedstuffs to produce
home-made concentrate rations (26.5%) and artificial insemination (21%).Ammonia
and ureatreatment seems nottobesuitableforthisarea.
Table 9.Number offarmersapplying other innovations,besides maizesilage
Package
Number of farmers
%
Single package
Only maize silage
74
28
Double
-packages 1
M. silage +Mufeed 2
M. silage +AI 3
M. silage +Feed mix
M. silage +Ammonia treatment
M. silage + Urea treatment
M. silage + Hay making
45
33
41
5
9
4
17
13
16
2
3
2
Treble
M. silage + Mufeed + Feed mix
M. silage + Mufeed + Al
M. silage + Feed mix + Al
M. silage + Mufeed + Feed mix +AI
10
24
13
6
4
9
2
5
1
somefarmers arecountedtwotimeswhenapplying morethantwo packages.
Molasses supplemented byurea,minerals andvitamins
3
Artificial Insemination
2
148
-Financial,nutritionalandacceptabilityassessment-
Farmers' pointof view
In the interviews, each farmer has given his point of view with respect to the
advantages ofusingmaizesilagetofeed hisanimals.Thequestionnaire allowed giving
feedback about these advantages recognized, when applying maize silage in the
feedingsystems.
Farmers have givenamultitudeof reasonsandadvantages realized. Table 10shows
these advantages inqualitative andquantitativesense.
Table 10.Advantages recognised byfarmers afterapplying maizesilage
Advantage
Increase in milk and meat production
(1)
Decreasein feeding cost (2)
Decreasein straw use(3)
Decreasein labour costs (4)
Decrease in shortage of fodder
between summer andwinter (5)
Numberoffarmers*
135
%
20
94
53
15
33
14
8
2
5
87
49
13
27
43
11
26
7
20
8
39
6
5
13
7
2
4
6
2
4
1
3
1
6
1
1
d)+(2)
(1)+(3)
(1)+(4)
(1)+(5)
(2)+(3)
(2)+(4)
(2)+(5)
(3)+(4)
(3)+(5)
(4)+(5)
(1)+(2)+(3)
(1)+(2)+(3)+ (4)
(1)+(2)+(3)+ (4)-» (5)
Source: DSAU,1998
*Farmers are counted more than one time when they do recognize morethanone
benefit.
Farmers recognisedfivesingleadvantages:
a) Most ofthefarmers (87%) recognisedthatfeeding maizesilage hasapositive effect
on both mitkandmeatproduction.
149
-Chapter 7-
b) A relatively highproportion ofthefarmers (60%) believedthatfeeding maizesilage
reduced feeding costs, as aresultofeither usingsmaller amounts ofconcentrates or
using only maizesilagewithout anyconcentrates.
c) Some farmers (34%), mainly practicing fattening, responded that maize silage
reducedthe useofwheat straw,which isrelatively expensive intheirlocation.
d) A small number of farmers (21%) are making maizesilagetofillthegap infresh
fodder availability betweensummer andwinterseasons.
e) A limited number of farmers, who usedtohire labour,were respondingthat using
maize silage reduced labour costs, because they tend to feed their animalstwice
instead offour times asintheirtraditionalfeedingsystem.
Multiple advantageswere recognisedas:
Double benefits
- Increased production andreducedfeedingcosts(56%)
- Increased production andreducedstrawuse(31.5%)
- Other combinations rangedfrom4.5to27%
Treble andtetra benefits
One quarter oftherespondents recognisedtreblebenefits,whileavery limited number
of farmers recognised morethanthreeadvantagesofmakingmaizesilageasseenin
Table 10.
Constraints inAshmonarea
The data in Table 11, show that 59.4% ofthefarmersdid notfaceanyproblems in
makingsilage.A rangefrom6to 15%ofthesamplefaceddifferent constraints.
Table 11. Constraints inmaking maizesilage inAshmon area
Constraint
No.offarmers
Machine isnotavailable intime
20
10
Highchopping costs
24
High laborcostassociatedwiththe machine
0
Notenoughfodder tomakesilage
92
Noconstraint
%
12.9
6.4
15.5
0
59.4
Conclusion
The results of this study support the hypothesis that nutritionalfactors representa
major limitation to increase system productivity and profit underthe prevailing
150
-Financial,nutritionalandacceptabilityassessment-
conditions in many similar districts in Egypt. In addition, the study showsthatthe
farmers' reaction/response tonewtechnologies isverypositive.
The diet of berseem with maizesilageonly (scenario 5)wasthebestdietfrom botha
nutritional and an financial point of view, followed by a diet, comprisingberseem,
concentrates, rice straw and maize silage(scenario 1)whichisnutritionallyfeasible,
but economically lessattractive. Usingconcentrateswaseconomically notviable atlow
production levels (below 2000 litre). Using berseemwith ricestraw can beusefulfor
low-yielding cows. Themarginoverfeeding cost isstillpositive,evenwhen milk prices
would decrease by 25%, if using maize silage or the price of maizesilagewould
becometwiceas highasthecurrentprice.
The financial analysis shows that feed mixtures with maizesilage reducefeedcost
compared with mixtures without maize silage.Thisconclusion holdsatpresent price
levelsfor landrentalandlabor, andfor pricesthataretill 100%abovepresent levels.
Farmers in the project area have quickly recognized theadvantageofadding maize
silage to the dietoftheir dairyanimals.Their observationsfocus onhigher production
levels and lower production costs, which is in line withthestep-wise analysisfrom
nutritional andfinancialviewpoint bythe researchers.
Maize silage was well introduced by the extension staff and widely adoptedwhen
farmers recognised itsadvantages.
References
Bowman,P.J., D.A. Wysel, D.G. Fowlerand D.H.White, 1989.Evaluationofanew
technology whenappliedtosheep production systems:part I-Model
description.Agriculture Systems29:35-47.
Congleton,W.R.Jr. 1984.Dynamicmodelfor combined simulation ofdairy management
strategies.J.DairySci.67:644-660.
Kearl, L.C., 1982.Nutrient requirements ofruminants indeveloping countries.
International Feedstuff Institute,UtahState Institute,Logan,381pp
Mainland, D.D. (1994).A DecisionSupport Systemfor Dairy Farmers andadvisors.
Agriculture Systems,45,217-231
Moll, H.A.J., 1993.On-farm livestock research:Aframework forplanning.Goat
production systems inthehumidtropics. Proceedings ofan international
workshop atthe ObafemiAwolowo University, lle-lfe, Nigeria,6-9 July 1992.
Pudoc Scientific Publishers,Wageningen.
Olney, G.R. andG.J. Kirk, 1989.A management modelthat helps increase profiton
westernAustralian dairyfarms.Agriculture Systems30:367-379.
Pearson, RE. &Miller, R.H. ,1981. Economicdefinition oftotal performance, breeding
goals, and breedingvaluesfordairycattle.J.Dair Sci.,64,857-69.
Schiere,J.B.andJ.DeWit, 1995.Feeding ureaammoniatreated ricestraw inthe
151
-Chapter 7-
tropics. II:Assumptions onnutritivevalueandtheirvalidityfor leastcost ration
formulation.Anim. FeedScience andTechnology, 51:45-63.
Schiere,J.B.,andA.J.Nell, 1993.Feedingof ureatreatedstraw inthetropics. I.A
review of itstechnical principlesandeconomics.Anim.FeedSci.and
Technology,43:135-147.
S rensen,J.T. 1989.A modelsimulatingthe production ofdualpurpose replacement
heifers.Agriculture Systems30:15-34.
Stott,A.W.and Elston,D.A., 1991. Interpretationoflinear profitfunction inthe
presence ofcorrelated predictors,withapplicationtodecision support inadairy
enterprise.
Tabana,A.S., 1998. Farmer responsetothe introduction of newextension packagesin
Ashmoundistrict.Serialdocument number4, DairySystemsAnalysis Unit,
Animal Production Research Institute,Cairo,Egypt.
Tigges, R.J.,Pearson,R. E.&Vinson,W. E., 1984.Useofdairy herd improvement
variablesto predict lifetime profitability.J.DairySci,67,180-4.
