The International Center for Agricultural Research in the Dry Areas
Assessing the Benefits and Costs of Participatory and
Conventional Barley Breeding Programs in Syria
Yasmin Mustafa (1)
Stefania Grando (2)
Salvatore Ceccarelli (3)
A Study Supported by the International Development Research
Centre
June 2006
(1)
Senior Economic Consultant, International Center for Agricultural Research in the Dry Areas. Email address: [email protected]
(2)
Senior Barley Breeder, International Center for Agricultural Research in the Dry Areas. E-mail
address: [email protected]
(3)
Consultant, International Center for Agricultural Research in the Dry Areas. E-mail address:
[email protected]
1
INDEX
1. Introduction............................................................................................................... 4
2. Conceptual Framework............................................................................................. 5
2.1. Benefit–cost Analysis ........................................................................................ 5
2.1.1. Farm-level analysis..................................................................................... 6
2.1.2. Market-level analysis .................................................................................. 6
2.2 Data Collection ................................................................................................... 7
3. Barley Production in Syria........................................................................................ 8
3.1 Farm Size and Land Tenure................................................................................ 8
3.2 Cropping Systems ............................................................................................. 10
3.3 Livestock Production ........................................................................................ 11
3.4 Barley Cropping Practices ................................................................................ 12
3.5 Enterprise Budgets ............................................................................................ 14
4. Participatory Plant Breeding Program .................................................................... 17
5. Farm-level Effects of Participatory Plant Breeding Varieties ................................ 19
6. Market-level Impact of Participatory Barley Breeding Varieties ........................... 26
6.1 Market-level Analysis....................................................................................... 26
6.2 Benefits of Barley Breeding Programs ............................................................. 28
6.2.1. Yield gain .................................................................................................. 28
6.2.2. Adoption rate and area planted with new varieties .................................. 31
6.2.3. The price of barley .................................................................................... 34
6.3 Costs of Barley Breeding Programs.................................................................. 34
7. Results..................................................................................................................... 37
7.1 Sensitivity Analysis .......................................................................................... 38
7.2 Poverty Alleviation ........................................................................................... 39
7.3 Intellectual Benefits .......................................................................................... 40
8. Conclusions............................................................................................................. 41
9. References............................................................................................................... 43
2
Assessing the Benefits and Costs of Participatory and Conventional Barley
Breeding Programs in Syria
Yasmin Mustafa, Stefania Grando, and Salvatore Ceccarelli
Abstract
This paper presents the results of a socioeconomic assessment of the impacts of
improved barley varieties used in two breeding programs: a conventional plant
breeding (CPB) program and a participatory plant breeding (PPB) program. The
participatory breeding program, which is run in Syria, was developed by ICARDA.
The objectives of this study were as follows:
(a) To investigate the current status of barley production in Syria;
(b) To evaluate and quantify the benefits and costs that barley producers and
institutions accrue as a result of using conventionally bred barley varieties
(‘conventional varieties’) and varieties bred using participatory techniques
(‘participatory varieties’);
(c) To assess the economic returns to investment associated with barley
research in Syria;
(d) To identify key points that must be considered during the development
and dissemination of new barley varieties in Syria.
This study provides some evidence that, no matter how many varieties are
released by the formal system, and no matter how great the yield gains they provide
over local varieties, farmers in marginal environments will not adopt them unless they
are selected through a process that involves their participation.
Analysis of the farm-level benefits and costs of barley production also showed
that farmer participation in the breeding program would not definitely result in higher
production costs. It was found that farmers adopting participatory breeding varieties
would likely pay higher input costs, but would also gain higher net returns. In
addition to the economic benefits, participation also provides other benefits, such as
the increase in human and social capital that results from farmers’ interactions with
breeders, technicians, and other farmers.
Using estimated adoption rates and weighted yield gains associated with
participatory and conventional varieties, market-level benefits were calculated for the
two breeding programs separately, using a gross economic benefit model. These
benefits were then compared with the estimated investment costs borne by ICARDA
for PPB and by ICARDA and national agricultural research systems (NARS) for
CPB. Under the baseline scenario, the benefit–cost ratio for PPB was 39 and the
internal rate of return (IRR) 46%. In the case of the CPB, the benefit–cost ratio was
15 while the IRR was 19%. The gross economic benefits accruing to society as a
result of adopting participatory varieties were calculated to be US$110.6 million,
while those derived from adopting conventional varieties were calculated to be
US$77.6 million.
3
Sensitivity analysis assumed that only 50% of the adoption rate and 50% of the
yield gain for the varieties produced by the two programs would be realized. This
analysis showed that the benefit–cost ratio and IRR remain favorable at 10 and 33%,
respectively, for PPB. The results obtained for CPB were also favorable in terms of
the benefit–cost ratio of 4 which was calculated; however, the 9% IRR obtained was
inefficient compared with a 10% commercial interest rate. Under the conditions
assumed in the sensitivity analysis, the gross economic benefits to society resulting
from the adoption of participatory varieties dropped to US$24.9 million, while for
conventional varieties the figure fell to US$14.4 million.
The study shows that the impact of PPB depends on the availability of the seed of
varieties produced using participatory breeding. Since most of the adopting farmers
operate in marginal areas where drought is a major risk, serious steps need to be taken
to ensure that such seed is available to farmers.
1. Introduction
Barley is usually grown under harsh, low-rainfall conditions, and is mainly
cultivated by small-scale resource-poor farmers in areas where no other crop can
grow. As a result, barley improvement research should benefit small resource-poor
farmers the most. This is important because it is widely recognized that conventional
barley breeding is more beneficial to those farmers who are able to profitably modify
their production practices to suit new cultivars. It has been of less benefit to those
farmers who could not afford to do this through the application of additional inputs
and who could not take the risk associated with replacing the traditional, well-known,
and reliable varieties they used.
Participatory plant breeding overcomes the limitations of conventional breeding
by offering farmers the chance to decide which varieties best suit their needs and
conditions without risking their livelihoods. It exploits the potential gains of breeding
for specific adaptation through selection in marginal environments. The participation
of farmers at the very early stages of selection helps to solve the problems associated
with the need to tailor a crop to both a multitude of target environment and user
preferences (Ceccarelli et al. 2001). Farmer participation also increases the
probability that a variety will be adopted, as well as the speed of adoption and the
efficiency and effectiveness of the breeding program (Ceccarelli and Grando 2002).
In 1991, the International Center for Agricultural Research in the Dry Areas
(ICARDA) began to gradually decentralize most of its barley selection work to
national programs. This has resulted in a number of participatory barley breeding
programs in Syria, Egypt, Jordan, Tunisia, Morocco, Yemen, Algeria, Iran, and
Eritrea.
One limitation of most of the participatory plant breeding work done around the
world in the past is the fact that most of the institutions promoting farmer
participation were not those responsible for plant breeding. This has limited both the
scale at which PPB was adopted by national programs and the extent of PPB’s
impact.
It is also widely believed that PPB methods result in higher costs for both
institutions and farmers than conventional breeding does. This often makes
4
institutions reluctant to embark on PPB programs (Mangione et al. 2006). Zeigler
(1996) for example, states that, as a result of adopting PPB, research institutions will
incur net additional costs associated with the possible need to lease land, and the need
to pay for additional travel, agricultural chemicals, vehicles, and labor, etc. Others
have stated that the operational costs of participatory breeding are higher than those
of conventional breeding (Lilja and Aw-Hassan 2003). However, other researchers
have stated that participatory work reduces the costs of the public sector (Pachico
1996). Traditional on-farm research requires an enormous amount of time with regard
to the monitoring undertaken by scientists and technicians. It is argued, therefore, that
efficient participatory research could replace much of the research undertaken on
station, thereby reducing costs through cost-sharing. In such efforts, farmers would
contribute to cost-sharing via their efforts, rather than financially. According to
Sthapit et al. (1996), farmers’ participation in selection reduces the costs of renting
land and labor. Ashby and Lilja (2004), moreover, concluded that it cannot be
concluded that participatory breeding causes major increases in costs.
The main goal of this study was to assess the adoption and impact of two different
barley breeding programs at the farm level and institutional level in Syria. Within this
overarching goal, the study had the following objectives:
1. To highlight barley breeding programs and investigate the current status of
barley production in Syria.
2. To evaluate and quantify the benefits and costs for barley producers and
institutions when using varieties bred using conventional and participatory
breeding techniques.
3. To assess the economic returns to investment associated with barley research
in Syria.
4. To specify key points that need to be considered during the development and
dissemination of new barley varieties in Syria.
Participatory barley breeding was conducted in Syria based on two principles. First,
the trials were conducted in farmers’ fields using farmer’s agronomic practices.
Second, farmers undertook selection in their own fields – making them the key
decision makers.
Estimating the cost of a program is not sufficient to properly judge the economic
situation of a program. Costs should be compared with the benefits associated with
the program. The ratio of the two components (the benefit–cost ratio) should not be
less than 1, otherwise the project will be being run at a loss.
For this study, the costs and benefits of conventional and participatory plant
breeding programs were estimated and a benefit–cost analysis conducted. Because
the calculated benefits would be affected by adoption rates and barley yield gains, the
study also analyzed how sensitive economic benefits were to those factors.
2. Conceptual Framework
2.1.Benefit–cost Analysis
5
2.1.1. Farm-level analysis
The first objective of this study was to evaluate and quantify the benefits and
costs of barley varieties selected by participatory barley breeding program in relation
to barley producers in Syria (at the farm and market levels). This analysis estimated
the effects that the new varieties of barley had on yields, variable costs, and net
revenues per hectare. It compared the crop budgets of improved varieties (selected by
farmers) with the crop budgets of conventional varieties (or landraces).
The benefits ascribed to the new varieties are not the net returns per hectare to
participating farmers. Rather, they are the differences between the net returns per
hectare for participating farmers and the net returns per hectare for non-participating
farmers. Thus, benefit–cost analysis will take into account two scenarios, one in
which the improved varieties are adopted, and one in which they are not. Since the
new varieties were released in the same locations, it is possible to measure the effects
of these new varieties on a farmer’s well being.
Data on the following is necessary for a farm-level impact analysis of PPB
varieties:
Data on conventionally bred varieties (or landrace varieties)
1. Average cost of production (SL/ha)
2. Average revenue (SL/ha). This requires researchers to know
a) The average yield (kg/ha)
b) The average farm price (SL/kg).
Data on varieties bred using participatory techniques
1. The average cost of producing new varieties (SL/ha) due to:
a) An increase or a decrease in seed costs.
b) The opportunity costs associated with a farmer’s participation in
the PPB program.
c) An increase in harvesting costs (in the case of harvesting cost is a
percentage of yield).
d) An increase in packaging costs, due to the harvest being larger.
2. The gross revenue of new varieties (SL/ha) based on:
a) Yield improvement in comparison with that of conventional
varieties (yield gain).
b) Changes in the quality of the harvested crop.
c) An increase in the production of straw.
2.1.2. Market-level analysis
One widely used method of estimating the ex-ante market impacts of a
production technology is to calculate the economic surplus changes and distributions
resulting from the adoption of a technology. There are two methods for calculating
economic surplus. The first is based on the assumption that technology adoption leads
to an outward shift in the product’s supply curve. The second method is to simulate
the impacts of the new technology on the relevant market variables using a structural
econometric model (Shideed and El-Mourid, 2006). These methods deal with the total
6
effect of the new technology: there is no way to disaggregate the effects of varieties
selected from different breeding programs.
Therefore, since the objective of this study is to calculate separately the impact
of adopting new varieties produced by conventional breeding and participatory
breeding programs, a gross economic benefit model was applied. This model was
used to quantify the economic benefits that the barley breeding programs in question
provide to society as a whole. It estimates the benefits resulting from the introduction
and adoption of both the new varieties released by conventional programs and the
varieties selected by farmers through their participation in the participatory program.
Since the calculated benefits would be affected by the adoption rate, barley yield gain
and the market price of barley, the study also considered the sensitivity of the
economic benefits to these factors.
2.2 Data Collection
To conduct the benefit–cost analysis for conventional and participatory plant
breeding programs, data were collected from ICARDA’s barley breeding program, as
well as from farm surveys, Syrian Ministry of Agriculture statistical reports, and from
the national agricultural research program in Syria. The data collected included the
costs of different activities associated with Syria’s national program and with
ICARDA’s participatory and conventional breeding programs. It also included data
on the costs associated with human capital in barley breeding, total area planted with
barley, percentage of area planted with new varieties of barley, the yield advantage of
improved varieties, and barley prices.
In this study, conventional plant breeding was defined as the type of breeding in
which all selection and part of the yield testing take place at research stations, though
the final stages of yield testing take place in farmers’ fields. Participatory plant
breeding, on the other hand, was defined as the type of breeding in which selection
and yield testing are conducted jointly by breeders and farmers in farmers' fields.
In each cycle the opinion of the farmers determines which material is promoted to
the next cycle (Ceccarelli and Grando, 2007). Except in the case of planting and
harvesting, breeders manage parallel experiments on research station, while farmers
manage experiments occurring in farmers’ fields.
Three groups of farmers were interviewed in a farm survey conducted during the
2004-2005 growing season: (1) “participant farmers”, (2) “evaluator farmers”, and (3)
“non-participant farmers”. A “participant farmer” was defined as a farmer who hosted
one or more trials in his field; an “evaluator farmer” was defined as a neighboring
farmer who participated in the selection of barley varieties. Finally, a “non-participant
farmer” was defined as a farmer who did not conduct trials and did not participate in
the selection process. Each participant farmer undertook selection in their fields and
had, in the past, participated in selection at a research station. Evaluators, the group
made up of neighboring farmers, also took part in selection in farmers’ fields.
The farm survey was conducted in seven provinces in Syria: Aleppo, Edlib,
Hama, Hassakeh, Raqqa, Deraa and Sweida. These are the areas in which barley is
produced in Syria. They are also the areas where ICARDA’s participatory barley
7
breeding program is implemented. The survey included 168 farmers, 56 from each of
the groups specified above.
3. Barley production in Syria
Sheep production is the main enterprise undertaken by communities in marginal
areas of Syria. Barley, which is the main crop used to produce sheep feed, is therefore
an important crop in the country. Barley straw is also used as bedding. Malting is the
second largest use for barley after feed. As a result, barley is also grown as a cash
crop.
In fact, barley is grown on over 2 million hectares in Syria. However, despite the
large area planted, little use is made of improved varieties. Barley growing in Syria
also covers a wide range of environments, with average annual precipitation ranging
between 200 and 350 mm. In the wetter areas of the country, if soils are fertile,
farmers can obtain up to 5 t ha-1 of barley grain in a good season when using
fertilizer. In the driest areas, soils are generally poor, and input levels are low. In
these areas grain yields vary from nil to 1.5 t ha-1. National average barley grain
yields are low, standing at 0.65 t ha-1 (Ceccarelli et al. 2001). Most of the barley is
grown in a risky, low-input marginal environment. In these areas barley is the most
common rainfed crop, and the choice of alternative crops and cropping systems is
very limited.
