November, 2020 AGRICULTURAL TRANSFORMATION AGENDA SUPPORT PROGRAM PHASE ONE FEDERAL GOVERNMENT OF NIGERIA/ AFRICAN DEVELOPMENT BANK SUPPORTED AGRICULTURAL TRANSFORMATION AGENDA SUPPORT PROGRAM PHASE ONE (FGN/AfDB - ATASP-1) NATIONAL PROGRAM COORDINATION TEAM (NPCT)
November, 2020 FEDERAL GOVERNMENT OF NIGERIA/ AFRICAN DEVELOPMENT BANK SUPPORTED AGRICULTURAL TRANSFORMATION AGENDA SUPPORT PROGRAM PHASE ONE (FGN/AfDB - ATASP-1) NATIONAL PROGRAM COORDINATION TEAM (NPCT) ISBN: 978-978-988-461-2
also goes to Zonal Program Coordinators and their teams in the Program states of Anambra, Enugu, Niger, Kebbi, Sokoto, Jigawa and Kano. They provided all they could in order to see the success of the data collection, and they also participated in accompanying the consultants, enumerators and the supervisors to the field in the various states. We will like to also appreciate the leaders of the various farming communities we visited for mobilizing the respondents and for organizing meetings with various trade groups. We also want to recognize and appreciate the team of data coders and the data analyst who tirelessly analyzed and summarized the data, we are equally grateful to other support staff of the Program headquarters office for their hospitality which contributed immensely towards our welfare as well as accommodating us during the preparation of this report.
Finally, we are grateful to the African Development Bank (AfDB), especially the National Program Coordinator ATASP-1 for the opportunity given to us to serve as consultants in this national assignment and we accept responsibility for all views and errors in this report.
DR.A.Y. NURA Team Leader ii
e acknowledged and appreciated the tremendous support and cooperation received from management staff of ATASP-1 at the headquarters who went extra mile toWsupport our data and other logistics requirements on time. Their contributions at the initial stage of this work especially during the preparation of the survey instrument is graciously Ouracknowledged.sincereappreciation
ACKNOWLEDGMENT
TIMEFRAMEACRONYMSLISTLISTACKNOWLEDGEMENT...............................................................................................................iiOFTABLES...........................................................................................................................viOFFIGURES........................................................................................................................vii..................................................................................................................................ixATASP-1INFORMATIONSHEET.................................................................................................x-MAINMILESTONES...........................................................................................x EXECUTIVE SUMMARY .................................................................................................................xi 1.0 INTRODUCTION ..............................................................................................................1 1.1 Background of the Study......................................................................................................1 1.2 Program ReviewATASP-1...................................................................................................2 1.1 Program Goal and Objectives...............................................................................................3 1.2 Program End-Line Outcomes ..............................................................................................3 1.3 Program Implementation Strategy .......................................................................................3 1.4 Program Components and Description.................................................................................3 Component 1: Infrastructure Development ...............................................................................3 Component 2: Commodity Value Chain Development..............................................................3 1.5 Justification for Study.........................................................................................................4 1.6 Objectives of the Survey ......................................................................................................5 2.0 METHODOLOGY.............................................................................................................7 2.1 StudyArea ...........................................................................................................................7 2.1.1 Bida-Badeggi SCPZ (Niger State)..............................................................................7 2.1.2 Adani-Omor SCPZ (Enugu andAnambra States) .......................................................8 2.1.3 Kebbi-Sokoto SCPZ (Kebbi and Sokoto States) .........................................................8 TABLE OF CONTENTS iii
2.1.4 Kano-Jigawa SCPZ (Kano and Jigawa States)............................................................9 2.2 Survey Design ...................................................................................................................10 2.4 Sampling Technique and Sampling Size ............................................................................10 2.4 Method of Data Collection.................................................................................................10 2.5 Data Coding, Entry and Processing ....................................................................................12 2.6 Analytical Techniques......................................................................................................12 2.6.1 Z-test ...........................................................................................................................12 2.6.2 Farm budgeting technique............................................................................................13 2.6.3 Double Difference..........................................................................................................13 2.6.4 Multiple regression model..............................................................................................13 2.6.5 Limitation of the Study ...................................................................................................14 CHAPTER THREE .....................................................................................................................15 FINDINGSAND DISCUSSION ...................................................................................................15 3.0 FARMERS .............................................................................................................................15 3.1 Demographic Characteristics of farmers across zones...............................................................15 3.1.1 Distribution of farmers according to their cropping enterprise across zones ....................16 3.1.2 Distribution respondents according to special needs .....................................................16 3.1.3 Gender of farmers ...........................................................................................................16 3.1.4 Marital status of farmer ...................................................................................................17 3.1.5 Level of education...........................................................................................................17 3.1.6Age of household head (years) ........................................................................................18 3.1.7 Household Size...............................................................................................................18 3.2 Estimation of Farmer'sAverage Income....................................................................................20 3.2.1 Profitability of sorghum enterprise..................................................................................20 3.2.2 Profitability of paddy rice Enterprise ............................................................................21 3.2.3 Profitability of Cassava enterprise ..................................................................................21 3.3 Rate of increase of real income of beneficiaries..............................................................23 3.3.1 Change in Output from Crop Enterprise ..........................................................................23 3.3.2 Change in price of Crops .................................................................................................24 3.3.3 Change in real income of crop enterprise per hectare.......................................................25 3.4 ComparativeAnalysis of Output, Prices of Crops and Income of farmers..................................27 3.4.1 Impact ofATASP-1 on output of farmers across zone ......................................................27 3.4.2 Impact ofATASP-1 on selling price of crops at harvest by farmers across zone................28 3.4.3 Impact ofATASP-1 on net income of farmers across zone ...............................................29 iv