152
-Financial,nutritionalandacceptabilityassessment-
Appendix 1. The optimization scenarios ofB,C,Rand Mutilization for different
milk production levelswith itsfeedingvaluesandcostsatcurrentprices.
MilkproFormulated2
1
Duction
DM TDN CP
Scenario1
2704 1674 353
1113
1670
2993 1855 402
3274 2036 451
2226
2783
3525 2215 496
3339
3713 2363 535
3896
3939 2542 574
4452
4156 2719 616
5009
4366 2897 657
5565
4569 3074 697
Scenario2 >
2704 1674 371
1113
2993 1855 412
1670
2226
3274 2036 563
3525 2215 605
2783
3339
3713 2363 636
3896
3939 2542 672
4452
4156 2719 707
5009
4381 2897 744
5565
4656 3074 791
ScenarioC \
1113
2704 1674 353
1670
2993 1862 402
3274 2107 451
2226
2783
3525 2452 496
3339
3713 2581 535
3896
3939 2738 574
4452
4156 2888 616
5009
4366 3033 657
5565
4569 3173 697
Scenario A\
1113
2704 1674 353
1670
2993 1855 402
2226
3274 2036 451
2783
3525 2215 510
3713 2336 535
3339
3896
4027 2542 574
4452
4311 2719 616
5009
4594 2897 657
5565
4875 3074 697
Scenario5
2704 1674 466
1113
Feedstuff
C
R
B
Balance4
DM TDN CP
M
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1094
1209
1382
1616
1878
2157
2445
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
15
87
0
0
0
0
0
0
0
0
0
17
9
113
109
101
99
92
87
94
1367
1517
1486
1672
1854
2077
2307
2529
2671
764 165
807 91
624 359
0
0
0
0
0
0
0
0
0
0
7
71
237
218
196
169
136
99
0
0
0
0
0
0
0
0
0
1318
1512
1724
1965
2123
2281
2452
2618
2782
0
0
0
0
0
0
0
0
0 -27
88 0
155 0
228 0
306 0
0
0
0
13
0
0
0
0
0
1094
1224
1290
1399
1497
1596
1693
112
1204
1376 0
1636 0
1887 0
2107 0
2081 279
1867 751
16101318
12961941
9462602
2361092
2071150
1601226
571361
01353
01321
01229
01129
01021
861893
1082095
22141060
21661359
19991714
17872152
15352621
13253056
14583198
725
790
0
0
0
0
0
0
0
01775
02095
02292
02245
02527
02768
03056
03341
03624
1376
1636
1887
2244
2339
2461
2652
2832
3005
0
0
0
0
0
0
0
0
0
1900 804
153
Feeding
Cost5
01280
01186
01171
01100
01025
0 945
2361092
2071150
1601226
01281
01374
01566
01659
01762
01870
0
0
0
0
876
984
876
984
-Chapter7-
1670
2993 1855 515
2226
3274 2036 563
2783
3525 2215 605
3339
3713 2363 636
3896
3939 2542 672
4452
4156 2719 707
5009
4366 2897 741
5565
4569 3074 773
Scenario6
1113
2704 1674 409
1670
2993 1855 451
2226
3274 2036 489
2783
3525 2215 510
3339
3746 2363 535
3896
4027 2542 574
4452
4311 2719 616
5009
4594 2897 657
5565
4875 3074 697
Scenario7
1113
3101 1674 425
1670
3437 1855 471
2226
3776 2036 516
2783
4119 2215 558
3339
4408 2363 592
3896
3939 2190 589
4452
4156 2311 622
5009
4366 2428 653
5565
4569 2541 684
Scenario8
1113
2736 1674 362
1670
3065 1869 402
2226
3557 2132 451
2783
3525 2165 470
3339
3713 2280 495
3896
3939 2419 525
4452
4156 2552 554
5009
4366 2681 582
5565
4569 2806 609
Scenario9
1113
2704 1883 353
1670
2993 2083 402
2226
3274 2278 451
2783
3525 2452 496
3339
3713 2581 535
3896
3939 2738 574
4452
4156 2888 616
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
113
113
109
101
99
92
84
76
1339
1486
1672
1854
2077
2307
2551
2802
0
0
0
0
33
88
155
228
306
0
0
0
0
0
0
0
0
0
56
49
38
13
0
0
0
0
0
1039
1137
1224
1301
1399
1497
1596
1693
0
0
0
0
0
0
0
0
0
397
444
502
594
695
0
0
0
0
0
0
0
0
0
72
68
65
62
57
15
6
-3
-13
1079
1141
1154
1218
1279
1339
0
0
0
0
0
0
0
0
0
32
72
283
0
0
0
0
0
0
-123
-167
-216
-268
9
0
0
-27
-40
-49
-62
-75
-88
1346
1493
1649
1752
1845
1958
2066
2170
2271
0
0
0
0
0
0
0
209
228
242
237
218
196
169
0
0
0
0
0
0
0
1388
1586
1781
1965
2123
2281
2452
2083 910
22141060
21661359
19991714
17872152
15352621
12283138
8843685
0
0
0
0
0
0
0
0
1946
2135
2274
2244
2302
2461
2652
2832
3005
0
0
0
0
0
0
0
0
0
0 758
0 858
01000
01281
01444
01566
01659
01762
01870
2163
2394
2619
2820
2970
3151
3325
3493
3655
0 938
01043
01157
01299
01438
0 788
0 831
0 873
0 914
01893 843
02095 970
022921265
024681058
025991114
027571182
029091247
030561310
031981371
01358
01654
01951
02245
02527
02768
03056
0
0
0
0
0
0
0
0
01346
01339
01323
01280
01186
01171
01100
154
-352
-408
-469
-533
0
14
96
-50
-83
939
823
911
998
-Financial,nutritionalandacceptabilityassessment•
4366 3033 657
03341
01025
0 136 0
5009
03624
0 945
5565
4569 3173 697
0
99
0
Scenario10
2704 1599 207
0
010821622
0 -75 -146
1113
2993 1770 229
0
0 -85 -173
1670
011971796
3274 1937 251
0
013101964
0 -99 -200
2226
014102115
0 -130 -226
3525 2085 270
0
2783
3713 2196 284
0
014852228
0 -167 -250
3339
3939 2330 302
015762363
0
0 -212 -272
3896
4156 2458 318
0
016622494
0 -261 -297
4452
4366 2583 334
0
017462620
0 -314 -322
5009
4569 2703 350
0
018282741
0 -371 -347
5565
Scenario11
2704 1674 409
0 758
1113
1946
0
0
0
56
0 858
2993 1855 451
2135
0
0
0
49
1670
01000
3274 2036 489
2274
0
0
0
38
2226
01281
3525 2215 510
2244
0
0
0
2783
13
01353
3339
3713 2363 535
2081 279
0
0
0
01321
3939 2542 574
1867 751
3896
0
0
0
01229
0
4452
4156 2719 616
16101318
0
0
4366 2897 657
01129
5009
12961941
0
0
0
01021
4569 3074 697
9462602
0
0
5565
0
Annual milk production inlitres
2
ln kilograms, Drymatter (DM),Total Digestible Nutrients (TDN)and Crude Protein
(CP) contents oftheformulated rations.
Proportional oftheformulatedfeedstuffs; B=Berseem,C=Concentrates, R=Rice
strawand M=Maizesilage.
4
Balance betweenanimal requirements andformulated diets, inkilograms.
5
Feedcost inLE.
155
2618
2782
648
717
784
845
890
944
996
1046
1095
939
1039
1137
1224
1382
1616
1878
2157
2445
GeneralDiscussion
-General Discussion-
General Discussion
This thesis dealswith apartialanalysis ofthepossibilitiesfordevelopment ofthedairy
sector inEgypt. Itaddressestwo interrelatedtopics. Firstly, itprovides anevaluation of
maize silage, that has been recently introduced as an intervention in smallholder
systems to improve the current feeding situation. Secondly, a model has been
developed for the irrigated mixed crop-dairy farm as a decision support tool in
optimizingthe useofavailable resources.
On the basis of available information,discussed inthisthesis,ageneral assessment
can be made ofthecurrent statusofmixed crop-dairyfarming inEgyptandthescope
forfuture development.