The trials took place in 25 villages across Syria, representing a range of climatic
conditions – from wet to dry. The farmers who participated displayed different levels
of education (from illiterate to college graduate). Farms varied in size (from 1 ha to
200 ha), as did families (ranging from 1 person to 35 people), and incomes (from
24000 SL annually to 8,640,000 SL annually). There were also differences in how
important barley was to each production system, as well as between the different
types of farming systems in terms of the interactions that occurred between cropping
and livestock production.
3.1 Farm Size and Land Tenure
The farms of the surveyed farmers differed in size at each trial location. They also
differed among the seven provinces involved. They ranged from 7 to 70 ha in Aleppo,
from 9 to 38 ha in Edlib, from 1 to 20 ha in Hama, from less than 1 ha to 120 ha in
Hassakeh, from 4 to 120 ha in Raqqa, from 5 to 200 ha in Deraa, and from 2.5 to 84
ha in Sweida. The largest farm (200 ha) was located in Deraa. The smallest farm (less
than a hectare) was in Hassakeh. On average, farms were largest in Raqqa and
smallest in Edlib. Average farm sizes in favorable areas such as Edlib and Hama were
smaller than was the case in harsh areas. The widest range in farm size occurred in
Deraa, and the narrowest was in Hama (Table 1).
In terms of size, the areas planted with barley also varied among provinces. And,
even though the largest farm was in Deraa, the largest single area planted with barley
(about 74 ha) was in Raqqa. Raqqa, which displayed the largest average farm size,
also had the largest average area planted to barley (23 ha). The smallest average area
planted to barley was in Edlib (almost 1.7 ha). In many provinces the minimum
barley planted area was equal to zero. This occurred because many farmers grow
8
barley every other year, while others do not grow barley during a particular season for
climatic reasons or because of lack of seed. The widest variation in barley planted
area was in Raqqa, while the narrowest was observed in Edlib.
Table 1. Average farm size and average barley planted area for farmers interviewed
during the 2004-2005 growing season in Syria.
Farm Size (ha)
Barley Planted Area (ha)
Average Max Min Variance Average Max Min Variance
Province
Aleppo
24.0
70.0
7.0
51666
10.6 35.0
0.0
9531
Edlib
9.4
37.8
9.4
10949
1.7
4.0
0.0
117
Hama
10.1
20.0
1.0
2475
3.1 10.0
0.6
531
Hassakeh
21.7 120.0
0.7
62840
8.7 60.0
0.0
21770
37.8 120.0
4.0 108989
23.0 74.0
2.0
45170
Raqqa
Deraa
31.4 200.0
5.0 318470
5.9 40.0
0.0
15063
26.9
84.0
2.5
43301
8.3 21.0
0.0
4864
Sweida
Total
23.0
93.1
4.2
85527
8.7 34.9
0.4
13864
The area planted to barley accounted for less than 20% of the total farm area in the
case of farmers surveyed in Edlib and Deraa, and for about one-third of total farm area
in Hama, and a little less than that in Sweida. In Hassakeh, by contrast, it accounted
for a little more than one-third of the area of the farms surveyed. In Raqqa the
percentage of area planted to barley was highest (62%). In Aleppo, barley was planted
on 40% of the area of the farms belonging to the farmers surveyed (Table 2).
Table 2. Total farm area and barley planted area for the surveyed farmers.
Province
Aleppo
Edlib
Hama
Hassakeh
Raqqa
Deraa
Sweida
Total Farm Area
(ha)
447.0
198.0
250.6
519.7
747.8
313.5
478.8
Total Barley Planted Area
(ha)
(%)
179.5
40.2
35.4
17.9
82.9
33.1
200.2
38.5
465.5
62.2
53.0
16.9
140.9
29.4
Surveyed farmers owned all of the land they farmed in Edlib and Deraa, and
almost 90% of the land they farmed in Sweida. In Aleppo, 80% of the land farmed by
the surveyed farmers was owned by them. The farmers interviewed in Hama and
Raqqa owned more than 76% of the land they farmed. In Hassakeh, farmers owned
no less than 60% of the land they farmed (Table 3). On average around 17% of the
land in the study area was rented. Most of the farmers only cultivated their own land.
However, 19% of the farmers surveyed did cultivate rented land in addition to their
own land; about half of them rented an area equal to or greater than the area they
owned. Only 3% of the farmers interviewed only cultivated rented land.
Share-cropping is the common practice in Aleppo, Raqqa and Sweida. In Hama
and Hassakeh two systems are in use: share-cropping and paying rent. The share
9
taken by the land-owner ranges from 20% to 25% of production if he/she does not
share any expenses. If, however, he or she pays the same share of the costs as the
producer, this amount may range from 40% to 60% of production. In Hassakeh, rent
ranged from 250 to 2000 SL/ha, while in Hama it ranged between 500 and 13,000
SL/ha; the official exchange rate used was Syrian Pound (SL) 50 to US$1 (Technical
Cooperation Department 2003).
Table 3. Total farmland, owned land and rented land for surveyed farmers.
Total Farm
Total Owned Land
Total Rented Land
Province
Area (ha)
Area (ha)
%
Area (ha)
%
Aleppo
Edlib
Hama
Hassakeh
Raqqa
Deraa
Sweida
447.7
198.0
250.6
519.7
747.8
313.5
478.8
360.0
198.0
192.5
315.7
570.8
313.5
429.2
80.5
100.0
76.8
60.7
76.3
100.0
89.6
87.7
0.0
58.1
204.0
177.0
0.0
49.6
19.5
0.0
23.2
39.3
23.7
0.0
10.4
3.2 Cropping Systems
The main crops grown in rainfed areas are wheat, barley, cumin, and legumes.
Olive and pistachio trees are also kept. Field crops are the dominant crops in the
areas, accounting for more than 80% of the land cultivated. Wheat is grown in all
areas and on 33.1% of the land covered by the survey. Barley was also grown at all
locations, covering different percentages of land: in Raqqa and Hassakeh barley
covered most of the farmland, while in the other provinces the percentage was lower.
Overall, barley covered 39.8% of the surveyed area. Cumin can be grown in a
marginal environment, which is why it is popular in the areas surveyed: around 6-9%
of the land in Aleppo and Edlib was planted with cumin. Legumes were grown at
many locations and covered about 5.3% of the area surveyed (Table 4).
The number of trees planted for commercial purposes has increased in several
provinces in Syria. Olives and pistachios were the most common trees in the areas
surveyed; grape is also grown there, they were covering about 5% of the cultivated
land. In Al-Jazira, the number of trees was limited and they were only kept to provide
for the family’s needs. About 3% of the land on the farms surveyed was irrigated,
while 12% was fallow land.
Raqqa and Hassakeh possessed the largest areas of cereal crops – more than
86% of the area surveyed in these two provinces was planted with wheat and barley.
Most of the rest of the land in these areas was fallow land.
Edlib and Sweida contained the largest areas of legume crops, with about 13%
of the farm area surveyed in these two provinces being planted with legumes,
including lentil and chickpea. About 22% of the land in Edlib and Hama was planted
with olive and pistachio trees. More than 23% of the area surveyed in Deraa was
fallow, while Hama contained the highest percentage of irrigated land.
10
Table 4. Crops cultivated by surveyed farmers during the 2004/2005 season in seven
Syrian provinces (area in hectares).
Aleppo
Area
Edlib
%* Area
Hama
% Area
Hassakeh
% Area
Raqqa
% Area
Deraa
% Area
Sweida
% Area
%
Barley
204
46
37
19
83
33
201
39
429
62
80
22
114
28
Wheat
123
28
54
27
27
11
252
48
175
25
139
38
184
46
Cumin
27
6
20
9
8
3
0
0
15
2
0
0
0
0
Legumes
34
8
26
13
17
0
8
2
0
0
15
4
52
13
Olive
11
3
40
20
35
7
0
0
5
1
13
4
1
0
Pistachio
0
0
4
2
25
14
0
0
2
0
2
1
0
0
Grape
0
0
1
0
8
3
0
0
0
0
7
2
0
0
Fallow
48
10
11
6
5
2
34
6
66
10
87 24
Irrigated
6
1
4
2
38
15
28
5
0
0
20
5
crops
Total Farm
100 199 100 256 100 521 100 691 100 369 100
Area
448a
* % is the percentage of crop area to the total interviewed area in that province.
58
14
0
0
403
100
a Numbers may not sum to the total due to the rounding of these numbers.
3.3 Livestock Production
Small ruminants are common in barley-producing areas, as barley is the main source
of feed for these animals. Sheep and goats are mainly raised for meat and dairy
production. More than 78% of the farms surveyed in the Al-Jazira area are
characterized by a crop–livestock system. However, this was found to be the case for
only about 40% of farms in the other provinces. In Raqqa 100% of the farmers
surveyed owned sheep and about two-thirds of them owned goats as well. Some of the
farmers surveyed owned very limited numbers of milking cows (Table 5). No farmer
in Raqqa owned any cows, though about half of the farmers interviewed in Deraa did.
Only about 10% of Daraa farmers owned sheep, and none of them owned goats.
Table 5. Total number of animals owned by farmers and the percentage of farmers
owning them.
11
Province
Aleppo
Edlib
Hama
Hassakeh
Raqqa
Deraa
Sweida
Percentage of Farmers Owning
Total Number of Animals Owned by
Livestock (%)
Farmers (head)
Sheep
Goats
Cows
Sheep
Goats
Cows
65
35
6
436
63
3
29
24
0
615
16
0
52
30
7
255
37
4
68
68
18
877
132
11
81
57
14
868
80
24
10
0
50
35
0
17
35
12
12
169
25
14
3.4 Barley Cropping Practices
In the case of rainfed barley production, how the land is prepared depends on soil
characteristics, the previous crop, and the financial position of the farmer in question.
Barley can follow barley, legumes, or fallow. Field preparation usually starts in
summer one month after harvesting, after sheep have grazed all the grain and straw
left in the field. When barley is being grown after barley or lentil, the land is first
tilled in July/August and then again in October/November, shortly before planting.
When barley is grown after fallow, the first tillage is applied in April. A second tillage
is then applied in July/August, and a third tillage before planting. Mechanical land
preparation is the most common practice for all barley producers. However, barley
planting can be done by hand or using machines, depending on the location. For
example, in Deraa and Sweida most of the planting was done by hand. Machinery
rental prices and the intensity of land preparation undertaken differ according to the
kind of operation and location in question.
The seed rate differs from location to location, and ranges between 40 kg/ha and
250 kg/ha (Table 6). On average the highest seed rate is used in Hama and the lowest
in Deraa. At some locations the seed rates used by participant farmers were lower than
those used by non-participant farmers, while in other areas they were higher.
Farmers who plant their fields mechanically clean their seed. Some of them also
treat their seed before planting it. Most of the farmers in Aleppo, Edlib, Hama,
Hassakeh, and Raqqa clean their seed before planting it, while about 70% of the
farmers in Sweida and 55% of those in Deraa do the same. More than 85% of the
farmers in Edlib treat their seed before planting. The same is true for almost half the
farmers in Hama, Hassakeh, and Raqqa. In Aleppo and Deraa, however, more than
two-thirds of farmers do not treat their seed.
Table 6. Seed rates used by different farmer groups, by province.
Seed rate (kg/ha)
Province
Participant farmers
Evaluator farmers
Non-participant farmers
Aleppo
187
186
175
12
Edlib
Hama
Hassakeh
Raqqa
Deraa
Sweida
Total
265
165
163
189
60
84
159
228
168
155
200
47
56
149
236
168
172
198
84
42
153
Farmers use two types of barley cultivar, the seeds of which differ in color (white or
black). The two-rowed black-seeded cultivar (named ‘Baladi Aswad’) is mainly
grown in the Al-Jazira area, while the two-rowed white-seeded cultivar (named
‘Baladi Abiad’) is grown in other areas. All the farmers interviewed in Hassakeh,
Sweida and Deraa only planted these local landraces. In the remaining provinces, in
addition to these landraces, farmers also planted some officially released improved
varieties such as ‘Furat 1’, ‘Furat 2’, and ‘Furat 3’ (bred by the Ministry of
Agriculture) and ‘Arta’ (bred by ICARDA). Also being used were some barley lines
produced by ICARDA and but not yet approved for official release. Such lines
included ‘Zanbaka’, ‘Harmal’, ‘Suran1’ and ‘Nawaiir1’ (Table 7). ‘Zanbaka’ and
‘Harmal’ were submitted to the official variety release systems in the early 1980s, but
were rejected. They were then included in the PPB trials and, because of the farmers’
preference for them, were eventually adopted. Some of the officially released varieties
have also been adopted by farmers as a result of being used as checks in the PPB
experiments.
Table 7. Percentage of farmers growing barley varieties in the farms surveyed in
different provinces.
Province
Aleppo
Edlib
Hama
Hassakeh
Raqqa
Deraa
Sweida
Average
Aswad Abiad Arta Zanb. F 1 F 2 F 3 Hml Suran1 Nawaiir1
47
32
100
35
31
21 6
67 13
8
45 10
100 100 37 7
16
10
6
4
-
5
8
5
3
5 14 13
4 3
3
1
11
3
ICARDA
varietya
Total
8
14
20
5
100
100
100
100
100
100
100
100
Aswad = ‘Arabi Aswad’, Abiad = ‘Arabi Abiad’, Zanb. = ‘Zanbaka’, F 1 = ‘Furat 1’, F 2 = ‘Furat 2’,
F 3 = ‘Furat 3’, Hml = ‘Harmal’
a
varieties received through ICARDA but for which the name was not available
Farmers do use fertilizers in barley production. However, whether or not they are
used depends on the amount of rainfall expected during the growing season. Such
expectations affect both the number of fertilizer applications used and the kind and
amount of fertilizer applied. Most of the farmers surveyed applied fertilizer at planting
13
by mixing it with the seed, as this prevents them from incurring the costs associated
with having to apply the fertilizer separately.
The second application of fertilizer occurs in spring. This is done either
mechanically or by hand, depending on the size of the field and the availability of
machinery. Surveys of farmers showed that super phosphate and nitrogen fertilizers
were used during the first application at planting. During the spring application, only
nitrogen fertilizer was applied. All the farmers surveyed in Edlib applied fertilizers
twice during the growing season. Most of the interviewed farmers in Aleppo, Hama,
and Raqqa applied fertilizer at planting, though only some of them applied it during
the spring. Only 30% of the farmers interviewed in Hassakeh applied fertilizer at
planting, and none of them applied it during the spring. In Deraa, 22% of the farms
surveyed used fertilizer twice a year. By contrast, none of the farmers interviewed in
Sweida used fertilizer in barley production.
With regard to barley production, pest and weed control varied greatly from
location to location. In Hassakeh, none of the farmers interviewed applied any form
pest or weed control, while in Deraa and Sweida only about 10% of farmers used pest
and weed control. In Aleppo 18% of the farmers used herbicides only, while in Raqqa
about 21% used pesticides; only one farmer there used herbicides. However, more
than 85% of the farmers interviewed in Edlib used pesticides, though only 14% used
herbicides. By contrast, 40% of the farmers interviewed in Hama applied herbicides,
though only 7% of them applied pesticides.
