This document analyzes the technical efficiency of rice farmers in Ahero Irrigation Scheme, Kenya. It begins with background on rice production and consumption trends in Kenya. Rice consumption has been increasing at 12% annually compared to 4% for wheat and 1% for maize. However, production has not kept pace with demand, resulting in a large import deficit. The study estimates a stochastic Cobb-Douglas production function to determine technical efficiency and its determinants. It finds the technical efficiency of rice farmers is 0.82. Gender, farming experience, income level, and distance to market significantly influence technical efficiency. The study recommends policies to improve input affordability and farm incomes, as well as transport infrastructure, to increase efficiency of rice
IOSR Journal of Applied Physics (IOSR-JAP) is an open access international journal that provides rapid publication (within a month) of articles in all areas of physics and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in applied physics. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
This review paper is focusing adoption of climate smart agricultural practices that focuses on the major factors affecting based on the dry land of Ethiopia
Presentation delivered by Dre. Ashok Gulati (Indian Council for Research on International Economic Relations, India) at Borlaug Summit on Wheat for Food Security. March 25 - 28, 2014, Ciudad Obregon, Mexico.
http://www.borlaug100.org
IOSR Journal of Applied Physics (IOSR-JAP) is an open access international journal that provides rapid publication (within a month) of articles in all areas of physics and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in applied physics. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
This review paper is focusing adoption of climate smart agricultural practices that focuses on the major factors affecting based on the dry land of Ethiopia
Presentation delivered by Dre. Ashok Gulati (Indian Council for Research on International Economic Relations, India) at Borlaug Summit on Wheat for Food Security. March 25 - 28, 2014, Ciudad Obregon, Mexico.
http://www.borlaug100.org
Factors Affecting Adoption and its Intensity of Malt Barley Technology Packag...Premier Publishers
Enhancing the probability of adoption and its intensity is not an easy task because there are numerous factors that affect producers’ adoption decision. Hence, the study was aimed to investigate the factors that affect adoption and intensity of adoption among malt barley producers in southern Ethiopia. Using random sampling technique, 251 smallholder malt barley producers were selected to collect primary data through semi-structured questionnaires. Descriptive statistics and econometrics model (Tobit model) methods were used for data analysis. The study identified five major malt barley technology packages in the study area. Such practices are; improved seed, seeding rate, fertilizer rate, plowing frequency and row planting. Thus, non-adopter accounted for 7.5% of total sample, partial adopter (50.2%), fully adopter (42.3%) and intensity ranges from 0.12-0.84 for partially adopter and 0.85-0.96 for fully adopter. The results of Tobit model indicated that factors influencing adoption and its intensity are; education, family size, land size, access to credit, membership to cooperative, access to training, access to demonstration, total livestock unit and distance to nearest market. Which are affected farmers adoption decision and intensity of adoption significantly in one or another way. Therefore, government and any development interventions should give emphasis to improvement of such institutional support system so as to achieve wider adoption, increased productivity and income to small scale.
Advancement in agricultural technologies is seen to result in the shift in production functions. The study was conducted to establish the impact of the improved rice variety on productivity in the Ejura-Sekyedumase and Atebubu-Amantin Municipalities of Ghana. The study was based on the survey of 208 rice farmers using a three-stage stratified sampling method. The study used a structured questionnaire to collect inputoutput data from the rice farmers. Data were analysed using the Cobb-Douglas production function. The study found that the technical change associated with the introduction of the improved rice variety was of the non-neutral type. Further, the adoption of the improved rice variety has increased rice productivity by about 46% for the adopters. The main determinants of productivity for the adopters were seed, land, fertiliser, herbicide, and education. Productivity among the non-adopters was positively influenced by seed, land, herbicide, and fertiliser. The study concluded that the improved rice variety has superior yield advantage. The study recommends for the simultaneous promotion of improved rice varieties and their recommended inputs to increase rice productivity.
The World Bank under request by Supreme National Economic Council (SNEC) and Ministry of Agriculture, Forestry, and Fisheries (MAFF) commissioned a diagnostics study to answer questions about possible directions of transformation of Cambodia agriculture over the coming decades, and its implication on farm incomes. The proposed diagnostics combines the analysis of the change of farming systems in Cambodia over the past decade with the review of agricultural development experiences in the region to develop agriculture development scenarios until 2030. Agrifood Consulting International Inc (ACI) was selected to implement the Study.
In order to address these questions, the Study Team combined the analysis of existing secondary data with primary data from a survey conducted in the same villages where a similar investigation was conducted ten years ago. The Team then built and analyzed different scenarios of future growth.
The key two messages of the study are:
a. Past drivers of growth will not be suitable for sustained growth in the future
b. Two new drivers are required including
(i) total factor productivity growth (TFP);
(ii) agribusiness development.
Technical Efficiency of Smallholder Sorghum Producers in West Hararghe Zone, ...Premier Publishers
This study was aimed at analyzing the technical efficiency of sorghum producing smallholder farmers in Chiro district. It was based on cross-sectional data of 130 sample sorghum producing households randomly selected. The estimated results of the Cobb-Douglas frontier model with inefficiency variables shows that the mean technical efficiency of the farmers in the production of sorghum is 78 percent. This implies that sorghum producers can reduce current level of input application by 22 percent given the existing technological level. The discrepancy ratio γ, which measures the relative deviation of output from the frontier level due to inefficiency, was about 84.6% and while the remaining 15.4% variation in output, was due to the effect of random noise. The estimated stochastic production frontier (SPF) model also indicates that Organic fertilizer, DAP fertilizer, Area, Labor and seed are significant determinants of sorghum production level. The estimated SPF model together with the inefficiency parameters shows that age, Frequency of extension contact, Household size, Slope, Fertility of soil and Livestock holding significantly determine the efficiency level of the farmers in sorghum production in the study area. Hence, emphasis should be given to improve the efficiency level of those less efficient farmers by adopting and using practices of relatively efficient farmers in the area so that they can be able to operate at the frontier. Beside this, a strategy of the government needs to be directed towards the above-mentioned determinants.
Computer based dissemination of agricultural
information, expert Systems and decision support systems
(DSS) play a pivotal role in sustainable agricultural
development. The adoption of these technologies requires
knowledge engineering in agriculture. Diversification in
application, spatio-temporal variation, and uncertainty in
environmental data pose a challenge for knowledge
engineering in agriculture. Wheat production management
decision in Pakistan requires acquisition of spatio temporal
information, capturing inherent uncertainty of climatic data
and processing information for possible solution to problems.
