the effects of price variability in wheat seed on farm...

The effects of price variability in wheat seed on farm organization

Hazneci, K.; Ceyhan, V.

Custos e @gronegócio on line - v. 12, n. 3 – Jul/Set - 2016. ISSN 1808-2882

www.custoseagronegocioonline.com.br

240


Recebimento dos originais: 29/03/2016

Aceitação para publicação: 07/11/2016

Kerem Hazneci (Corresponding author)

PhD in Agricultural Economics

Institution:, Ondokuz Mayıs University, Faculty of Agriculture

Adress: Ondokuz Mayıs University, Faculty of Agriculture, Department of Agricultural

Economics,

55139, Samsun /Turkey

E-mail: [email protected]

Vedat Ceyhan

PhD in Agricultural Economics

Institution:, Ondokuz Mayıs University, Faculty of Agriculture

Adress: Ondokuz Mayıs University, Faculty of Agriculture, Department of Agricultural

Economics,

55139, Samsun /Turkey

Abstract

The main objective of this study was to determine the effect of changes that may occur in seed

prices in wheat seed production inTR83 region of Turkey on farm organization. Data were

collected from 72 farms growing wheat seed by using questionnaire. Conventional economic

analysis approaches were used for the economic analysis of the sample farms. To determine

the effect of changes in seed prices on optimum plan, variable price programming method was

performed. The results of the study revealed that economic performances of large-scale farms

are better than that of small-scale farms. Supply of wheat seed was inelastic in both groups. In

the research area, supply elasticities of small and large-scale farms were 0.78 and 0.02,

respectively. The study suggests that policy makers should pay attention the supply elasticity

of wheat seed and their variation associated with farm size and ensure the security of wheat

supply by adjusting the prices based on elasticity.

Keywords: Wheat seed. Price variability. Normative supply function.

1. Introduction

Input use in agriculture is the key element in increasing the efficiency. Efficient input

use increases the crop and livestock production and quality. Seed, one of the most important

basic production inputs used in crop production, is of vital importance in terms of enhancing

the efficiency and productivity of agricultural products as well as obtaining more durable, less

expensive, competitive and high quality products. The use of high-quality seed is affected by

various reasons such as technical knowledge levels and financial conditions of farmers and

seed prices. Farmers establish a connection between the prices of seed and crop. They are

mailto:[email protected]





241

negatively affected and their demand for certified seed decreases in the periods where the

prices of seed surpass the price of product. Changes in seed price not only affect the demand

for certified seed but also the decisions of seed-producers to grow seed. Due to the

opportunity cost in the market, that grow seed farmers may tend to move towards other

agricultural products and thus the farms using seed as an input can adversely be affected

because of the increased production costs. Due to its strategic importance and extensity,

investigation on the effect of changes in wheat seed prices has the priority into the agenda.

Therefore, knowing that how the changes in seed prices affect the amount of production is of

vital importance for the policy makers.

For this reason, several studies have been conducted in different regions to make a

general evaluation of the seed sector in Turkey and in the world, to examine the seed

production and trading, to analyze seed growing and to identify the relations between contract

farming model and seed production. Almost all these studies are based upon macro level

secondary data. The studies involving farm level data are very scarce. Although there are

several studies on seed use, seed production conditions, seed marketing structure, seed

distribution and seed trading (Balcı, 1993; Usal, 1996; Akdoğan, 2005; Arısoy, 2005;

Demirtas and Keles, 2005; Acar, 2008; Yağdı et al., 2010), studies assessing the economic

performance of the seed-growing farms are limited (Kumar et al., 2000; Fert, 2004; Engiz,

2007; Zararsız, 2010). In addition, there are few studies that examine the effect of price

changes on optimum plan and income (Ceyhan, 1998; Kılıç et al., 2008). For this reason, this

study aimed to determine the effect of changes that may occur in seed prices on seed growing

and farm organization in Turkey.