Harvesting is mechanized in all areas except Deraa and Sweida, where it is done
by hand. A rented combine harvester is usually used. Harvesting services could be
paid for in grain (a percentage of the grain harvested); the service would also include
packaging and the transportation of the bags to a farmer’s house. The percentage paid
ranged from 6% to 8% of grain yield. In some locations, the cost of harvesting did not
include any costs other than the cost of the combine harvester. Packaging, loading,
transportation and unloading costs were paid separately, and could be paid per unit of
land. The rental fee for a combine harvester varied from 500 to 1000 SL per hectare.
The fee for a mechanically harvested unit of land was lowest in Aleppo and highest in
Edlib.
Post-harvest activities included chemical treatment (to reduce post-harvest seedgrain losses) and packaging. About two-thirds of the farmers interviewed in Edlib and
about one-quarter in Aleppo and Hama treated their grain. However, this was true of
no more than 12% of the farmers surveyed in Hassakeh and Sweida. None of the
farmers in Deraa treated their grain, and the same was true in Raqqa, except in the
case of one farmer. At all locations, most of the farmers interviewed packaged their
barley. Some of them used plastic bags because they are cheap (only 10 SL per bag)
even although they are not strong enough and can be easy tired up; others used
secondhand bags (15-30 SL per bag), the rest used new bags (50 SL per bag).
3.5 Enterprise Budgets
Compared to other crops, barley production is a relatively low-input activity as it
takes place in a marginal environment. Data collected through farmer interviews were
used to estimate farmers’ costs in relation to barley production in the study area. The
14
costs of producing barley in each province were estimated separately in order to
identify cost differences among the locations studied. Since three groups of farmers
were interviewed (“participant”, “evaluator” and “non-participant” farmers), the costs
for each group were estimated separately. In addition, costs were also calculated for a
fourth group, which grouped all the farmers together.
The estimates obtained represent average costs (only variable costs were
included) and returns for all respondents in the sample. These budgets showed that
the average cost of barley production was highest in Edlib (10,143 SL/ha) and lowest
in Deraa (2459 SL/ha). There was therefore a high level of variation among these
costs: production costs in Edlib were four times more than they were in Deraa, for
example. The second-highest production costs were found to occur in Hama (7461
SL/ha). Average costs in Aleppo, Raqqa, Hassakeh and Sweida were 5588 SL/ha,
5406 SL/ha, 4145 SL/ha and 3958 SL/ha, respectively. The differences between the
three farmer groups were not constant. Participant farmers in Aleppo, Edlib and
Sweida shouldered the highest average costs in comparison to the other two groups,
whereas in Hama and Hassakeh the highest costs were borne by evaluator farmers.
Non-participant farmers in Raqqa and Deraa had the highest average costs compared
to the other two groups.
These budgets also varied considerably with respect to the cost of specific items,
probably (1) because different levels of input were used at different locations and (2)
because operation costs varied. In Aleppo, Edlib, Hama, Hassakeh, Raqqa and Deraa,
farmers’ material input costs were higher than the operational costs of the three
groups of farmers, accounting for more than 60% of total costs in almost all cases.
The exceptions were Hama and Deraa, which accounted for nearly 50% of total costs
(Table 8).
Seeds, harvesting and nitrogen fertilizer costs were the three major costs for all
groups of farmers in Aleppo, Edlib, Hama and Raqqa. For the farmers in Hassakeh,
seeds, harvesting and plowing costs were the major outlays. The three groups of
farmers in Sweida and the evaluator farmers in Deraa had operational costs that were
higher than their material input costs, accounting for more than 70% of their total
costs. In Deraa, seeds, plowing, and harvesting were the most costly items, while in
Sweida the highest cost items were harvesting, plowing and seeds. Harvesting alone
accounted for nearly 50% of the total cost of the three groups of farmers in Sweida
because it is done by hand (Appendix A, Tables A1-A7).
The enterprise budgets indicated that the average yield of barley ranged from a
maximum of 2.63 tonnes per hectare to a minimum of zero for the different groups of
farmers at different locations. However, many farmers achieved significantly higher
yields.
Average yields varied considerably across provinces and groups. It was not clear
which of the groups produced the highest average yield, because participant farmers,
for example, achieved the highest yield in one location and the lowest in another, and
this pattern was true for the other groups as well. Yield varied greatly depending on
the variety planted, and farmers tended to grow different varieties. Participant
farmers, for example, might grow the local landrace or a PPB or a CPB variety. This
was also true for the other groups of farmers. Average yields for farmers in Hassakeh,
15
Deraa and Sweida were lower than those for farmers in other provinces due to the
nature of the marginal environments of these provinces.
When yields are expected to be low, because of adverse climatic conditions,
farmers do not harvest their fields in order to save the harvesting cost. Instead, they
rent the field for grazing, which means that grazing will be the only return from the
crop in such a case.
Table 8. Average production cost, average yield, and average total and net returns for
all groups of farmers.
Non Participant Farmer Evaluator Farmer Participant Farmer
All Farmers
Total Costs P e r c e n t Total Costs Percent Total Costs P e r c e n t Total Costs Percent
Items
S L / h a
%
S L / h a%
S L / h a%
S L / h a%
ALEPPO
Operation
2317.3
44.1
1770.4
33.1
2136.4
36.0
2071.2
37.1
Material Inputs
2940.3
55.9
3576.6
66.9
3804.7
64.0
3512.0
62.9
Total Expense
5257.5
100.0
5347.0 100.0 5941.1
100.0
5583.2
100.0
Yield (kg/ha)
2050.0
1176.0
1202.5
1394.1
Total Returns (SL/ha) 21725.0
12680.0
16772.9
15448.5
Net Returns (SL/ha)
16467.5
7333.0
10831.8
9865.3
EDLIB
Operation
3503.0
37.2
4086.0
39.5
3763.1
36.0
3831.8
37.8
Material Inputs
5916.9
62.8
6268.8
60.5
6689.1
64.0
6311.6
62.2
Total Expense
9419.9
100.0
10354.7 100.0 10452.2 100.0 10143.3 100.0
Yield (kg/ha)
2509.0
2625.0
2549.0
2550.0
Total Returns (SL/ha) 25147.0
31696.0
29353.0
28620.0
Net Returns (SL/ha)
15727.1
21341.3
18900.8
18476.7
HAMA
Operation
3563.0
49.6
4538.0
59.6
3445.0
48.3
3722.9
49.8
Material Inputs
3626.0
50.4
3078.6
40.4
3682.0
51.7
3747.9
50.2
Total Expense
7189.0
100.0
7616.6 100.0 7127.0
100.0
7470.8
100.0
Yield (kg/ha)
1523.8
1916.6
2008.0
1852.6
Total Returns (SL/ha) 18171.9
21286.7
21983.0
20763.4
Net Returns (SL/ha)
10982.9
13670.1
14856.0
13292.6
HASSAKEH
Operation
1531.7
40.8
1868.0
40.7
1650.0
40.2
1680
40.5
Material Inputs
2226.7
59.2
2717.5
59.3
2453.1
59.8
2464.5
59.5
Total Expense
3758.4
100.0
4585.5 100.0 4103.2
100.0
4144.5
100.0
Yield (kg/ha)
750.0
1385.0
956.3
1023.0
Total Returns (SL/ha) 10348.3
14060.0
10911.9
11687.3
Net Returns (SL/ha)
6590.0
9474.5
6808.8
7542.8
RAQQA
Operation
1736.6
30.2
1390.5
28.9
1803.5
33.8
1745.1
32.3
Material Inputs
4010.4
69.8
3425.0
71.1
3536.6
66.2
3661.3
67.7
Total Expense
5747.0
100.0
4815.5 100.0 5340.1
100.0
5406.4
100.0
Yield (kg/ha)
1108.0
1150.0
1307.0
1242.0
Total Returns (SL/ha) 12661.0
12727.5
15524.3
14440.0
Net Returns (SL/ha)
6914.0
7912.0
10184.2
9033.6
DERAA
Operation
1538
49.1
1533.3
72.0
896.5
43.3
1365.0
55.5
Material Inputs
1594.0
50.9
596.7
28.0
1173.0
56.7
1093.6
44.5
Total Expense
3132.0
100.0
2130.0 100.0 2069.5
100.0
2458.6 100.0
Yield (kg/ha)
450.0
107.0
0.0
234.0
Total Returns (SL/ha)
9550.0
6756.7
5000.0
7547.0
16
Net Returns (SL/ha)
6418.0
Operation
Material Inputs
Total Expense
Yield (kg/ha)
Total Returns (SL/ha)
Net Returns (SL/ha)
2695.0
762.0
3457.0
600.0
10940.0
7483.0
78.0
22.0
100.0
4626.7
SWEIDA
3461.0
82.7
724.0
17.3
4185.0 100.0
547.0
10818.0
6633.0
2930.5
3527.0
704.0
4231.0
814.0
15144.0
10913.0
5088.4
83.4
16.6
100.0
3227.7
730.0
3957.7
697.9
11990.0
8032.3
81.6
18.4
100.0
The value of barley grain and either the value of straw or the rent obtained as a
result of renting the field out for grazing were the components of total return in the
enterprise budgets. Total returns ranged from 5000 SL/ha to more than 31,000 SL/ha,
depending on grain yield, straw yield or field rent and prices. Edlib farmers had the
highest returns among the farmers surveyed, while Deraa’ farmers had the lowest.
Net returns are the difference between total returns and total expenses. In other
words, they are what are left to farmers after they cover all production expenses. Net
returns ranged between 21,341 SL/ha in Edlib and 2931 SL/ha in Deraa. Many
farmers achieved significantly higher net returns.
4. Participatory Plant Breeding Program
The plant breeding method used in Syria, as well as in the other countries where
similar programs are implemented, is the bulk-pedigree. In this method, crosses are
created on station. The F1 and the F2 generations are also grown on station. This is
followed by three years of yield testing and the selection of bulk breeding material
(Fig. 1) (Ceccarelli and Grando, 2007).
Yield testing begins with unselected F3 bulks in trials called Barley Initial Trials
(BIT) in the conventional program and Farmer Initial Trials (FIT) in the participatory
program. The F4 bulks that are selected are then tested in the field in trials known as
Barley Preliminary Trials (BPT) in conventional programs and Farmer Advanced
Trials (FAT) in participatory programs. This is followed by the field-testing of the
selected F5 bulks in trials known as Barley Advanced Trials (BAT) and Farmer Elite
Trials (FET) in the two programs, respectively.
BIT, BPT, and BAT are grown only on research stations while FIT, FAT, and
FET are grown in farmers’ fields. Work in farmers’ fields begins with the FIT, which
are unreplicated trials consisting of two-hundred 12-m2 plots. These contain 170
entries plus one or two checks repeated 30 times. In the second year of trials,
breeding material selected from the FIT is tested in the FAT. In the FAT, the number
of entries and checks used varies from village to village and from year to year. FAT
trials use 45-m2 plots that produce enough seed on farm for the selected entries to be
planted on larger plots in the third year.
One of the most important advantages of PPB is the fact that it brings forward in
time the delivery phase normally associated with plant-breeding programs. In
conventional programs the most promising lines are released as varieties, their seed is
produced under controlled conditions (certified seed) and only then can farmers
decide whether or not to adopt them. In many developing countries this process
results in many varieties being released and only a small fraction adopted. As a result,
the considerable amount invested in developing these varieties and in producing their
seed is simply lost. In the case of PPB, however, initial adoption by farmers takes
17
place towards the end of the three-year selection phase, which drives the decision of
which variety to release. As a consequence, adoption rates are expected to be higher,
and risk of non-adoption is minimized, as the farmers gain intimate knowledge of
variety’s performance as part of the selection process. Last but not least, the
institutional investment in seed production is nearly always paid off by farmers’
adoption of the variety.
Conventional Plant
Breeding
On-Station
Participatory Plant
Breeding
Crosses
Year 1
Crosses
F1
Year 2
F1
F2 Bulks
Year 3
F2 Bulks
On-Station
Barley Initial
Trials (BIT)
Year 4
Farmer Initial
Trials (FIT)
Barley Preliminary
Trials (BPT)
Year 5
Farmer Advanced
Trials (FAT)
On Farm
Barley Advanced
Trials (BAT)
On Farm
Year 6
Farmer Elite Trials
(FET)
Adoption Release
00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00
00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 0
0
On-Farm Trials
(OFT)
Year 7
On-Farm Trials
(OFT)
Year 8
00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00
00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00
On-Farm Trials
(OFT)
Year 9
00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00
00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00
Fig. 1. The two plant breeding programs implemented in Syria.
18
The two types of breeding program differ in a number of aspects. Using the
conventional program, as it is applied by the Syrian National Program, it takes nine
years of research to identify a variety for release, and this variety may only be suited
to a certain environment. The PPB program can produce many different varieties
suitable for many different environments in as little as six years, because even at the
same location farmers will choose more than one variety that meets their preferences.
The most important factor affecting the adoption of a new variety is its
performance, which varies with environment and management factors (Aw-Hassan
and Shideed 2003). Since PPB occurs in farmers’ fields and involves farmers’ own
practices instead of those used on research stations, it is a simple way of convincing
farmers that the variety they select has benefits and that they should adopt it. This
limits the additional amounts that need to be spent on disseminating the new varieties.
In some cases farmers adopt all of the varieties selected through the PPB program. In
the case of conventional research, by contrast, many released varieties are never
adopted by farmers. Their development costs must therefore be considered a loss to
society that reduces the Gross Economic Benefit (GEB) achieved by the program.
5. Farm-level Effects of Participatory Plant Breeding Varieties
The effects that participatory plant breeding have on the costs of barley
production at the farm level, as well as on the incomes of farmers, were analyzed by
comparing the enterprise budgets of farmers growing PPB varieties and participating
in the participatory barley breeding program with those of farmers growing local
landraces and not participating in the program. The new varieties necessitated
changes in some inputs and production factors. Thus, the evaluation of farm-level
impacts requires one to estimate not only the effects that a new variety has on crop
yield, but also its effect on the cost of production.
Only the variable costs were included when estimating the enterprise budget,
because the fixed costs were assumed to be the same for the landrace and the new
variety. According to the survey, the price of the seed of new varieties is one to oneand-a-half Syrian pounds (SL) higher than the price of landrace seed; thus, the farmer
who adopts a new variety would face at least a 10% increase in the cost of seed
keeping the seed rate constant.
Since the new variety will increase barley yields, harvesting and post-harvesting
costs will also increase. These costs include the harvesting cost charged as a
percentage of yield, grain treatment costs, packaging costs. In addition, farmers who
participate in the program bear an opportunity cost for the time they spend on
program activities. Such costs depend on the extent of their involvement, which
differs between participant and evaluator farmers. The participant farmers spent, on
average, 7-10 days on project-related activities during the season as a result of their
involvement in the program (a figure which depends on the province considered);
evaluator farmers spent 1-3 days, on average, on project-related activities (Table 9).