In this paper a frame work for engineering of knowledge base
and soft computing model for production management of
wheat crop is presented The frame work include an ontology
based knowledge representation scheme along with structured
rule based system for query processing. A soft computing
model for acquisition and processing of wheat production
information for decision support is presented along with
knowledge delivery through semantic web.
DETERMINANT OF RICE CONSUMPTION: EVIDENCE FROM PANEL DATA IN INDONESIAIAEME Publication
Rice is the main staple food for the population of Indonesia. Although people in several provinces such as Papua and Maluku initially consumed staple foods other than rice such as sago and tubers, they are currently switching to consuming rice. Rice demand for consumption in Indonesia is increasing with the increasing population. This study aims to determine the dynamics of rice consumption and its determinants in Indonesia. The data used are data originating from the Central Bureau of Statistics and the Ministry of Agriculture, which includes data from 33 provinces in the period 2010-2018. The data was analyzed using panel data regression analysis with the selected model fixed effect model on the equality of functions of rice consumption in Indonesia. The results of the analysis show that rice consumption in Indonesia influenced by the number of households, rice prices, cooking oil prices, chicken prices, participation in rice consumption, age and social assistance. Price elasticity and income elasticity is inelastic, but income elasticity not statistically significant. There are indications that food diversification is happening, can be seen from consumption decline due to social assistance which provides alternative choices of consumption
Technical Efficiency Differentials and Resource - Productivity Analysis amon...researchagriculture
The importance of soybean as a high protein, primary input in vegetable oil,
diary and feed industries is not in doubt. The technical efficiency and
resource
-
productivity of smallholder soybean farmers in Benue State, Nigeria were
estimated using cross sectional data obtained on 96 soybean farmers in the empirical
analysis. Results obtained with transcendental logarithmic (translog) stochastic
frontier model showed that the technical efficiencies varied widely from
0.254 to 0.999 with a mean of 0.718. This indicates that smallholder soybean
production was in the irrational stage of production (stage III) as depicted by the
returns
-
to
-
scale (RTS) of
-
2.848. Land and fertilizer were effectively allocated and
used, as confirmed by each variable having estimated coefficient value between zero
and unity, depicting stage II in the production curve. The productivity of the factors
can be enhanced by expanding the farm size at the existing level of labour so that the
variable of labour used could move from stage III to stage II in the production curve.
Labour saving resource and/or practices should be encouraged for productivity and
technical efficiency to be enhanced.
Lower and/or inappropriate usages of improved agricultural technologies are among the major of causes for decline of production and productivity of wheat as compared to the potential in Ethiopia. This study aims to measure the status and extent of improved wheat technology adoption and identify its determinants among wheat producing smallholder farmers’ in Sekela district of West Gojjam zone of Ethiopia. Multi-stage sampling techniques used to select 204wheat producing farmers. The study primarily used collected primary data for 2017/18 production year using structured questionnaire. In order to analyze the data, both descriptive statistics and econometrics techniques such as double hurdle model are applied. The result shows that family size, availability of oxen and attitude towards risk affected positively adoption status of wheat production. While, farming experience, and off-farm income affected the extent of improved wheat variety adoption. On the other hand, farm size and cultivated farm land affected negatively the extent of improved wheat varieties adoption. Based on the result, the study recommended that the above factors should be considered both at stages in evaluating strategies aimed at promoting wheat production and productivity of the study area.
Relationship between Farmers’ Participation in Technology Development and Dis...Premier Publishers
Improved sugarcane varieties have been developed and promoted in Kenya, to enhance sugarcane productivity. However, their acceptance by farmers is low. This paper investigates this phenomenon in attempt to underpin contributing factors to low acceptance. It examines the relationship between farmers’ participation in technology development and dissemination processes; and acceptability of improved sugarcane varieties in Kakamega County. This study used cross-sectional survey research design. Target population was 137,355 small-scale sugarcane farmers from Kakamega County, from which a sample of 384 farmers was randomly selected. Questionnaires were used to collect data, which was analyzed using descriptive and inferential statistics. The study established limited participation of sugarcane farmers in the development and dissemination of improved sugarcane varieties. Significant relationships were established between farmers’ participation in the development and dissemination of improved sugarcane varieties with their acceptability by farmers. The number of year’s farmers had produced these varieties was found to be a strong indicator of their acceptability by farmers. Research findings indicate need to avail necessary information about the improved varieties to farmers by the extension service providers. Utilization of farmer Participatory Technology Development and Dissemination approaches need to be enhanced in the development and dissemination of improved sugarcane technologies.
Analysis of Resource Use Efficiency in Small-Scale Maize Production in Tafawa...IOSRJAVS
his paper analyzed the resource-use efficiency of small-scale Maize production in Tafawa-Balewa local government area of Bauchi State. Data were collected from a sample of 120 Maize farmers selected through multi-stage sampling procedure using questionnaire and analyzed using simple descriptive statistics, double-log function and marginal value productivity analysis. The result showed that 90.17% had formal education; 51.67% were males; 90.17% were between the ages of 21-50. Majority 72.50% were married. In terms of farming experience, majority (86.67%) of the respondent had farming experience between 5-20 years. 75.00% had no contact with extension. The double-log function gave the best fit with Adjusted R2 of 81.16%. Production inputs such as seed, fertilizer, labour affected output significantly. Maize production in the study area has an increasing return to scale from the sum of elasticity of production (1.747). Seed and fertilizer were underutilized in Maize production, whereas labour was over used. The major problem confronting the farmers include high cost of inputs (77.50%); Untimely disbursement of credit/inputs (62.50; inadequate extension services (59.17); unstable price (41.67%); draught (33.33%), inadequate credit facilities (31.67%) etc. Profit could be enhanced by increasing the quantity used of seed and fertilizer inputs, its timely supply. Labour should be reduced to optimum level for increase output and total revenue respectively. It is also recommended that extension education and financial support to farmers be improved to allow them increase output and total revenue. There is need for adjustment in resource use in order to improve farm profit at this level of technology used by Maize farmers in the study area.
Factors Affecting Adoption and its Intensity of Malt Barley Technology Packag...Premier Publishers
Enhancing the probability of adoption and its intensity is not an easy task because there are numerous factors that affect producers’ adoption decision. Hence, the study was aimed to investigate the factors that affect adoption and intensity of adoption among malt barley producers in southern Ethiopia. Using random sampling technique, 251 smallholder malt barley producers were selected to collect primary data through semi-structured questionnaires. Descriptive statistics and econometrics model (Tobit model) methods were used for data analysis. The study identified five major malt barley technology packages in the study area. Such practices are; improved seed, seeding rate, fertilizer rate, plowing frequency and row planting. Thus, non-adopter accounted for 7.5% of total sample, partial adopter (50.2%), fully adopter (42.3%) and intensity ranges from 0.12-0.84 for partially adopter and 0.85-0.96 for fully adopter. The results of Tobit model indicated that factors influencing adoption and its intensity are; education, family size, land size, access to credit, membership to cooperative, access to training, access to demonstration, total livestock unit and distance to nearest market. Which are affected farmers adoption decision and intensity of adoption significantly in one or another way. Therefore, government and any development interventions should give emphasis to improvement of such institutional support system so as to achieve wider adoption, increased productivity and income to small scale.