- The dairy sector is themain provider ofanimalproducts,but itdoes notcoverthe
national demand for animal products, the gap between demandand production
seemsto becontinuingforthecomingyears.
- Feed supply and herd management appear the major technical production
constraints. Fordairyproducers,quantitativeandqualitativefeedshortages arethe
major constraints for expansion ofherdsizeand/ortransformationto highyielding
animals.
- As a consequence, animals are exposed to sub-optimal feeding conditions, i.e.
either over orbelowthe requirements.
- The degree of commercialisation (economic objective) isquite highfor bothcrop
andanimal production.This impliesthat:
- The most suitable breed for the mixed farming systems must beadual
purpose breed, allowingfarmerstoswitcheasily andwith lowrisks between
enterprises (e.g. switching from fattening to dairyandfrom cashtofodder
crops),depending onthemarketsituation.
- At the current degree of commercialisation, farmers tend to accept new
technologies, if economically attractive.These newtechnologies, leadingto
production increases, should be accompanied by improvement ofexisting
marketing channels or development of additional channels, through cooperatives and/or NGO's (NonGovernmental Organisations).
- For further development, the mixedcrop-dairyfarmingsystems should beadapted
for regular, non-seasonal production; this requiresayear-roundoptimumfeeding
regime of cultivated greenfodderandconserved goodqualityforages, if necessary
supplemented with concentrates, and proper housing would also bebeneficial.
Special arrangements will have to be madetomeetthetechnicaldemands (e.g.
housing, milking machines andcalf rearing programs) intensive buffalofarming.
158
-General Discussion-
- Maize silage appears a proper technical intervention to arrive at an improved
feeding situation; from this study it may be concluded that maizesilage hasno
technical implementationconstraints andiseasilyadopted byfarmers.
- Improved farm planning andmanagement procedures by individualfarmers, leading
to proper allocation of resources anduseofimprovedtechnology and inputs,are
keystooptimising useofavailable resources.
Implication of making silage
Thestudy hasshownthatatthecurrent production levelofupto2700 litres perannum
or9litresperday,arationconsisting ofberseem, ricestraw and maizesilageonly,
suffices, i.e. there isnoneedto useconcentrates, ifmaizesilage isavailable. Figure1
illustratesthat adietofberseem andmaizesilageonly, issufficient tocoverthefeed
requirements ofacowproducing 9litres/d; belowthat level,ricestraw canbeusedand
abovethat levelconcentrates areneeded.
Figure 1.Daily feedallowancesfordairy animals intheimprovedfeedingsystem.
13-|
11-
Jm
97• • •
5-
±
• Berseem
• Concentrates
3.
>
1i
*%. •
^^m
JA""T~~
-1i
)
4
8
16
12
k Ricestraw
X Maize silage
20
Dailymilk production
Forpractical implementation,thefollowing equations canbeusedtoformulatethe
daily ration (Y) inkgdry matter inanimprovedfeeding system,fordifferent milk
production levels:
159
-General Discussion-
• berseem
'concentrates
'rice straw
'maize silage
-0.0387X2
0.0451X2
0.0075 X2
-0.0176X2
+ 0.7905X
- 0.4323X
- 0.2240X
+ 0.3763X
+
+
+
+
1.4802
0.685
1.549
2.0969
R2=0.90
R2=0.98
R2=0.72
R2=0.82
WhereX=daily milk production (4%fat),forananimalof450 kgbodyweight
- Inclusion ofmaizesilage inthe localfeeding systems leadsto rationsthat are more
efficient interms of nutritionalvalueandeconomic profitability, and readily accepted
byfarmers.
- In addition to improvingthefeedingsystems,silagemaking hasdirect implications
for employment for owners of tractors andoperatorsofchoppers. Duringthetime
of making silage the tractors are off work, neither used for harvesting nor land
preparation. Thus, silage makingmaycontributeto reducedunemployment and/or
increased incomeoftractorowners.
- Using maizesilage reducesthe labour requirementstofeedtheanimals, compared
tothecut andcarrysystem usedforberseem.
- Cultivating maize for silage insummer reducesthearea requiredforcultivationof
berseem in winter, which means that more landisavailabletocultivatewheatfor
humanconsumption.
Further development of MDFM
Infurther developing MDFM,attention hastobepaidto:
- including new crops, more and different types of animals (e.g.sheep,goatand
donkeys), feedstuffs and interventions
- compilation in theformofsoftwarewithdialogboxesforeasydataentryfor useby
the localextension staff
- include more farmeconomics,especially cost-benefit analysestodemonstrate and
compare different farm enterprises (e.g.dairyvs.fattening) usingformal economic
analysis criteria
- translation intoArabicfor usebythe local extensionists
Overview of the study
- The study is translating the ultimate goal of the nationaldevelopment planinto
operational programs and investment projects,which isoneofthe mostcriticaland
difficult tasks facing administrators intheanimalproductionsector especiallywith
for small andmedium scalefarming.
160
-General Discussion-
- The study introduces a new approach ofusingacomputer modelasanadvisory
toolfor usebytheextension staff atfarmlevel.
- The results of the study provide a framework for evaluation ofnewtechnology
packages, especially with respect to feeds andfeeding packages. Otherfeeding
packages,developed by FSDPshould beevaluated inasimilarway.
- Due to the largevariability infarmers'objectives andenvironmental conditions, itis
difficult to develop effective extension methodologies and formulate extension
messages for groups of farmers: the model developed inthis study providesthe
possibility forguidanceto individual holders.
- The useofMDFMprovidesthe missing link intheconnectionfarmers-extensionistsresearchers, which will finally leadtobetter understanding ofthefarming systems
andtoformulation ofresearch objectives, bettergearedtofarmers' problems.
Implementation of the model
A problem may be the implementation ofMDFMimplementation intheformulation of
long-term plans at provincial and local governorate level bybothpublicand private
sectors. The challenge is to provide an adequate joint formulation ofplanning and
implementation in a two-wayflow ofinformation betweenthose responsibleforfurther
development of MDFM (the researchers) those responsible for the expansion of
interventions (theextensionists) andtheclients (thefarmers).
Inpractice,three stepsshould befollowedtosuccessfully implementthemodel:
1) preparation oftheextension staffto implementthe newtechnologies
2) intensive training oncomputer skillsand MDFMoperation
3) follow upthe implementation tomaketheextendtheapplication domain ofthe
model
161
Summary
-Surrmary-
Summary
The study, reported inthisthesis,wascarriedoutpartly inEgyptandfortheother part
in The Netherlands.Optimization ofresource useinmixedcrop-dairy farms inthe Nile
Delta in Egypt was its objective. Itinvolvestwocomponents:(i)modellingthe mixed
crop-dairy farming system; (ii) assessment of the introduction of maizesilage asa
technical interventionto improvethelocalfeedingsystems.
The thesis starts with ageneral introductiononthemainproblemsandconstraints of
animal production in Egypt, followed by a research scheme, that addresses the
problems and emphasises potentialsolutions. InChapter 2,aclassification ofanimal
production systems for Egypt is presented, emphasising the specific role of each
system and its potential contribution todevelopment,withspecialreferenceto mixed
crop-dairy farming systems, which is the targetsystem inthisstudy. InChapter 3,a
detailed analysis/description ofthetargetsystem ispresented,withspecialattentionto
thefactors/relationships/components that arerequiredfordevelopment ofaquantitative
mathematical model of the system. Based on the qualitative and quantitative
description of themixed crop-dairyfarming system,adecision supporttool intheform
of a computer model is developed (Chapter4).The model isconstructedto simulate
activities of a mixed crop-dairy farm foroneyear, including the introduction of maize
silage inthe localfeeding systems.
The possible role of maize silage was assessedthrough on-farmtrials (Chapter 5),
followed by on-station testing,using animals (Chapter6)andfinally, aneconomic and
nutritional assessment, accompanied byanexamination offarmers'opinions (Chapter
7).The majorfindings aresummarized below.
Over 70% of thetotaldomestic animalpopulation inEgypt(expressed asanimal units
on the basis of average live weight, and excluding poultry) consists of cattleand
buffaloes. The dairy sector is themainproducer ofanimalproducts.Currently, Egypt
imports dairy products to avalueofabout500million£E (1£E=1.4U$)perannum,
representing 43% of the total consumption of dairy products.The mixed crop-dairy
farming systems are the most important animalproduction activity, comprising about
76% of the total animal population, followed by integrated farming systems(17%).