3.5 Factors Influencing Profitability of Crop EnterpriseAmong beneficiariesAcross Zone ....30 3.6 Effect of GoodAgronomic Practices (GAP) Technologies among farmers ........................32 3.7 Effectiveness of support for GoodAgronomic Practices (GAP) among farmers ................33 3.8 Type of Inputs Support needed by farmers across zones.....................................................34 3.9 Impact of GoodAgricultural Practice on beneficiaries' income..........................................35 3.10 Constraints militating against wealth creation among farmers.........................................35 CHAPTER FOUR........................................................................................................................38 FINDINGSAND DISCUSSION ...................................................................................................38 4.0 PROCESSORS.........................................................................................................................38 4.1 Socio-economic Characteristics' of Processors across SCPZs...................................................38 4.1.1 Gender of processor ........................................................................................................38 4.1.2 Level of education of processors ...................................................................................38 4.1.3Age of household head (years) ........................................................................................39 4.1.4 Household size of Processors........................................................................................39 4.1.5 Experience of Processors ................................................................................................40 4.2 Type of crops processed across SCPZs......................................................................................40 4.2.1 Types of value chain activities undertaken across SCPZs by Processors..........................41 4.3 Usefulness of Support Received fromATASP-1 by the Processors............................................42 4.4 Change in level of patronage among beneficiaries before and afterATASP-1............................43 4.5 Change in Quantity (kg/Mt) of Output Processed PerAnnum across SCPZs .............................44 4.6 Change in processors monthly income ......................................................................................45 4.7 Perception of beneficiaries awareness on sorghum Processing Technologies Extended by ATASP-1 ........................................................................................................................................46 4.8 Perception of Beneficiaries awareness on Rice Processing Technologies Extended byATASP-1 ................................................................................................................................... 47 4.9 Perception of Beneficiaries awareness on Cassava Processing Technologies Extended 4.10byATASP-1....................................................................................................................................48Constraintsmilitatingagainstprocessingamongbeneficiaries...............................................50 CHAPTER FIVE..........................................................................................................................52 FINDINGSAND DISCUSSION ...................................................................................................52 5.0 FABRICATORS.......................................................................................................................52 5.1 Socio-economic characteristics' of the respondents. .................................................................52 5.1.1 Gender and Level of education of fabricators ..................................................................52 5.1.2Age of household head (years) ........................................................................................53 v
5.1.3 Household size of fabricators..........................................................................................53 5.1.4 Experience......................................................................................................................54 5.2 Usefulness of Support Received fromATASP-1 by Fabricators .........................................54 5.3 Change in level of patronage..............................................................................................55 5.4 Change in yearly income of fabricators..............................................................................56 5.5 Comparative analysis of fabricators' yearly income...........................................................57 5.6 Effect of training on quality of fabrication .........................................................................58 5.7 Constraints militating against fabrication among beneficiaries across zone.......................59 CHAPTER SIX.............................................................................................................................61 6.0 CONCLUSIONAND RECOMMENDATION ........................................................................61 6.1 Conclusion................................................................................................................................61 6.2 References:Recommendation......................................................................................................................62....................................................................................................................................63 vi
Table page Table 1: Sampling size for ProgramProgram beneficiaries, non-beneficiaries and control group............................................................................................... 11 Table 2: Distribution of farmers according gender, marital status and level of education 18 Table 3: Distribution of farmers according to their age and household size across SCPZs.............................................................................................. 19 Table 4: Profitability of sorghum enterprise per farmer....................................................20 Table 5: Profitability of paddy rice enterprise per farmer..................................................21 Table 6: Profitability of cassava enterprise ..................................................................... 22 Table 7: Change in output of crop enterprise.................................................................... 24 Table 8: Change in price of crops.....................................................................................25 Table 9: Change in income/ha of farmers.........................................................................27 Table 10: ImpactATASP-1 on output of farmers across zone.............................................28 Table 11: ImpactATASP-1 on selling price of crops at harvest by farmers across zone.......29 Table 12: ImpactATASP-1 on net income of farmers across zone......................................30 Table 13: Factors influencing profitability of crop enterprise among beneficiaries across zone....................................................................................32 Table 14: Effect of GoodAgronomic Practices (GAP) technologies among farmers.........33 Table 15: Type of inputs support required by famers across zones.....................................34 Table 16: Constraints militating against wealth creation among beneficiaries...................36 Table 17: Distribution of processors across gender and level of education.........................39 Table 18: Distribution of processors across age, household size and experience................40 Table 19: Type of crops processed across SCPZs..............................................................41 Table 20: Types of value chain activities undertaken across