01998 Applied Poultry Science, Inc
DRINKER
TECHNOLOGY
AS AN EXAMPLE
OF IMPROVING
PRODUCTION
EFFICIENCY'
K. MICHEL, C. GEMPESAW2,J. PESEK, J. BACON, and H. TlLMON
Delaware Agricultural Experiment Station, Department of Food and
Resource Economics, College of Agriculture and Natural Resources,
University of Delaware, Newark, DE 19717
Phone: (302) 831-2511
F a : (302) 831-3651
Primarv Audience: Industrv Analvsts. Producers. Researchers
jective of this study is to evaluate the effect of
DESCRIPTION
OF PROBLEM
adopting new technology, along with other facThe United States broiler industry is reported to be the most technologically developed in the world [l]. The industry has refined
all facets of production to take advantage of
areas where production efficiency can be enhanced. This has led to vertical integration,
large technologically advanced broiler growing houses, sophisticated control of diseases,
and highly mechanized rendering and packaging facilities, among other things. The fundamentals of the industry are in place. In order
to realize higher levels of efficiency, however,
and to stay ahead of competing broilerproducing countries, the United States broiler
industry will have to depend, at least in part,
on the rapid adoption of technology. The ob-
tors, on the efficiency of poultry production.
The current study focuses on the
Delmarva region, which is made up of counties
in Delaware, Maryland, and Virginia on the
Delrnarva Peninsula. This region is the fifthlargest poultry production area in the United
States [ 2 ] .In 1995,623million broiler chickens
were produced on the peninsula with a total
processed and delivered value estimated at
$1.5 billion. In Delaware alone, the poultry
industry accounts for two-thirds of the total
farm income.
The new technology evaluated in this
study is the water dispensing equipment, commonly called drinkers. Currently, the best
technology in drinkers is called the nipple
No. 1642 in the Journal Series of the Delaware Agricultural Experiment
Station.
2 To whom correspondence should be addressed
1 Published as Paper
Research Report
145
MICHELetul.
drinker. Before the nipple drinker, various
watering methods were used that involved
standing water that could be splashed onto the
litter. Wet litter can pack down and become
solid, inducing conditions with high levels of
ammonia from packed feces, a greater level of
foot damage, and a greater likelihood of disease [3]. Because it does not allow for water
spillage, the nipple drinker is more sanitary
and thus, it is hypothesized, can increase production efficiency by cutting down on disease.
It is also hypothesized that with reduced water
spillage on the litter, the costs of maintaining
a clean floor of litter will be lower and efficiency and profits can increase. Excellent references on the technical discussion of nipple
drinkers can be found in Carpenter et uf. [4],
Lee and Zimmermann [5], Vest [6], and Carr
The two variables chosen to represent
broiler production efficiencygains from better
technology were weight gain per day and percent mortality. If efficiencies are gained from
the new technology, mainly in the area of decreased disease, then it is theorized that weight
gain per day will increase, producing a larger
and more profitable chicken. Correlated with
a decrease in disease would also be a decrease,
in flock mortality. This would be a cost savings
for the grower and thus a gain in efficiency.
The combination of these two factors should
result in more efficient and profitable broiler
production.
grower had adopted the new drinker technology; this is the period of full implementation.
In order to analyze the effect of the new
drinking technology, two regression models
were estimated. As noted previously, efficiency gains are represented in this study by
changes in weight gain/bird/day and the total
percentage of mortality in each flock. These
two variables, which were the dependent variables, were hypothesized to be a function of
various factors in broiler production and the
changes in technology over the 10-yr time span
of the data.
The two regression models were estimated using ordinary least squares. The factors measured against weight gain and
mortality in these models were the cost of litter
cleanouts, the payment to growers per 1,OOO
chickens placed, the average cost of propane
gas to heat the buildings, the percentage of
flocks placed that were not broilers, the size of
the flock placed, the adjusted kilocalories fed
to the birds, the percentage of farm condemnations per grower, the cost of water medication to keep the birds healthy, and two
variables representing the periods of transition to the new technology and full implementation of the technology.