Advancement in agricultural technologies is seen to result in the shift in production functions. The study was conducted to establish the impact of the improved rice variety on productivity in the Ejura-Sekyedumase and Atebubu-Amantin Municipalities of Ghana. The study was based on the survey of 208 rice farmers using a three-stage stratified sampling method. The study used a structured questionnaire to collect inputoutput data from the rice farmers. Data were analysed using the Cobb-Douglas production function. The study found that the technical change associated with the introduction of the improved rice variety was of the non-neutral type. Further, the adoption of the improved rice variety has increased rice productivity by about 46% for the adopters. The main determinants of productivity for the adopters were seed, land, fertiliser, herbicide, and education. Productivity among the non-adopters was positively influenced by seed, land, herbicide, and fertiliser. The study concluded that the improved rice variety has superior yield advantage. The study recommends for the simultaneous promotion of improved rice varieties and their recommended inputs to increase rice productivity.
The World Bank under request by Supreme National Economic Council (SNEC) and Ministry of Agriculture, Forestry, and Fisheries (MAFF) commissioned a diagnostics study to answer questions about possible directions of transformation of Cambodia agriculture over the coming decades, and its implication on farm incomes. The proposed diagnostics combines the analysis of the change of farming systems in Cambodia over the past decade with the review of agricultural development experiences in the region to develop agriculture development scenarios until 2030. Agrifood Consulting International Inc (ACI) was selected to implement the Study.
In order to address these questions, the Study Team combined the analysis of existing secondary data with primary data from a survey conducted in the same villages where a similar investigation was conducted ten years ago. The Team then built and analyzed different scenarios of future growth.
The key two messages of the study are:
a. Past drivers of growth will not be suitable for sustained growth in the future
b. Two new drivers are required including
(i) total factor productivity growth (TFP);
(ii) agribusiness development.
Technical Efficiency of Smallholder Sorghum Producers in West Hararghe Zone, ...Premier Publishers
This study was aimed at analyzing the technical efficiency of sorghum producing smallholder farmers in Chiro district. It was based on cross-sectional data of 130 sample sorghum producing households randomly selected. The estimated results of the Cobb-Douglas frontier model with inefficiency variables shows that the mean technical efficiency of the farmers in the production of sorghum is 78 percent. This implies that sorghum producers can reduce current level of input application by 22 percent given the existing technological level. The discrepancy ratio γ, which measures the relative deviation of output from the frontier level due to inefficiency, was about 84.6% and while the remaining 15.4% variation in output, was due to the effect of random noise. The estimated stochastic production frontier (SPF) model also indicates that Organic fertilizer, DAP fertilizer, Area, Labor and seed are significant determinants of sorghum production level. The estimated SPF model together with the inefficiency parameters shows that age, Frequency of extension contact, Household size, Slope, Fertility of soil and Livestock holding significantly determine the efficiency level of the farmers in sorghum production in the study area. Hence, emphasis should be given to improve the efficiency level of those less efficient farmers by adopting and using practices of relatively efficient farmers in the area so that they can be able to operate at the frontier. Beside this, a strategy of the government needs to be directed towards the above-mentioned determinants.
Computer based dissemination of agricultural
information, expert Systems and decision support systems
(DSS) play a pivotal role in sustainable agricultural
development. The adoption of these technologies requires
knowledge engineering in agriculture. Diversification in
application, spatio-temporal variation, and uncertainty in
environmental data pose a challenge for knowledge
engineering in agriculture. Wheat production management
decision in Pakistan requires acquisition of spatio temporal
information, capturing inherent uncertainty of climatic data
and processing information for possible solution to problems.
In this paper a frame work for engineering of knowledge base
and soft computing model for production management of
wheat crop is presented The frame work include an ontology
based knowledge representation scheme along with structured
rule based system for query processing. A soft computing
model for acquisition and processing of wheat production
information for decision support is presented along with
knowledge delivery through semantic web.
DETERMINANT OF RICE CONSUMPTION: EVIDENCE FROM PANEL DATA IN INDONESIAIAEME Publication
Rice is the main staple food for the population of Indonesia. Although people in several provinces such as Papua and Maluku initially consumed staple foods other than rice such as sago and tubers, they are currently switching to consuming rice. Rice demand for consumption in Indonesia is increasing with the increasing population. This study aims to determine the dynamics of rice consumption and its determinants in Indonesia. The data used are data originating from the Central Bureau of Statistics and the Ministry of Agriculture, which includes data from 33 provinces in the period 2010-2018. The data was analyzed using panel data regression analysis with the selected model fixed effect model on the equality of functions of rice consumption in Indonesia. The results of the analysis show that rice consumption in Indonesia influenced by the number of households, rice prices, cooking oil prices, chicken prices, participation in rice consumption, age and social assistance. Price elasticity and income elasticity is inelastic, but income elasticity not statistically significant. There are indications that food diversification is happening, can be seen from consumption decline due to social assistance which provides alternative choices of consumption
Technical Efficiency Differentials and Resource - Productivity Analysis amon...researchagriculture
The importance of soybean as a high protein, primary input in vegetable oil,
diary and feed industries is not in doubt. The technical efficiency and
resource
-
productivity of smallholder soybean farmers in Benue State, Nigeria were
estimated using cross sectional data obtained on 96 soybean farmers in the empirical
analysis. Results obtained with transcendental logarithmic (translog) stochastic
frontier model showed that the technical efficiencies varied widely from
0.254 to 0.999 with a mean of 0.718. This indicates that smallholder soybean
production was in the irrational stage of production (stage III) as depicted by the
returns
-
to
-
scale (RTS) of
-
2.848. Land and fertilizer were effectively allocated and
used, as confirmed by each variable having estimated coefficient value between zero
and unity, depicting stage II in the production curve. The productivity of the factors
can be enhanced by expanding the farm size at the existing level of labour so that the
variable of labour used could move from stage III to stage II in the production curve.
Labour saving resource and/or practices should be encouraged for productivity and
technical efficiency to be enhanced.