SCPZs..................................42 Table 21: Change in Quantity (kg/Mt) of Output Processed PerAnnum Across SCPZs....................................................................................................44 Table 22: Change in processors' monthly income..............................................................46 Table 23: Perception of beneficiaries on sorghum processing technologies extended byATASP-1........................................................................................47 Table 24: Perception of beneficiaries on rice processing technologies extended byATASP-1........................................................................................48 Table 25: Perception of beneficiaries on cassava processing technologies extended byATASP-1........................................................................................49 Table 26: Constraints militating against processing among beneficiaries..........................50 Table 27: Gender and level of education across SCPZs......................................................53 Table 28: Age, household size and experience across SCPZs.............................................54 Table 29: Change in yearly income of fabricators...............................................................57 Table 30: Comparative analysis of fabricators yearly income............................................58 Table 31: Constraints militating against fabrication among beneficiaries..........................60 LIST OF TABLES vii
Figure page Figure 1: Map of Nigeria showingATASP-1 Program location.............................................. 9 Figure 2: Consultants with the NPC during the review of the survey instruments............... 14 Figure 3: Enumerators training in one of the SCPZs............................................................ 14 Figure 4: Data collection exercise in one of the host communities...................................... 14 Figure 5: Pear review meeting and data cleaning exercise in one of the SCPZs.................. 14 Figure 6: Distribution of farmers cropping enterprise across zones..................................... 15 Figure 7: People with special needs...................................................................................... 16 Figure 8: Proportion of farmers that received input support fromATASP-1........................... 34 Figure 9: Impact of GoodAgricultural Practice on beneficiary's income.............................. 35 Figure 10: Land preparation in one of the Rice field.............................................................. 37 Figure 11: Supervision of wash bore drilling......................................................................... 37 Figure 12: Nursery establishment in one of the production clusters...................................... 37 Figure 13: Rice transplanting in progress in one of the production cluster 37 Figure 14: Well flooded transplanted rice field in one of the production clusters...................... 37 Figure 15: Awell-established rice field................................................................................... 37 Figure 16: Awell-established rice field................................................................................... 37 Figure 17: Some of the sorghum variety promoted by the Project through collaboration with the Research Institutes................................................................................... 37 Figure 18: Usefulness of support received from ATASP-1 by Processors............................. 43 Figure 19: Change in level of patronage among beneficiaries before and after Intervention...........................................................................................................ATASP-1 43 Figure 20: Cassava peeling at the village Garri processing centre......................................... 51 Figure 21: Cassava grating in progress in one of the village Garri processing centre........... 51 Figure 22: Pressing of grated cassava and fermentation process at the village Garri processing centre…............................................................................................... 51 Figure 23: Final processing process: Garri frying.................................................................. 51 Figure 24: Final processing process: Garri frying.................................................................. 51 Figure 25: Final processed product on display at the market centre....................................... 51 Figure 26: Rice mill in operation........................................................................................... 51 Figure 27: Usefulness of Support Received from ATASP-1 by Fabricators............................ 55 Figure 28: Change in level of patronage due to ATASP-1 intervention.................................. 55 Figure 29: Effect of training on quality of fabrication.............................................................. 59 Figure 30: One of the programme beneficiary in his workshop constructing thresher component.................................................................................................... 60 Figure 31: Final machine coupling by one of the ATASP-1 beneficiary fabricator 60 Figure 32: Rice parboiling unit in operation fabricated by ATASP-1 beneficiary.................. 60 Figure 33: Final coupling of rice thresher fabricated by ATASP-1 beneficiary...................... 60 Figure 34: Threshers ready for sell......................................................................................... 60 LIST OF FIGURES viii
ADPs Agricultural Development Programs AfDB African Development Bank ATA Agricultural Transformation Agenda ATASP-1 Agricultural Transformation Agenda Support Program -1 ESMP Environmental and Social Management Plan FAO Food and Agriculture Organization GAP Good Agricultural Practices GON Government of Nigeria FMARD Federal Ministry of Agriculture and Rural Development Ha Hectare IAR Institute for Agricultural Research ICRISAT International Crops Research Institute for the Semi-Arid Tropics IFAD International Fund for Agricultural Development IITA International Institute of Tropical Agriculture KPIs Key Performance Indicators LGAs Local Government Areas MANR Ministry of Agriculture and Natural Resources MFIs Micro-finance Institutions MIS Market Information System MTR Mid-Term Review MDGs Millennium Development Goals NAIC Nigerian Agricultural Insurance Corporation NARES National Agricultural Research and Extension Systems NCRI National Cereals research Institute NIRSAL Nigeria Incentive-based Risk Sharing for Agricultural Lending NRCRI National Root Crops Research Institute OECD Organization for Economic Co-operation and Development PRSP Poverty Reduction Strategy Processes PWSNs Peoples With Special Needs PZIUs Processing Zones Implementing Units SMEs Small and Medium Enterprises SCPZs Staple Crops Processing Zones UA Unit of Account USD United States Dollars VCAs Value Chain Actors WB World Bank ACRONYMS ix
ATASP-1 INFORMATION SHEET LOAN & GRANT RECIPIENT: Federal Government of Nigeria EXECUTING AGENCY: Federal Ministry of Agriculture and Rural Development FINANCING PLAN: SOURCE AMOUNT (MILLION) UNITINSTRUMENT OF ACCOUNT NAIRA African Development Bank Fund Loan 98.78 22,983.17 Loan African Development Bank Fund Grant 0.25 58.17 Grant Government 13.85 3,221.34 Beneficiaries 0.66 153.28 TOTAL PROGRAM COST 113.54 26,416.25 Source: ATASP 1 Appraisal Report TIMEFRAME - MAIN MILESTONES ACTIVITY TIMEFRAME Government Request for Bank Support August, 2012 Identification Mission November, 2012 Preparation Mission February, 2013 Concept Note Approval July, 2013 Appraisal Mission July, 2013 Board Approval October, 2013 Effectiveness April, 2014 Launch March, 2015 Completion December, 2020 Last Disbursement March, 2021 Source: ATASP 1 Appraisal Report and Information Sheet x
The distribution of farmers according to the cropping enterprises revealed that rice is the leading crop under cultivation among beneficiaries and non-Program beneficiaries. The result further revealed a low percentage (< 0.4%) distribution of Program beneficiaries among peoples with special needs (PWSNs). On gender wise, the distribution of famers across gender shows that the male gender was the dominant group, accounting for 67.6% and 80.2% for both beneficiaries and non-Program beneficiaries. Most of the sampled farmers have formal education. The result further shows that ATASP-1 farmers were relatively young, as reflected by the mean ages of 34 Detailsyears.