DATA DESCRIPTION
Before the regression results are discussed, it is helpful to examine the descriptive
statistics of the variables used in the statistical
models. The means, standard deviations,
minimums, and maximums of thevariables are
listed in Table 1. The mean weight gai4day
(WEIGHT) of the chickens included in this
data set is 0.097 Ib. Not included in the regression, but part of the data set, is the average age
of the chickens at slaughter. This number is
49.7 days. Multiplying the average daily weight
gain by the average number of days of growth
produces a bird with an average weight of
4.82 Ib. The birds grown on the Delmarva
Peninsula are typically larger than those grown
in the rest of the country. In 1994, the average
chicken produced in the United States was
grown for 42 days and achieved a weight of
4.18 lb [l].
Average mortality in the United States
poultry industry is generally from 3 to 5%.
In this data set the average mortality (MORTALITY) was 5.7% with a minimum of 0.0 and
MATERIALS
AND METHODS
The data for this study covered a period
of approximately 10 yr. The nature of the research required data from three overlapping
periods: before adoption of nipple drinkers;
transition to the new drinker technology;
and full implementation of the new technology. A Delmarva poultry integrator gathered data from over 400 poultry contract
growers and supplied the data to the Department of Food and Resource Economics at the
University of Delaware. The pooled time
series-cross sectional data covered the period
from January 1986 to mid-February 1996.
Prior to January 1990, there were no nipple
drinkers in any of the production facilities
for which data were collected. Between
January 1990 and January 1992, nipple
drinkers were being installed. This is the
transition period. After January 1992, every
JAPR
DRINKER TECHNOLOGY
146
VARIABLE*
MEAN
STANDARD
DEVIATION
MINIMUM
MAXIMUM
WEIGHT
0.097
0.005
0.083
0.119
MORTALITY
5.772
1.751
0.825
20.133
0.0022
LI?TER
0.0018
0.020
0.00004
PAYMENT
175.009
36.824
117.540
339.300
PROPANE
17.476
7.144
0.00
86.000
PLACED
KILOCAL
I
I
44.323.740
I
20.739.150
2.901.260
I
98.278
I
I
5.966.670
2.359.630
1
1
119.756.520
3.305.000
CONDEMN
0.889
0.400
0.210
4.198
MED
0.016
0.022
0.00
0.160
a maximum of 20.133%. The variable LITTER
represents the litter cost per pound of bud
moved in each flock. The mean cost is $0.00226
with a standard deviation of $0.0018. This
represents the cost of cleaning out litter to
maintain a sanitary and productive growing
environment. The lower the litter costs, while
keeping other variables such as weight gain
and mortality constant, the more efficient the
grower. It is hypothesized that the litter cost
will decrease with the introduction of the new
drinker technology.
The mean payment to the growers per
1,OOO chickens placed (PAYMENT) is $175.01
with a standard deviation of $36.82. In most
parts of the U. S., contract payment is typically
set on a per pound basis. In the Delmarva
region, however, most contracts are paid on
a per thousand bird basis. It is hypothesized
that as production efficiency increases in the
form of healthier and heavier birds, the payment to the grower should increase as well.
The average cost of propane consumption
(PROPANE) is $17.48 with a standard deviation of $7.14. Costs are likely to increase with
inflation over any time series data set, but the
more costs are contained relative to other variables, the more efficient a production facility
will be. It is hypothesized that as production
efficiency increases the average cost spent on
propane consumption should fall.
The average number of chicks placed with
each grower (PLACED) is approximately
44,323 birds, representing almost two houses.
The standard deviation for this variable is
20,647 birds, or approximately one house. It is
known in the United States that as the poultry
industry has advanced, larger flocks of birds
have been grown in larger houses to capitalize
on economies of scale. It is hypothesized that
a better drinker technology will allow more
birds to be placed in the houses, enabling the
grower to sell more birds at the end of the
growing cycle.