Some farmers, however, stated that they spent up to 15 days during the season. The
wage rate was taken to be 250 SL per day, in order to take into account their
involvement cost. This cost was divided by the area planted with barley by the farmer
to calculate the farmer’s involvement cost per unit of land.
19
20
Table 9. Average number of days spent by farmers in the participatory plant breeding
program.
Province
Participant Farmer
Evaluator Farmer
Aleppo
Edlib
Hama
Hassakeh
Raqqa
Deraa
Sweida
9
9
10
7
8
7
8
2
2
3
1
1
2
2
The analysis showed that barley production costs per unit of land for participant
farmers were higher than the costs for non-participant farmers (Tables 10-13). In
three provinces (Edlib, Hama, and Raqqa) they were 12-20% higher, while in Aleppo
the costs were more than 47% more. This difference was due to the low costs incurred
by non-participant farmers in Aleppo in comparison with participant farmers (Table
10).
A comparison of seed, harvesting, post-harvest, and participation costs for the two
groups of farmers showed that participants faced higher costs than non-participants in
all provinces with some exceptions; in Hama, harvesting costs for the non-participant
farmers were higher than that for the participant farmers, also in Edlib, the costs of
post harvesting for the non-participant farmers were higher than that for the
participant farmers. Participant farmers at all locations bore additional costs as a
result of participating in the program. These ranged from 327 to 1270 SL/ha, with
differences occurring as a result of variation in the area planted with barley and in the
average number of days spent participating. In Aleppo (Table 10), harvesting costs
were 22% higher, post-harvest costs 70% higher, and seed costs 13% higher for
participant farmers than they were for non-participant farmers. In the case of farmers
in Edlib (Table 11), harvesting costs for participants were 52% higher than those of
non-participants; however, the costs participants faced for post-harvest services and
packaging were 10% lower than those faced by non-participants. Seeds costs were
similar for the two groups in Edlib.
Harvesting costs for non-participant farmers in Hama (Table 12) were 30% higher
than those of participant farmers, because the manual harvesting undertaken by some
farmers was more expensive than mechanical harvesting. However, manual
harvesting does not incur post-harvest service costs. It follows that the post-harvest
costs for participant farmers were 278% higher than those faced by non-participants.
Seeds costs were 19% higher. In Raqqa (Table 13), harvest, post-harvest, and seed
costs were higher for participant farmers than for the non-participants by 29%, 49%
and 4%, respectively. Overall, farmers who adopted the PPB variety experienced
yield gains of 15% in Edlib, 89% in Hama, 30% in Aleppo, and 41% in Raqqa (Table
14).
Given the expected yield gain and the low increase in variable costs, Edlib
farmers are expected to experience a 0.2% decrease in cost per metric ton, while
21
farmers from Hama and Raqqa are expected to benefit from decreases of as much as
36% and 19% in costs per metric ton respectively. However, Aleppo farmers are
expected to experience a 13.5% increase in the cost per metric ton.
Table 10. Farm-level analysis of barley production costs and returns in Aleppo.
Non-Participant
Participant
Farmers
Farmers
Total Costs
Total Costs
(SL/ha)
%
(SL/ha)
%
INPUTS
Operations
Plowing
733.3 15.5
933.3 13.3
Sowing
183.3
3.9
100.0
1.4
Seed Cleaning & Treatment
75.0
1.6
96.7
1.4
Fertilizer Application
41.7
0.9
111.7
1.6
Pesticide & Herbicide Application
0.0
0.0
83.3
1.2
Harvesting
716.7 15.1
875.0 12.5
Post Harvesting Seed Treatment
25.0
0.5
33.3
0.5
Packing
180.0
3.8
234.0
3.3
Opportunity Cost of Participation
0.0
0.0
708.3 10.1
Subtotal
1955.0 41.2
3175.6 45.4
Material Inputs (kg)
Seeds
1433.3 30.2
1623.3 23.2
Fertilizer: Nitrogen
616.7 13.0
1007.5 14.4
Phosphorus
466.7
9.8
670.8
9.6
Seed Treatment
0.0
0.0
58.3
0.8
Pesticide & Herbicide
0.0
0.0
112.3
1.6
5.7
351.0
5.0
Bags
270.0
Subtotal
2786.7 58.8
3823.3 54.6
Total Expenses
4741.7 100.0
6998.9 100.0
RETURNS
Yield
1500.0
1950.0
Return from Grain
12250.0
18200.0
Return from Straw
2133.0
4106.7
Total Returns to Farm
14383.0
22306.7
Net Return
9641.3
15307.8
Cost Per Tonne of Grain
3161.1
3589.2
22
Table 11. Farm-level Analysis for Barley Production Costs and Returns in Edlib.
Non- Participant
Participant Farmers
Farmers
Total Costs
Total Costs
(SL/ha)
%
(SL/ha)
%
INPUTS
Operations
Plowing
1091.7
11.2
1012.5
9.0
Sowing
350.0
3.6
325.0
2.9
Seed Cleaning & Treatment
92.5
0.9
46.3
0.4
Fertilizer Application
191.4
2.0
162.5
1.4
Pesticide & Herbicide Application
90.0
0.9
193.8
1.7
Harvesting
1321.4
13.6
2018.8
18.0
Post Harvesting Seed Treatment
223.6
2.3
156.3
1.4
Packing
312.9
3.2
410.0
3.7
Opportunity Cost of Participation
0.0
0.0
1270.8
11.3
Subtotal
3673.5
37.7
5595.8
49.9
Material Inputs (kg)
Seeds
2259.2
23.2
2250.0
20.0
Fertilizer: Nitrogen
1811.3
18.6
1434.4
12.8
Phosphorus
1082.9
11.1
800.0
7.1
Seed Treatment
236.7
2.4
431.3
3.8
Pesticide & Herbicide
121.7
1.2
251.3
2.7
Bags
554.2
5.7
412.5
3.7
Subtotal
6065.8
62.3
5579.4
50.1
Total Expenses
9739.3 100.0
11175.2 100.0
RETURNS
Yield
2489.0
2860.0
23338.0
27900.0
Return from Grain
Return from Straw
1833
2563
Total Returns to Farm
25171.7
30462.5
Net Return
15432.4
19327.3
Cost Per Tonne of Grain
3912.9
3907.3
23
Table 12. Farm-level Analysis for Barley Production Costs and Returns in Hama.
Non-participant farmers Participant farmers
Total Costs
Total Costs
(SL/ha)
%
(SL/ha)
%
INPUTS
Operations
Plowing
1283.3
19.6
1310.0 16.6
Sowing
218.3
3.3
240.0
3.0
Seed Cleaning & Treatment
85.0
1.3
121.3
1.5
Fertilizer Application
120.0
1.8
79.1
1.0
Pesticide & Herbicide Application
130.0
2.0
70.0
0.9
Harvesting
1708.3*
26.0
1190 15.1
Post Harvesting Seed Treatment
8.3
0.1
16.0
0.2
Packing
100.0
1.5
374.6
4.7
Opportunity Cost of Participation
0.0
0.0
743.0
9.4
Subtotal
3653.3
55.7
4144.0 52.5
Material Inputs (kg)
Seeds
1387.5
21.1
1648.3 20.9
Fertilizer: Nitrogen
590.0
9.0
850.3 10.8
Phosphorus
375.0
5.7
451.0
5.7
Seed Treatment
126.7
1.9
66.0
0.8
Pesticide & Herbicide
270.0
4.1
117.0
1.5
Bags
158.3
2.4
619.6
7.8
Subtotal
2907.5
44.3
3752.1 47.5
Total Expenses
6560.8
100.0
7896.1 100.0
RETURNS
Yield
1012
1911
Return from Grain
9763
18255
Return from Straw
3992
2648
Total Returns to Farm
13754
20903
Net Return
7193.2
13007
Cost Per Tonne of Grain
6483
4131.9
* Harvesting costs are higher because some farmers use manual harvesting.
24
Table 13. Farm-level analysis for barley production costs and returns in Raqqa.
Non-participant
farmers
Participant farmers
Total Costs
Total Costs
(SL/ha)
%
(SL/ha)
%
INPUTS
Operation
Plowing
430.0
8.0
562.5
9.3
Sowing
174.0
3.2
162.5
2.7
Seed Cleaning & Treatment
48.0
0.9
48.8
0.8
Fertilizer Application
65.0
1.2
22.5
0.4
Pesticide & Herbicide Application
37.3
0.7
33.0
0.5
Harvesting
791.4
14.6
1021.4
16.8
Post Harvesting Seed Treatment
16.0
0.3
0.0
0.0
Packing
0.0
0.0
0.0
0.0
Opportunity Cost of Participation
0.0
0.0
327.4
5.4
Subtotal
1561.7
28.9
2178.0
35.8
Material Inputs (kg)
Seeds
1749.0
32.4
1825.0
30.0
Fertilizer: Nitrogen
902.0
16.7
809.4
13.3
Phosphorus
570.0
10.5
518.8
8.5
Seed Treatment
178.0
3.3
103.1
1.7
Pesticide & Herbicide
75.7
1.4
67.0
1.1
Bags
370.0
6.8
575.6
9.5
Subtotal
3844.7
71.1
3898.9
64.2
Total Expenses
5406.4 100.0
6076.9 100.0
RETURNS
Yield
1075
1511.3
Return from Grain
10413.2
14760.0
Return from Straw
1480.0
2897.4
Total Returns to Farm
11893.2
17657.4
Net Return
6486.8
11580.5
Cost Per Tonne of Grain
5029.2
4050.5
Table 14. Percentage change in yield and costs for participant farmers growing PPB
varieties compared with non-participant farmers growing the local variety.
Percentage Change
Post
Harvesting harvesting
Costs per
cost/ha
metric
ton
Yield/ha
Seeds
cost/ha
costs/ha
Province
Aleppo
30%
13%
22%
30%
14%
Edlib
15%
0.4%
52%
-10%
- 0.2%
Hama
89%
19%
-30%
278%
- 36%
Raqqa
41%
4%
29%
49%
- 19%
25
The benefits farmers received were evaluated quantitatively and qualitatively.
Economic benefits resulting from adopting a new variety include higher yield, greater
stability, and improved sustainability. It was also assumed that working with
researchers would improve the human capital of participating farmers. If the work is
done in groups or if information-sharing is encouraged, then the social capital,
defined as the ability of farmers to work together and share information, should
increase as well (Johnson et al., 2000).
Individual interviews with farmers were conducted to assess impacts on human
and social capital. Changes in participants’ knowledge and understanding of the
program, their interaction with researchers and with other farmers, and their ability to
diagnose problems and solve them were also assessed through a questionnaire.
About 81% of the farmers interviewed stated that, even if the PPB research ends,
they would keep practicing what they have learned through PPB and selection. They
also assured us that they would protect the seeds of the new varieties, and would keep
looking for good varieties with other farmers and then planting them. Up to 31% of
the farmers interviewed said that PPB enhanced their knowledge of barley
production, as well as agricultural in general. Nearly 44% said that they had gained
new knowledge of variety selection as a result of their participation in the evaluation
and selection process. Twenty-one percent stated that their knowledge increased as a
result of their interaction with other farmers, and 27% that their knowledge increased
as a result of their interaction with breeders. The PPB program had a positive impact
on the economic status and the livelihood of 65% of the participant farmers,
according to those farmers. The other 35% stated that there was as yet no change in
either their economic status or in their livelihoods as a result of being involved in the
program. Most of these farmers are in the area where PPB has not yet reached the
final stage.
When asked how the program’s benefits should be shared, only 7% of the farmers
interviewed believed that farmers who selected the varieties should keep the
economic benefits, resulted from producing the seeds of that variety and sell them to
other farmers, for themselves; 93% believed that these benefits should be distributed
at the community level.
6. Market-level Impact of Participatory Barley Breeding Varieties
6.1 Market-level Analysis
Benefits. The economic benefits attributed to barley breeding programs are generally
estimated as the additional production value that results from the adoption of new
varieties developed by breeding programs. Three key parameters are needed to
calculate this value: (1) the area planted with new varieties; (2) the productivity gains
associated with the adoption of these varieties; and (3) the price of the crop (Morris et
al. 2003). Productivity gains are often expressed in terms of yield per unit land area.
The gross economic benefit (GEB) model was used to calculate the benefits
associated with the new varieties. The GEB formula (Manyonk et al. 2003) is
expressed as follows:
26
m n
GEB = ∑ ∑( Aj * Iij * Yij * Pij )
j=1 I=1
With
Pij = pij / E
Yij = yij - Lij
Where GEB = gross economic benefit, i = barley variety, j = location, A = area
planted with new variety (ha), I = percentage of area cultivated to variety i, Y = yield
advantage (kg ha-1), P = crop price ($ t-1), y = average farm yield for an improved
variety (kg ha-1), L = average farm yield for local variety (kg ha-1), p = crop price in
local currency, E = exchange rate of local currency to US $.
Costs: Costs are the time series of investments by the public and private sector in the
development of the new variety.
Investment Performance Indicators: The two most common measures of return on
an investment are the benefit–cost (B–C) ratio and the internal rate of return (IRR).
Benefit–cost analysis is a method of comparing the benefits obtained from a project
with the costs incurred as a result of conducting the project. The benefits are
calculated as the dollar value of benefits received by the users of the research
project’s output. The costs are calculated as the sum of direct and indirect costs
invested by the public and private sectors in the development of the technology. The
internal rate of return is defined as the interest rate that equates the net present value
of the benefit and cost flow to zero, as calculated using the equation:
t=n
B -C
Σ ——
=0
t
t=1
t
(1 + r)t
where Bt and Ct are the values of the benefit and cost streams in each time period
from t =1 to n, and r is the interest rate that solves the equation (i.e. r is the IRR).
Since project costs are incurred before benefits are realized, both costs and
benefits should be calculated in present value (PV) terms. The value of the benefit–
cost ratio may be greater than, equal to, or less than 1. If it is greater than 1, it
indicates that the present value of benefits is greater than the present value of costs.
This implies that the returns from the project are more than the amount of money
invested in it. The IRR is the return obtained on the money invested in the project,
which will cover the investment cost and guarantees an additional annual percentage
of return on the use of the money in the meantime. A project is considered profitable
if its IRR exceeds the average market interest rate during the life of the project.
27
6.2 Benefits of Barley Breeding Programs
The participatory barley breeding program started in 1996 in 11 locations (nine
farmers’ fields and two research stations) with 200 plots at each location (Ceccarelli
et al. 2000, 2003). Its second phase began in 2000 and covered 25 villages in seven
provinces in Syria. By the end of the 2005 growing season, 10 varieties had already
been selected for release and named by farmers: Suran-1, and Nawaiir 1 and 2 in
Suran (Hama province); Raqqa 1 and Raqqa 2 and Akrem and Kareem in Baylounan
(Raqqa province); and Yazem, Etihad, and Salam in Jurn Al-Aswed (Raqqa
province). Most of these varieties are still at the seed-production stage of the process.