n 2012, the Government of Nigeria (GON) initiated the Agricultural Transformation Agenda (ATA) program designed to significantly reduce food imports by increasingIproduction of five key crops: rice, cassava, sorghum, cocoa and cotton. The Program envisions bringing agriculture back to the centre of Nigeria's economy that it once occupied, and by so doing solving the problems of rural poverty, youth unemployment and over-reliance on imported foods. Further, it is the mechanism by which Nigeria can replicate the agriculturedriven economic success stories of countries such as Brazil, Thailand, China, Malaysia, Indonesia, Kenya and Malawi. The AfDB funded Agricultural Transformation Agenda Support Program Phase-1 (ATASP-1) was subsequently established in 2015 as a lynchpin Program for the Agricultural Transformation Agenda (ATA) and is currently being implemented in four Staple Crop Processing Zones (SCPZs). The specific development objectives of the program include: to improve food and nutrition security, create jobs and enhance the incomes and shared wealth of the program beneficiaries on a sustainable basis through rice, sorghum and cassava value chains. The states covered by the Zones are Anambra and Enugu (Adani-Omor Zone), Niger (Bida-Badegi Zone), Kano and Jigawa (Kano-Jigawa Zone), and Kebbi and Sokoto (Kebbi-Sokoto Zone). The Program is presently providing interventions in over 200 rural communities spreading across 33 LGAs in the participating seven States.
of profitability analysis of sorghum enterprise per farmer across zones the shows that sorghum farmer's income varies across zones from N 142,296.0 per ha at Kano-Jigawa zone to N 148,401.0 per ha at Bida-Badeggi zone. The national average income shows that Program beneficiaries earned N111, 590.3 while the non-beneficiaries earned N95, 835.3. Sorghum output per hectare was higher (2.99MT) at Bida – Badeggi zone, while profit earned was more at Kebbi-Sokoto (N 73,470.0). The least cost of production was recorded at Kano-Jigawa zone
xi
EXECUTIVE SUMMARY
(N75, 302.0), while the highest production cost was observed at Bida-Badeggi zone (N89, 687.0)
Results of the profitability analysis of cassava enterprise per farmer across the zones equally revealed that Bida-Badeggi zone recorded the highest output of 33.99Mt/ha, followed byAdaniOmor zone (32.44Mt/ha) and Kano-Jigawa zone (22.61Mt/ha). Similarly, the result also shows that cassava farmer's income varies across zones from N 131,821.0/ha at Kano-Jigawa zone to N 150,008.0/ha atAdani-Omor zone. The national result shows Program beneficiaries earned more income; hence, more profit than non-beneficiaries. The least profit realised by cassava farmers under Program beneficiaries was observed at Bida-Badeggi zone (N 57,062.0/ha) and the highest was observed at Adani-Omor zone (N 76,857.0/ha). Comparatively, the percentage change in net income generated by the crop enterprises before and after the Program intervention across the staple crop processing zones is reported to be 29.9%, 39.3%, and 37.7% for paddy rice, cassava and sorghum farmers respectively. In all indices, the percentage change in output and net income of Project beneficiaries is over and above the 25% Project benchmark.