2. Methodology

2.1. Research area

TR83 region (37294 km2)

which covers Amasya, Çorum, Samsun and Tokat provinces

accounts for approximately 5% of Turkey’s total surface area and constitutes 3.6% of

Turkey's population (2.72 million in 2012 census) (Figure 1). TR83 Region abounds in arable

land and crop production. The region is cut out for farming and livestock raising. When

regional gross value added is examined, the share of the agricultural sector in regional

economics in 2014 is 18.5%. This ratio is more than two-fold greater than that in Turkey's

economy. In 2011, the region ranks third in terms of agricultural employment. With respect to





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quantity and efficiency of crop production, TR83 region is placed near the top in Turkey. In

2011, the amount of crop production is 9.69 million tons which corresponds to 6.83% of

Turkey’s total crop production. Among 26 regions, TR83 region ranks fourth in grain and

other crop production, and second in fruit and vegetable production (URL 1).

Figure 1: Research area (TR83 region)

2.2. Research data

The research data collected from 72 wheat seed growing farms signed a declaration to

grow seed in Tokat, Amasya and Çorum provinces by using questionnaire in February 2014,

considering the 2012-2013 production year.

2.3. Classification of sample farmers

Since the sample farms differ in size and financial structure, they were classified based

on the preliminary results of the economic analysis by performing cluster analysis. Farmers’

profiles which reflect the management characteristics of the farmers such as education status,

and experience in seed growing, total land area which reflects the scale of a farm and

economic profitability variables which reflect the economic success of the farms were used as

the criteria in cluster analysis. Based on the results of the cluster analysis, 66 farms with lower

economic profitability, experience and education level were named as "small-scale farms" and





243

the remaining 6 farms with better qualification in terms of aforementioned criteria were

named as "large-scale farms”.

2.4. Eliciting the sensitivity of seed production to the changes in seed prices

Linear programming method was used for the determination of optimal farm

organization. Optimal farm plans were determined through a cluster analysis and established

by farm groups. The farm models developed to determine optimum farm organizations

included a total of 41 different activities (25 production, 3 transfer and 13 leasing activities).

Dairy cattle and beef cattle activities were also included in the model. The model also

involved activities of haymaking, hay purchasing, land-leasing and labor supplying. The

prices of products used in the model were the average farmyard prices which belong to 2012-

2013 production periods. Small-scale and self-consumption-oriented production activities

were excluded from the plan. The input prices were taken from the average prices reported in

the survey which belong to farmyard prices in 2012-2013 production periods.

To determine the effect of variability in wheat seed price on optimal plan, "variable-

price programming" technique was used. An optimal plan prepared according to the current

circumstances is based upon the amount of resources, input-output coefficients and net prices

used in the plan. Any change in one of these three components may also lead to a change in

the optimal plan. The advantage of variable-price programming is that it offers optimum plan

series for each price levels. Although it is possible to change the price of more than two

production activities with this method, the result is difficult to present and interpret (Candler,

1957, Heady and Candler 1973). There is no difference between parametric programming

which allows replacement of one or more limitations and "variable price" or “variable

resource” programming (Garwin, 1960; Kreko, 1968; Ignizio, 1982; Barnard and Nix, 1986).

Therefore, the concepts of parametric programming and variable price programming are used

in the same sense in the study.

Variable price programming makes use of revised simplex method in solving linear

programming model (Candler, 1957). Variable price programming method involves two

important steps. The first is to introduce the problem in an appropriate manner for variable-

price programming. Thus, it is necessary to arrange the production activities whose prices are

parameterized (modified) in two separate operations as production and sale activities.

Considering production and sale activities as a single activity may lead difficulties in





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monitoring the effects of price variation on optimal plans (Barnard and Nix, 1986). Therefore,

sale and production activities of wheat seed were separated in the study. The next step is to

make a plan for the related price levels and to ask the following question of what price change

makes other plan optimal at every turn? (Candler, 1957).