In addition to the above varieties, others (such as Arta, Harmal and Zanbaka)
were introduced to farmers through the PPB program and were, as a result, accepted
and adopted by the farmers involved. Six varieties were also released by the
conventional program between 1994 and 2003. However, many of these varieties
were actually introduced to farmers through PPB, since they were used as checks in
the PPB trials.
The impact of plant breeding programs is not limited to the yield advantage
provided by new varieties. Improved varieties may also have other important traits,
such as resistance to disease and drought. Such traits can have an important impact, in
that they can reduce the risk associated with rainfed farming and stabilize farmers’
incomes.
As mentioned previously, three key parameters are needed to estimate the
potential benefit of PPB and CPB barley varieties: yield gain, area on which the new
varieties are adopted, and barley price. Therefore, before estimating the benefits,
these parameters need to be estimated.
6.2.1. Yield gain
Yield gain is the advantage in terms of average yield that the new variety gives over
the average yield of the local variety. The production function method was used to
estimate the net effect of new varieties on barley productivity. For this, four
production functions were estimated, one for each of the four provinces where the
new varieties were grown (namely Aleppo, Edlib, Hama and Raqqa). The dependent
variable of these functions was “total production”, while the independent variables
included “area planted with barley”, “land preparation cost”, “total amount of seed”,
and “total amount of fertilizers”. A dummy variable was also included for farmers
who planted PPB varieties, as was another for the farmers who planted CPB varieties.
The estimated coefficients are presented in Table 15.
The estimated coefficients showed that the use of PPB varieties had a net effect
of 32% on barley productivity in Aleppo and 19% in Edlib. In Hama and Raqqa, by
contrast, the net effect was 59% and 53% respectively. This implies that, for the same
level of inputs, the PPB varieties will produce yields per unit of land that are 32%
higher than local varieties in Aleppo, 19% higher than local varieties in Edlib, and
59% and 53% higher than local varieties in Hama and Raqqa, respectively.
28
Table 15. Estimated coefficients for barley production functions in four provinces.
Estimated Coefficients
Variables
Aleppo Edlib
Hama
Raqqa
Constant
0.26
0.43*
0.69** 0.47**
(0.253) (0.199) (0.199) (0.211)
Area (ha)
0.059
(0.329)
-0.222*
(0.107)
-0.85*
(0.434)
1.74**
(0.459)
0.28
(1.22)
Land Preparation (SL/ha)
Seeds (kg/ha)
Fertilizer (kg/ha)
Dummy Variable for PPB Variety
0.42**
(0.158)
0.65
(0.383)
0.003
(0.024)
-0.041
(0.442)
0.46*
(0.221)
0.397
(1.519)
0.037
(0.025)
0.66
(0.745)
0.6**
(0.265)
-0.37
(0.839)
0.42
(2.484)
-
0.15
(0.162)
0.41*
(0.226))
0.005
(0.338)
0.816**
(0.215)
0.17
(0.366)
0.156
(1.8)
0.63
14.976
35
0.74
17.001
35
0.89
27.899
20
0.85
30.201
26
Dummy Variable for CPB Variety
2
R
F
N
-
Standard errors are in parenthesis.
* Significant at 0.01 level, ** significant at 0.05 level
The actual data collected by interviewing farmers were also used to calculate the
actual yield gains. Only in Edlib was the actual yield gain observed less than that
estimated (Table 16).
Table 16. Actual and potential yield gain for participatory plant breeding (PPB)
varieties and conventional plant breeding (CPB) varieties
PPB yield gain
CPB yield gain
Province
Total (actual)%Net (potential)%Total (actual)%Net a (potential)%
Aleppo
43
32
56
-Edlib
12
19
7
17
Hama
74
59
55
49
Raqqa
63
53
52
-a
The data available was insufficient to estimate CPB net yield gain in Aleppo and Raqqa.
Actual yield gains in Aleppo, Hama and Raqqa were higher than the yield gains
estimated for these locations. The relatively high yield gains seen most likely resulted
from the combined effects of the new variety and input intensification. This mean that
using these rates in the benefit analysis would probably inflate the gain in
productivity induced by the new variety and would lead to the returns to the barley
breeding programs being overestimated. Thus, estimating the net effect that a new
variety has on barley productivity is very important in order to isolate any other
29
effects resulted from input combination. These estimates do, however, show that there
is still a potential for yield to be increased, as long as the estimated yield gain is
greater than the actual gain.
Yield gain was estimated based on the actual data for the 2004-2005 growing
season which (when assessed in relation to historical weather data) is considered to be
a normal season in terms of the amount and distribution of rainfall. The estimated
production function showed that the use of improved varieties developed under PPB
provided a yield advantage over the local variety which ranged from 19% to 59%.
This yield advantage does not reflect yields under the conditions actually experienced
in the dry areas of Syria, which are subject to frequent droughts which alternate with
normal weather conditions. Therefore the yield gains were adjusted to take into
consideration three levels of rainfall (normal, dry and good). This process of adjusting
the yield gains involved the following steps.
1. Historical rainfall and yield data were collected and analyzed at the province level
for the 1976-2003 cropping seasons. The historical yield data were used to classify
cropping seasons into the categories “normal”, “dry” and “good” depending on the
weather conditions. Average yield levels were calculated for the corresponding
season in each of three groups and the percentage yield changes between the
“normal” and each of the “dry” and “good” seasons were calculated.
2. Using the historical yield data and rainfall information, the probability of the
occurrence of each of the three types of season was calculated (Table 17). It was
found that drought occurred in many years during the 1976-2003 period, and that
the probability of drought occurring is 30% in Aleppo, 13% in Edlib, 35% in
Hama and 52% in Raqqa. The probability of a good season occurring is 5% in
Aleppo, 22% in Edlib, 8% in Hama and 13% in Raqqa. These probabilities show
that the season could not be considered “normal” in 35-65% of the cases and that
therefore the estimated yield gains are not applicable and that they should be
adjusted. It is also important to notice that in Raqqa and Hassakeh provinces,
which contain around 50% of the country’s total barley-growing area, the
probability of drought is about 50%. In addition to this, most of the barley-growing
areas in Raqqa and Hassakeh are in marginal environments where barley is the
main crop and there are no other alternatives.
3. The calculated yield gain from the production function was adjusted using the
probabilities of the three types of season occurring. The adjusted yield gains are
presented in Table 17.
It is important to mention here that the calculation of the yield gain using crosssectional data for one season will reflect only one state of nature, which only partially
reflects the conditions found in dry areas. Using such an estimate without adjusting it
to various rainfall conditions will, therefore, lead to an overestimate of yield gain and
the corresponding benefits. This point is clearly shown in Table 17, where adjusted
yield gain is much lower than calculated using only the production function.
30
6.2.2. Adoption rate and area planted with new varieties
Plant breeding research generates benefits only when new varieties are adopted and
grown by farmers. The amount and the value of these benefits depend on the area
planted with new varieties. Therefore, the first step that needs to be taken when
calculating the benefits of PPB and CPB research is to estimate the area planted to
these varieties. It is important to estimate not only the area planted to PPB and CPB
varieties at a specific point in time, but also the rate of diffusion of these varieties
over time, since these estimates will be used when calculating financial measures that
involve dynamic aspects, such as the benefit–cost ratio and internal rate of return.
Most studies of the diffusion of new varieties assume that the cumulative
proportion of the area planted to a new variety follows the logistic pattern, which is
mathematically described as:
Yt = K/ {1 + e-a-bt}
Where Yt is the cumulative percentage of adoption at time t, K is the upper limit
of adoption (adoption ceiling), a is a constant related to the time when adoption
begins, b is a constant related to the rate of adoption and t is time. It is more practical
to use ordinary least squares regression to estimate a transformed version of the
logistic curve equation (Morris et al. 2003):
ln [Yt / K-Yt] = a + bt
K can be selected by running the regression using several different values of K,
to select the value that maximizes R2. Accordingly, the actual data of area planted
with PPB and CPB barley varieties in the four provinces of Syria for the period 19962005 were used to estimate the equations of a variety of diffusion curves for PPB and
CPB varieties in each province (Table 18). Adoption ceilings ranged from 40% to
80%; 10% intervals were used as K values to estimate these equations.
Table 18. Estimated coefficients for the diffusion curves of participatory and
conventional barley varieties in four provinces.
Participatory Barley Breeding
Conventional Barley Breeding
Province
A
b
R2
K
A
b
R2
K
Aleppo
-14.352
1.241 0.77 0.50 -7.525
0.455
0.58
0.50
(2.928) (0.338)
(0.801) (0.123)
Edlib
-13.7
1.25
(1.708) (0.197)
0.91
0.40
-5.24
(0.383)
0.477
(0.059)
0.87
0.40
Hama
-5.89
0.698
(0.726) (0.112)
0.80
0.70
-5.35
(0.249)
0.65
(0.042)
0.96
0.50
Raqqa
-4.357
0.714
(1.089) (0.153)
0.73
0.40
-7.952
(1.098)
0.556
(0.133)
0.78
0.40
31
Standard errors are in parenthesis.
The adoption ceiling for PPB varieties was found to be 50% for Aleppo, 40% for
Edlib and Raqqa, and 70% for Hama – since these ceilings gave the highest R2 value
of all the estimates. The selected ceilings were the same for the CPB and the PPB
varieties in all provinces except Hama, where they were 50% for CPB varieties and
70% for PPB varieties. In addition to estimates made of the adoption rate for the
1996-2005 period, estimates were also produced for the adoption rate for the period
2006-2015. It was clear that the adoption of PPB varieties took 8-15 years to reach its
peak for all locations, while for CPB varieties it required 16-20 years; the estimated
rates are presented in Appendix A, Table A8. The adoption rates estimated were used
to draw the diffusion curves for the participatory barley breeding varieties and the
conventional varieties in the four provinces in which these varieties have been
adopted (Fig. 2).
D iffu s io n C u r v e s fo r C P B a n d P P B in A le p p o
A doption Rate (% )
0.60
0.50
0.40
C P B V a rie t y
0.30
P P B V a rie t y
0.20
0.10
2022
2020
2018
2016
2014
2012
2010
2008
2006
2004
2002
2000
0.00
Ye a r
0.45
0.40
0.35
0.30
0.25
0.20
0.15
0.10
0.05
0.00
C P B V ariety
15
20
12
20
09
20
06
20
20
20
00
97
19
19
03
P P B V ariety
94
A doption Rate (% )
D iffu s io n C u r v e s fo r P P B a n d C P B V a r ie tie s in E d lib
Y ears
B a r le yP P B & C P B
D if f u s io n c u r v e s in H a m a
0 .8 0
0 .6 0
0 .5 0
C P B V a r ie ty
0 .4 0
PPB V a r ie ty
0 .3 0
0 .2 0
0 .1 0
14
20
12
20
10
20
08
20
06
20
04
20
02
20
00
20
98
19
96
19
94
0 .0 0
19
A doption Rate (% )
0 .7 0
Y ear
32
CPB V a r ie ty
18
20
2
1
09
15
20
20
03
0
06
20
20
20
00
97
PPB V a r ie ty
2
19
94
0 .4 5
0 .4 0
0 .3 5
0 .3 0
0 .2 5
0 .2 0
0 .1 5
0 .1 0
0 .0 5
0 .0 0
19
Ado p tio n R a te (% )
B a rle y P P B & C P B D iffu s io n C u r v e s in R a q q a
Ye a r
Fig. 2. Diffusion curves representing the estimated adoption rates for barley varieties derived
from two different plant breeding programs: conventional plant breeding (CPB) and participatory
plant breeding (PPB), in four different provinces.
It is clear that at all locations, during the first three years after release, no CPB
varieties were adopted. CPB varieties began to be adopted in 1996 in Edlib, in 1999
in Hama and in 2001 in Aleppo and Raqqa. However, in the case of the latter two
provinces, adoption actually came about as a result of the PPB program – because the
CPB varieties were used in the PPB trials as a check, and farmers began to grow them
after seeing how they performed. It is therefore fair to say that the PPB program
played a major role in disseminating the CPB varieties and that without the PPB
program the adoption of the CPB varieties would probably have been lower. PPB
varieties began to be adopted as soon as they were seen by the farmers, during the
testing and selection period. If enough seed had been available to meet demand, these
varieties would have been adopted very fast and would have reached the adoption
ceiling much more quickly.
The diffusion of PPB varieties occurred much more quickly than that of CPB
varieties. In Aleppo, PPB varieties reached the adoption ceiling of 50% 11 years
earlier than the CPB varieties did. In Edlib, they did so 5 years earlier, and 1 and 6
years earlier in Hama and Raqqa respectively.
Seed production is very important if the adoption of the selected varieties is to be
guaranteed to occur at the predicted rate. Leaving this task to the local farmers will
not achieve the objective of the project, since most of them operate in marginal
environments. In such marginal environments, the risk of a dry season occurring is
very high, which would result in either no grain being produced, or such a low level
of production that all the grain grown has to be used to feed the livestock. Therefore a
dry year, in addition to all other undesirable effects it has, will seriously set back the
adoption process. Because of this, someone must be given the responsibility of
producing seed and making it available to farmers regardless of the weather
conditions occurring in the previous season.
Survey data shows that farmers are willing to pay higher prices for the seed of
PPB varieties. The survey also showed that the price of barley grain (for feed) was on
average 8240 SL/ton compared to 10,000 SL/ton for the barley seed (for planting).
However, not all farmers can get PPB seed, so the farmers interviewed expressed
their willingness to pay on average 11,910 SL/ton to get these seeds. This implies that
they are willing to pay 19% more for the seed they want.
33
6.2.3. The price of barley
The farmers interviewed reported that the price they received for their crop
varied considerably over the year, depending on supply and demand. Post-harvest
barley prices are much lower than those obtained during the winter season. Farmers
also stated that they sell their product for a price that is lower than the price they
would need to pay to purchase barley seed to be planted in the next season. The floor
price set by officials may be higher than the market price, but farmers still sell their
crops to the dealers for less to avoid the extra costs (e.g. packaging and transport
costs) they would have to bear if the sold their product to the seed company. In the
2005 harvesting season, for example, some farmers sold their crop immediately for
8000 SL/ton. Later in the season, however, the price of barley reached 11,000 SL/ton.
For the purposes of this analysis, the average price of barley for the last ten years
(1996-2005) was calculated to be 8020 SL/ton. The official exchange rate used was
Syrian Pound (SL) 50 to US$1 (Technical Cooperation Department 2003). Using this
exchange rate the price of barley was calculated to be to be US$160/ton.