Similarly, study on output and income derived from crops enterprises using Z-test to test the hypothesis whether changes observed in output and income of crop per farmers per ha was as a result of ATASP-1's intervention displays a significant difference at (P<0.05), (P<0.01) and (P<0.001) for the selected crops. The regression coefficients of multiple determination which 2 measures factors that influence farmers income revealed R of 0.705, 0.691, 0.813, 0.671 and 0.937 for Adani-Omor, Bida-Badeggi, Kano-Jigawa, Kebbi-Sokoto and national result respectively, meaning that 70.5%, 69.1%, 81.3%, 67.1% and 93.7% variability in profit generated by farmers from crop enterprise at Adani-Omor, Bida-Badeggi, Kano-Jigawa, KebbiSokoto and National result respectively was accounted for by the explanatory variables included xii
National result of the Profitability analysis of paddy rice enterprise across zones shows that the total cost of paddy rice production was N 183,666.0 per ha and N 191,089.8 per ha for the beneficiaries and non-beneficiaries respectively. The highest cost of paddy rice production (N 189,177.0 per ha) for beneficiaries was observed at Bida-Badeggi Zones. Under the nonbeneficiaries categories, the high cost of paddy rice production (N 205,463.00) was observed at Kebbi-Sokoto. The national result shows that total output realised by paddy rice farmers was 6.18Mt/ha and 5.93Mt/ha for beneficiaries and non-beneficiaries respectively However, the result of paddy rice output across zones indicated Kebbi-Sokoto recorded the highest out of 6.79MT/ha and the least output was recorded at Bida-Badeggi zone (5.50Mt/ha). Furthermore, the result shows that unit price of paddy rice per Kg varies across zones from N 111 per Kg at Kebbi-Sokoto to N 124 per Kg at Bida-Badeggi. The national result shows that the unit price of paddy rice was N 115 per kg for beneficiaries and N 114.5 per kg for non-beneficiaries. The result also shows that paddy rice farmer's income varies across zones from N 243,376.0/ha at Kano-Jigawa zone to N 286,440.0/ha at Bida-Badeggi zone. The national result shows Program beneficiaries earned more income than non-beneficiaries. The least profit realised by paddy rice farmers under Program beneficiaries was observed at Kano-Jigawa zone (N 54,837.0) and the highest was observed at Kebbi-Sokoto zone (N 86,612.0). Generally, the result shows that paddy rice farmer's beneficiaries were more profitable than the non-beneficiaries.
On the other hand, Distribution of fabricators on gender basis revealed that, male gender was the sole dominant figure (100.0%) both beneficiaries and non-Program beneficiaries. Empirical result has shown that the level of patronage enjoyed by the fabricators has increased by 58.8%. In the same token, their annual income level has also increased by 33.3% which above the projected 25% increment cited by the Project log frame matrix. Result of the Z-test has revealed that this change in yearly income is significant (P<0.01). Conclusively, it can be inferred that ATASP-1 Program had impacted positively on the beneficiaries' income. Some of the major constraints militating against fabricator's activities were reported to be inadequate power supply (40.0%), lack of capital (20.0%), limited access to raw materials (20.0%) and inadequate market information (20.0%). The study is recommending among other things that the Program should try to render production input support to farmers as well as provide capacity building, market linkage and credit supply to all beneficiaries. Accordingly, ATASP-1 Program should try to be inclusive, and accessible especially to persons with disabilities. Article 27 of the UN convention on the Rights of Persons with Disabilities should be taken into consideration when designing future intervention Program. xiii
in the model. The explanatory variables are: age of farmers, household size, level of education, farming experience, farm size, cost of production, extension contact and adoption of improved technology. The F-value was significant at P<0.01 level of probability indicating a goodness of fit of the regression across zones. The coefficient of age (0.088) was positive and statistically significant (P<0.05), except at Bida-Badeggi zone. This implies that positive relationship exists between age of the farmers and profit realised from crop production in the study area. National result on perception of Good Agronomic Practices (GAP) Technologies amongst ATASP-1's farmers shows in various proportions that GAP had enhanced labour savings among farming communities. It has equally enhanced crops yield and farmers capacities in controlling soils erosion and enhancement of soil fertility Correspondingly, the result revealed that good agricultural practice promoted by the Program had impacted positively on farmers' income. However, some of the major constraints militating against wealth creation among farmer's beneficiaries were identified to be poor record keeping (27.5%), human conflict (36.3%), poor roads network (20.30%) and inadequate capital (17%). Reported inputs support preferred by ATSPS-1 farmers are; seeds, fertilizer, agro chemicals and credit support. Result on distribution of beneficiaries under processors category across gender showed that females were the dominant group, accounting for 60.0% and 44.5% for both beneficiaries and non-Program beneficiaries respectively. Most of the value chain activities undertaken by respondents across zone were rice milling and cassava processing. The study further shows that the level of patronage before and after intervention at national scale increased to 59.0%. Concurrently, the result equally revealed that average monthly income of the processors has increased by 46.0% within the period under study Some of the major constraints militating against processing activities amongst ATASP-1 beneficiaries were reported to be lack of power supply (22.2%), insufficient capital (14.8%) and inadequate market information (14.5%). Other constraints reported by beneficiaries include inadequate water supply (14.8%), low patronage (11.1%) and limited access to raw materials (7.4%).