Variable price programming is widely used in agricultural management and

agricultural policy studies (Barnard and Nix, 1986). In this way, the normative supply curve

can also be obtained. Normative supply curve is used to determine how farmers should act

against the relative changes in price levels of the products.

Both the objective function and the first set of constraints were identical to a standard

linear programming formulation; gross revenues are maximized subject to a set of farm-level

constraints. The wheat seed price variable programming model was:

where E is gross farm income; c is a 1 by n vector of activity expected gross revenues; x is an

n by 1 vector of activity levels; A is the technical coefficients matrix; and b is the vector of

resource stocks.

Wheat seed price variable programming model included land, rotational constraints,

and seasonal constraints on labor, seasonal working capital, and barn and feed requirements

for a dairy herd. Activities in the model included Wheat, wheat seed, barley, sunflower, sugar

beet, onion, maize, maize seed, maize for silage, opium poppy, vetch, chickpea, tomato,

pepper, eggplant, apple, cherry, peach, walnut, grape, and dairy. Additional activities labor

hire (monthly) were also included.

When estimating the coefficients showing the relationship between the quantity and

the price of wheat, ordinary least squares method (OLS) and quadratic functional forms were

used. In model, the amount of wheat production (sales) Q (ton) was used as a dependent

variable and the price of wheat (TL/kg) was as an independent variable.

Supply elasticity that represents the relative change that will occur in the amount of

production in the face of relative change occurring in product price is used to assess the

sensitivity of price to the amount of production (Mansfield, 1985, Bronfenbrenner et al.,

1990). Supply elasticity was calculated using the following formula:





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where p represents the wheat seed price and q is the amount of demanded wheat seed. At first

price level (p) was setting in the equation and production quantity (q) was calculating. Then,

slope of the supply was calculated by taking the first derivative of the function (dq/dp).

Following, obtained values was substituted into the elasticity formula to calculate supply

elasticity (Brennan, 1965).

3. Results and Discussion

3.1. Socio-economic characteristics of the farms growing wheat seed

The total labor in man labor force unit (AWU) in small and large farms were 2.46 and

3.93, respectively. Labor capacity was larger in large-scale farms. The mean land area of

small and large-scale farms were 35.13 and 170 hectares, respectively. These values were

quite higher than that of Turkey (6.8 hectares) (URL 2). Seed-producing firms selected the

farms for signing contract considering the criteria such as specialization in field crops, having

irrigated fertile farmlands that it size was enough for 2-year crop rotation. Research results

showed that farm income increased by farm-size in the research area. Farm income per

hectare for small and large-scale farms were ₺1960 and ₺2720, respectively. Active capital

value per hectare were ₺43351 and ₺47796 for small and large-scale farm, respectively (Table

1).

Table 1: Some socio-demographic characteristics of farms and farm managers

Small farms Large farms

Mean Standard

error Mean Standard error

Farm size (ha) 35.13 2.31 170.00 19.66

Labor (AWU) 2.46 0.12 3.93 0.58

Farm Income (₺/ha) 1962.30 328.60 2715.50 766.90

Total capital (₺/ha) 43351.00 2844.70 47795.70 10058.30

Current ratio 0.62 0.14 2.33 0.51

Acid test ratio 0.85 0.21 2.14 0.49

Return on asset (%) 2.77 0.35 5.48 0.61

Return on equity (%) 2.90 0.44 6.09 0.88 1 ₺ (one Turkish lira) equaled 2.9 USD and 3.1 Euros.





246

The average current ratio of small-scale farms growing wheat seed (0.62) was lower

than that of large-scale farms (2.33). The acid-test ratios were 0.85 and 2.14, respectively.