The estimated parameters for yield gains, adoption rates and barley price were
then used to calculate the GEBs of adopting (1) the varieties released through the
CPB program and (2) the varieties selected by farmers through the PPB program. For
the purposes of this analysis, data on the area planted to barley during the period
1994-2005 was obtained for each province from the relevant Syrian Statistical
Reports (SSRs) 1994-2003. The area which it was predicted would be planted in each
province during the period 2006-2015 was estimated using the estimated trend
equations of planted area for the period 1994-2005. Barley yield for the local variety
was estimated from a combination of information, including farm survey data for the
2004-2005 seasons and SSRs for the 1994-2003 seasons. A moving average of ten
years was calculated for the yield of 2006-2015. The benefits stream for CPB
varieties was calculated for the period 1985-2015 and then deflated using a discount
rate of 3%. The same technique was applied to the benefit stream for PPB varieties
for the period 1993-2015. To get the benefit–cost ratio and to calculate the IRR, the
annual cost associated with the two programs must be calculated for the period of
development and diffusion.
6.3 Costs of Barley Breeding Programs
The costs of the two types of breeding programs (conventional and participatory)
at ICARDA were assessed through consultations with the breeders. This was done to
specify which projects cover participatory activities and which conventional research
activities. During the period 2000-2005 there were eight projects involving
conventional research expenditures, five projects involving participatory research,
and six projects involving both types of expenditure in different proportions. The
annual costs of each program were calculated for the same categories as determined
by the finance department at ICARDA.
The costs of the conventional program in Syria accounted for 15% of the total
conventional costs of ICARDA’s barley breeding program. These costs show that
personnel costs are the highest cost in relation to barley breeding. The second-highest
34
cost was expenditure on contract services, a category which includes the labor hired
to do most of the agricultural work. Ranked third was expenditure on travel, including
local and international travel expenses and per diems. The study made it clear that
ICARDA’s conventional research costs were close to those of participatory research
(Table 19).
To obtain information about the distribution and the magnitude of the investment
in human resources made by the two types of breeding programs, the human resource
cost at ICARDA for 2004 was used. After specifying the staff involved in the two
programs, the study calculated the proportion of their time spent on each and then
calculated the cost for each program (Table 20). The results showed that investment
in human resources for PPB amounted to US$72,046, which was about one-quarter of
the total costs of CPB, which amounted to US$283,630. Syria’s proportion of the
total CPB cost was US$42,545.
Table 19. Annual costs of the conventional and participatory plant breeding programs
at ICARDA (US dollars).
Costs
Supplies
Contract Service
Travel
Repair and Maintenance
Miscellaneous
Training
Inter-departmental Allocation
Depreciation
Utilities, Rent, Communication
Salaries
Other Employment Costs
Grand Total
Total CPB Costs
Syria CPB Costs
Syria PPB Costs
2000
2001
2002
2003
2004
35288
95108
68411
5355
13494
10193
34823
7943
5546
218260
123043
547818
475844
83273
71974
74132
107419
97714
6870
44851
2705
2000
5780
2943
258168
167428
766010
647319
113281
118691
59923
69458
59433
16468
28166
5856
97264
3856
3256
266580
159369
575101
477539
83569
97561
94442
187409
64188
6221
7888
2793
7159
5210
4135
232600
124515
722240
637680
111594
84560
151809
214574
72936
59247
31251
11242
0
5178
7234
283653
182274
1019398
914937
160114
104461
Contract Service included consultant, casual labor, membership fees and NARS contract research.
Table 20. ICARDA investment in human resources in barley breeding programs.
35
NPO: National Professional officer.
GS: General Services
In addition to the PPB research costs, the study also calculated farmers’
participation costs by assuming that each participant farmer spent nine working days
on the project on average and each evaluator two working days on average. A wage
rate of 250 SL/day was applied to the two groups. Annual participation costs were
then added to the annual research costs.
The cost stream for the PPB program was calculated for the period 1993-2015,
since the program started in 1996 in farmer’s fields, but was preceded by three years
of on-station research. The PPB costs for 2006-2015 were assumed to continue at the
same level as in 2005. For the CPB program, a cost stream was calculated for the
period 1985-2004, since the earliest adopted variety that is still in use was released in
1991. Six years of NARS field work were assumed to have occurred prior to the
release of the variety. This figure was based on the fact that, most of the time, NARS
obtain materials from ICARDA and test them for three years on station followed by a
further three years in farmers’ fields. These costs were considered until 2004 – the
year in which varieties were last released.
The barley research-related expenditure of NARS was estimated based on data
provided by Beintema et al. (2006), who reported total agricultural research
expenditure and the total number of researchers for NARS in 2003. These two values
were used to calculate the average cost per NARS scientist, and this cost was then
converted from Syrian pounds to US dollars using a weighted exchange rate of
SL48.1 to US$1 (Technical Cooperation Department 2003). Beintema et al. (2006)
also reported that 151.3 researchers were working to conduct crop genetic
improvement in full-time equivalent posts. Since 5% of the scientists conducting crop
research were working on barley, this percentage was applied to the scientists
Category
P level staff
P6
P5
Post
Doctorate
NPO
NPO
NPO
GS5
GS6
Annual costs (US$)
No.
of Average Employment
Total
staff salary
cost
% of time % of time
spent
spent
on PPB
on CPB
PPB
costs
CPB costs
1
1
70875
49203
65205
45267
136080
94470
0.2
0.1
0.8
0.9
27216 108864
9447 85023
1
24000
18000
42000
0.25
0.75
10500
31500
1
1
1
2
2
12500
12500
12500
4540
5262
6000
6000
6000
1861
2157
18500
18500
18500
6401
7419
0.2
0.9
0.05
0.05
0.2
0.08
0.1
0.95
0.95
0.8
3700
16650
925
640
2968
14800
1850
17575
12162
11856
Total Costs
341870
72046 283630
working in crop genetic improvement to get the number of scientists working in
barley breeding.
36
Figures for the research expenditure of NARS in 2003 were obtained by
multiplying the average cost per scientist and the number of researchers involved in
barley breeding. Beintema also reported a growth rate of 3.8% for the period 19982004, and this was used to calculate the annual research costs of NARS for the same
period. For 1985-1997, another growth rate was estimated based on data provided by
Pardey et al. (1989) who reported total agricultural research expenditures by country
for the periods 1961-1965 and 1981-1985 in the appendix of their work (pp. 414421). The annual growth rate estimated (2.8%) was used to calculate the annual
research costs for the period 1985-1997. Total CPB costs per year were obtained by
adding ICARDA’s annual conventional breeding costs to the NARS’ annual research
costs. Total annual costs were then deflated using the same annual discount rate as
used previously (3%).
7. Results
Analysis of the farm-level benefits and costs of barley production in seven Syrian
provinces shows that the production costs for participant farmers are not always
higher than those of non-participant farmers. Participant farmers adopting
participatory varieties would likely pay higher costs per unit of land, but gain higher
returns as a result of higher yields per unit of land. The analysis also showed that the
net return per hectare is also higher for the participant farmers. Even though they pay
higher costs per hectare, the costs per ton of barley grain produced by them are less
than those of the barley grain produced by non-participant farmers. This is due to the
greater yields and higher prices associated with the PPB varieties. However, the price
cannot always be higher, as it is higher precisely because the new seed of the new
varieties in question is not available to everybody. After a while, once most of the
farmers start producing their own seed, seed prices will go down. This will, in return,
reduce the returns from selling the grain produced by such new varieties.
Market-level benefits, which were calculated separately for the two breeding
programs using a GEB model, were then compared with the estimated investment
costs of the two programs (Table 21). Research expenditures for CPB were almost
twice as high as those for the PPB program. This was the case because two sets of
institutions invested in the CPB program (ICARDA and NARS) while only ICARDA
invested in the PPB program. The benefit–cost ratio for the PPB program was 39 and
its internal rate of return (IRR) was 46%. In the case of the CPB program, the
benefit–cost ratio was 15 and its IRR 19%. The gross economic benefits to society
resulting from the adoption of participatory varieties for the period 1993-2015 were
calculated to be US$110.6 million, while those resulting from the adoption of
conventional varieties for the period 1985-2015 were calculated to be US$77.6
million. This means that adopting PPB varieties will generate around US$33 million
more in net returns than CPB, and will do so in less time. Annual research
expenditure by the PPB program was calculated to be less than half that of the CPB
program. Meanwhile, the annual economic benefits derived from the PPB program
were 92% higher than those derived from the CPB program.
37
Table 21. Summary of results for participatory plant breeding (PPB) and
conventional plant breeding (CPB) programs.
PPB Program
CPB Program
Research Expenditure (million US$)
2.8
5.0
Gross Economic Benefits (million US$)
110.7
77.6
Period of Study
1993-2015
1985-2015
Annual Research Expenditure (million US$)
0.122
0.251
Annual Economic Benefits (million US$)
4.8
2.5
Discount Rate (%)
3
3
Internal Rate of Return (%)
46
19
Benefit–cost Ratio
39
15
7.1 Sensitivity Analysis
To show the sensitivity of the results to changes in certain factors, only half of
the estimated adoption rate for the varieties of the two programs was applied. The
result obtained shows that the benefit–cost (B-C) ratio and the IRR remain favorable
(at 19.9 and 43% respectively) for PPB. They also remain favorable for CPB, with a
B-C ratio of 8 and an IRR of 14%. The gross economic benefits obtained from
adopting participatory varieties were found to be US$52.5 million, while those
obtained through conventional varieties amounted to US$33.8 million.
It was also found that implementing only one-half of both estimated adoption
rate and estimated yield gain for the varieties of the two programs led to a B-C ratio
and IRR of 10 and 33% respectively for the PPB program. For CPB program the
figures obtained were 4 and 9% respectively. The IRR for CPB was inefficient when
compared with the commercial interest rate of 10%. The GEB obtained as a result of
adopting participatory varieties dropped to US$24.9 million, while that associated
with conventional varieties fell to US$14.4 million (Table 22).
Table 22. Adoption rate and yield gain sensitivity analysis for participatory plant
breeding (PPB) and conventional plant breeding (CPB) programs. B-C Ratio =
benefit–cost ratio; IRR = internal rate of return; GEB = gross economic benefit.
Status
PPB Program
CPB Program
GEB
GEB
B-C
B-C
IRR
(million
IRR
(million
Ratio
Ratio
US$)
US$)
Benchmark a
39
46
110.7
15
19
77.6
50% of Benchmark
Adoption Rate b
19.9
43
52.5
8
14
33.8
50%of Benchmark
Adoption Rate &
Yield Gain c
10
33
24.9
4
9
14.4
38
a
Benchmark of adoption rate is 50% for Aleppo and 40% for Edlib and Raqqa for PPB and CPB, for
Hama it is 70% for PPB and 50% for CPB. Benchmark of yield gain is 24% for Aleppo, 20% for
Edlib, 45% for Hama, and 31% for Raqqa.
b
Adoption rate is 25% for Aleppo and 20% for Edlib and Raqqa for PPB and CPB, for Hama it is 35%
for PPB and 20% for CPB.
c
Adoption rate is as in b, yield gain is 12% for Aleppo and 10% for Edlib, 22.5% for Hama and 15.5%
for Raqqa.
7.2 Poverty Alleviation
In 1990 more than 1.2 billion people – 28% of the developing world’s population
– lived in extreme poverty. By 2002, the proportion had decreased to 19%. However,
poverty rates in Western Asia and Northern Africa remained almost unchanged
between 1990 and 2002 (United Nations 2006). The majority of the poor live in rural
areas, and agriculture is their main occupation. Indeed, most of the rural poor are
small-scale and marginal farmers.
Poverty alleviation is now one of the Millennium Development Goals. This does
not simply require short-term relief and the satisfaction of basic human needs, but
also the development of strategies that will increase the long-term productive
potential, and therefore the incomes, of the rural poor (D’Silva 1992:1-2).
To study the effect that the programs considered here have had with regard to
relieving the poverty of participant and non-participant farmers, the surveyed farmers
were divided into three groups depending on their level of income: (1) those living
above the poverty line (farmers with incomes of more than US$2 per person per day);
(2) those living in moderate poverty (farmers with incomes of between US$1 and
US$2 per person per day) and (3) those living under critical poverty (farmers with an
income of less than US$1 per person per day).
The results show that the average income of the 38% of the non-participant
farmers whose income was less than US$1 per day (Table 23) was US$0.44 per
person per day. Only 25% of the participant farmers fell into this “critical poverty”
group, however. Moreover, the average income of participant farmers earning less
than US$1 per day (US$0.75 per person per day) was higher than that of the nonparticipant farmers.
Twenty-two percent of the non-participant farmers were in the “moderate
poverty” group, earning on average US$1.35, while 40% of them lived above the
poverty line and earned, on average, US$5.67 per day (Table 23). In the case of
participant farmers, 25% fell into the “critical poverty” group, while 15% were in the
“moderate poverty” group, earning an average of US$1.36 per day. Finally, 60% of
them earned, on average, US$9.7 per person per day.
In other words, the majority of the participant farmers generated incomes that
were above the poverty line, earning more than US$2 per person per day, while the
majority of the non-participant farmers earned incomes of less than US$2 per person
per day (Table 23).
Table 23. Income distribution of participant and non-participant farmers, according to
poverty category.
39
Non-participant
Participant
Farmers
Farmers
Poverty Category
Percentage of
Average Per
Average Per
Percentage of
(Per Capita
Farmers in Poverty
Capita
Capita
Farmers in Poverty
Income/Day)
Category
Income/Day (US$)
Category
Income/Day (US$)
US$ < 1
38
0.44
25
0.75
US$ 1 – 2
22
1.35
15
1.36
US$ > 2
40
5.67
60
9.7
Two factors caused the incomes of the participant farmers to be higher than those
of the non-participant farmers: (1) the yield gains that resulted from them adopting
the new varieties and (2) the higher prices obtained for the grain of the new varieties
(from which participants benefited as they sold this grain as seed during the early
years of adoption). The effect of the second factor will be limited over time, and will
be lost once farmers start to produce their own seeds or once sufficient amounts of the
seed of new varieties is available to meet demand. The yield advantage gained is,
however, likely to ensure that the incomes of participant farmers remain stable.
Another factor that could be responsible for this higher income is that the farmers
who chose to participate in the program were already wealthier than the nonparticipant farmers (i.e. before the program began). There is no baseline socioeconomic data that can help to verify this possibility.
7.3 Intellectual Benefits
As a result of their participation, farmers may gain intellectual benefits, as well
as economic benefits. This is because the knowledge gained by farmers as a result of
participating in the program will improve their ability to make decisions regarding
varietal testing and selection. Individual interviews with farmers were used to assess
the impact that the program had in terms of human and social capital. Changes in
participants’ knowledge and understanding of the trials were assessed through a
questionnaire, as were their changes in their interactions with researchers and other
farmers.
About 81% of the farmers interviewed stated that, even if the PPB research ends,
they would continue practicing what they have learned about variety selection. They
also assured us that they would protect the seeds of the new varieties already
developed, and would keep working with other farmers to find and plant good
varieties. Up to 31% of the farmers interviewed said that PPB had enhanced their
knowledge of barley production, as well as their knowledge of agriculture in general.
Nearly 44% of them said that they had gained new experience in variety selection
through their participation in the evaluation and selection process.