Background of the Study
INTRODUCTION 1.1
Nigeria is endowed with abundant natural resources and has substantial agricultural potential. Agriculture is an important sector of the economy with high potentials for employment generation, food security and poverty reduction. However, these potentials has remained largely untapped which has led to the dwindling performance of the agricultural sector both domestically and in the international trade over years (Federal Ministry of Agriculture and Rural Development, FMARD, 2011). While Nigeria ranks first among the leading agricultural producers in the region, it is also the largest importer of staple products in West Africa. Despite the preponderance of hydrocarbons, the agricultural sector continues to play a decisive role in Nigeria's economic development. Agriculture accounts for about 36.5% of the creation of gross domestic product in the country and employs nearly 45% of the country's workforce (FMARD, 2014). In 2012, the Government of Nigeria (GON) initiated the Agricultural Transformation Agenda (ATA) program designed to significantly reduce food imports by increasing production of five key crops: rice, cassava, sorghum, cocoa and cotton. The overall objective was to increase agricultural production in order to increase domestic food production and generate employment (FMARD, 2014). The Nigeria Agricultural Transformation Agenda (ATA) is an initiative by which the Federal Ministry of Agriculture and Rural Development envisions bringing agriculture back to the centre of Nigeria's economy that it once occupied, and by so doing solving the problems of rural poverty, youth unemployment and over-reliance on imported foods. Further, it is the mechanism by which Nigeria can replicate the agriculture-driven economic success stories of countries such as Brazil, Thailand, China, Malaysia and Indonesia and, closer to home, Kenya and Malawi. In summary, the ATA is to bring about among others the following by 2015: creation of more than 3.5 million jobs along the value chains of rice, 1 1
1.0
In pursuance of ATA initiative, FGN introduced a number of import-substitution measures which include initiation of a policy mandating cassava flour inclusion in wheat flour, starting with a 10 percent cassava flour inclusion rate in 2012, to increase steadily to reach 40 percent by 2015; and increasing domestic rice production to make the country self-sufficient in rice production by 2015, when rice imports was to be banned. Also, attempts have been made to inculcate good agricultural practices (GAP) in the farmers by reaching out to them with required inputs of fertilizers and improved seeds. However, implementation has been spotty and all supporting infrastructure is grossly inadequate.
1.2 Program ReviewATASP-1
The AfDB funded Agricultural Transformation Agenda Support Program Phase-1 (ATASP-1) was initiated in Nigeria in 2015 and is currently being implemented in four Staple Crop Processing Zones (SCPZs). The states covered by the Zones are Anambra and Enugu (Adani/Omor Zone), Niger (Bida/Badegi Zone), Jigawa and Kano (Jigawa/Kano Zone), and Kebbi and Sokoto (Kebbi/Sokoto Zone). The Program is presently providing interventions in over 200 rural communities spreading across 33 LGAs in Seven States of Anambra, Enugu, Kano, Kebbi, Jigawa, Niger and Sokoto. 2
Many farmers continue to state that the GON policies and efforts have had little or no impact on their production as Nigeria still remains a food deficit country and domestic agriculture remains underdeveloped (Ojong andAnam, 2018).
cassava, sorghum, cocoa and cotton; and achieve food security by increasing production of key food staples of rice, cassava, and sorghum by 20 million metric tons (rice, 2 million metric tons; cassava, 17 million metric tons; sorghum, 1 million metric tons) (FMARD, 2017).
Nigeria is a country blessed with potentially good land and water resources required for sustainable agricultural development. It is a known fact that many government agricultural intervention development Programs in Nigeria have not had lasting impact on agricultural development and many have not yielded the expected results of sustained increase in food production (Amodu, et al., 2011).Agricultural production methods have remained undeveloped despite many years of efforts on technology generation and transfer in Nigeria. Rural financial supports are scarce and most rural finance policies implemented previously have impaired rather than assisted in improved agricultural production (IFPRI, 2012). However, in an attempt to alleviate poverty among rural Nigerians and also to increase the incomes and productivity of the rural inhabitants as an approach of meeting up with the millennium development goals (MDGs) of food sufficiency and poverty eradication, the Federal Government of Nigeria through the pooled African Development Bank came up with ATASP-1 Program to finance the development of ATASP-1 lands by introducing small-scale farmers and some infrastructure facilities (Schools, Clinics, Markets, Roads & Bridges and Irrigation Scheme) in states with ATASP-1 development potentials. This was the first phase of the program which will subsequently followed by the second phased calledATASP-II.
1.4 Program Components and Description
1.1 Program Goal and Objectives
The program implementation strategy is based on commodity value chain development approach. This implementation strategy is geared towards ensuring improved crop productivity and continuous linkages with the off-takers of produce leading to incremental food supply and strong partnership of value chain actors in the domestic markets, thereby contributing to enhanced food and nutrition security, promoting employment creation, promoting income generation and wealth creation, and reducing hunger in Nigeria.
1.3 Program Implementation Strategy
The major outcomes expected from the interventions are: a) 20, 000 metric tons of food crops produced per annum b) 350, 000 Revised new Jobs created along commodity value chains c) 25% Increased Incomes of beneficiaries. d) 40, 000 RevisedYouths trained on agribusiness and enterprise development
1.2 Program End-Line Outcomes
The main/primary goal of ATASP-1 is to contribute to poverty reduction, employment generation, import substitution, economic diversification and growth of Nigeria, particularly inAdani-Omor, Bida-Badeggi, Kano-Jigawa and Kebbi-Sokoto Staple Crop Processing Zones. The specific development objectives of the program include: to improve food and nutrition security, create jobs and enhance the incomes and shared wealth of the program beneficiaries on a sustainable basis through rice, sorghum and cassava value chains.