When compared with the mean current ratio (1.27) and the mean acid-test ratio (0.52) of

agricultural sector in Turkey calculated by using last three years figures (2011-2013), it was

clear that current and acid ratio of small and large farms were larger than that of Turkey’s

average values (URL 3). Return on equity in small-scale farms was 2.90%. It’s meant that

sample farms in the research area gained a profit of ₺2.90 by using ₺100 equity. This ratio

was 6.09% for large-scale farms. The return on asset for small and large farms were 5.48%

and 2.77% respectively. Since the return on asset was lower than that of equity for sample

farms, all the sample farms covered the opportunity cost of debt (Table 1).

3.2. Effect of price variability on optimum farm organizations and supply elasticity

3.2.1. Optimum farm organization for small-scale farms

The land area allocated to wheat seed growing in the current situation increased from

10.97 hectares to 13.09 hectares in the optimal plan. Others are follows; sugar beet from 3.52

to 13.09 hectares; maize for silage from 1.64 to 3.4 hectares; vetch from 0.12 hectares to 1.7

hectares; chickpea from 0.17 hectares to 1.16 hectares and pepper from 0.15 hectares to 0.5

hectares. In spite of existing in current cropping pattern under prevailing condition, wheat

(irrigated, non-irrigated), barley (irrigated, non-irrigated), sunflower (irrigated, non-irrigated),

onion, grain corn, opium poppy, tomato, apple, cherry, peach and grapes were not included in

the optimal plan due to the fact that they did not compete with other products. Similarly,

walnut (0.5 hectares) and maize seed (1.7 hectares) were included in the optimal plan (Table

3.2).

Beef cattle breeding activity was included in the optimal plan (increased from 0.18

head to 0.28 head), whereas dairy cattle breeding was not included in the optimal plan (under

current situation 0.97 head) (Table 3.2).

If the sample farms implemented the optimum plan, gross farm would increase from

₺88 thousand to ₺193 thousand, which equaled the rate of income growth by 118%.

Regarding the gross income per hectare, it increased from ₺2510 to ₺5480. (Table 2).

