1 COMPARATIVE ECONOMICS OF FARM LEVEL ORGANIC AND CONVENTIONAL SESAME (Sesamum indicum L.) PRODUCTION IN NASARAWA STATE, NIGERIA BY UMAR, HARUNA SULEIMAN PG/M.Sc/07/42731 DEPARTMENT OF AGRICULTURAL ECONOMICS, UNIVERSITY OF NIGERIA, NSUKKA JULY, 2010
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1
COMPARATIVE ECONOMICS OF FARM LEVEL ORGANIC AND
CONVENTIONAL SESAME (Sesamum indicum L.) PRODUCTION IN
NASARAWA STATE, NIGERIA
BY
UMAR, HARUNA SULEIMAN
PG/M.Sc/07/42731
DEPARTMENT OF AGRICULTURAL ECONOMICS,
UNIVERSITY OF NIGERIA, NSUKKA
JULY, 2010
2
COMPARATIVE ECONOMICS OF FARM LEVEL ORGANIC AND
CONVENTIONAL SESAME (Sesamum indicum L.) PRODUCTION IN
NASARAWA STATE, NIGERIA.
BY
UMAR, HARUNA SULEIMAN
PG/M.Sc/07/42731
A DISSERTATION SUBMITTED TO THE DEPARMENT OF AGRICULTURAL
ECONOMICS, UNIVERSITY OF NIGERIA, NSUKKA IN PARTIAL
FULFILLMENT OF THE REQUIREMENTS FOR THE AWARD OFTHE
DEGREE OF MASTERS OF SCIENCE (M.Sc) IN AGRICULTURAL
ECONOMICS
JULY, 2010
3
CERTIFICATION
UMAR, Haruna Suleiman, a postgraduate student in the Department of Agricultural
Economics with registration number PG/M.Sc/07/42731 has satisfactorily completed the
requirements for the award of Degree of Masters of Science (M.Sc) in Agricultural
Economics.
The work in this thesis is original and has not been submitted in part or in full for any
other degree or diploma of this or any other University.
------------------------------------ -------------------------------- Prof. C. U. Okoye Prof. E. C. Nwagbo (Supervisor) (Head of Department)
4
DEDICATION This work is dedicated to my mum, Hassana Suleiman and daughter, Ramatu Haruna.
5
ACKNOWLEDGEMENTS I wish to thank Almighty Allah for making this programme a reality. I am particularly
grateful to my supervisor, Prof. C. O. Okoye, for his contributions and guidance which
led to the completion of this work. My appreciation also goes to Head of Department,
Prof. E.C. Nwagbo, PG Seminar Coordinator, Dr. A. A. Enette and all other lecturers of
the department for their contributions to this work.
I wish to acknowledge with profound gratitude the assistance and support of my
family and friends. May Allah reward you abundantly.
To my class mates, I sincerely appreciate your efforts in creating a conducive
atmosphere for studied together in peace and harmony.
6
TABLE OF CONTENTS
Title page - - - - - - - - - i
Certification - - - - - - - - - ii
Dedication - - - - - - - - - iii
Acknowledgement - - - - - - - - iv
Table of contents - - - - - - - - v
List of Tables - - - - - - - - viii
Abstract - - - - - - - - - x
CHAPTER ONE: INTRODUCTION
1.1 Background of the Study - - - - - - 1
1.2 Problem Statement - - - - - - - 5
1.3 Objectives of the Study - - - - - - 8
1.4 Hypotheses of the Study - - - - - - 9
1.5 Justification of the Study - - - - - - 9
CHAPTER TWO: LITERATURE REVIEW
2.1 Concept of Organic and Conventional Crop Production Systems - 10
2.2 Organic Crop Production Practices and Principles - - - 10
These were estimated for both organic and conventional farms.
3.4.3 Gross margin analysis
Gm = G1 – TVC
Where;
Gm = gross margin (N/ha)
GI = gross income (N/ha)
47
TVC = total variable cost (N/ha) which include:
Seeds (N/kg); labour (N/man hour); fertilizers (animal dung or NPK/Urea) (N/kg) and
pesticides (natural or synthetic) (N/lt).
This was estimated for both organic and conventional farms.