The variable KILOCAL is a measure of
feeding efficiency in a poultry production facility. It stands for the adjusted kilocalories
(kcal) in the feed and is an indication of the
energy contained within the feed. Younger
buds receive fewer kcal and mature birds need
more kcal. The mean for this data set is
2,901.26 kcal with a standard deviation of
98.27 kcal. It is hypothesized that an increase
in technological efficiency may contribute to
an increase in feeding efficiency. This will
allow a lower percentage of money to be spent
on feed, the single largest cost in producing
poultry.
When a grown bird reaches the processing plant, it is either processed and sent out for
retail or condemned due to some problem.
Problems can include disease or ammonia
irritation caused by improper management
on the farm,damage sustained during transportation to the plant, and damage due to
improper handling once the bird has reached
the processing plant. Any problems caused by
improper management on the farm can be
charged back to the grower. The variable
CONDEMN stands for this event. The mean
Research Report
147
MICHEL et al.
for this variable is 0.889% (less than 1%).This
is a reasonable number in the industry. Because the new drinking technology is hypothesized to reduce disease, ammonia irritation,
and foot problems in the birds, it follows that
the condemnation percentage at the processing plant charged back to the grower will
decrease, resulting in better production
efticiency.
Another cost for the grower is the cost of
medication (MED) to keep down disease and
mortality. The mean cost of MED is $0.016,
less than 2e/lb of bird moved. It is hypothesized that as the new technology decreases the
incidence of disease, the cost of medication
will also decrease, and this will result in better
production efficiency.
Three variables included in the models
but not in Table 1 are NOTBROIL, N2, and
N3. These variables are dummy variables
(having the data points of 0 and 1) and thus
are not adequately described by means and
standard deviations. Over the data set only
11% of the birds raised are not broilers
(NOTBROIL), meaning that a vast majority of
the data points deal with broilers. Note that
those growers who produced birds that were
not broilers did not begin doing so until 1992.
The other variables (N2 and N3) have to do
with the technology periods. The period before nipple drinkers were installed accounts
VARIABLE^
for 20% of the data points in the data set; 26%
are from the time of transition to the new
technology; and 54% are from the period of
full implementation.
RESULTS
AND DISCUSSION
The results for the model measuring
weight gain are presented in Table 2. This
model postulates weight gain/bird/day as the
dependent variable. The parameter estimates
of the explanatory variables are the partial
slope coefficients corresponding to the effect
each variable has on the average weight gain
of the birds per day. The R2 of 83% indicates
that the explanatory variables explain the
changes in the dependent variable very well,
considering that cross-sectional data sets do
not generally produce models with high R2
results. This means that the explanatory variables account for 83% of the variation in
weight gain/bird/day.
The first variable, MORTALITY, was
found to have an increasing effect on the daily
average weight gain of the birds. As long as
total growout mortality is within bounds, this
may occur because as more chickens die there
is more room in the poultry house for the
remaining birds, resulting in a more favorable
environment for gaining weight. The net effect
to the farmer may be close to zero as the gain
PARAMITER ESIlMATE
STANDARD ERROR
Intercept
0.123548
0.003159
MORTALITY
0.000143***
0.000053
-0.015619
LITITR
PAYMENT
PROPANE
NOTBROIL
I
I
I
0.043802
O.ooOo37*** *
I
O.OoooO5
I
O.ooo092** *
I
I
O.ooOo16
I
I
O.O04%I6** * *
PLACED
-2.327 E-'*'* *
0.000570
0.0
KILOCAL
-0.000013*'**
0.0000009
CONDEMN
-0.001356** * *
0.000221
MED
0.005833'
0.003377
N2
O.O01306** * *
0.000224
N3
o.m3247** * *
0.oO02.50
148
in payment for heavier chickens is canceled
out by the cost of higher mortality.