Other systems only play aminorrole.
The detailed descriptive analyses of mixed crop-dairy farming systems include:
cropping calendars of the main agricultural commodities, cropping pattern, herd
structure and size, milk and meat production, fertility and animal health,temporal
calving distribution,feeding systems andanimalnutrition.
164
-Summary-
The major problems identified, canbesummarized asfollows: 1)deficiency inforage
availability between harvesting periods of successive forage crops; 2) the major
constraint forexpansion ofherdsizeisthe limitationoffeedresources;3) relatively low
milk production (compared to pure dairy breeds, such as Friesian);4) animals are
offered unbalanced rations year-round; 5) animals are subjected to sub-optimal
conditions bybeingfedoverorbelowtheir requirements.
One of the important features isthatthemixedfarmisafamily-owned and-operated
enterprise, with a relatively high degree ofcommercialization (economic objective) in
bothcropandanimalproduction.
Problem identification, followed bydescription ofthetwosub-systems (cropanddairy)
formed thebasisfordevelopment ofafarming system conceptual model,that provided
thebasisforamathematical computermodel.
The Mixed Dairy Farming Model(MDFM) hasbeendeveloped primarilyfor useatfarm
level by extension or management staff. The objective of the model istoanalyze
present activities ofamixedfarmandtomaximize itsoverallprofitcombining boththe
crop and dairy component. It also allows testing of biological parameters and
management strategies atfarm level,toexaminetheir impact onprofit.
The model represents 365days,divided intoa 12(monthly) periods.Simultaneously, it
predicts animalproduction levels,nutrient requirements andcropping patternbasedon
leastcost rationformulation andoptimalfarm revenues.
Technical evaluation of maize silage included identification offactorsthat influence
subjective and objective silage quality characteristics.Theexamined factorswere 1)
length ofchopped material;2)variety; 3)ageofmaizeatensiling;4) proportion ofears
included in the silage;5)timefromensilingtoopening;6)off-takefeeding period.The
effect of eachfactorwasdescribed quantitatively. Goodquality silageswere generally
obtained, indicating satisfactory preservation for all silages. The highest qualities
corresponded with whole maize (without removing ears),ensiledatanaverage ageof
108 days, after 17 days of fermentation, and upto45daysoff-takefeedingperiod.
Variety and type of chopper used in this study had no significant effect onsilage
quality. The fermentation characteristics, such as pH, lactic and volatile fatty acid
contents, were measured,andvisualcharacteristics monitored.Regression equations,
relating fermentation characteristics to the examined factors, generally were
characterised by low R2 -values. Itisconcludedthatsilage makingwaswell adopted
under the local conditions and theexaminedfactors have insignificant effects onthe
quality ofmaizesilage producedon-farm.
165
-Surrmary-
The nutritional evaluation involved twodirect andthree indirect metabolismtrialswith
sheep, as the basis for detailed analyses of the development of thefermentation
process, and chemical composition of the maize silage, anddigestibility, nutritional
values and intakeofberseem,ricestraw,aconcentrate mixture andmaizesilage.
Fermentation is characterised byafastdrop inpHvaluesduringthefirst8days, upto
16 days the changesaremoderate,while upto96daysthevaluesvarywithin narrow
limits.After 96days conservation,totalvolatilefattyacid (VFA) contentwas low. Except
for acetic and propionic acid, the silage was free from undesirable VFAs, and
characterized by high lactic acid content and low pH.Efficiency offermentationwas
favourable, as indicated by the ratio of lactate to acetate. With respectto nutrient
digestibilities of the four feedstuffs, results indicatethat maizesilage hasthe highest
DM and OM digestibility coefficients, with no significant differences between maize
silage and berseemforthefibrefraction except NDF.Dry matter intakeofmaize silage
was higher than of berseem. Intakeofberseemwith maizesilagewas higherthanof
berseem with ricestraw and lowerthanofberseemwithconcentrates.Total Digestible
Nutrient (TDN) and Digestible Crude Protein (DCP) contentsdecreased inthe order
concentrates > maize silage > berseem > rice straw for TDN and berseem >
concentrates >maize silage >ricestrawforDCP.
The third set of evaluation criteria involvedacombination ofeconomic and nutritional
characteristics of combining maizesilage(M)with B(Berseem), R(Ricestraw) andC
(Concentrates). The sensitivity offarm profitabilitytomilk priceand production costsof
maize silage wasstudied.Moreover,farmer responsetofarm resource availability and
silage making wasexamined.Thestudy includedcomparison ofeleven rationswithor
without maize silage (scenarios).Thescenarios (S)are:S1(B+C+R+M), S2(B+C+R),
S3 (C+R+M), S4(B+R+M), S5(B+C),S6(B+M),S7(B+R),S8(C+R),S9(C+M),S10
(R+M) and S11 (B+C+M).Theanalysis showsthatthetraditionalfeeding system(S2,
berseem, concentrates and ricestraw) isconstrainingfor productionofmediumor high
yielding dairy cows. Itindicatesthatfeeding berseemwith ricestraw does notmeetthe
nutritional requirements of thedairycowsatany production level.Usingberseemwith
rice straw and concentrates increasestheproduction costsby30%,which meansthat
farmers canmake aprofit onlyfromcowsproducing over2000 litreperyear.
The diet of berseem with maize silage only (S6) was thebestdietforthe lowmilk
production level, from boththe nutritional andtheeconomic pointofview,followed by
the diet comprising berseem,concentrates, ricestrawand maizesilage (S1),which is
nutritionally satisfactorily, but expensive. Using concentrates is economically not
remunerative atlow production levels (below 2000litre). Using berseemwith ricestraw
is an attractive alternative for low-yielding cows.The marginoverfeeding costs isstill
positive when milk pricesdecrease by25%,ifmaizesilage isused,orwhentheprice
of maize silagedoubles.
166
-Summary-
The response of profitability of the feeding systems (scenarios) tochanges inmilk
prices indicates that changing the price to 1.2 £Eper litre(currently 0.8) resulted in
positive margins for all (especiallythe lower) production levels inallscenarios.At 1.0
£E,themarginwas negativeat lowproduction levelsonly (S2,S3andS4).
At the current farm gate milk price,themargin ispositivefor S1, S4,S5andS6atall
production levels, and negative for scenarios S2,S3,S7andS8at levels upto 1700
litre perannum.
For milk prices decreasingto 0.6£Eperlitre,themargin ispositivewhen berseem and
maize silageor ricestraware used (S1, S5andS6),andnegativewhen using BwithC
(S2 and S4).When,using Cwith Mand/or Rmilk production isnot remunerative upto
3300 litre (S3,S7andS8).
The response offeeding coststo increasingthe priceofmaizesilage by20,40,60,80
and 100% at different levelsofproductionwas alsoexamined.Marginswere positive
when the price of M increased byupto60%ofthecurrent price,and negativewhen
price increases exceeded 60%. Usingconcentrateswithmaizesilage (S8)was more
sensitive tochanges inmaizepriceandledto negative marginswhen prices increased
by20%.
Adoption of maize silage by farmers was also examined.Theadvantages of maize
silage as recognised by farmers were: 1) Increased milk and meat production;2)
reduced feeding costs; 3) reduced straw use; 4) reduced laborcosts; andfinally5)
reduction inshortageoffodder betweenthesummer andwinter periods.
167
-Summary(Dutch)-
Samenvatting
Het in dit proefschrift beschreven onderzoek is deelsuitgevoerdinEgypte,deelsin
Nederland. Dedoelstelling van hetonderzoekwasoptimalisering van hetgebruikvan
hulpbronnen in gemengde bedrijfssystemen in de Nijl-delta. Het bestond uit twee
componenten: (i) modelleringvanhetgemengde bedrijfssysteem;(ii)evaluatievande
introductie van snijmaiskuil als eentechnische innovatie inhetsysteemomdelokale
voersituatie teverbeteren.