3.4.4 Student t-test (for testing hypothesis i)
Where,
gX = mean of total factor productivity of organic sesame crop production
cX = mean of total factor productivity of conventional sesame production.
2cS = variance of TFP in conventional sesame production 2gS = variance of TFP in organic sesame production
ng = number of respondents (organic farmers)
nc = number of respondents (conventional farmers)
Level of significance = 0.05
3.4.5 Chow Test (for testing hypothesis ii)
According to Koutsoyiannis (1977), chow test can be calculated as follows:
F* = {e2p (e21 + e2
2 )}/k ____________________ (e2
1 + e22 )/ (n1+n2-2k)
Where; F*= Observed F-test (as suggested by G.C.Chow) e2p=Sum of square residual of pooled function e2
1 =Sum of square of n1 observation
c
c
g
g
cg
nS
nS
XXt22
48
e22 =Sum of square of n2 observation
K= Degree of freedom(number of b’s, including the intercept bo) n= Number of observation from organic farm n2=Number of observation from conventional farm
3.4.6 Student t-test (for testing hypothesis iii)
t
c
c
g
g
cg
nS
nS
XX22
Where t = test
cX = mean of farmers income from conventional sesame crop production
gX = mean of farmers’ income from organic sesame crop production.
Sc2 = variance of farmers’ income from conventional sesame crop production
Sg2 = variance of farmers’ income from organic sesame crop production
nc = number of the respondents (conventional farmers).
ng = number of the respondents (organic farmers)
level of significance = 0.05
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CHAPTER FOUR
4.0 RESULTS AND DISCUSSION
4.1 Socio Economic Characteristics of Sesame Farmers
Sex. Sesame production in the state is dominated by male farmers. Table 3 shows that
both systems of sesame production are dominated (92% for organic and 80% for
conventional) by male farmers. The women farmers are largely involved in sesame
processing and marketing.
Age. The age of the farmers to a large extent affect their labour productivity and output.
It can also influence the adoption of innovation in traditional farming (Adewumi and
Omotosho, 2002). Table 3 shows that the bi- modal age brackets for organic farmers were
21-32 and 45-56 years, while the modal age bracket for conventional sesame farmers was
33-44 years. The mean age for both categories of farmers was 40 years. This implies that
sesame production is handled by active adults who placed much interest in the high crop
yield and profit maximization. The probable reason for the bi-modal age brackets for
organic farmers is that young adult farmers were very much practicing organic farming as
elderly farmers.
Marital status. Table 3 shows that married people constitute 97% of organic farmers and
98% of conventional farmers. The unmarried young adult farmers were more involved in
providing labour on hired basis for sesame production instead of owning the sesame
farms.
Household size. Household size is an important factor in the availability of family
labour. However, the members of the household, particularly the young adults were
mostly engaged in menial jobs so as to supplement the household heads’ contribution in
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running the household instead of providing the family labour. The mean household size
for organic farming households was 9 members as against 12 members for conventional
farming households. Even though the mean household size is large for both categories of
farmers, family labour utilization is low for both them. This could be as a result of
engagement of young adults in menial jobs, schooling and rural-urban migration.
Table 3: Socio-Economic Characteristics of Sesame Farmers Organic sesame farmers Conventional sesame farmers Variables Frequency Percentage Frequency Percentage Sex: Male Female Total
household size and farming experience are presented in tables 9 and 10.
4.6.1 Regression Estimates for Factors of Total Factor Productivity of Organic
Sesame Farms.
The lead equation for determinants of TFP for organic farms was the Double log
function. Table 10 shows that coefficients of pesticide, household size, farm size, farming
experience and education have expected positive apriori signs. Increase in any of these
coefficients will increase the productivity level of organic farms, as they contribute little
or no cost to the total production cost. Increase in farmer’s educational status and farming
experience will definitely enhance his management skill and hence his productivity.
The coefficients of seed, labour and fertilizer were negative. This result follows
since seed and labour were over-utilized, more productivity can still be attained when
their quantity are reduced. The negative coefficient of fertilizer arose from the fact that
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where high concentration of green manure exist or where sesame is planted in rotation
with legumes, decrease in the quantity of animal manure can still increase or improve
Table 10: Regression Estimates for Factors of Total Factor Productivity of Organic
Sesame Farms – Double Log function.