Lower and/or inappropriate usages of improved agricultural technologies are among the major of causes for decline of production and productivity of wheat as compared to the potential in Ethiopia. This study aims to measure the status and extent of improved wheat technology adoption and identify its determinants among wheat producing smallholder farmers’ in Sekela district of West Gojjam zone of Ethiopia. Multi-stage sampling techniques used to select 204wheat producing farmers. The study primarily used collected primary data for 2017/18 production year using structured questionnaire. In order to analyze the data, both descriptive statistics and econometrics techniques such as double hurdle model are applied. The result shows that family size, availability of oxen and attitude towards risk affected positively adoption status of wheat production. While, farming experience, and off-farm income affected the extent of improved wheat variety adoption. On the other hand, farm size and cultivated farm land affected negatively the extent of improved wheat varieties adoption. Based on the result, the study recommended that the above factors should be considered both at stages in evaluating strategies aimed at promoting wheat production and productivity of the study area.
Relationship between Farmers’ Participation in Technology Development and Dis...Premier Publishers
Improved sugarcane varieties have been developed and promoted in Kenya, to enhance sugarcane productivity. However, their acceptance by farmers is low. This paper investigates this phenomenon in attempt to underpin contributing factors to low acceptance. It examines the relationship between farmers’ participation in technology development and dissemination processes; and acceptability of improved sugarcane varieties in Kakamega County. This study used cross-sectional survey research design. Target population was 137,355 small-scale sugarcane farmers from Kakamega County, from which a sample of 384 farmers was randomly selected. Questionnaires were used to collect data, which was analyzed using descriptive and inferential statistics. The study established limited participation of sugarcane farmers in the development and dissemination of improved sugarcane varieties. Significant relationships were established between farmers’ participation in the development and dissemination of improved sugarcane varieties with their acceptability by farmers. The number of year’s farmers had produced these varieties was found to be a strong indicator of their acceptability by farmers. Research findings indicate need to avail necessary information about the improved varieties to farmers by the extension service providers. Utilization of farmer Participatory Technology Development and Dissemination approaches need to be enhanced in the development and dissemination of improved sugarcane technologies.
Analysis of Resource Use Efficiency in Small-Scale Maize Production in Tafawa...IOSRJAVS
his paper analyzed the resource-use efficiency of small-scale Maize production in Tafawa-Balewa local government area of Bauchi State. Data were collected from a sample of 120 Maize farmers selected through multi-stage sampling procedure using questionnaire and analyzed using simple descriptive statistics, double-log function and marginal value productivity analysis. The result showed that 90.17% had formal education; 51.67% were males; 90.17% were between the ages of 21-50. Majority 72.50% were married. In terms of farming experience, majority (86.67%) of the respondent had farming experience between 5-20 years. 75.00% had no contact with extension. The double-log function gave the best fit with Adjusted R2 of 81.16%. Production inputs such as seed, fertilizer, labour affected output significantly. Maize production in the study area has an increasing return to scale from the sum of elasticity of production (1.747). Seed and fertilizer were underutilized in Maize production, whereas labour was over used. The major problem confronting the farmers include high cost of inputs (77.50%); Untimely disbursement of credit/inputs (62.50; inadequate extension services (59.17); unstable price (41.67%); draught (33.33%), inadequate credit facilities (31.67%) etc. Profit could be enhanced by increasing the quantity used of seed and fertilizer inputs, its timely supply. Labour should be reduced to optimum level for increase output and total revenue respectively. It is also recommended that extension education and financial support to farmers be improved to allow them increase output and total revenue. There is need for adjustment in resource use in order to improve farm profit at this level of technology used by Maize farmers in the study area.
Analysis of Resource Use Efficiency in Small-Scale Maize Production in Tafawa...IOSRJAVS
This paper analyzed the resource-use efficiency of small-scale Maize production in Tafawa-Balewa local government area of Bauchi State. Data were collected from a sample of 120 Maize farmers selected through multi-stage sampling procedure using questionnaire and analyzed using simple descriptive statistics, double-log function and marginal value productivity analysis. The result showed that 90.17% had formal education; 51.67% were males; 90.17% were between the ages of 21-50. Majority 72.50% were married. In terms of farming experience, majority (86.67%) of the respondent had farming experience between 5-20 years. 75.00% had no contact with extension. The double-log function gave the best fit with Adjusted R2 of 81.16%. Production inputs such as seed, fertilizer, labour affected output significantly. Maize production in the study area has an increasing return to scale from the sum of elasticity of production (1.747). Seed and fertilizer were underutilized in Maize production, whereas labour was over used. The major problem confronting the farmers include high cost of inputs (77.50%); Untimely disbursement of credit/inputs (62.50; inadequate extension services (59.17); unstable price (41.67%); draught (33.33%), inadequate credit facilities (31.67%) etc. Profit could be enhanced by increasing the quantity used of seed and fertilizer inputs, its timely supply. Labour should be reduced to optimum level for increase output and total revenue respectively. It is also recommended that extension education and financial support to farmers be improved to allow them increase output and total revenue. There is need for adjustment in resource use in order to improve farm profit at this level of technology used by Maize farmers in the study area.
Effects of Value Addition on the Profitability of Irish Potato Production in ...Premier Publishers
In Bomet County farmers produce Irish potatoes for household consumption and income generation. The farmers have been urged to adopt value addition practices to increase their profits and household income. But since value addition comes with a cost, it raises a question of whether value addition increases farm profitability or not. The study used single cross-sectional data from 200 randomly selected farmers to determine the effect of value addition on the profitability of Irish potato production. The data were collected using a structured and unstructured questionnaire. Gross Margin Analysis was used in determining the profitability of various forms of value addition. Statistical packages for social scientists was used in data analysis. The study found that the most common form of value addition practiced by the farmers was sorting while grading, chipping and frying were practiced by few farmers. The study found that value adders earned more profits than non-value adders. The study further established that sorting was more profitable to farmers while frying, grading and chipping led to losses. Therefore, there is a need to identify cost-cutting technologies for grading, chipping and frying as these forms of value addition are not profitable to the farmers.
Drivers of Improved Cassava Variety Adoption among Farmers in Oyo State, NigeriaPremier Publishers
Low cassava productivity in Nigeria has been linked to low adoption of modern technologies amongst farmers, creating a large gap between the current and the potential yield of cassava. Therefore, this study examined the level of adoption of improved cassava variety (TME 419) and its drivers among cassava farmers in Oyo state, Nigeria. Data collected from 236 cassava farmers with the aid of structured questionnaires were analyzed using descriptive statistics, adoption index and logit regression model. Results showed that cassava farmers in Oyo state were 49 years of age with farming experience of 21 years and farm size of 4 ha. About 69% of surveyed farmers adopted the improved cassava variety while the adoption coefficient was 0.66. The likelihood of adopting improved cassava varieties was significantly influenced by education, household size, primary occupation, farming experience, farm size, land ownership and age. Therefore, increasing the years of farmers’ education, farm size, ownership of land, entry of younger farmers, household size and non-farm occupation will increase the likelihood of adopting improved cassava variety among farmers.