Het proefschrift begintmeteenalgemene inleiding,waarindevoornaamste problemen
en beperkingen vandierlijke productie inEgypteworden gepresenteerd,gevolgd door
een onderzoeksvoorstel waarin de problemen worden geTdentificeerd en
oplossingsrichtingen aangegeven. In Hoofdstuk2wordt eenclassificatiesysteem voor
dierlijke productiesystemen in Egyptegepresenteerd,metde nadruk opdespecifieke
rol vanelk vandiesystemenendemogelijke bijdrage die hetkanleverenaanverdere
ontwikkeling van de dierlijke productiesector, met speciale aandacht voor het
gemengde systeem dat onderwerp is van deze studie. Hoofdstuk 3 bevat een
gedetailleerde beschrijving van hetgemengde bedrijfssysteem,metspeciale aandacht
voor de factoren/relaties/componenten die nodig zijn voor de ontwikkeling vaneen
mathematisch model van hetsysteem.Opgrandvandekwalitatieve en kwantitatieve
beschrijving van het gemengde systeem, is eenbeslissingsondersteunend systeem
ontwikkeld, in devormvaneencomputermodel(Hoofdstuk 4). Hetmodel beschrijft de
activiteiten van het gemengde systeem voor een periodevaneenjaar,en bevatde
mogelijkheidmaissilage inhetsysteemoptenemen.
De mogelijke rol van snijmaissilage is geevalueerd middels proeven op
praktijkbedrijven (Hoofdstuk 5)enophetproefstation,met inbegrip van voederproeven
met dieren (Hoofdstuk 6), en tenslotte is een economische en veevoedkundige
evaluatie uitgevoerd,gecombineerdmeteenonderzoek naardemeningvanboeren.
Meer dan 70%vandetotale populatie aanlandbouwhuisdieren van Egypte (uitgedrukt
in diereenheden, op basis van het levend gewicht, enmetuitsluiting van pluimvee)
bestaat uit rundvee (koeien en buffels). Het grootste deelvandedierlijke productie
wordt gerealiseerd door de melkveesector. Op het ogenblik importeert Egypte
zuivelproducten met een totale waarde van500miljoen£E(1£E (Egyptisch pond)~
1.4 U$)perjaar, overeenkomendmet43%vandetotaleconsumptie. Hetgrootste deel
van de dierlijke productie wordt gerealiseerd ingemengde bedrijfssystemen,die76%
van de veepopulatie omvatten, gevolgd doorgeintegreerde bedrijfssystemen (17%).
Deoverige systemen spelengeen rolvanbetekenis.
168
-Summary (Dutch)-
De gedetailleerde beschrijvende analyse van het gemengde bedrijfssysteem omvat: de
gewaskalenders van de voornaamste gewassen, gewaspatronen, kuddegrootte- en
samenstelling, melk- en vleesproductie, vruchtbaarheid en diergezondheid, het
temporele afkalfpatroon, voersystemen en diervoeding. De voornaamste problemen die
geldentificeerd zijn, kunnen als volgt worden samengevat: 1) voertekorten in de
periode tussen de oogst van twee opeenvolgende voedergewassen; 2) de belangrijkste
beperking voor kuddegroei is beperkte voerbeschikbaarheid; 3) relatieve lage
melkproducties (vergeleken met die van zuivere melkveerassen zoals Friesians; 4) de
dieren krijgen het helejaar door ongebalanceerde rantsoenen aangeboden; 5) de
dieren verkeren dus in sub-optimale omstandigheden doordat ze ofwel boven ofwel
onder de behoefte worden gevoerd.
Een van de belangrijkste kenmerken van het gemengde bedrijfssysteem is dat het een
familiebedrijf is, met een relatief sterke marktgerichtheid (economische doelstelling)
zowel voor gewasproductie als voor dierlijke productie.
Identificatie van de problemen, gevolgd door beschrijving van de twee sub-systemen
(gewas en melkvee) hebben gediend als basis voor de ontwikkeling van een
conceptueel model van het gemengde bedrijfssysteem, van waaruit een
computermodel is ontwikkeld.
Het Gemengde Bedrijfsmodel (GBM) is in de eerste plaats ontwikkeld voor gebruik op
bedrijfsniveau door de voorlichtingsdienst of de bedrijfsleiding. Het doel van het model
is om de huidige bedrijfsvoering te analyseren en het bedrijfsresultaat te optimaliseren,
gecombineerd voor de gewas- en dier(sub-)systemen. Het model biedt de mogelijkheid
biologische parameters te testen, en verschillende strategieen met betrekking tot de
bedrijfsvoering te beoordelen, voor wat betreft hun invloed op het economisch
bedrijfsresultaat.
Het model beschrijft intotaal 365 dagen, onderverdeeld in 12 (maandelijkse) perioden.
Het berekent simultaan dierlijke productieniveau's, voederbehoeften en gewaspatronen
gebaseerd op minimum-kosten rantsoenen en maximum-bedrijfsopbrengsten.
De technische evaluatie van snijmaissilage omvatte identificatie van de factoren die de
subjectieve en objectieve kwaliteitskenmerken van de silage be'invloeden. De
onderzochte factoren zijn: 1) lengte van het gehakselde materiaal; 2) maisvarieteit; 3)
leeftijd van de ma'is bij inkuilen;4) fractie kolven mee-ingekuild; 5) tijd tussen inkuilen
en openen van de kuil; 6) lengte van de vervoederingsperiode. Het effect van elk van
de factoren op de kwaliteitskenmerken is kwantitatief beschreven. Het bleek dat op alle
bedrijven de kwaliteit van het kuilvoer bevredigend was, wijzend op goede
inkuilmethoden. De hoogste kwaliteit werd bereikt door een combinatie van inkuilen
van de hele plant (inclusief de kolven), op een gemiddelde leeftijd van 108 dagen 17
dagen na inkuilen, en een vervoederperiode tot 45 dagen. Varieteit en type hakselaar
169
-Summary (Dutch)-
hadden in deze studie geen significant effect op de kwaliteit van het kuilvoer. De
kwaliteitskenmerken, zoals pH en gehalten aan melkzuur envluchtigevetzurenzijn
gemeten en visuele kenmerken beschreven. De regressievergelijkingen tussen
kwaliteitskenmerken en de onderzochte factoren werden over het algemeen
gekenmerkt door lage correlatiecoefficienten. De conclusie is dat de techniekvan
inkuilen onderdeplaatselijke omstandighedenbevredigend isgeaccepteerd,endatde
onderzochte factoren,overdeinhetonderzoek betrokken range,geen invloed hebben
opde kwaliteitvandeophetbedrijfgemaaktesilage.
De voederevaluatie bestond uit twee directe en drie indirecte voederproeven met
schapen, als basis voor een gedetailleerde analyse van de ontwikkeling van het
fermentatieproces en de chemische samenstelling van de silage, en van de
verteerbaarheid, voederwaarde en opname van berseem (Trifoliumalexandrinum),
rijstestro,snijmaissilageeneenkrachtvoermengsel.
Tijdens het fermentatieproces daaltde pHsnelgedurende deeerste8dagen,gevolgd
door een langzame daling in de volgende 8dagen,terwijldaarna,tot 96dagen,de
waarden binnen nauwegrenzenvarieren.Na96dagen inkuilenwas hettotale gehalte
aan vluchtige vetzuren laag. Hetkuilvoer bevatte geenongewenste vluchtigevetzuren,
behalve kleine hoeveelheden azijnzuur enpropionzuur, enwerdgekenmerkt dooreen
lage pH en een hooggehalte aanmelkzuur. Deefficientie vanfermentatiewashoog,
wat bleek uit deverhouding lactaat/acetaat.
Voor de vier voedermiddelen was de verteerbaarheid van de droge stof-en de
organische stof het hoogst voorsnijmaissilage,terwijlervoordeverteerbaarheid van
de ruwvezel geenverschilwastussensilage enberseembehalve voorde NDF-fractie.
De opname aan droge stof uitsnijmaissilage was hogerdanvan berseem.Opname
van berseem, gemengd met silage was hogerdanvan berseem metrijstestro maar
lager dan van berseem met krachtvoer. Totaal verteerbare nutrienten (TDN) en
verteerbaar ruweiwit (vre)verminderdenindevolgorde krachtvoer >silage >berseem
> rijstestro voorTDNenberseem >krachtvoer >silage >rijstestro voorvre.