Variables Coefficients Standard Error T-value
Constant 2.937 1.023 2.872***
Farm size X1 0.891 0.232 3.831***
Seed X2 -0.475 0.175 -2.715***
Labour X3 -0.587 0.127 - 4.605***
Education X4 0.178 0.149 1.194NS
Fertilizer X5 - 0.001 0.073 - 0.009NS
Pesticide X6 0.162 0.160 1.013NS
Household size X7 0.278 0.118 2.360**
Farming experience X8 0.258 0.105 2.467***
Source: Data analysis, (2009)
F-value 5.963**
R2 – value 0.584
***: Significant at 1% level of probability.
**: Significant at 5% level of probability. NS: Not significant.
productivity level of the sesame farm. The variable coefficients for farm size, seed,
labour and farming experience were significant at 1% level of probability. Household
size was significant at 5% level of probability. The variable coefficients for education,
fertilizers and pesticides were insignificant. The result implies that farm size, seed,
labour, farming experience and household size influence productivity level of organic
sesame farms.
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The R2 value for double log function was 0.584. This implies that hypothesized
determinants included in the regression model accounted for about 58% variations in the
productivity level recorded in the organic sesame enterprise. The F-value was 5.963 and
significant at 5% level of probability. This means that the joint effects of variables
included in the regression model on the productivity level of organic sesame farms were
significant.
4.6.2 Regression Estimates for Factors of Total Factor Productivity of
Conventional Sesame Farms.
The lead equation for determinants of TFP level of conventional sesame farms was a
linear function. Table 11 shows that the variable coefficients for farm size, education and
farming experience have expected positive aprori expectations. Increase in these
variables can enhance productivity level of conventional sesame farms. The coefficients
for seed, labour, fertilizer, pesticide and household size were negative. Since seed, labour,
and pesticide were over-utilized by conventional sesame farmers, their decrease in
quantity can increase the productivity level of conventional farms. The negative
coefficient of fertilizer arose from the fact that high quantity of local variety was used by
conventional farmers. The local variety of sesame seed does not respond well to chemical
fertilizer, especially where the soil fertility is high. In such condition, productivity can be
increased even when the quantity of chemical fertilizer is reduced.
63
Table 11: Regression Estimates for Factors of Total Factor Productivity of
Conventional Sesame Farms – Linear Function.
Variables Coefficients Standard Error T-value
Constant 1.111 0.410 2.70***
Farm size X1 0.944 0.144 6.568***
Seed X2 -0.042 0.23 -1.847*
Labour X3 -0.001 0.000 -2.302**
Education X4 0.006 0.016 0.337NS
Fertilizer X5 - 0.002 0.001 -1.821*
Pesticide X6 -0.075 0.042 -1.795*
Household size X7 -0.006 0.026 -0.241NS
Farming experience X8 0.019 0.021 0.885NS
Source: Data Analysis, (2009)
F-value 9.154**
R2 – value 0.589
***: Significant at 1% level of probability.
**: Significant at 5% level of probability. * Significant at 10% level of prob.
The variable coefficients for farm size, and labour were significant at 1% and 5% levels
of probability respectively, while coefficients of seed, fertilizer and pesticide were
significant at 10% level of probability. This implies farm size, labour, seed, fertilizer and
pesticide influence the productivity level of conventional sesame farms. The coefficient
of educational status, household size and farming experience were not significant and
hence they have no influence on productivity level. The R2 value for the linear function
was 0.589, indicating that the hypothesized variables included in the regression model
accounted for about 59% variations in the productivity level of conventional sesame
farms. F-value was 9.154 and significant at 5% level of probability. This implies that the
64
joint effects of variables included the regression model on total factor productivity of
conventional sesame farms were significant. The significant influence of land, labour and
fertilizer on TFP is in conformity with result of Fakayode et al (2008).
4.7 Hypotheses Testing
The results of hypothesis testing are shown in Tables 12, 13 and 14. The results
confirmed that there was no significant difference between productivity level of organic
and conventional sesame farms; the difference in amount of income earned from both
enterprises were insignificant; and, there was no significance difference between the
effects of determinants on TFP for both enterprises.