Table 2: Current and optimal farm organization associated by farm scale

Small farms Large farms





247

Activities Current Condition Optimum Plan Current Condition Optimum plan

ha % ha % ha % ha %

Wheat seed 10.97 31.25 13.09 37.25 34.20 20.12 66.50 39.12

Wheat (non-irrigated) 0.49 1.39 0 0 2.78 1.64 0 0

Wheat (irrigated) 1.86 5.30 0 0 19.98 11.75 0 0

Barley (non-irrigated) 0.29 0.82 0 0 2.17 1.27 0 0

Barley (irrigated) 1.18 3.37 0 0 6.63 3.90 0 0

Sunflower (irrigated) 2.80 7.98 0 0 10.70 6.29 0 0

Sunflower (non-irrigated) 0.39 1.10 0 0 2.92 1.72 2.00 1.17

Sugar beet 3.52 10.02 13.09 37.25 15.03 8.84 0 0

Onion 7.88 22.47 0 0 36.00 21.18 66.50 39.12

Maize Seed 0 0 1.70 4.84 5.00 2.94 0 0

Maize (grain) 3.39 9.65 0 0 17.08 10.05 0 0

Maize for silage 1.64 4.67 3.40 9.68 7.42 4.36 16.00 9.41

Opium poppy 0.06 0.16 0 0 0.33 0.20 0 0

Vetch 0.12 0.33 1.70 4.84 0 0 8.00 4.71

Chickpea 0.17 0.48 1.16 3.30 1.08 0.64 8.00 4.71

Tomato 0.14 0.39 0 0 0 0 0 0

Capia pepper 0.02 0.04 0.50 1.42 0.83 0.49 1.50 0.88

Eggplant 0 0 0 0 0.83 0.49 0 0

Apple 0.10 0.28 0 0 0 0 0 0

Cherry 0.08 0.22 0 0 0.33 0.20 0 0

Peach 0.01 0.02 0 0 0 0 0 0

Walnut 0 0 0.50 1.42 6.67 3.92 1.50 0.88

Grape 0.02 0.06 0 0 0 0 0 0

Total 35.09 100 35.13 100 170 100 170 100

Dairy cattle (head) 0.97 0 0 0

Feeder cattle (head) 0.18 28.00 0 35.00

Gross income (₺) 88033.76 192583.90 548870.47 559230.80

Agricultural income (₺) 68940.27 173490.41 461637.06 471997.39

Gross farm income(₺/ha) 2505.80 5481.70 3228.60 3289.60

Agricultural income (₺/ha) 1962.30 4938.20 2715.50 2776.50

3.2.2. Sensitivity of farm plans to the price variability for small-scale farms

To be included in the optimal plan, the price of wheat seed must be at least ₺0.36/kg.

At this critical price level, wheat seed growing was included in the optimal plan with 0.05

hectare and the amount of crop production 248.78 kg and after the price level of ₺5.89/kg, due

to rotation and other constraints, it remained in the optimal plan with 16.56 hectares and the





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amount of wheat seed production 89870 kg. In this group, as the price of wheat seed

increased, the production activities of wheat (irrigated), barley (irrigated), opium poppy,

vetch, maize for silage and maize for seed decrease and some were completely substituted for

wheat seed and other production activities (Table 3.3).

When the price of wheat seed was ₺0.57, wheat growing activity (irrigated) and when

the price of wheat seed was ₺0.83, maize for seed growing activity was excluded from the

optimum plan and wheat growing was replaced by other more profitable production activities.

Barley (irrigated) and opium poppy productions were replaced by other activities when the

wheat seed price reached to ₺0.64/kg. While maize growing activity was included in the

optimum plan when the price of wheat seed was ₺0.83/kg. However, it declined after at this

price level and was excluded when wheat seed price reached ₺1.45/kg, replacing by other

production activities. Although vetch growing activity decreased to a certain level as wheat

seed price increased, it was included in the optimal plan due to the fact that feeder cattle

activity filled the barn capacity at any price level (28 head) (Table 3.3).

Therefore, the increase in wheat seed growing activity with more profitable rotation

activities lead to increase in onion and sugar beet production and ensuring them in the

optimum plan. From wheat seed price level of ₺1.45/ kg, onion growing activity was included

in the optimal plan and it’s cropping pattern increased at each price level. Sugar beet growing

activity was included in the optimal plan with the wheat price level of ₺0.36/kg (Table 3.3).

Wheat seed price did not affect the pepper production at acceptable price level since it

was relatively profitable in this farm group. However, at higher price levels that was not

possible under prevailing condition (₺5.89/kg for pepper), pepper growing activity was

excluded from the optimum plan replacing for other more profitable production. Walnut

production competed with other products at any price level of wheat seed and included in the

optimum plan using constraint areas (Table 3).





249

Table 3: Cropping patterns of small-scale farms according to various wheat seed price

levels (ha)

Activities

(ha)

Wheat seed price levels(₺/kg)

0.23 0.36 0.43 0.48 0.51 0.53 0.57 0.62 0.63 0.64 0.77 0.83 1.43 1.45 1.77 5.89

Wheat

seed 0.00 0.05 3.00 4.07 7.80 9.12

10.5

4

11.1

2

12.6

8

13.0

9

13.0

9

13.9

4

14.2

8

15.6

4

16.3

1

16.5

6

The amount of

wheat

seed (ton)

0.00 2.50 162.

70

221.

10

423.

20

495.

00

571.

90

603.

30

688.

20

710.

40

710.

40

756.

50

775.

30

848.

80

885.

20

898.