De derde set evaluatiecriteria bestond uit een combinatie van economische- en
voederwaardekenmerken van het vervoederen van mengselsvansnijmaissilage (M),
berseem (B),rijstestro (R)enkrachtvoer (C).Degevoeligheidvandewinstgevendheid
van het bedrijf voorveranderingen inmelkprijsenkostenvanhet makenvansilageis
geanalyseerd.
In de studie werden elf rantsoenen (S) bestudeerd,metenzonder snijmaissilage: S1
(B+C+R+M), S2 (B+C+R), S3(C+R+M),S4(B+R+M),S5(B+C),S6(B+M),S7(B+R),
S8 (C+R), S9 (C+M), S10 (R+M), en S11 (B+C+M). De analyse laat ziendatde
voederwaarde van het traditionele voedersysteem (S2, berseem, krachtvoer en
rijstestro) productiebeperkend isvoor matigenhoogproductieve melkkoeien.De
170
-Summary (Dutch)-
voederwaarde van berseem in combinatie met rijstestro (S7) is onvoldoende voor
productie. Vervoederen van berseem, gecombineerd met rijstestro en krachtvoer leidt
tot een verhoging van de kostprijs van melk met 30%,zodat de boer alleen winst maakt
bij eenjaarlijkse melkproductie per koe boven 2000 I.
Een rantsoen van berseem met snijmaissilage (S6) bleek het best voor lage
melkproductieniveau's, zowel uit het oogpunt van voederwaarde als uit economisch
oogpunt, gevolgd door een rantsoen van berseem, krachtvoer, rijstestro en silage (S1),
dat toereikend is uit het oogpunt van voederwaarde, maar duur. Het gebruikvan
krachtvoer is economisch niet aantrekkelijk bij lage productieniveau's (minder dan 2000
l/jaar). Het gebruik van berseem met rijstestro is aantrekkelijk voor laag-productieve
dieren. Het economisch overschot, boven de voederkosten is nog positief als de
melkprijs met 25% daalt, wanneer snijmaissilage wordt gebruikt, of wanneer de
productiekosten van silage verdubbelen.
De respons van de winstgevendheid van de verschillende voedersystemen (scenario's)
op veranderingen in melkprijs laat zien dat bij een prijs van £E 1.2/1 (vergeleken met
0.8 nu) melkproductie winstgevend is bij alle productieniveau's en alle voersystemen.
Bij een melkprijs van £E 1.0/1 is het overschot negatief bij lage productieniveau's (S2,
S3 en S4). Bij de tegenwoordige melkprijs is het overschot positief voor S1, S4, S5 en
S6 voor alle productieniveau's en negatief voor de scenario's S2, S3, S7 en S8 voor
productieniveau's tot 1700 i/jaar.
Voor een melkprijs van £E 0.6/I, is het overschot positief wanneer berseem wordt
gecombineerd met snijmaissilage of rijstestro (S1, S5 of S6) en negatief wanneer
berseem en krachtvoer worden gebruikt (S2 en S4). Wanneer krachvoer wordt
gebruikt, gecombineerd met kuilvoer en/of rijstestro, is melkproductie niet winstgevend
beneden 3000 l/jaar (S3, S7 en S8).
De respons van voederkosten op toenemende productiekosten van snijmaissilage (20,
40, 60, 80 en 100% hoger), bij verschillende productieniveau's is ook onderzocht. Het
overschot bleef positief tot een verhoging met 60%, en werd negatief bij verdere
verhoging. Het resultaat bij gebruik van een rantsoen van krachtvoer met
snijmaissilage (S8) was gevoeliger voor veranderingen in de prijs van silage en
resulteerde in negatieve overschotten bij een prijsverhoging met 20%.
Het onderzoek naar de perceptie van de boeren met betrekking tot snijmaissilage liet
zien dat ze als voornaamste voordelen zagen: 1) verhoging van de melk- en
vleesproductie; 2) verlaging van de voederkosten; 3) vermindering van strogebruik; 4)
verminderde arbeidskosten; en 5) vermindering van de voedertekorten in de periode
tussen zomer en winter.
171
»-••*>j J l *J> ASJJUJ -LP r*>L-~^ J U ? l j-a.jaftjJli ^ j s r j ?»IP u r y j j J l j ASlkJl J A Uljsrf A«?-u j * UljJl j i T l AiJlP J l t J i j j l*» r ' ^ J l j (*a->jJ| AjJUtS -
f>-a$il j l j»Ui-l
( W j ^ J* J j ^
1
j * J ^ £%~1\ cy W*Ji^ J 5 " ^ " ^ " ^ *s* s ' -
j ! s i j i c * ~ * j J i AJJU«J*LP l^p *--)jJl ** ^*>L~J( AJJUJ -UP J j T t l l *lJt*Jl<u«S'oabj -
Jl
Ll ^ f j j AJU*JI J ^ J ^ I J ^ ^ % - J l J**J »>Ul £ & l j o b cJbr1^ 1 AJUP J * fljy^l 4JjA-i
>J
P Alb- J Ail J (*-*J ( l«i* J0*^*)
J
r" I
.(jj—Jl J * CJ\£j*
t\j£t j\ ^QMijJt APljjJ d l J i AijUL»j »j*i|t
«kT . r ^ - ~ U « j > ^ APIJJ j £ AsrjJl J-Ja»*SH& Aili J i l l j - l j y l j J £ • AJUJJI j l j ^ '
j l « «4
ji'jJ
j i U f l J * i l j AjlJUdl <L?-ull J * A i b w i l 4asrls3'!H O b j - u J J A%Ul S-sTjI <UJ%»t^JLa j»-ftJl
tj <uJL«Jl tAsll^J j * o ^ 3 ^ a ->"^ r*^=* J f'JW^- 1 ' tJl pjlaJl <W , As i j fljjJl £^~>> ^lAwi-d D J J J
^J
ljv»l
i j j J J l ) o l ^ 1 ^ 1 J&>^3 J-o-^ ( j * J (fcs*^ *4** j* •jS*"^' 'Mj^" 1 -U!^ 1 p te*} ^ i U a d h l l jJ-\
j;
ll J _ J l j i J l j _ ^ » . O l i j * « j JUIji ^ ^g,,.aib aj^X U JPJPJ
j
aJa fi&j 0!