Working with researchers is also assumed to improve the human capital of
participating farmers. If work is done in groups, or if information sharing is
encouraged, then social capital (defined as the ability of farmers to work together and
share information) should increase as well. Twenty-seven percent of the farmers
interviewed stated that their knowledge had increased as a result of their interaction
with breeders and technicians – which means that there was an improvement in the
40
human capital of participating farmers. Moreover, 21% stated that their knowledge
had increased as a result of their interaction with other farmers, which shows an
increase in social capital.
The PPB program had a positive impact on the economic status and the
livelihood of 65% of the participant farmers. The other 35% stated that there had, as
yet, been no change in either their economic status or in their livelihood as a result of
being involved in the program. However, most of these farmers are in those areas
where PPB has not yet reached its final stage.
When asked about the distribution of the economic benefits of the program, only
7% of the farmers interviewed believed that those farmers who selected the new
varieties should keep the benefits for themselves. The other 93% believed that
benefits should be distributed at the community level.
8. Conclusions
For the last ten years, a large number of barley producers have been involved in
the participatory plant breeding (PPB) program. When the program began, several
trials were conducted in nine villages. Now the program has expanded to include 25
villages in seven provinces, representing about 90% of Syria’s barley-producing area.
Evaluation of the adoption of barley varieties produced using conventional plant
breeding (CPB) showed that farmers in marginal environments such as Hassakeh,
Deraa and Sweida did not adopt varieties derived from the conventional breeding
program. And even in less marginal environments the adoption rates of CPB varieties
(which ranged from 5% to 33%) were lower than those of PPB varieties (which
ranged from 12% and 43%).
The adoption ceilings in Hama, Aleppo, Edlib and Raqqa were similar for the
two programs and ranged between 40% and 50%. The exception was Hama, where
the adoption ceiling was 50% for the CPB varieties and 70% for the PPB varieties.
Compared with the PPB varieties, the CPB varieties took 5 to 7 years longer to reach
the same ceiling. This reflects the speed of adoption and indicates that PPB varieties
are adopted faster than the CPB varieties.
The impact at farm level is represented by the effect of the selected varieties on
crop yield and cost of production. In all locations, farmers who had adopted the PPB
varieties experienced yield gains ranging from 15% to 89%. They also incurred
higher production costs due to higher seed prices, harvesting costs and post-harvest
costs in addition to the opportunity cost they had bear for the time they spent
participating in the program. However, the effect of higher yields offset the effect of
higher costs and generated higher returns. The net returns obtained by the participant
farmers adopting PPB varieties were higher than those obtained by the nonparticipant farmers who grew landrace varieties.
Market-level analysis showed that the amount invested in research in the CPB
program was almost twice as much as that invested in research in the PPB program.
This is because two institutions invested in the CPB program (ICARDA and NARS),
while only ICARDA invested in the PPB program. Gross economic benefits to
society resulting from the adoption of participatory varieties were US$110.6 million;
the figure for the adoption of conventional varieties was lower: US$77.6 million. This
41
means that adopting PPB varieties will generate around US$33 million higher net
returns, in less time.
The benefit–cost ratio for the PPB program was 39 compared with 15 for the
CPB program. The internal rate of return (IRR) for the PPB program was 46%, while
that for the CPB program was 19%. The annual research expenditures for the PPB
program were equal to US$122,000 and to US$251,000 for the CPB program.
Meanwhile, the annual economic benefit was US$4.8 million for the PPB program
and US$2.5 million for the CPB program.
Sensitivity analyses showed that the benefit–cost ratio and IRR were still
favorable for each program, even if only half the estimated adoption rate was
achieved. However, in the case where only half the estimated yield gain was
achieved, in combination with only half of the estimated adoption rate, the IRR for
CPB varieties (9%) became inefficient when compared with the commercial interest
rate of 10%.
The study showed that the benefits gained by farmers were not only economic:
some of the farmers interviewed stated that their experience and knowledge had
increased as a result of their interaction with breeders and technicians; this meant that
there was an improvement in the participating farmers’ human capital. These farmers
also stated that their experience and knowledge increased due to their interaction with
other farmers. This meant that their participation in the program also led to an
increase in social capital.
The selection of varieties that are suitable for farmers’ specific agro-climatic
conditions and preferences is not enough in itself, however. It is also important to
ensure that the seed of the selected varieties is available to farmers. One way to
achieve this is through the development of community biased seed production system.
This requires training of farmers on the production of quality seeds and provision of
mobile seed cleaning machine (may be through micro finance and credit schemes). A
regulatory framework for the informal seed production is needed as seed
multiplication of improved varieties is done by the formal seed system in Syria.
There is also a need for the extension services to be more involved, so that they can
take up the new varieties, and enhance their transfer to other users in similar zones.
Developing varieties which are better adapted to the specific conditions farmers
face is also expected to reduce farmers’ vulnerability to climate change, as the
varieties’ favorable traits (such as greater drought tolerance and heat resistance) will
help stabilize yields. This will have an important impact in reducing the risk
associated with rainfed farming and will thus stabilize farmers’ incomes.
International and national organizations should continue their research
investment in PPB programs. More research is needed to develop effective ways of
scaling-up and scaling-out the approaches used in PPB programs. In addition, policy
makers and development projects should invest more in PPB, in light of both its
effectiveness in addressing the needs of local communities and its high pay off.
42
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Shideed, K.H. 2006. Theoretical Framework for Assessing Adoption and Impact of
improved Technologies. Pages 1-29 in Adoption and Impact Assessment of Improved
Technologies in Crop and Livestock Production Systems in the WANA Region
(K.H.,Shideed and M. El-Mourid). International Center for Agricultural Research in
the Dry Areas (ICARDA), Aleppo, Syria.
United Nations. 2006. The Millennium Development Goals Report. New York, pp. 46.
Wehrheim P. 2003. agricultural and Food Pinolicies in Syria: Financial Transfers and
Fiscal Flows. Chapter 4 in Syrian Agriculture at the Crossroads (Technical
44
Cooperation Department). FAO Agriculture Policy and Economic Development
Series 8.
Zeigler, R.S. 1996. Implementing farmer participatory plant breeding: a research
management perspective. Pages 37-41 in New Frontiers in Participatory Research and
Gender Analysis. Proceedings of an International Seminar on Participatory Research
and Gender Analysis for Technology Development. CIAT, Cali, Colombia.
45
Appendix A
Table A1. Barley production costs and returns in Aleppo
Item
INPUTS
Operations
Plowing
Sowing
Seed Cleaning
&Treatment
Fertilizer
Application
Pesticide &
Herbicide Application
Harvesting
Post Harvesting
Treatment
Packaging
Subtotal
Material Inputs (kg)
Seeds
Fertilizer: Nitrogen
Phosphorus
Seed Treatment
Pesticide &
Herbicide
Bags
Subtotal
Total Expenses
RETURNS
Yield (kg/ha)
Grain Value
Farmers’ Income
(from Grain & Straw)
Net Return
Benefit / Cost
Non-Participant
Farmer
All Farmers
Evaluator Farmer Participant Farmer
Total Costs Percent Total Costs Percent Total Costs Percent Total Costs Percent
SL/Hectare %
SL/Hectare %
SL/Hectare %
SL/Hectare %
675.0
187.5
12.8
3.6
640.0
150.0
12.0
2.8
802.5
131.3
13.5
2.2
724.7
150.0
13.0
2.7
86.3
1.6
57.0
1.1
61.3
1.0
65.9
1.2
56.3
1.1
40.0
0.7
74.4
1.3
60.0
1.1
0.0
975.0
0.0
18.5
60.0
670.0
1.1
12.5
56.4
715.6
0.9
12.0
44.1
763.2
0.8
13.7
18.8
318.5
2317.3
0.4
6.1
44.1
51.0
102.4
1770.4
1.0
1.9
33.1
16.3
278.8
2136.4
0.3
4.7
36.0
27.1
236.2
2071.2
1525.0
587.5
29.0
11.2
1405.0
770.0
26.3
14.4
1602.5
916.9
27.0
15.4
1526.2
796.2
0.5
4.2
37.1
0.0
27.3
14.3
350.0
0.0
6.7
0.0
1040.0
78.0
19.5
1.5
714.1
46.9
12.0
0.8
724.3
45.0
13.0
0.8
0.0
0.0
477.8
9.1
2940.3 55.9
5257.5 100.0
130.0
153.6
3576.6
5347.0
2.4
2.9
66.9
100.0
106.3
418.1
3804.7
5941.1
1.8
7.0
64.0
100.0
65.9
354.4
3512.0
5583.2
1.2
6.3
62.9
100.0
2050.0
18512.5
1176
9382
1202.5
11013.1
1394.1
12297.9
21725.0
16467.5
4.1
12680
7333.0
2.4
16772.9
10831.8
2.8
15448.5
9865.3
2.8
46
Table A2. Barley production costs and returns in Edlib
Item
INPUTS
Operations
Plowing
Sowing
Seed Cleaning
&Treatment
Fertilizer Application
Pesticide &
Herbicide Application
Harvesting
Post Harvesting
Treatment
Packing
Subtotal
Material Inputs (kg)
Seeds
Fertilizer: Nitrogen
Phosphorus
Seed Treatment
Pesticide &
Herbicide
Bags
Subtotal
Total Expenses
RETURNS
Yield (kg/ha)
Grain Value
Farmers’ Income
(from Grain & Straw)
Net Return
Benefit / Cost
Non-Participant
All Farmers
Farmer
Evaluator Farmer Participant Farmer
Total Costs Percent Total Costs Percent Total Costs Percent Total Costs Percent
SL/Hectare %
SL/Hectare %
SL/Hectare %
SL/Hectare %
1128.6
142.8
12.0
1.5
858.3
250.0
8.3
2.4
875.0
306.3
8.4
2.9
954.8
304.8
9.4
3.0
92.5
191.4
1.0
2.0
119.2
128.3
1.2
1.2
77.5
151.9
0.7
1.5
94.4
158.3
0.9
1.6
90.0
1321.4
1.0
14.0
207.6
1849.2
2.0
17.9
196.9
1724.4
1.9
16.5
158.3
1625.7
1.6
16.0
223.5
312.8
3503.0
2.4
3.3
37.2
138.3
535.0
4086.0
1.3
5.2
39.5
103.1
328.1
3763.1
1.0
3.1
36.0
153.3
382.1
3831.8
1.5
3.8
37.8
2304.3
1624.0
999.6
202.9
24.5
17.2
10.6
2.2
2194.2
1690.0
947.1
358.3
21.2
16.3
9.1
3.5
2708.8
1864.1
1073.8
335.6
25.9
17.8
10.3
3.2
2426.9
1734.3
1012.9
297.9
23.9
17.1
10.0
2.9
1.4
131.1
655.0
7.0
5916.9 62.8
9419.9 100.0
487.5
591.7
6268.8
10354.7
4.7
5.7
60.5
100.0
249.4
457.5
6689.1
10452.2
2.4
4.4
64.0
100.0
278.0
561.7
6311.6
10143.3
2.7
5.5
62.2
100.0
2509.0
23433.0
2625.0
26300.0
2549.0
24709.0
2550.0
24738.0
25147.0
15727.1
2.7
31696.0
21341.3
3.1
29353.0
18900.8
2.8
28620.0
18476.7
2.8
47
Table A3. Barley production costs and returns in Hama
Item
INPUTS
Operations
Plowing
Sowing
Seed Cleaning
&Treatment
Fertilizer Application
Pesticide &
Herbicide Application
Harvesting
Post Harvesting
Treatment
Packing
Subtotal
Material Inputs (kg)
Seeds
Fertilizer: Nitrogen
Phosphorus
Seed Treatment
Pesticide &
Herbicide
Bags
Subtotal
Total Expenses
RETURNS
Yield (kg/ha)
Grain Value
Farmers’ Income
(from Grain & Straw)
Net Return
Benefit / Cost
Non-Participant
Farmer
Evaluator Farmer Participant Farmer
All Farmers
Total Costs Percent Total Costs Percent Total Costs Percent Total Costs Percent
SL/Hectare %
SL/Hectare %
SL/Hectare %
SL/Hectare %
1406.0
208.0
19.6
2.9
1450.0
325.0
19.0
4.3
1346.0
222.0
18.9
3.1
1387.0
240.4
18.6
3.2
94.0
109.0
1.3
1.5
125.0
150.0
1.6
2.0
120.0
65.0
1.7
0.9
113.2
96.9
1.5
1.3
108.0
1531.0
1.5
21.3
192.0
1833.0
2.5
24.1
112.0
1146.0
1.6
16.1
128.9
1413.0
1.7
18.9
6.0
101.0
3563.0
0.1
1.4
49.6
0.0
463.0
4538.0
0.0
6.1
59.6
19.0
415.0
3445.0
0.3
5.8
48.3
10.9
332.6
3722.9
0.1
4.5
49.8
1387.5
817.5
758.0
141.0
19.3
11.4
10.5
2.0
1683.3
103.3
733.0
0.0
22.1
1.4
9.6
0.0
1602.0
785.0
458.0
75.0
22.5
11.0
6.4
1.1
1562.5
853.8
608.1
78.1
20.9
11.4
8.1
1.0
3.4
246.0
276.0
3.8
3626.0 50.4
7189.0 100.0
163.0
396.0
3078.6
7616.6
2.1
5.2
40.4
100.0
158.0
604.0
3682.0
7127.0
2.2
8.5
51.7
100.0
185.2
460.2
3747.9
7470.8
2.5
6.2
50.2
100.0
1523.8
14309.4
1916.6
17583.3
2008.0
19407.0
1852.6
17560.7
18171.9
10982.9
2.53
21286.7
13670.1
2.79
21983
14856.0
3.08
20763.4
13292.6
2.78
48
Table A4. Barley production costs and returns in Hassakeh
Item
INPUTS
Operations
Plowing
Sowing
Seed Cleaning
&Treatment
Fertilizer Application
Pesticide &
Herbicide Application
Harvesting
Post Harvesting
Treatment
Packing
Subtotal
Material Inputs (kg)
Seeds
Fertilizer: Nitrogen
Phosphorus
Seed Treatment
Pesticide &
Herbicide
Bags
Subtotal
Total Expenses
RETURNS
Yield (kg/ha)
Grain Value
Farmers’ Income
(from Grain &
Straw).