70

Onion 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.49 1.53 2.33

Sugar

beet 0.00 0.05 3.00 4.07 7.80 9.12 10.5

4

11.1

2

12.6

8

13.0

9

13.0

9

13.9

4

14.2

8

14.1

5

14.7

8

14.2

3 Wheat

(irrigated)

17.0

0

16.9

5

14.0

0

12.9

3 5.48 2.84 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Barley

(irrigated) 3.40 3.40 3.40 3.40 3.40 3.40 3.40 3.40 0.82 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Opium poppy

1.70 1.70 1.70 1.70 1.70 1.70 1.70 0.55 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Maize for silage

3.40 3.40 3.40 3.40 3.40 3.40 3.40 3.40 3.40 3.40 3.40 3.40 2.71 0.00 0.00 0.00

Vetch 1.70 1.70 1.70 1.70 1.70 1.70 1.70 1.70 1.70 1.70 1.70 1.70 1.70 1.70 0.36 0.36

Maize for

seed 1.70 1.70 1.70 1.70 1.70 1.70 1.70 1.70 1.70 1.70 1.70 0.00 0.00 0.00 0.00 0.00

Chickpea 1.16 1.16 1.16 1.16 1.16 1.16 1.16 1.16 1.16 1.16 1.16 1.16 1.16 1.16 1.16 1.16

Pepper 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.00

Walnut 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50

Feeder cattle

(head)

28.0

0

28.0

0

28.0

0

28.0

0

28.0

0

28.0

0

28.0

0

28.0

0

28.0

0

28.0

0

28.0

0

28.0

0

28.0

0

28.0

0

28.0

0

28.0

0

Gross farm

income

(₺) 1724

84

.60

1725

14

.70

1735

23

.20

1746

17

.30

1757

81

.00

1767

68

.20

1789

83

.60

1819

74

.80

1826

42

.70

1833

49

.20

1925

83

.90

1968

46

.20

2422

47

.90

2438

02

.50

2709

82

.80

6356

73

.40

Gross farm income was ₺172 thousand at ₺0.23/kg level in which wheat seed

production activity was not included in the optimum plan. With price level of ₺0.36/kg, gross

farm income increased to ₺173 thousand. After this price level, gross farm income increased

until the price of wheat seed was ₺5.89/kg and reached ₺636 thousand at this price level

(Table 3).

3.2.3. Normative supply function for small-scale farms

Limit wheat seed prices, the corresponding amount of wheat seed production and farm

incomes based on the results of the variable price programming were presented in Table 3.3.

Normative supply function of wheat seed obtained from the data for small-scale farms was

depicted in Figure 2.





250

Figure 2: Normative supply function of wheat seed in small businesses

Accordingly, normative supply function of wheat seed for small-scale farm was as

follows:

(16.778) (42.227) (20.612)

According to the estimated supply function, 83% of the changes occurring in wheat

seed production (R2 = 0.833) was explained by the changes in the price of wheat seed. The

estimated supply function was statistically significant (F = 33.423, p <0.01). Supply function

indicated that an increase in wheat seed price by ₺1 per kilogram might lead to 52933.48 kg

increase in the amount wheat seed supply. Negative intercept in the normative supply function

meant that wheat seed price per kilogram should be at least ₺0.36 for initiating wheat seed

production.

Price elasticity for small-scale farm was 0.78, indicating that increase in wheat seed

price by 1% caused an increase in the amount of wheat seed production by 0.78%. It was clear

based on the elasticity coefficient that supply of wheat seed was inelastic in small farms.

3.2.4. Optimum farm organization for large-scale farms





251

The land area allocated to wheat seed growing under current plan increased from 34.2

hectares to 66.5 hectares in the optimum plan. Others are as follows; onion from 34 to 66.5

hectares; chickpea from 1.08 hectares to 8 hectares; maize for silage from 7.42 to 16 hectares;

pepper from 0.82 hectares to 1.5 hectares. On the other hand, sunflower (non-irrigated)

cultivation area decreased from 2.92 hectares to 2 hectares and walnut from 6.67 hectares to

1.5 hectares. Wheat (irrigated, non-irrigated), barley (irrigated, non-irrigated), sunflower

(irrigated), sugar beet, corn seed, grain corn, opium poppy, eggplant and cherry which were

not included in the optimum plan due to their low level completion power. Although not

included in the current situation, vetch with its maximum land area of 8 hectares was included

in the optimal plan.