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Table 12: Result of t-test Comparing Productivity of Organic and Conventional
Sesame Farms
c
c
g
g
cg
nS
nS
XX22
t* <t 0.05
Thus, null hypothesis is accepted
Source: Data Analysis, (2009).
Computation Value
gX 1.9
cX 1.7
S2g 1.1 2cS
2.0
ng 60
nc 60
t*
= 1
66
Table 13: Result of Chow Test Comparing the Influence of Identified Factors on
TFP of Organic and Conventional Sesame Farms.
Computation Value
Σe2p 10.6
Σe21 4.7
Σe22 47
n1 60
n2 60
K 9
F* = Σe2p – (Σe22 + e2
2) /k
(Σe21 + Σe22/(n1 + n2 – 2k)
Thus F* < F0.05 and hence we accept
null hypothesis.
= - 9.2
Source: Data Analysis, (2009)
67
Table 14: Result of t-test Comparing Incomes from Organic and Conventional
Sesame Farms.
Source: Data Analysis, (2009)
4 .8 Constraints to Sesame Production
The major constraints to increased sesame production confronting both categories
of farmers are shown in table 15 and 16. Poor access to credit facility, poor access road
network and low market price for sesame grains have been identified as major constraints
to sesame production. High cost of chemical fertilizer, shortage of chemical and organic
fertilizer also constituted major constraints to sesame production. Scarcity of improved
seed variety and high cost of synthetic pesticide also pose constraints to sesame
production.
Computation Value
gX 62,409
cX 64,567 2gS
2003905225 2cS
2270905225
ng 60 nc 60 T* < t 0.05. Thus, null hypothesis is accepted
= - 0.00003
c
c
g
g
cg
nS
nS
XXt22
*
68
Table 15: Constraints to Organic Sesame Production
Constraints Frequency Rank
i. Poor access to credit 53 1st
ii. Poor access road network 44 2nd
iii. Low market prices for sesame grain 39 3rd
iv. Shortage of organic fertilizer 18 4th
v. Scarcity of improved sesame seed 09 5th
vi. Poor storage facility 08 6th
vii. Pests and diseases 05 7th
viii. High cost of organic fertilizer 04 8th
Total 180*
Source: Field Survey, (2009)
* Multiple choices were allowed hence total frequency exceeded sample size
69
Table 16: Constraints to Conventional Sesame Production.
Constraints Frequency Rank
1. High cost of chemical fertilizer 54 1st
2. Poor access to credit 53 2nd
3. Poor access road net work 35 3rd
4. Shortage of chemical fertilizer 26 4th
5. Low market price for sesame grain 17 5th
6. High cost of synthetic pesticides 17 5th
7. Scarcity of improved seed 09 7th
8. Poor storage facility 09 7th
9. Pest and disease 03
Total 223*
Source: Field Survey, (2009)
* Multiple choices were allowed hence total frequency exceeded sample size
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CHAPTER FIVE
4.0 SUMMARY, CONCLUSION AND RECOMMENDATIONS
5.1 Summary
The study was designed to compare the economics of organic and conventional
sesame production systems in Nasarawa State, Nigeria.
The broad objective was to conduct a comparative economic analysis of organic
and conventional sesame production systems in Nasarawa State. Specifically, the study
intended to achieve the followings: describe socio-economic characteristics of organic
and conventional farmers, identify organic and conventional farming practices, identify
input and output levels in both farms, estimate productivity levels of organic and
conventional sesame farms, identify the determinants of productivity level in both farms,
determine enterprise profitability in both farms and identify constraints to increased
sesame production.
Multi-stage sampling was used to select 120 farmers; made up of 60 organic and 60
conventional sesame farmers. Data were collected based on 2008/9 cropping season
through structured questionnaire. Data were analyzed using descriptive statistics, TFP
estimate, OLS regression analysis and gross margin analysis.
The results show that men and married farmers dominated production of sesame,
and they were mostly adult. The mean household size for organic farmers was 9 members
compared to 12 members for conventional farmers. They were more literate farmers
(72%) in organic farming than conventional farming (45%). Over 76% of organic farmers
and 60% of conventional farmers have been farming sesame crop for over 8 years. The
mean of farming experience was 12 years for both farmers. Most farmers (85% organic
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and 75% conventional) acquired sesame farm land through inheritance. Traditional
implements like hoe and cutlasses were employed exclusively for farming sesame by
93% of organic and 80% of conventional farmers. Most farmers (55% organic and 53%
conventional) belong to one form of agricultural cooperatives or the other. More of
conventional farmers used improved seed (73%) than organic farmers (63%) and Hired
labour was mostly patronized by both organic (72%) and conventional (77%) farmers.