Factors Affecting Adoption of Value Addition Practices among Smallholder Iris...Premier Publishers
In Kenya, value addition in Irish potatoes provides farmers with substantial income. However, the adoption of value addition practices is still low among farmers. Currently, there is a dearth of information on the factors affecting the adoption of value addition practices among smallholder Irish potato farmers in Bomet County. Using single cross-sectional data from 200 randomly selected respondents, the study determined factors affecting the uptake of value addition practices using the Binary logistic regression model. Descriptive statistics show that the majority of the Irish potato farmers (62.5%) adopted value addition practices. It was also found that the majority of the farmers did not attend training, and were not accessing agricultural extension services and credit facilities. Logistic regression results show that group membership (P = 0.013), cost per unit of potatoes (P = 0.041), and total land size (P = 0.058) were key variables that significantly influenced adoption of value addition. From the results, it is critical for farmers to join farmer groups and increase acreage under Irish potato production to reduce cost per unit. Farmers should also adopt modern value addition technologies to be encouraged to reduce post-harvest losses of potatoes and to improve smallholder farmers’ income.
Efficiency and Competitiveness of Corn Farming in Sumbawa Regencyiosrjce
IOSR Journal of Agriculture and Veterinary Science (IOSR-JAVS) is a double blind peer reviewed International Journal edited by the International Organization of Scientific Research (IOSR). The journal provides a common forum where all aspects of Agricultural and Veterinary Sciences are presented. The journal invites original papers, review articles, technical reports and short communications containing new insight into any aspect Agricultural and Veterinary Sciences that are not published or not being considered for publication elsewhere.
Determinants of Adoption of Improved Maize Technology among Smallholder Maize...BRNSS Publication Hub
Introduction: As part of Ghana’s agricultural modernization agenda aimed at ensuring the National Food Security, the Ministry of Food and Agriculture (MOFA) through its extension directorate has been promoting the adoption of improved maize technologies. Method and Material: This paper presents the finding of a study conducted to assess the determinants of adoption of improved maize technologies among smallholder farmers in the Bawku West District of the Upper East Region of Ghana. Exploratory survey design was employed with multistage sampling techniques adopted in selecting 400 maize farmers for the study. Result: Personal interviews, administration of semi-structured questionnaire, observations, and focus group discussions were the main methods employed in data collection. Probit regression model was applied in analyzing determinants of the adoption of improved maize technologies. Household annual income, access to labor, access to credit, and extension contact were found as significant determinants of farmers’ level of adoption of improved maize technology. Conclusion: The study recommends to the MOFA to promote the use of labor saving simple farm tools in carrying out the various production recommendations under the improved maize technology. Furthermore, MOFA needs to work with financial institutions to support maize farmers with credit to enable them to acquire the necessary inputs required in the implementation of the improved maize technology.
Determinants of Adoption of Improved Maize Technology among Smallholder Maize...BRNSS Publication Hub
Introduction: As part of Ghana’s agricultural modernization agenda aimed at ensuring the National
Food Security, the Ministry of Food and Agriculture (MOFA) through its extension directorate has been
promoting the adoption of improved maize technologies. Method and Material: This paper presents
the finding of a study conducted to assess the determinants of adoption of improved maize technologies
among smallholder farmers in the Bawku West District of the Upper East Region of Ghana. Exploratory
survey design was employed with multistage sampling techniques adopted in selecting 400 maize
farmers for the study. Result: Personal interviews, administration of semi-structured questionnaire,
observations, and focus group discussions were the main methods employed in data collection. Probit
regression model was applied in analyzing determinants of the adoption of improved maize technologies.
Household annual income, access to labor, access to credit, and extension contact were found as
significant determinants of farmers’ level of adoption of improved maize technology. Conclusion: The
study recommends to the MOFA to promote the use of labor saving simple farm tools in carrying out the
various production recommendations under the improved maize technology. Furthermore, MOFA needs
to work with financial institutions to support maize farmers with credit to enable them to acquire the
necessary inputs required in the implementation of the improved maize technology.
Cost and returns of paddy rice production in Kaduna State of NigeriaPremier Publishers
As a result of increasing population growth and urbanization, there is a high and increasing demand for rice, this necessitates the high attention for its production. This research was conducted to determine the profitability of paddy rice production in Chikun Local Government Area of Kaduna State. Data were collected from 60 randomly selected paddy rice farmers using a well structured questionnaire and analyzed using the descriptive statistics, net income and multiple regression models. The result showed that 97% were male, 88% married and had an average household size of 10 people. All respondents had one form of education and their average farm size was 15ha producing about 3.2tonnes of paddy per hectare. Paddy rice production in the area was estimated to have a profit $902.51 (N179,600) and a net returns of $766.83 (N152,600). Farm size, system of rice cultivation and household size accounted for 78% of the observe variation in the farmer’s income. The study however concluded that paddy rice production in the study area is a profitable enterprise and it also recommended that consistent government policies that would favour increase in paddy production, market information, extension service delivery, input subsidization and credit facilities be implemented.
Optimization Model of Use of Production in Order to Increase Production and E...AI Publications
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An analysis of technical efficiency of rice farmers in ahero irrigation scheme, kenya
1. Journal of Economics and Sustainable Development www.iiste.org
ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)
Vol.4, No.10, 2013
9
An Analysis of Technical Efficiency of Rice Farmers in Ahero
Irrigation Scheme, Kenya
Samuel Onyango Omondi*
and Kelvin Mashisia Shikuku
Department of Agricultural Economics, University of Nairobi, P.O Box 29053-00625, Nairobi, Kenya
*
onyisam316@yahoo.com
Abstract
Rice has continued to be an important cereal in Kenya in the recent years. Although it is third after maize and
wheat in terms of consumption and production, its rate of consumption has increased over the years compared to
maize and wheat. Rice production in Kenya does not meet demand, and the deficit has to be met with imports.