The variable LITTER, the litter cost in
dollars per pound of bird moved weighted by
the number of flocks grown by the ith grower,
is the only explanatory variable found to be
insignificant in explaining the dependent
variable. Given its insignificance, the effect of
LITTER on weight gain cannot be determined.
PAYMENT, the variable representing the
payment in dollars to the ifhgrower per 1,OOO
chickens placed, has a positive effect on the
average weight gain of birds per day. Although
it would be more appropriate to use payment
per pound to measure its effect on weight gain,
the absence of the payment per pound data
precludes this analysis. However, it should be
noted that the variable PAYMENT has an
important positive effect on weight gain, indicating that more efficient growers receive
higher payments. This may also indicate that
efficient growers who make more money from
their production process than the average
grower tend to put profits back into production and, perhaps, realize greater efficiencies.
One of the costs for poultry growers, especially in an area like the Delmarva Peninsula
which experiences cold weather in winter,
is energy costs for heating. In this data set
energy costs are measured by the variable
PROPANE, the average cost in dollars of propane consumption for the ith grower. In this
model an increase in spendingon propane has
a significant effect on an increase in weight
gain, indicating that warm, comfortable birds
are likely to grow more efficiently than buds in
an inhospitable environment.
As noted in the data description, the average weight of chickens grown on the Delmarva
Peninsula is greater than the average weight of
chickens grown in the United States as a
whole. In addition, many roasters are grown in
the Delmarva region. Roasters are grown
longer and weigh more than broilers. Not surprisingly, the result of this model indicates that
an increase in the number of birds that are not
broilers (NOTBROIL) has a significant correspondence to an increase in weight gain per
day.
The effect of the number of birds placed
in a house (PLACED) has the exact opposite
effect. As the number of buds placed increases, there is a significant and negative ef-
DRINKER TECHNOLOGY
fect on the daily weight gain of the birds being
grown. Evidently the birds’ ability to gain
weight and grow bigger is diminished as they
become more crowded. Thus, the more birds
the grower has to take care of, the higher the
chance that management mistakes will lead to
reduced weight gain.
KILOCAL, the adjusted kcal fed to the
birds, is a measure of feed efficiency. The
older the birds are, the more kcal, or units of
energy, are fed to them. The result of this
model, that an increase in the adjusted kcti1 fed
to the birds is accompanied by a decrease in
average daily weight gain, is contrary to what
is normally thought to take place.
The variable CONDEMN, representing
the percentage of farm condemnations per
grower, is an indicator of grower efficiency.
The fewer the condemnations of a grower’s
birds, the more healthy birds the grower is
producing. In this model an increase in farm
condemnations is accompanied by a decrease
in average weight gain per day. This may occur
because heavier birds are in general healthier
and less vulnerable to disease than underweight birds.
MED, the variable representing the cost
of water medication charged to the grower,
has a significant relationship with the dependent variable. It shows that an increase in the
cost of water medication is accompaniedby an
increase in the average weight gain per day.
Birds kept free of diseases are likely to gain
weight faster.
The variable N2, which represents the
transition period to nipple drinker technology,
is significant in this model and positive. This
shows that during the transition to the new
technology the average daily weight gain increases. This indicates an increase in efficiency for the growers.
An even greater increase in weight gain is
seen with the variable N3, the time period of
full implementation of the new drinker technology. While it is hypothesized that a new,
clean technology like the nipple drinker will
increase poultry production efficiency, not all
new technologies are beneficial. This result
confirms that the nipple drinker technology
does indeed have a positive effect on production efficiency.
The second regression model estimated
measures the effect of production variables
on the total grow-out mortality per flock, an-
Research Report
149
MICHEL et al.
other measure of efficiency. The results are
presented in Table 3. The degree to which
the explanatory variables explain the changes
in the mortality is rather good for a crosssectional data set, with an R2 of 44%.