U l j (^sJJl r Isil J A JUjJ r % - J l ^
j j j i j ( A P I j j J i «-»!>• t j u » * i ^
(
AjOAsJl 01^g.-fltb O j P j I j l l 14j i l J l ^ - * l l
AJJLKJI fljd j « J J i US' A P j j l i J > - b AJU«JI C A J I & J AJJUSJI U L J I S J
.AJIJUJI ( J I J J - I A^rb- A J M J t ^ y J>^\
^^^L-^JC'LiiU-lt^UjJ-l
(*-J* (• J 4 ^JS ? " **>**•J r^~«*Jl J-***
jlj*jjilil
f.J& J l U j P j I j i l U J J d~s- AAISCJj i T ' i l o l j s i J l j ^ JUJ
Jitj jJW>L-">ljJ^L«WU-
^ ^ ^ ^ ^ A k - ^ ^ l ^ ^ j G l I ^ I ^ J i l j S o l ^ A.^lj^l-IN
pj j\j^i\^_ji-^=c°j
^ I J ^ V i L ^ i j^d-a-1
jihnjeyf
*iL-jli<^UI<i5Uil
)^Ci-V(L.jya8 ^ _ _ ^ ) v
J
iU-tUjIjil
.4802+j^O . 7 9 0 5 +2 j ^ 0 •0 3 8 7 - = ^ ^
0 .685+j^O . 4 3 2 3 - 2 L ^ = 0 . 0 4 5 1 = / j ^ L r
1 .549+jaO . 2 2 4 0 - ^
2 . 0 9 6 9 + j 4 ) .3 7 6 3 + 2 ^
.0075=.^^
.0 1 7 6 - = ^ y
\J4
i 12 J ' <w~&» * i - i J " ^ *..,hill £>0£ j j l t oljjAaU Ld A J U » JV»UJJI a j i <ulp A A A ; . ? j l j i l
A_J\i*Jl o U r W ^ J (K-Jr-I O j j J oibjJl d i l i S ' j l ^ r U i l j S j x l l OLWl A ^ o U l J ^ ^
AJISM
tJ}< fr'ill 4 yoS'j APljjJl A L > J l AJUsMb O b l j J - l JA A~JU«ii»*£•}*£• J & V j s J ' AifUJl S-s^J 5 J
J_-ia?ti» j ^ j k * j.jte J dJJi APUS JSO: A A ^ J I J J A P J J I I ^ y - j * U j l ^ j l Ljlai?- j l Igsrbjl <_^rljJl
J JTI—i^JJ y
JJ
?- JIJUJ *i .u-ljoJi aJLa Oli lJU J l P j
. * k M JLia AJU- J A*3JSU di\yi\j
<_AJI&JJ
A3 Jlju LilJUa A-»l-lAi«jl j S \ £ J \ v__*b- £ * U j j » J i } l i l C_?- d l lJ t£*Us3 J-! AJjJU O L ^ j J
^ j l j ^ o J T O U l £ » l i_
?- J i i l l O L ^ j s i l f.-bifj &)P
a
JJ~"
S j ^ 1 f l k J L H * ^ ' fr^J^ {&* £~£ A5*>U-JU
O L ^ J J £_jijli ^ i s i j i f * g ~ ! aSjjJi AjiUasSMij A ^ I ol3j*!>i A-J\JJ j ^ j x j j A J U J I I ^ 44UJ1*.ji-»
£^L
£ b i l J l < ^ i j j as jjJl J-»»JP A=_J 4 _ \ j i Jjr" csJUlj ajJJl r % ~ J 4^*0-1.1(t ^isll •
(2 AvsJbt: -J.I u i l
Jj
--p^ (1 i^ft J-«lj*ll a i a j c r ^ j ' j i ' Ak«>ljj flj^T Jbu a i U i j l a i j J r l
k ( 4 r*>L-Jl J-OJJ cJaJ-l «-• Vgn.jhflfj l ^ j j j j l \ Olj«£j\ < u i (3 r*>L-Jl J-»* <k& O U j I
2 _ d JL* AiJutoil ijA J j k (6 ^ro&l ex» (5 (gjnh\\ J . u j b t u J l - u T l l I p ^a *>taf) Axkiil «.ljsr*s!(
j jflJI
ASUJ ^
Lo«i1j ( ^ l j i l l j 4 » \ j J l j OjUl) ^ s ^ j l l J-i»«sI» n j b i c J i . r *>L-Jl <UjT
jia
3- t d l — J j j ! !l j 4
4k
-IJJ ^
j j j
3" t d U i - 1 j i ? - cdLiiJl j ^ a - t4-i?_j*i-\ * T J * ) " j ^ S i O i l O t T j l l
J.I £ ^ L - J l 01^
(U>«^> J l 4iU?^b ^y-*S(l SjUkJl A-jsoll J s l ^ - ' i l j d L j J j - J l
j) 4ialT O U U j<« guLl r ^ s - J i l CJlS" gJVaJt Jj»sl O l j iUlP ALOJ <U!IP flijr j i L5*j>jlt
r%—}\
»iyr j & *ij fjt 17 JA JJTI j * « J l a^si J j ^ J ^ J J 108 1 » J * P i i - i j i « c(0\j-T AJ\ P JJ
<» US'111 £ j
i j l u i — i « f l ] l J (JJ^tf-'sH t j a j j i j .?y_ 4 5 ««H» ^ j AjJutdl <Uj£jl «ui AJI-U JLJ>
W A J > i~is ajJUl r ^ L - > 01 d i l i ^ ^yaJLni-il a i j .r*)L~Jl a i j r J * i > * » J j j * AJ( J l AJ»J&C~A\
.ry*CJ. b j i k j f j l j l l l bjJLii d i l i J l A j t i s i l ^ - b s U A-aill O l 3 j « i l ^ i3U» ( _ r J j * J ^ I AiJL!
Tl J J j A J I S K J e^SLo J ^ - l y J o l j A ^ d l A-L-oiJ 4 - t l j i Jjr 1 e j i l l r %~1 ^ a * ! l j»-iJl •
OJ
r*>^
Ol
J
JJ ( j i l i i l l j ^ i J l JJT 1 CJJJi'.AgilJLl.l 4—.Ijjjl ^ b j j p J-a»tdl gJlaJt J l P 4-itjjJl c i > U >
jS"jll •
j.o-S' |»_
•-"> O L U P J P J-^UsJl J ^ Jbjll uLAS" »3JJS jiLSCll »lJtf«-j\j |^jaA O j b t
a j j l «. « j \ " y » £ * ^ * <oi*Jl Jc& ejJJl r*A~-J A J ^
1
fr\^l
A«-«Jb kiJJi AS*>VPJ AJIJUJI
I ^ I J £»UJ\ C - A « J J " .j j ' i l l J l i j l O l j S ' j J l l
djJj> 500 j» ^jk
I* OUloU^ai* iljsi-^b J-OA*yS 0111 <jj*-j ij^'H Olji-> «J«2JJIJlta1- •
i~~ji}yH 4~-UJ4_)li-l ^ bi*lJl.Jaj4~«-J »i>l U 4jp JAU ,JLP JU-lJ^r-" J ^J^-<ufj^* *v^
.OlSLJl iJl* J oibjll
Oj£a ( j s r l j ^ l il*~->\ «J>4Jlj-?- OlJ^-jS' UU»*-i ) dj^all o l i l j J - l il0*3 j * % 7 0 j * jSSl •
.l...~i A.Ai;n.'y»AJT-UIJOliljji-1till} *—«-5jj ,*ij*Urlj JV5J*5J\ / ^
-Js-eW) JaisAll^)j>s
C
1
^?^ ^
£**(*J\*r ^ l ^ j S " ) OUIjJ-1JUrl % 7 6 £\y
•
jlJUJJA %17 Jlj»- J i f i j J*tScLl£_Wlll^Uaj j * <u?*i1J AJJ^JUlf l k J l j (OLJl ^ W
.4«iu»lac...,...;( ^ j ^ l ^1=5*JH JaJ* A U J J OUljJ-l
0*< aJJUJlJ-^l^l< W l i j^-43 t S ^ J JaisAli OlJlll^ W f l k J ^i^S\ j ^J-fi£\ JJbnsIl •
j* <UrW^JZ~J> j (UJS'JJJ<Wsv<U?-U j * «.;lai.[lj^jwJl /?US'Ig-Sbualkj ULfijj lftft,;,A7
j**-
Jt t£i! (£JUjlJ^aiJlA«sr\y , ^ - j j J-^lisJl ^ Jbji) .uiLiJl-uifcJt ^
j fj»*Ulj OU^I
: .JlsJlobJbM j j T U l l
J*>* 9-i J^U-IOl
iljsTvD4^-Ull*lj*ajM L J ^ ^ I *s*jjj A s^' <J * * ^ j ' AJUS'f»0P .(Jy-'M J j - ^ i l * * b j j J i ^
yjfj
1
<J>a^l JUas-juL») 4JUa*s!\ £j\jj&\