The common organic farming practices were crop rotation with legumes,
application of animal manure and local pesticide (neem solution) as well as green
manure. On the other hand, the use of chemical fertilizer (e.g. NPK, urea), insecticide
(e.g. Karate and cymbush), burning of crop residues and intensive tillage were common
practices among conventional farmers.
A total of 159 and 169 hectares were put under production of sesame by both
organic and conventional farmers. 2.6 hectares per organic farmer and 2.8 hectares per
conventional farmer were the mean hectares cultivated by both farmers. The average
quantities of seed planted per hectare by both farmers were 7kg (organic farmers) and
7.7kg (conventional farmers). On organic farm, average man-hours spent was 327 per
hectare compare to 283 man-hours per hectare spent by conventional farmers. An average
of 1381kg of animal manure was used per hectare as against 69kg per hectare of chemical
fertilizer. The litre of natural pesticide used per hectare was 5.6 compared to 1.9 litre per
hectare of synthetic pesticides. The average output per hectare of organic and
conventional farms were 506kg and 552kg respectively.
The gross returns from organic and conventional farms per hectare were N93838
and N100875, while total variable costs from organic and conventional farms per hectare
72
were N31419 and N36308 respectively. The gross margins from both farms were N62409
per hectare of organic farm and N64567 per hectare of conventional farm. The Internal
Rate of Returns was higher in organic farms with N2 as against N1.8 in conventional
farms.
On the average, TFP estimates for organic farms (1.9) was higher than that (1.7)
recorded for conventional farms. This implies that organic farms were more productive
than conventional farms on the average.
The result of regression model (Double log function) for determinants of TFP of
organic farms indicated that farm size, seed labour, farming experience and house hold
size influence productivity level of organic farms positively except for seed and labour.
The R2 value was 0.584 and F-value was 5.963 and was significant at 5% level of
probability, while the result of regression model (linear function) for determinants of TFP
of conventional farms showed that farm size, labour, seed, fertilizer and pesticide
influence productivity level of conventional farms negatively except for farm size . The
R2 value was 0.589 and F-value was 9.154 and was significant at 5% level of probability.
The identified major constraints to increased sesame production confronting both
farmers were poor access to credit facility, poor road network to the villages, low market
price, high cost of chemical fertilizer, and shortage of chemical and organic fertilizers.
Others include non availability of improved seed as well as high cost of synthetic
pesticide.
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5.2 Conclusion
Based on the findings of the study, the difference in gross margin earned between
organic and conventional farms was insignificant. Similarly, the difference in
productivity level between organic and conventional farms was not significant. The
effects of determinants on total factor productivity (productivity level) between organic
and conventional farms were similar. Therefore, organic sesame farming, which has the
advantage of ensuring sustainable farm productivity and income should be encouraged
and incorporated into agricultural policy and programme of the state as a means of
achieving food and income security.
5.3 Recommendations
Based on the findings of the study, the following recommendations are made.
1. In order to ensure sustainable sesame production, organic sesame farming
should be encouraged by the government through appropriate policy.
2. Sesame farmers’ access to credit is very poor in the state. Therefore, to ensure
wider cultivation of the crop, credit facility should be channeled to the real
farmers through cooperative organizations. Farmers should be encouraged to
form viable agricultural cooperatives.
3. Feeder roads should be constructed and those in deplorable conditions should
be repaired in the rural areas. This will facilitate movement of sesame produce
from rural areas to town and urban markets and there by reducing the glut and
ensuring a better price for the produce.
4. The present government policy of buying excess produce from farmers during
harvesting season at higher prices should be extended to rural communities
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where farming is taking place. This will reduce price fluctuation and making
farmers to earn more income.
5. Sesame farmers should be assisted with inputs that are essential to farming
activities like improved seed, tractor, organic fertilizer etc.
6. Sesame farmers should be guided on appropriate quantity of inputs use per
hectare by extension agents to avoid wastage.
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