In the first model daily average weight
gain increased as mortality increased. In the
second model the same effect is seen: an increase in weight gain (WEIGHT) is accompanied by an increase in mortality. As explained
previously, this may reflect that the remaining
chickens can gain more weight because more
space is left in the growing houses. That the
same effect occurred in both models confirms
the results.
An increase in the cost of litter per pound
of bird moved (LITTER) has a significant and
negative effect on total grow-out mortality.
A cleaner environment is beneficial for the
growing birds, so one in which more is spent
on keeping it clean should experience lower
mortality rates.
The effect on mortality of an increase in
the payment to growers per 1,OOO birds placed
(PAYMENT) is both significant and negative.
This means that as payments increase, mortality decreases. This would be expected because
a grower with high mortality may have less
healthy birds in general and may therefore
receive less in payment for his flock than a
grower who experiences a lower mortality
rate.
The variable representing propane consumption (PROPANE) in this model does not
produce significant results. Its effect on mortality therefore cannot be determined.
NOTBROIL, the variable representing
the percentage of birds in each flock that are
not broilers, reveals interesting results for this
model. As the percentage of birds that are not
broilers increases, the percentage of total
grow-out mortality also increases. Further examination of the data set shows that the average mortality rate for the NOTBROIL data set
was 6.7596,which was higher than the average
mortality rate for broilers and supports these
results.
The variable PLACED also yields an interesting result. The negative coefficient
means that as the number of birds placed increases, there is an accompanying decrease in
mortality. This is a good thing for the growers,
but at some point too many birds will be placed
and mortality will likely increase. For this data
set, however, newer, larger, and more technologically advanced growing houses were
added over the 10-yr time span, allowing for
increased placement and a concomitant decrease in mortality.
The variable KILOCAL, representing
feed efficiency, produces significant results in
TABLE 3.Model II results (Effect on mortality)
*WEIGHT=Average weight gain/day in Ibs; LITTER=Litter cost per pound of bird moved in each flock;
PAYMENT= Payment to growers per 1,OOO birds placed; PROPANE= Ener costs; NOTBROIL= Nonbroiler
birds; PLACED = Number of birds placed per grower; KILOCAL = Adjusted Ea1 as a measure of feed efficiency;
CONDEMN= Bird condemnations at processing resulting from im roper grower management; MED = Medication
costs; N2 =New nipple drinker technology transition period; N3 = &w nipple drinker technology fully implemented.
****significantat0.001 level: ***~imificant
at 0.01 level: **significant at 0.05level; 'Significant at 0.101evel;R
'=
.a.
DRINKER TECHNOLOGY
150
this model. As the energy in the food given to
the birds increases, there is an accompanying
decrease in the percentage of total grow-out
mortality. This may occur because buds fed
properly will be less vulnerable to diseases.
The relationship between the variable
representing the percentage of farm condemnations (CONDEMN) and total grow-out
mortality is signifcant and positive. Farm condemnations are condemnations done at the
processing plant that are charged back to the
grower because they are generally caused by
poor growing conditions. For example, too
much ammonia in the growing house produces
an inferior bud. A grower who experiences an
increase in farm condemnations might also
experience an increase in grow-out mortality.
The variable MED, representing the cost
of medication in the water, shows a result
which is positive and significant at the 10%
level. As the cost of medication increases,
there is an increase in the percentage of total
grow-out mortality. The positive relationship
between increased medication and increased
mortality may reflect disease outbreaks:
higher medication costs incurred in treating
the disease occur at the same time as an increase in mortality due to the disease.
The variable N2, representing the transition phase of the drinker technology, produces
curious results in this model. During the transition to the new technology, the regression
results show a positive impact on percentage
of total grow-out mortality. This increase in
mortality may reflect growers’ errors in judgement while learning to use the new technology.