jIULutfJJa_-> ^aM\ p*ts~ &\A lJL» J&j <Jy&*i\ »Jj j* g}ail\ ^J- }j£\ J-»l*J\ AJG-1j i L a l l f>IJ>c^l ASUS"j w j i j i iJoAr J>±£- _)JLA»
o
^»" j — ? * * ( j - i p << !%M o l i t j J - l 4JJU3fOP Jt « r j J 0U*il ^ 4-sistdl 4~rWil -
]_jf J i t 8 j U j «l*-L3>-l j < jSft ^ I P O l j - i - l J^flrfs OjbS i«JLu«* AA«flj AjtJi«Il O l i r l s » - ' i l
.tJjJLiJ JJP v-Jb" (^"-^J j^*"'-» j ; P (_s*"^' J*JJ (J* t5^Jd
A<4 L'Ult lAjj-Uj L j ^ i i **-}p & laLal.\OU^I^U5\ ^ikJ aj-J.1,y»JUai-l^ 1 j * 4_AJ'J * i j
-j (»»O^1 ^ . ^ , J * % 7 0 &\y 01 d-»- ^aUdlH ajb^l JA JlP
.OjOUflJlJj^ut]^ Ak^iljj U^PU?jj l lyty.^j j l Oj-rf^Hiia-*\y
ii
i
5*1 »jejiaj /f (
\^*h^\
) i ) i « l ( ^JP^JJ^ r Will alTK («-»Ujj)ri j £ j * 4—<*jJJ>OJLA4j»Ji3l»j^ai
f'JjoJJJ * ^ ' t i ' i ' ( t M * l i 1 J l * ^ >-^-4i •U^J , J' , J i J ^ ^ ' j ' L^-Wl1*k-»t_^4<«l-b«-.(
^y-Jp Jj__a«Jd Ji*1|lJJ-1r i^<J( ^02J>US' KUudl4ji«slt jjaa JLISJ UJ A-uJljAjiUa3*l|\ V»Ul
r i j _ « J l »lJbt:
J\ j—&:_ .<uJL<AijSai^jaiil *JJL«Jj<-iajij ii'j-^-l j ^UJl r Willj» *J.J^y^oSl
J _ > i ^J* dlJi j y b j AiJbitfr b l O'iJtfuj l 4JJ-A^ r ^ ^ J 1 *i>i*JlJai j » OJJJIJI 4JJIA«J Je>\ya^i^i
jf <_§—\\g j ' l d i j oU^i«ll ^aAi-ib fljjj^ f <g^ •iS'l^t r i j f i j j j k i J * - l y j (JIJL»I J&J*S~*J ytj
j i—kje> ^ 0 ^ .j j j j M j ; ! > l j 4k-it_ji U j j j k i f ^J( O ^ i U j J A»U9*^WdJlill J^jJ) J l$Jt J-Pjsil
4
— ^ J ^ ts*J fc*^ i M ^ ***< ^
Jl d
J - * * ^ 1 O U L J I dUiTj J^i *_--bJJ \i\*s\ ^yi\ o u U J
iUs'JlUfrlj-4^-1u^U'Jll Jai?- C-JJJJ 4-ftT dUJlS"t j ^ l l l J ~ * W j *JJUL\\J - ^ I S M J J APtjjJl
J_J J A L T fIP jlJU J l p 42J«UJs.'Jll v / j J l j AJlJUJlOlrLxs-^l j f_pJJ) j jJUl ^ 2*jsl( ^ t o l l l
Jj—<ai-\ J—&L "^'^ L T ^ ' J OUIj-^-t AJJIAJu i J l & j J~,*l£t rlsit u U l £ i r i j * J l Jfijxu^t AAgJt
.APJJIIJ 4^-bLli j l j l l 4it£j JsVSt fUbta-.'sIl j * <A*
j f j 4—f.jj* 155 i J (. JA O L P i ^ l d l i i j 4~iJl<L>-Uil j * 4jJJ\ r">L-> J * P <u£d^t0~» *J3 ^A
•i j i p j l j l l 4k*»t^ «J.\ r">\~Jl «ijsr JbJUns!LSLo-Tj U i ^ j *>Ll£ UgJUL^
J
r\J.\ J £>jJ- «jj!l 4-*>l^j £*A~«AliSjU^i\ <~Sj&\ j * J ^ o l i J l J * JUjlt *^i(ji J \ LJJ^J J * J
*.
a ^j^WkT j l »iji£_fljOJlr%~J 4j\JUdl <U_flJlj^ai>\ 0*>l«U»J l A3U>^bj * > d l <uU*i «j5Lil
j j ' i l JSJj j T j l l I_A!«J|J*~-ijJt J i * lfitaAs«jl *JUJt <JUa]t it>» j i * *
J i 4 s-U-i iL~r JA ^-->JJIJ d J i AJjLwj <->jJ-\ J A "SIJU £ % ~ J I J A J SJJJI ^tsil y b 4 - ^ 3 ^ A J J
d^ ss-j
ifi\
« A^-JMII * i « i l *JxJb AJOJI&JI <uJu«sJlJ i j AJJU* ^.aa«u«i\ <jli( ^ i j j AJU*J( J (ji'j'ili
.frA\*-£>i •jb^' 5 '' ^ ^ (^JlJlj-p- <oi«! <uJU3lS-a^j5 *+J?K» iJ^J c^JJ^' J* * ^ ( o* ^f^
d>-*.jsi\ J \ J
aJOS t_~~ajbuo^l «JJ> ^U5j( -UPJ J i T j r Id*!!Ij - ^ b J 4-ilJ-\ jU-»^( ^Jbu^ib
^jlj_!>\ AJI^« -\ 4
J
<iP 4
~AJ
frji 4^iLw jf J^oill IJL»AJU J .DLi*il ^L5( J J £ j ! j l l J > i J ^ diJi ji\3j
4 s_k;JLP<u~ij l^_J.^ i ojtyjlj Sjki <i^rj ^ U»jLUt o l i ^ w j XJJJ-\
OUAJJ
d>d& . \ J J J 4 A J I $ J \ i*s*\J.\j <UjkJl frljsrSllj j«a£ <u*l jOJl eJu j * <uU*J( frljyty *>>*-(«• *
A y IsLl i j l j i l JA fliUi-i*iH j»Ja«3J j i s j p IsJJt <ukj: OUSlI £ & ! ^UaS jtja3
jJ
It 0j£s3 j fc-ilj J l k i ^
J A<?LJ.I J j 4*11 j j J l
(jj.Ja.-ii AsUyl OLusJl A A J * ^ tgX» j t a ^ ' j i - j j s l l j j&JwJl f j ' j * ^
:^fu<iL<il j j i ' j ^ r j * A*II
^—lai 3
e l y j Is]J I A«ktf AOJUJI ^ j j
3 1
fc^?1 ( ^ t / 1 ^ SA>* C-*' A " J t ^ " S — ^ fI4A&-.I 1
.(JljJt - J - P t f ) . U s A l l ^ I j j J l 2.lai)H
j? J l 4 -siJi ^ j i - l t ^ J ^ l 8jJJl r " > t - o ) * i iUasi'ih j 4~iJl SLyldt j * ^-"^
i£J
i
^ ^ *J"^' r ^ r * ^
2
«j j J i i iliiJS" j ( J l j J - l A»JU«J J a j i^S- ^JJJ>t-\JJii\9\\ai i\£\s. pj>by, i k - i l j j Laij-iJj l^CJldl
.Ajtfsll kills! £ j » j l l Ajl*i-i(
: AILJJJI J j - ^ i O b j s i ja*<l» Jfi^ ^Ji U J j
«.
^
~&y l#uy A*IP AA^U y'js^-1 r Vsi^lU<u>li-( oUijail j J T l i i l j P <UlP<UJLiCJjSlI J-aiJl ?JLJ
L/i& ^ j
<uAMALI ^ j ^ a j j J i " U l ( «JL* J J - 4S-JS2H J J J U - I J J U - t ^-iJjJl J i>LWl £_ldt J ^ L i A
S i L j j ] AS-gUJ4 J l £ » t j ,yrlsSt ^llaj JS" AyPlJ j-AC A)ULSJ( c i ' j s ^ r lsJ*!|l *JaJ UL-fij3 j <J>,l,/it i A J j
«*1U11J-»ll
4 f-jjj> 3 6 JJ
,j
t- O U L J UOAs^wa ialssxlt j U ^ I r Isil ^UxJ ^yft^J'j i/"*fl
IP J . <*j-l' jf . 0 ( J J
J4
LM^
1
^'^
Jfj*-^-
J*>0aJ> b j f i l^aulsa j p j IsljJt <uku Js« OlliSW 4s^t Jo l» A*j>»
O l i O i l j <U>^J\ O I I ' A J J I J l AJU'iU (OU*il ^(sil - J - ^ l i l ^Isil - AliUJl ) ^Ikd] A - . J Jt O U j ^ H
.IslJl Attk-J i a l ^ t l l OL,J^\ ^ U i ( ^Ikj ^ U i ^ L ^ ? - ^ i j f i ^ w e i A»j^l
t£j_UJl ^ ^ J L J J <uij=- ^-^^ri (j"^ J,j*^ o**^
lu
<CL i ?jot—o» XJ?*\