Improving productivity would ensure increase in production, improved food security, reduced rice import bills
and increased income among smallholder farmers. The current study, therefore, estimated technical efficiency of
rice farmers in Ahero Irrigation Scheme, Kisumu County, Kenya. Stratified sampling and probability
proportionate to size sampling was used to sample 220 rice farmers. A stochastic Cobb Douglas production
function was used to estimate technical efficiency. The study further assessed the factors that affect technical
efficiency of the rice farmers. The coefficients of fertilizer and labour were found to positively influence paddy
productivity while that of chemical cost negatively influenced paddy productivity. The level of efficiency of rice
farmers was found to be 0.82. The study further found that gender, farming experience, income level and
distance to market were found to be significant determinants of technical efficiency. The study therefore
recommended policies that will ensure that the costs of productive inputs are affordable to farmers and
improving households’ income through better prices for their outputs. Improvement in the transport
infrastructure is also important in reducing inefficiencies in paddy production.
Key words: Rice, technical efficiency, stochastic Cobb Douglas production function, Kenya
1.0 Introduction
Cereals continue to play an important food security role in Kenya. Among this subsector, maize ranks first,
followed by wheat and rice (Export Processing Zones Authority 2005, Republic of Kenya 2008, Kamau 2013).
Although over the years there has been over dependence on maize as a food security crop in Kenya (Emongór et
al. (2009); Chemonics International Inc. (2010)), during the two time periods of 2000-2004 and 2005-2009,
maize consumption has declined by about 4%. During the same periods the consumption of rice has steadily
increased by about 32% (Table 1). Moreover, according to the National Rice Development Strategy (NRDS
2008 – 2018) the annual rice consumption has been increasing at a rate of 12% compared to 4% and 1% for
wheat and maize (Republic of Kenya, 2008).
Table 1: Consumption of major cereals in Kenya (kg/capita/year)
Year Difference
between the two
periods
Average
Commodity 2000-2004 2005-2009 Percentage
change
Rice 5.8 7.6 1.8 6.7 31.7
Sorghum
Millet
Wheat
1.6
1.0
25.3
2.0
1.3
25.4
0.3
0.3
0.0
1.8
1.2
25.4
20.7
34.5
0.2
Maize 83.4 79.8 -3.6 81.6 -4.4
Source: Computed from FAOSTAT 2013 data
Some authors attribute the increase in rice consumption vis-à-vis the other cereal staples to the changes in eating
habits (Emongór et al., 2009). The challenge, however, is that production has not kept pace with the increase in
demand for rice. For instance, rice productivity declined from 42 bags per hectare in 2003 to 29 bags per hectare
in 2007 (Emongór et al. 2009). The decline in production has been largely blamed on production inefficiencies
(Kuria et al., 2003; Kamau, 2013) and increase in demand. As a consequence of the decrease in productivity and
increase in demand there is a huge deficit of about 75%-85% which is met by imports (Chemonics International
Inc., 2010).
Reliance on the world market for supply of rice is also constrained. Gulati and Narayanan (2002), for example
argue that the world rice market is still characterized by thinness, volatility, and segmentation. Despite the
growing absolute volumes, trade constituted only about 4.5 percent of world rice production from 1961 to 2000,
compared with 18 percent for wheat and 13.6 percent for maize (Gulati and Narayanan, 2003). This is partly
attributable to the fact that much rice is consumed where it is produced and partly because of the nature of
policies pertaining to rice sectors across the world. Moreover, importation of rice has a high opportunity costs as
2. Journal of Economics and Sustainable Development www.iiste.org
ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)
Vol.4, No.10, 2013
10
the funds are diverted from productive investment such as purchase of productive agricultural inputs including
fertilizer as well as investment in infrastructure development. Increased investment in the rice sub-sector has a
great potential to increase farm incomes, boost productivity, lower the price to consumers and increase food
security in the country (Republic of Kenya, 2008).
In recognition of the important role of the rice subsector, the Government of Kenya developed and implemented
the National Rice Development Strategy (NRSDS 2008 – 2018) in efforts to reverse the declining trends in rice
production. The strategy emphasizes that rice is a source of cash and food security for small scale farmers, a
view that is supported by several authors (Emongór et al., 2009; Gitau et al., 2011). Gitau et al., (2011), for
instance, argues that although the country meets only 20% of its rice consumption needs, there is need to shift
from dependence on maize for food security to other cereals like rice and wheat.
About 20% of the rice produced in Kenya is from government established irrigation schemes (Mwea, Ahero,
Bunyala and West Kano) while 20% is from under rain fed conditions (Republic of Kenya 2008). As envisioned
in the NRDS (2008 – 2018), there is need to increase rice productivity hence increasing food production.
Furthermore, rice is one of the crops identified to boost food security in Kenya, the other one being potato. The
government of Kenya is also aiming at increasing the area under irrigation especially in schemes that majorly
produce rice (Republic of Kenya, 2009). This will help in increasing farmers’ incomes and enhancing food
security, hence achieving the Millennium Development Goal (MDG) of eradicating extreme poverty and hunger.
Studies undertaken to assess the performance of the rice sub-sector emphasize technical inefficiencies as the
main cause of declining productivity. Kuria (2003), for example argues that that farmer’s failure to use the most
efficient techniques might be due to non-physical inputs, such as socio-economic and institutional factors. In a
study that assessed technical efficiency among smallholder farmers in Mwea irrigation scheme, Kuria et al.
(2003) found that farmer’s education level, farming experience, availability of credit and extension facilities
influenced technical efficiency. Emongór et al. (2009) examined the rice value chain in Kenya with preference to
producers. The authors argue that labour and capital are major constraints to rice production in the country.
While previous studies point to the need to improve productivity by enhancing human capital, improving farmers’
access to productive inputs, and increased investment in infrastructure, none to the best of our knowledge has
examined the productivity of the productive inputs. Hence, this is an attempt to determine the productivity levels
of rice farmers in Ahero irrigation scheme in Nyando District, Kisumu county, Kenya, and factors that determine
their productivity levels. Such information will be useful in designing policies that target improving farmers’
productivity, income and food security.
2.0 Materials and method
2.1 Study area
The study was conducted in Ahero Irrigation Scheme in Nyando District, Kisumu County, Kenya. The scheme is
located in Kisumu County in the outskirts of Kisumu city. The climate of the area is relatively dry with high
temperatures. The scheme is managed by the National Irrigation Board in partnership with the farmers who are
charged Kshs.3100 per acre per year for scheme Operation and Maintenance (O&M). The area under cultivation
is 2168 acres which is divided into 12 blocks with a total of 1650 farmers. Nearly all irrigated farmland is used
for paddy cultivation.