Component 2: Commodity Value Chain Development Capacity development for relevant ministries and departments; private and communitybased institutions; training value chain actors in technical and managerial skills; 3
These communities and Local Government Areas of the seven States occupy about 194,426 square kilometre of land area with a population of 32,121,944 people who are predominantly farmers and rural entrepreneurs.
The Program is made up of three complementary and mutually reinforcing program components, as described below: Component 1: Infrastructure Development Rehabilitation of agricultural and ancillary social infrastructure, namely: irrigation water conveyance canals, various hydraulic structures, feeder roads, primary schools, community health centres, provision of potable water supply and sanitation/hygiene facilities; rehabilitation of demonstration and technology centres, and community produce markets.
Sub-Component 2: Skill development activities on (i) agribusiness development, (ii) processing and marketing, and (iii) promotion of youth entrepreneurship in agriculture.
Component 3: Program Management Coordination of program activities; management based on results measurement framework; monitoring and evaluation; implementation of Environmental and Social Management Plan (ESMP); program procurement, disbursement, financial management, audit and reporting. The mandates of the CGIARs include; IITA for cassava; AfricaRice for rice; and ICRISAT for sorghum with their national partners, and IITA as the prime contractor for executing the outreach sub-program. This Sub-Program has three sub-components as follows: Sub-Component 1: Technology verification and extension with activities on (i) Technology verification, (ii) seed systems, planting material production, and diffusion.
promoting use of science & technology; training in post-harvest reduction methods; business and entrepreneurship training; training of communities and health workers on prevention and management of common diseases, nutrition and hygienic practices; development of market information system (MIS); management of environmental and social impacts; implementation of policies to promote private sector investment in Thereagriculture.isanoutreach
sub-program ofATASP-1, which is embedded in the component 2 of the program, and implemented by IITA and its consortium, comprising IITA, AfricaRice and ICRISAT The responsibility of implementing Component 2, rest on CGIAR centres in Nigeria and with the objective of transforming Nigeria's cassava, rice, and sorghum sectors with the three CGIAR centres.
Sub-Component 3: Effective program management comprising activities such as: (i) M&E studies, (ii) performance management & reporting, (iii) establishment of an appropriate management structure, and (iv) the establishment of Youth Agribusiness Training Centres. The targeted beneficiaries of the outreach sub-program include; farmers' groups, processor groups, farmer input/service provider groups, sensitized persons (for market information services, open days, mass media), fabricators, marketers and transporters, seed companies, the youths, training participants, and policy makers.
1.5 Justification for Study Nigeria's rural economy till date is driven by agriculture. Until the early 1960s when Nigeria first discovered oil, popularly called the 'Black gold' at Oloibiri, agriculture was the mainstay of the overall economy and accounted for over 60% of global exports of palm oil, 30% of groundnut, and 15% of cocoa. However, NBS (2008) estimate show that 4
the petroleum sector now generates about 95% of Nigeria's external earnings as against agriculture which contributes less than 5%. Like in many rich and poor countries, the issue of poverty and well-being has been of great concern. As a result, poverty reduction strategy processes (PRSP) have been at the centre-stage of development programs.
Nigeria's government is more eager than ever to move its populace out of poverty while the rich nations are increasingly aware of the need to promote security through poverty reduction (NBS, 2004).
(i) estimate the average income data ofATASP-1 beneficiaries across PZIUs; (ii) determine the proportion of the participants that attained this estimated income level; (iii) ascertained the rate of increase in real income of beneficiaries; (iv) compare the average income before and after ATASP-1 intervention across the SCPZs; (v) validate the inclusiveness of the ATASP-1 beneficiaries in terms of youth and gender; (vi) ascertain the factors influencing the profitability rate ofATASP-1 beneficiaries; (vii) determine the effect of GAP (for rice, cassava and sorghum) on farmers' income generated. 5
The objective of this study is therefore to estimate the average income of the ATASP-I participants. The Beneficiary income and Profitability Assessment has the main objective of determining the estimate average income, profitability rate and assess the effect on ATASP-1 beneficiaries who are supported under Outreach Program (rice, sorghum and cassava value chain) at the Adani-Omor, Bida-Badeggi, Kano-Jigawa and Kebbi-Sokoto Staple Crop Processing Zones (SCPZs). In specific terms, the objectives of the survey are to:
The principal goal of the Program which is to sustainably increase the income of beneficiaries is being achieved through financing investment in productive assets and community infrastructure; strengthening the capacities of States and Local Government to deliver efficient services and also promoting socially inclusive and www.ccsenet.org/ijef International Journal of Economics and Finance Vol. 6, No. 7; 2014 177 environmentally sustainable management of natural resources. The report of the Mid-Term Review (MTR) conducted on the program shows that household income generation, progression and sustainability under ATASP-1 implementation bringing enhancing income and wealth creation (baseline of N 215,000.00 per annum for rural farmers and N 302,000.00 per annum for rural entrepreneurs) - 20.5% incremental income over baselines achieved, and total accumulative revenue to farmers and entrepreneurs to N 36.224 billion.