Table 4: Cropping patterns of large-scale farms according to various wheat seed price

levels (ha)

Activities

(ha)

Wheat Seed Price Levels (₺/kg)

0.34 0.35 0.41 0.44 0.47 0.57 0.58 0.79 1.14 1.19 1.32 5.42 6.10

Wheat

seed 0 21.84 29.00 29.00 54.50 62.50 66.50 66.50 73.04 74.50 78.28 79.03 79.78

The amount of

wheat seed

(ton)

0 1514.4

0

2010.7

0

2010.7

0

3778.6

0

4333.3

0

4610.6

0

4610.6

0

5063.7

0

5165.3

0

5427.1

0

5479.1

0

5531.1

0

Onion 0 0 0 0 0 0 0 0 0 1.62 1.87 4.87 4.87

Sugar beet 0 21.84 29.00 29.00 54.50 62.50 66.50 66.50 73.04 72.89 76.40 74.15 74.90

Wheat (irrigated)

80.00

58.16 51.00 51.00 0 0 0 0 0 0 0 0 0

Barley

(irrigated)

16.0

0 16.00 16.00 16.00 16.00 0 0 0 0 0 0 0 0

Opium

poppy 7.16 0 0 0 0 0 0 0 0 0 0 0 0

Sunflower

(dry)

((888(nonnoirrigated

kuru)

2.00 2. 00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00

Maize for Silage

16.00

16.00 16.00 16.00 16.00 16.00 16.00 16.00 2.93 0 0 0 0

Vetch 8.00 8.00 8.00 8.00 8.00 8.00 8.00 8.00 8.00 8.00 0.45 0.45 0.45

Corn

(seed) 8.00 8.00 8.00 8.00 8.00 8.00 0 0 0 0 0 0 0

Chickpea 8.00 8.00 8.00 8.00 8.00 8.00 8.00 8.00 8.00 8.00 8.00 8.00 8.00

Pepper 1.50 1.50 1.50 1.50 1.50 1.50 1.50 1.50 1.50 1.50 1.50 0 0

Walnut 1.50 1.50 1.50 1.50 1.50 1.50 1.50 1.50 1.50 1.50 1.50 1.50 0

Feeder

cattle (head)

35.0

0 35.00 35.00 35.00 35.00 35.00 35.00 35.00 35.00 35.00 35.00 35.00 35.00

Gross farm

income (₺)

3864

01

.90

3868

72

.90

3984

55

.40

4044

87

.30

4152

20

.30

4580

68

.10

4624

07

.10

5592

30

.80

7210

28

.50

7463

67

.60

8136

97

.20

3038

800

.00

3411

407

.00





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Beef cattle breeding, although not included in the current situation, were included in

the optimal plan (35 head completely filling the barn capacity). Dairy was not included in

optimal plan in large-scale farms.

3.2.5. Sensitivity of farm plans to the price variation for large-scale farms

To be included in the optimal plan, the price of wheat seed must be at least ₺0.35 per

kilogram. At this critical price level, wheat seed growing was included in the optimal plan

(farmland 21.84 hectares and the amount of crop production 151442.20 kg) and after the price

level of ₺6.1 per kilogram, due to rotation and other constraints, it remained in the optimal

plan with land area of 79.77 hectares and the amount of crop production 553106.30 kg (Table

4).

As in small-scale farms, as the price of wheat seed increased, the production activities

of wheat (irrigated), barley (irrigated) opium poppy, vetch, maize for silage and maize for

seed decreased and some are completely substituted for wheat seed and other production

activities. When the price of wheat seed was ₺0.47, wheat growing activity (irrigated) and

when the price of wheat seed was ₺0.58, maize growing activity for seed was excluded from

the optimum plan and wheat growing was replaced by other more profitable production

activities. Barley (irrigated) and opium poppy productions were replaced by other activities

when the wheat seed price reaches to ₺0.57 and ₺0.35 per kilogram, respectively. While maize

growing activity was included in the optimum plan when the price of wheat seed was ₺0.79

per kilogram, declined after at this price level and was excluded when wheat seed price

reached ₺1.19 per kilogram, replacing by other production activities. Although vetch growing

activity decreased to a certain level as wheat seed price increased, it was included in the

optimal plan due to the fact that feeder cattle activity filled the barn capacity at any price

level (35 head) (Table 4).