When the drinker technology is fully implemented (N3), however, the change in mor-
tality is both significant and negative. When
the drinkers have been installed in all of the
houses, total grow-out mortality decreases.
This result supports Model I (effect on weight
gain per day) in showing that the change to
nipple drinker technology does indeed have a
positive effect on poultry production efficiency.
This study focused on a new drinker technology that was adopted on the Delmarva
Peninsula. The methodology applied in our
study, however, can be used to evaluate the
effect of any new technology and other factors
on the efficiency of poultry production. The
study revealed many significant results and
supported the notion that enhanced technology can have a positive effect on production
efficiency.
As global competition in the poultry industry grows, the importance of technology
grows with it. Generally, the lowest cost producers have an advantage over higher cost
producers. A recent study, found that Brazil
has the lowest cost of production among nations and that the United States has the second
lowest cost [l].In order to stay competitive it
will be important for the United States poultry
industry to seek efficiencies in technology to
keep costs down. Those countries that are able
to produce chickens in the most efficient way
will have an advantage over others. The appropriate use of technology, as has been demonstrated in this study, is an important factor in
enhancing efficiency and should therefore be
considered an important factor in any poultry
production facility today.
CONCLUSIONS
AND APPLICATIONS
1. Daily average weight gain per bird and total grow-out mortality rates were used as measures
of the gains in efficiency that producers experienced over the 10-yr data set. Because
technology was not the only variable affecting these measures, other production variables
were also included in the regression models. Most of the production variables included in
the regression models were found to have a significant relationship with the dependent
variables.
2. The significant variables contributing to the largest increases in daily average weight gain
were the cost of medication, the percentage of birds placed that were not broilers, and the
implementation of technology. The full implementation of technology had a larger effect
than the transition period of technology. A few variables contributed to a decrease in weight
gain per day, but their effect was smaller than the positive effect from other variables.
Research Report
MICHEL el ai.
151
The variables contributing most to a decrease in mortality were the full implementation of
drinker technology, an increase in the cost of cleaning out the litter (which is assumed to
mean that the houses were cleaned out more often), and an increase in the amount paid to
, OO birds placed. It is signifcant that the largest contributor to decreased
producers per 1O
mortality is the variable representing the full implementation of the new technology. This
bears out the hypothesis that the technological improvement really does contribute to
improved efficiency of production.
A new technology, such as nipple drinkers, along with other production variables utilized
in an efficient way, can have a critical effect on the improved efficiency of a poultry
production facility.
REFERENCES
AND NOTES
1. Henry, R a n d G. RolhweU, 1995.The World Poultry
Industry. The World Bank and Intl. Finance Cop., Washington, DC.
5. Lee, R and N.G. Zlmmermann, 1987. Effects of
enclosed nipple drinkers vs. dome waterers on broiler
performance. Poultry Sci. 66(Suppl):132.
2. Delmarva Poultry Industry, Inc., 1996. Voice of
Delmam’s Poultry Industry. Pamphlet. Georgetown,
DE.
6. Vest, LR,1986. Management of closed water systems for poultry. Poultry Sci. 65(Suppl):139.
3. Appleby, M.C., B.O. Hughes, and H A Elson, 1992.
Poultry Production Systems: Behavior, Management, and
Welfare. C.A.B. Intl., Oxford, England.
4. Carpenter, G.H., Rk Peterson, W.T.Jones, K.R
Daly, and W.A. Hypes, 1992. Effects of two nipple drinker
types with different flow rates on the productive performance of broiler chickens during summerlike growing
conditions. Poultry Sci. 71:145&1456.
7. Carr, LE, 1984. Comparison of three drinker systems for broilers. Pages 1-20 in: Proc. Amer. SOC.Agric.
Engineers 1984 Winter Conference, paper number 844520. St. Josephs, MI.
ACKNOWLEDGEMENT
The authors gratefully acknowledge the assistance of
the editor and two anonymous journal reviewers for their
suggestions in improving the manuscript.