Net Return
Benefit / Cost
Non-Participant
All Farmers
Farmer
Evaluator Farmer Participant Farmer
Total Costs Percent Total Costs Percent Total Costs Percent Total Costs Percent
SL/Hectare %
SL/Hectare %
SL/Hectare %
SL/Hectare %
600.0
308.3
16.0
8.2
733.0
275.0
16.0
6.0
587.5
287.5
14.3
7.0
635
290
15.3
7.0
76.7
13.3
2.0
0.4
65.0
41.7
1.4
0.9
47.5
37.5
1.2
0.9
61.5
31.5
1.5
0.8
0.0
520.0
0.0
13.8
0.0
753.3
0.0
16.4
0.0
672.5
0.0
16.4
0
651
0.0
15.7
13.3
0.0
1531.7
0.4
0.0
40.8
0.0
0.0
1868.0
0.0
0.0
40.7
17.5
0.0
1650.0
0.4
0.0
40.2
11
0
1680.0
0.3
0.0
40.5
1625.8
158.3
0.0
70.0
43.3
4.2
0.0
1.9
1570.8
400.0
0.0
90.0
34.3
8.7
0.0
2.0
1593.1
325.0
0.0
51.3
38.8
7.9
0.0
1.2
1596.2
297.5
0.0
68.5
38.5
7.2
0.0
1.7
0.0
0.0
656.7 14.3
2717.5 59.3
4585.5 100.0
0.0
483.8
2453.1
4103.2
0.0
11.8
59.8
100.0
0.0
502.3
2464.5
4144.5
0.0
12.1
59.5
100.0
0.0
0.0
372.5
9.9
2226.7 59.2
3758.4 100.0
750
7600.0
1385
12726.7
956.3
9740.6
1023.0
9994.3
10348.3
6590.0
2.75
14060.0
9474.5
3.07
10911.9
6808.8
2.66
11687.3
7542.8
2.82
49
Table A5. Barley production costs and returns in Raqqa
Item
INPUTS
Operations
Plowing
Sowing
Seed Cleaning
&Treatment
Fertilizer Application
Pesticide & Herbicide
Application
Harvesting
Post Harvesting
Treatment
Packing
Subtotal
Material Inputs (kg)
Seeds
Fertilizer: Nitrogen
Phosphorus
Seed Treatment
Pesticide & Herbicide
Bags
Subtotal
Total Expenses
RETURNS
Yield (kg/ha)
Grain Value
Farmers’ Income
(from Grain & Straw)
Net Return
Benefit / Cost
Non-Participant
All Farmers
Farmer
Evaluator Farmer Participant Farmer
Total
Costs
Percent Total Costs Percent Total Costs Percent Total Costs Percent
SL/Hectare % SL/Hectare %
SL/Hectare %
SL/Hectare %
475.0
178.3
8.3
3.1
450.0
150.0
9.3
3.1
619.2
169.2
11.6
3.2
561.9
170.0
10.4
3.1
48.3
62.5
0.8
1.1
50.0
12.5
1.0
0.3
51.5
23.5
1.0
0.4
50.5
33.6
0.9
0.6
124.6
834.5
2.2
14.5
0.0
728.0
0.0
15.1
20.3
919.7
0.4
17.2
48.2
877.1
0.9
16.2
13.3
0.0
1736.6
0.2
0.0
30.2
0.0
0.0
1390.5
0.0
0.0
28.9
0.0
0.0
1803.5
0.0
0.0
33.8
3.8
0.0
1745.1
0.1
0.0
32.3
1757.5 30.6
901.7 15.7
641.7 11.2
148.3
2.6
252.9
4.4
308.3
5.4
4010.4 69.8
5747.0 100.0
1875.0
725.0
625.0
0.0
0.0
200.0
3425.0
4815.5
38.9
15.1
13.0
0.0
0.0
4.2
71.1
100.0
1739.2
676.0
470.2
120.4
41.2
489.6
3536.6
5340.1
32.6
12.7
8.8
2.3
0.8
9.2
66.2
100.0
1757.4
745.1
533.9
116.9
97.8
410.2
3661.3
5406.4
32.5
13.8
9.9
2.2
1.8
7.6
67.7
100.0
1108.0
10428.0
1150.0
10912.5
1307.0
12883.1
1242
11994
12661.0
6914.0
2.2
12727.5
7912.0
2.6
15524.3
10184.2
2.9
14440
9033.6
2.7
50
Table A6. Barley production costs and returns in Deraa
Item
INPUTS
Operations
Plowing
Sowing
Seed Cleaning
&Treatment
Fertilizer Application
Pesticide &
Herbicide Application
Harvesting
Post Harvesting
Treatment
Packing
Subtotal
Material Inputs (kg)
Seeds
Fertilizer: Nitrogen
Phosphorus
Seed Treatment
Pesticide &
Herbicide
Bags
Subtotal
Total Expenses
RETURNS
Yield (kg/ha)
Grain Value
Farmers’ Income
(from Grain & Straw)
Net Return
Benefit / Cost
Non-Participant
Farmer
Evaluator Farmer Participant Farmer All Farmers
Total Costs Percent Total Costs Percent Total Costs Percent Total Costs Percent
SL/Hectare %
SL/Hectare %
SL/Hectare %
SL/Hectare %
720
130
23.0
4.2
566.7
116.7
26.6
5.5
633.3
116.7
30.6
5.6
654.5
122.7
26.6
5.0
40
30
1.3
1.0
16.7
0.0
0.8
0.0
25.0
50.0
1.2
2.4
29.5
27.3
1.2
1.1
18
600
0.6
19.2
0.0
833.3
0.0
39.1
71.5
0.0
3.5
0.0
30.9
500.0
1.3
20.3
0
0
1538
0.0
0.0
49.1
0.0
0.0
1533.3
0.0
0.0
72.0
0.0
0.0
896.5
0.0
0.0
43.3
0.0
0.0
1365.0
0.0
0.0
55.5
888
120
170
26
28.3
3.8
5.4
0.8
513.3
0.0
0.0
40.0
24.1
0.0
0.0
1.9
616.7
266.7
150.0
6.7
29.8
12.9
7.2
0.3
711.8
54.5
77.3
24.5
29.0
2.2
3.1
1.0
6.7
210
180
5.7
1594.0 50.9
3132.0 100.0
0.0
0.0
43.3
2.0
596.7 28.0
2130.0 100.0
133.0
6.4
0.0
0.0
1173.0 56.7
2069.5 100.0
131.8
5.4
93.6
3.8
1093.6 44.5
2458.6 100.0
450
4500
107
1173.3
0.0
0.0
234
2360
9550.0
6418.0
2.0
6756.7
4626.7
2.2
5000.0
2930.5
1.4
7547.0
5088.4
2.1
51
Table A7. Barley production costs and returns in Sweida
Item
INPUTS
Operations
Plowing
Sowing
Seed Cleaning
&Treatment
Fertilizer Application
Pesticide &
Herbicide Application
Harvesting
Post Harvesting
Treatment
Packing
Subtotal
Material Inputs (kg)
Seeds
Fertilizer: Nitrogen
Phosphorus
Seed Treatment
Pesticide &
Herbicide
Bags
Subtotal
Total Expenses
RETURNS
Yield (kg/ha)
Grain Value
Farmers’ Income
(from Grain &
Straw).
Net Return
Benefit / Cost
Non-Participant
Farmer
All Farmers
Evaluator Farmer Participant Farmer
Total Costs Percent Total Costs Percent Total Costs Percent Total Costs Percent
SL/Hectare %
SL/Hectare %
SL/Hectare %
SL/Hectare %
790
84
22.9
2.4
690.0
100.0
16.5
2.4
500
106
11.8
2.5
660.0
96.7
16.7
2.4
13
0
0.4
0.0
16.0
0.0
0.4
0.0
19
0
0.4
0.0
16.0
0.0
0.4
0.0
0
1700
0.0
49.2
50.0
2500.0
1.2
59.7
0
2700
0.0
63.8
16.7
2300.0
0.4
58.1
0
108
2695.0
0.0
3.1
78.0
16.0
89.0
3461.0
0.4
2.1
82.7
20
182
3527.0
0.5
4.3
83.4
12.0
126.3
3227.7
470
0
0
156
13.6
0.0
0.0
4.5
488.0
0.0
0.0
16.0
11.7
0.0
0.0
0.4
438
0
0
18
10.4
0.0
0.0
0.4
465.3
0.0
0.0
63.3
0.3
3.2
81.6
0.0
11.8
0.0
0.0
1.6
0.0
0
136
3.9
762.0 22.0
3457 100.0
50.0
170.0
724.0
4185.0
1.2
4.1
17.3
100.0
0
248
704.0
4231
0.0
5.9
16.6
100.0
16.7
184.7
730.0
3957.7
0.4
4.7
18.4
100.0
600.0
6740.0
547.0
5404.0
814.0
8554.0
697.9
6971.3
10940.0
7483.0
3.2
10818.0
6633.0
2.6
15144.0
10913.0
3.6
11990.0
8032.3
3.0
52
Table A8. Estimated adoption rates for varieties developed through participatory plant
breeding (PPB) and conventional plant breeding (CPB) with different adoption ceilings in
four provinces
Province
Aleppo
Edlib
Hama
Raqqa
Breeding Program
CPB
PPB
CPB
PPB
CPB
PPB
CPB
PPB
Adoption Ceiling
50%
50%
40%
40%
50%
70%
40%
40%
Year
Adoption Rate Adoption Rate Adoption Rate Adoption Rate
1994
0.00
0.00
0.00
0.00
0.00
0.00
0.0
0.00
1995
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1996
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
1997
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.01
0.01
0.00
0.00
0.00
0.00
0.01
1998
0.00
0.00
1999
0.00
0.00
0.02
0.00
0.01
0.01
0.00
0.02
0.03
0.00
0.02
0.02
0.00
0.04
2000
0.00
0.00
2001
0.01
0.00
0.05
0.00
0.03
0.03
0.01
0.07
2002
0.01
0.01
0.08
0.00
0.05
0.06
0.01
0.13
0.11
0.01
0.09
0.11
0.02
0.19
2003
0.02
0.02
2004
0.02
0.06
0.15
0.03
0.14
0.19
0.03
0.26
2005
0.04
0.16
0.20
0.09
0.21
0.30
0.06
0.32
2006
0.06
0.31
0.25
0.20
0.28
0.42
0.09
0.36
2007
0.08
0.43
0.29
0.31
0.35
0.52
0.14
0.38
0.32
0.37
0.41
0.60
0.19
0.39
2008
0.12
0.48
2009
0.17
0.49
0.35
0.39
0.44
0.65
0.24
0.39
0.37
0.40
0.47
0.67
0.29
0.40
2010
0.22
0.50
2011
0.28
0.38
0.48
0.69
0.33
0.39
0.49
0.69
0.36
2012
0.33
0.39
0.49
0.70
0.37
2013
0.38
0.39
0.50
0.39
2014
0.41
2015
0.44
0.40
0.39
2016
0.46
0.40
2017
0.47
2018
0.48
2019
0.49
2020
0.49
2021
0.50
53
Table A9. Average production costs, yields, total and net returns and benefit–cost ratio for all
groups of farmers in seven provinces.
PROVINCE
ALEPPO
Operations
Material Inputs
Total Expense
Yield (kg/ha)
Total Returns (SL/ha)
Net Returns (SL/ha)
Benefit / Cost
EDLIB
Operations
Material Inputs
Total Expense
Yield (kg/ha)
Total Returns (SL/ha)
Net Returns (SL/ha)
Benefit / Cost
HAMA
Operations
Material Inputs
Total Expense
Yield (kg/ha)
Total Returns (SL/ha)
Net Returns (SL/ha)
Benefit / Cost
HASSAKEH
Operations
Material Inputs
Total Expense
Yield (kg/ha)
Total Returns (SL/ha)
Net Returns (SL/ha)
Benefit / Cost
RAQQA
Operations
Material Inputs
Total Expense
Yield (kg/ha)
Total Returns (SL/ha)
Net Returns (SL/ha)
Benefit / Cost
DERAA
Operations
Material Inputs
Total Expense
Yield (kg/ha)
Total Returns
Net Returns (SL/ha)
Benefit / Cost
SWEIDA
Operations
Material Inputs
Total Expense
Yield (kg/ha)
Total Returns (SL/ha)
Net Returns (SL/ha)
Benefit / Cost
Non-Participant
All Farmers
Farmer
Evaluator Farmer Participant Farmer
Total
Total
Total
Total
Costs
Percent
Costs Percent Costs
Percent
Costs Percent
SL/ha
%
SL/ha
%
SL/ha
%
SL/ha
%
2317.3
2940.3
5257.5
2050.0
21725.0
16467.5
4.1
44.1
55.9
100.0
1770.4 33.1
3576.6 66.9
5347.0 100.0
1176.0
12680.0
7333.0
2.4
2136.4
3804.7
5941.1
1202.5
16772.9
10831.8
2.8
36.0
64.0
100.0
2071.2 37.1
3512.0 62.9
5583.2 100.0
1394.1
15448.5
9865.3
2.8
3503.0
5916.9
9419.9
2509.0
25147.0
15727.1
2.7
37.2
62.8
100.0
4086.0 39.5
6268.8 60.5
10354.7 100.0
2625.0
31696.0
21341.3
3.1
3763.1
6689.1
10452.2
2549.0
29353.0
18900.8
2.8
36.0
64.0
100.0
3831.8 37.8
6311.6 62.2
10143.3 100.0
2550.0
28620.0
18476.7
2.8
3563.0
3626.0
7189.0
1523.8
18171.9
10982.9
2.5
49.6
50.4
100.0
4538.0 59.6
3078.6 40.4
7616.6 100.0
1916.6
21286.7
13670.1
2.8
3445.0
3682.0
7127.0
2008.0
21983.0
14856.0
3.1
48.3
51.7
100.0
3722.9 49.8
3747.9 50.2
7470.8 100.0
1852.6
20763.4
13292.6
2.8
1531.7
2226.7
3758.4
750.0
10348.3
6590.0
2.8
40.8
59.2
100.0
1868.0 40.7
2717.5 59.3
4585.5 100.0
1385.0
14060.0
9474.5
3.1
1650.0
2453.1
4103.2
956.3
10911.9
6808.8
2.7
40.2
59.8
100.0
1680 40.5
2464.5 59.5
4144.5 100.0
1023.0
11687.3
7542.8
2.8
1736.6
4010.4
5747.0
1108.0
12661.0
6914.0
2.2
30.2
69.8
100.0
1390.5 28.9
3425.0 71.1
4815.5 100.0
1150.0
12727.5
7912.0
2.6
1803.5
3536.6
5340.1
1307.0
15524.3
10184.2
2.9
33.8
66.2
100.0
1745.1 32.3
3661.3 67.7
5406.4 100.0
1242.0
14440.0
9033.6
2.7
1538
1594.0
3132.0
450.0
9550.0
6418.0
2.0
49.1
50.9
100.0
1533.3 72.0
596.7 28.0
2130.0 100.0
107.0
6756.7
4626.7
2.2
896.5
1173.0
2069.5
0.0
5000.0
2930.5
1.4
43.3
56.7
100.0
1365.0 55.5
1093.6 44.5
2458.6 100.0
234.0
7547.0
5088.4
2.1
2695.0
762.0
3457
600.0
10940.0
7483.0
3.2
78.0
22.0
100.0
3461.0 82.7
724.0 17.3
4185.0 100.0
547.0
10818.0
6633.0
2.6
3527.0
704.0
4231
814.0
15144.0
10913.0
3.6
83.4
16.6
100.0
3227.7 81.6
730.0 18.4
3957.7 100.0
697.9
11990.0
8032.3
3.0
54