Therefore, the increase in wheat seed growing activity with more profitable rotation

activities lead to increase in onion and sugar beet production and ensuring them in the

optimum plan. From wheat seed price level of ₺1.39 per kilogram, onion growing activity was

included in the optimal plan and its production area increased at each price level. Sugar beet

growing activity was included in the optimal plan with the wheat price level of ₺0.35 per

kilogram (Table 4).





253

Wheat seed price did not affect the pepper and walnut production at acceptable price

level since it was relatively profitable in this farm group. However, at the price levels of ₺6.1

per kilogram for walnut and ₺5.42 per kilogram for pepper, pepper growing activity was

excluded from the optimum plan and replaced for other more profitable production (Table

3.4).

Gross farm income was ₺386 thousand at the price level of ₺0.34 per kilogram. With

price level of ₺0.35/ kg, gross farm income increased to ₺387 thousand. After this price level,

gross farm income increased until the price of wheat seed was ₺6.10 per kilogram and reached

₺3.41million (Table 4).

3.2.6. Normative supply function for large-scale farms

Limit wheat seed prices, the corresponding amount of wheat seed production and farm

incomes based on the results of the variable price programming were presented in Table 3.4.

Normative supply function of wheat seed obtained from the data for large-scale farms was

depicted in Figure 3.2.

Accordingly, normative supply function of wheat seed for large-scale farm was as

follows:

Q = -495.240 + 2 2145.548 P -1067.992 P2

+ u

(168.024) (496.001) (300.985)

Based on the results of the estimated supply function, 83% of the changes occurring in

wheat seed production (R2 = 0.827) was explained by the changes in the price of wheat seed.

The estimated supply function was statistically significant (F = 24.929, p <0.01). Supply

function showed that an increase of ₺1 per kilogram in wheat seed price led to 9562.29 kg

increase in the amount wheat seed supply. Negative intercept in the normative supply function

meant that wheat seed price per kilogram should be at least ₺0.35 for initiating wheat seed

production.

Price elasticity for small-scale farm was 0.02, indicating that increase in wheat seed

price by 1% caused an increase in the amount of wheat seed production by 0.02%. It was clear

based on the elasticity coefficient that supply of wheat seed was inelastic in large farms.





254

Figure 3: Normative supply function of wheat seed for large-scale farms

4. Conclusions and recommendations

It was clear from the research findings that large-scale farms had larger farmland

comparing to typical Turkish farms and they were innovative and more equipped with

agricultural machinery than rest. The study results also revealed that capital structures of

large-scale farms were strong. The study results also showed that when the farms growing

wheat seed turned from the current situation into the optimal plan, their gross farm income

and agricultural income were increased. In both groups, supply of wheat seed is inelastic.

Study suggests that decision-makers should consider the price elasticity of supply

when they develop support policy. Somehow, considering seed price supply elasticity may

positively contribute to ensure security of wheat supply.

To achieve the desired benefits with the contract farming model in the sample farms,

farmers should be more organized than past to satisfy the benefits of contract farming.

Moreover, to enhance the contract production model, farmers should become organized with

marketing cooperatives that may create pressure on the market. By this way, seed production

that matters security food supply security can be operated more effectively in terms of

farming techniques. The most important factor in ensuring food security is the amount of





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agricultural production per capita. This is also realized with seed which is a basic input in

production. Ensuring food security can be achieved by supporting the farms in the basic input

and by establishing the balance between production-consumption chains. In this respect,

strategic significance of seed growing in agricultural production should not be ignored.

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