2.3 The data
A household questionnaire was used to collect primary data from rice farmers in Ahero irrigation scheme, in the
month of April 2012. A sampling frame which is a list of all the farmers in the various blocks was obtained from
the Ahero regional office. Stratified sampling was performed using the 12 blocks as strata. 8 blocks out of the 12
blocks were then randomly selected. Probability proportionate to size sampling was then performed to give a
sample of 220 farmers. Properly trained and carefully selected enumerators pre-tested the questionnaire and later
collected data on input use, outputs and socioeconomic characteristics.
2.4 Empirical model
Variations in output by different producers, caused by technical inefficiencies can be captured through
specification of a production function. Technical efficiencies can be estimated using Stochastic Frontier
Approach (SFA) or Data Envelopment Analysis (DEA), which is a non-parametric approach. DEA assumes that
there are no random effects in production. The current study therefore employed the stochastic production
frontier approach because most farmers operate under uncertain conditions (Abedullah and Ahmad, 2006).
Review of literature revealed that Cobb Douglas and Translog production functions are the widely used forms in
agriculture. However, Translog production function specification suffers from multicollinearity problem as a
result of the square and interaction terms of the inputs used (Hussain et al., 2012). The current study therefore
estimated a Cobb Douglas production function, specified as:
= , + −
Where Yi is the output; xi is a vector of inputs quantities used in production; β is a vector of parameters of the
3. Journal of Economics and Sustainable Development www.iiste.org
ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)
Vol.4, No.10, 2013
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production function. The frontier production function {f (xi, β)} measures the maximum potential output from a
vector of inputs. The error components vi and ui causes deviations from the frontier.
vi is the systematic error component which captures random deviations from the frontier, caused by factors
beyond the farmers’ control such as temperature and natural hazards. It is assumed to be independently and
identically distributed with a mean of zero and constant variance –N (0, σv
2
) and independent of ui.
ui is a non-negative error component that captures deviations from the frontier caused by controllable factors . It
represents the inefficiencies in production. It is assumed to be half normal, identically and independently
distributed with a mean of zero and constant variance-N (0, σ 2
).
Technical efficiency (TE) is defined in terms of the observed output relative to the production frontier, given the
available technology, such that 0≤TE≤1.
The production function can be log linearized to be:
= + + −
Where Yi is dry paddy in kg/acre;x1 is seed in kg/acre;x2 is fertilizer in kg/acre;x3 is labour man-days/acre; x4 is
chemical costs in Kenya shillings/acre;β0 is the intercept: βk are the production function parameters to be
estimated; vi and ui are as defined above.
Cobb-Douglas functional form is used in this study because the coefficients estimated directly represent
elasticity of production (Abedullah and Ahmad, 2006). Cobb-Douglas production function is adequate in the
representation of the production process since we are only interested in the efficiency measurement, and not
production structure (Taylor and Shonkwiler, 1986). Furthermore, Cobb Douglas production function has been
widely applied in estimating farm efficiencies (Ahmad et al., 1999; Kebede, 2001; Hassan and Ahmad, 2005;
Abedullah and Ahmad, 2006; Ogundari and Ojo, 2007; Abedullah and Mushtaq, 2007; Oladeebo and Fajuyigbe,
2007; Narala and Zala, 2012; Hussain et al., 2012).
There is evidence that socioeconomic variables influence producers’ efficiency, which will be included in the
inefficiency model (Seyoum et al., 1998; Oladeebo and Fajuyigbe, 2007). The inefficiency effects model is
specified as:
= +
Where,
µi is farm specific inefficiency; γ0 is the intercept; γk is the parameter of the kth
explanatory variable; z1 is farming
experience in years;z2 is gender (1=male, 0=female); z3 is number of years of formal education;z4 is extension
contacts in the year 2011(1=accessed extension services, 0=did not access extension service); z5 is off farm
income (1=earns off farm income, 0=do not earn off farm income); z6 is distance to market (km); z7 is income
level 1 in Ksh./year(1=earns between 1-30,000, 0=otherwise); z8 is income level 3 in Ksh./year(1=earns between
60,001-90,000, 0=otherwise); z9 is income level 4 in Ksh./year(1=earns between 90,001-120,000, 0=otherwise)
The models were estimated using STATA version 10, using the maximum likelihood estimation method.
4. Journal of Economics and Sustainable Development www.iiste.org
ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)
Vol.4, No.10, 2013
12
3.0 Results and discussion
Table 3: Descriptive statistics (N=221)
Age in years
15-30 3.20
31-45 27.60
46-60 34.80
61-75 30.30
Above 75 4.10
Farming experience in years
0-5 6.33
6-10 19.46
11-15 21.27
Above 15 years 52.94
Education level
None 7.69
Primary education 61.09
Secondary education 28.05
College 2.26
University 0.90
Annual income category (Kenya shillings)
1-30,000 3.62
30,001-60,000 18.55
60,001-90,000 49.77
90,001-120,000 22.17
120,001-150,000 5.88
Earned off farm income 39.37
Had access to extension services 76.47
Table 3 represents the descriptive statistics. Rice production in Ahero Irrigation Scheme, in Kenya is dominated
by male farmers who comprised about 70% of the sampled farmers. Most farmers are in the 46-60 years category
which was about 35% of the sample, with a mean of 54 years. This implies that rice farming is mainly practiced
by older farmers. Consequently, about 53% of the sampled farmers have more than 15 years farming experience,
with an average of 18 years. Most farmers, about 61% had completed only primary school education, with a
mean of 7 years of formal education. About half of the sampled respondents earned 60,001-90,000Kshs annually,
5. Journal of Economics and Sustainable Development www.iiste.org
ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)
Vol.4, No.10, 2013
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with a mean of Kshs 79,202. About 39% of the respondents earned off farm income while 76% had access to
extension services with a mean of 1.86 contacts during the 2011/2012 season.
Table 4: Summary statistics of output, input and other variables
Variable Mean Std. error
Dry paddy (kg/acre) 2024.21 36.76
Fertilizer(kg/acre) 83.60 2.05
Seed(kg/acre) 25.25 0.21
Labour (man-days) 97.25 0.85
Chemicals cost (Kshs./acre) 494.07 23.23
Land size cultivated (acres) 3.23 1.23
Distance to market(km) 3.07 1.22
Source: computed from field survey data 2012
Rice farmers in Ahero Irrigation Scheme harvested about 2024kg per acre. Farmers applied on average 84kg and
25kg of fertilizer and seeds respectively per acre. The average labour used in rice production was 97 man-days
per acre. Farmers in Ahero irrigation scheme spent about Kshs 494 on chemicals used in rice production to
control diseases. The average land size under paddy was 3 acres while distance to market was about 3km (Table
4).
Table 5: Maximum likelihood estimates of the stochastic production function for rice production
Variable Coefficient Std. error Z value
Fertilizer 0.085 0.050 1.68*
Seed -0.118 0.137 -0.86
Labour (man-days) 0.430 0.141 3.04***
Chemical cost -0.019 0.009 -2.18**
Sigma2
61.308 137.501
Gamma
Mean technical efficiency
0.999
0.82
0.001
H0: No inefficiency component -5.605***
Log likelihood -23.331
Prob>chi2
0.0019
Source: Computed from field survey data 2012 *,**,*** means significance at 10%, 5% and 1% level
Table 5 represents the results of the MLE of the Cobb Douglas production function. The null hypothesis that
there is no inefficiency was rejected at 1% level of significance, indicating that there were inefficiencies in rice
production. The Wald statistic was significant at 1% level of significance indicating that the variables included
fits the model appropriately. The Gamma variable shows that about 99.9% of variations in productivities among
farmers is caused by farmer specific inefficiencies. This is particularly true for Ahero irrigation scheme because
the physical conditions such as weather conditions and soil characteristics are similar.
Three of the four variables are significant. Fertilizer and labour coefficients are positive and significant while
chemical cost coefficient is negative and significant. This implies that increase in fertilizer and labour would
increase the output while increase in chemical costs reduces rice productivity. The mean technical efficiency of
0.82 shows that productivity can be increased by 18% if the inefficiencies are eliminated, using the same input
levels.
Table 6: Elasticity of production and returns to scale
Variable Elasticity
Fertilizer 0.085
Seed -0.118
Labour (man-days) 0.430
Chemicals cost -0.019
Returns to scale 0.378
Source: Computed from field survey data 2012
The estimated coefficients of a Cobb Douglas production function can be directly interpreted as elasticities of
production. Labour has the highest elasticity of production of 0.43 followed by fertilizer (Table 6). This implies
that a 10 percent increase in man- days and fertilizer will lead to a 4.3 percent and 0.8 percent increase in dry
6. Journal of Economics and Sustainable Development www.iiste.org
ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)
Vol.4, No.10, 2013
14
paddy respectively. However, increase in seed quantity and chemical cost reduces the output. The value of
Returns to scale of 0.35 indicates that rice farmers are operating in a decreasing returns to scale stage.
Table7: Efficiency score distribution (N=220)
Efficiency score range Percentage
0.20-0.30 0.5
0.31-0.40 1.4
0.41-0.50 2.7
0.51-0.60 2.7
0.61-0.70 7.7
0.71-0.80 15.9
0.81-0.90 48.2
Above 0.90 20.9
Maximum TE 0.95
Minimum TE 0.30
Mean TE 0.82
Source: Computed from field survey data 2012
The estimated farm specific technical efficiency ranged between 0.30 and 0.95 with a mean of 0.82 (Table 7). It
is observed that about 31% of the sampled farmers operate below the mean efficiency score of 0.82. However,
about 21% of the farmers operate above 0.90 level of technical efficiency. The mean efficiency score of 0.82
indicates that in the short run rice productivity can be increased by 18% through reduction of inefficiencies.
Table 8: Inefficiency effects model
Variable Coefficient Std. error t value
Gender -0.050 0.18 -2.79***
Education level -0.007 0.128 -0.57
Farming experience -0.002 0.001 -1.98**
Extension contact -0.010 0.019 -0.55
Off farm income 0.018 0.017 1.05
Income level 1 (1-30,000) 0.137 0.044 3.11***
Income level 3 (60,001-90,00) -0.074 0.022 -3.41***
Income level 4 (90,001-120,000) -0.091 0.025 -3.69***
Distance to market 0.007 0.004 1.68*
Constant 0.311 0.037 8.33***
Source: Computed from field survey data 2012
Table 8 represents the results of technical inefficiency effects model. The coefficients of farming experience,
income levels and distance to market had the expected priori signs and were significant in determining farmers’
efficiency in rice production. Farmers with more experience are more efficient than farmers with less experience
in farming. Experience helps farmers in using farming techniques that reduce the inefficiencies. Similar findings
were reported by Kuria et al. (2003), Abedullah and Ahmad (2006), Kinkingninhoun-Meˆdagbe´ (2010), Narala
and Zala (2010), and Maganga (2012). As the income levels of the farmers increased, so did their efficiency.
Farmers who earned income in level 1 (Ksh1-30,000) had lower efficiency compared to those in income levels 2
(Ksh60,001-90,000) and 3 (90,001-120,000). Income is a proxy for wealth, implying that wealthy farmers can
afford expensive farming inputs which improves their productivity. Ojo (2012) used farm income which was
positively related with efficiency, although was found to be insignificant. Distance to market is positively related
with inefficiency, implying that as distance increases, the inefficiencies in production also increase. The gender
variable is also significant in determining farmers’ efficiency. Male rice farmers were found to be more efficient
compared to their female counterparts.
Education level, extension contact and off farm income have the expected signs although not significant.
Increase in education level reduces the inefficiencies in rice farming. This is consistent with findings of Kuria et
al. 2003, Abedullah and Ahmad (2006), Abedullah et al. (2007), Maganga (2012) and Ojo (2012). Contact with
extension worker reduces the inefficiencies as expected. Off farm income on the other hand increases the
inefficiencies rice production. Rice farming is a labour intensive enterprise hence involvement in off farm
activities reduces the time devoted to farming. Similar findings were reported by Maganga (2012).
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Vol.4, No.10, 2013
15
4.0 Conclusion and policy implications
The study has revealed that rice farmers in Ahero irrigation Scheme are not fully technically efficient in using
the productive resources. The results of Cobb Douglas production function shows that increase in fertilizer and
labour in rice farming could increase its productivity. On the other hand, seed and chemical cost reduces rice
productivity. Policies should therefore aim at reducing the cost of productive inputs such as fertilizer and
chemicals in order to enable farmers increase their usage.
Farming experience, gender, income level and distance to market were found to be important determinants of
technical efficiency. Policies should therefore target improving transport infrastructure in the region to improve
on efficiency. This will improve market access for both produce and inputs. Rural households’ incomes should
also be improved, which improves on adoption of agricultural technologies. This can be achieved by improving
productivity through use of improved technologies such as high-yielding varieties and fertilizer, improving
market access, and reducing postharvest losses.
Improving farmers’ efficiency in rice production therefore has a potential of increasing rice production in the
country. This in turn will have direct effects of increased output, hence food security, increased income among
the farmers and reduction of the supply demand gap which will reduce rice import bill to be used in other
development initiatives.
Acknowledgement
The authors acknowledge the financial support from the African Economic Research Consortium (AERC).
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