1.6 Objectives of the Survey
(viii) determine the effect of technology adopted on entrepreneurs (fabricator and processors) income generated.
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(ix) identify the constraints militating against the wealth creation among the ATASP1 beneficiaries, and (x) make recommendations for improvement in wealth creation.
2.0 METHODOLOGY
2.1.1 Bida-Badeggi SCPZ (Niger State) Niger State is in the North Central of Nigeria, with tropical climate. The climate and weather varies by the interaction between the moist, northerly air coming off theAtlantic Ocean and the drier northern air. The wet and dry seasons are dominant. The rain season span April - September, with annual rainfall of between 750 mm and 3,000 mm. The dry season starts around October and terminates in April with high temperatures and low humidity. Generally, the south-westerlys wind current is predominant during the rainy season while the north-early current dominates the dry season (AfDB, 2013). The mean o oannual maximum and minimum temperatures are put at 32 C and 20 C respectively The major soil types are fluvisols, regosols, gleysols, acrisols, ferrasols, alisols, lixisols, cambisols, luvisols, nitosols, arenosols and vertisols (Food and Agriculture Organisation, undated). These soils are associated with low productivity given inadequate moisture retention capacity and low organic matter (AfDB, 2013). The estimated average yields for rice, sorghum and cassava in Niger State were 3.12 mt/ha, 1.32mt/ha and 20.63mt/ha respectively (Federal Ministry of Agriculture & Rural Development, 2014). The main river is the Niger River, with the Kaduna River being its 7 2
2.1 StudyArea The study was carried out in all the four Staple Crop Processing Zones (SCPZs) of ATASP-1 including Adani-Omor, Bida-Badeggi, Kano-Jigawa and Kebbi-Sokoto as shown below Each of the zones has distinct agro-ecological features and agronomic practices adopted by the Program beneficiaries which include farmers and farmers' cooperatives, commodity processors, private sector operators and registered Small and Medium Enterprises (SMEs), input dealers and service providers in the four staple crop processing zones.
The Climatic condition in Adani-Omor SCPZ is largely influenced by the interaction between the moist, northerly air of the Atlantic Ocean and the drier air arriving from the north. The Zone has two dominant seasons: the wet and the dry seasons. The rain season begins in late January/February to early March lasting through September, with rainfall range of between 1.2mm in January and 330.1mm in September The dry season is short from December to February, being closer to the damp ocean winds. The break in rainfall during late summer rarely results in a complete dry season but gives farmers a brief period in which to harvest their crops (AfDB, 2013). The Zone is affected by two principal wind currents. The south-westerlys dominate the rainy season of the year while north-easterlies (harmattan winds) dominate the dry season. Depending on the shifts in the pressure belts in the Gulf of Guinea, these winds are interspersed respectively by south-easterlies and north-westerlys in different parts of the year. The temperature in Adani-Omor is typically higher during the dry season, with average annual maximum of o o31 C and average annual minimum from 20 C. Adani-Omor zone lies at the base of the sedimentary basins that occupy the central x-shaped area in the country. It is predominantly within sedimentary formations, which give rise to sandy and less variable soils that are deficient in plant nutrient (AfDB, 2013). The average yield of rice in Enugu and Anambra States range between 1.7 mt/ha and 3.8mt/ha, while that of cassava span 18.92mt/ha - 25.41mt (FMARD, 2014).
2.1.3 Kebbi-Sokoto SCPZ (Kebbi and Sokoto States)
key tributary. The Zone is also associated with numerous rapids and waterfalls. The Zone is generally Guinea Savannah.
The highlands and hills are predominantly igneous structures, whilst the valleys are the sedimentary basins. The Zone is in the southern plains of the country Gently undulating plains, which become waterlogged during the rainy season, are found in these areas. The soils in this Zone can be classified into three (climatic) zones that are soil associations. The groups are: (i) Interior zone of laterite soils; (ii) Southern belt of forest soils; and (iii) Zone of alluvial soils (Mwangi and Kariuki, 2015). The major drainage system in the area is the Niger River and its tributaries. It is a perennial river but non navigable because of numerous rapids and waterfalls along its length (AfDB, 2013). Few large animals are found in the rain forest. Flora in the Zone varies from the freshwater swamp forests, which are diversified and includes varieties of palms, the Abura, and Mahogany, to the rain forest, which forms a belt with an average width of some 130 km. Principal trees include theAfrican mahogany, Iroko,African walnut, and the most popular export wood, the Obeche (AfDB, 2013).
2.1.2 Adani-Omor SCPZ (Enugu andAnambra States)
The climate and weather largely depends on the interaction between the moist, northerly air of the Atlantic Ocean and the drier air from the north. The climate is generally arid. Two main dominant winds are south-westerlys and north-easterlies which dominate the orainy and dry seasons. The average maximum and minimum temperatures are 35 C and 8
o18 C respectively. The main soil types are mainly vertisols, alisols, acrisols, ferrasols and arensol. These are soils of low productivity, given their low moisture retention capacity and low organic matter The Zone is endowed with surface water such as Rivers Rima, Niger, Zamfara, Ka and Shalla and underground water resources, including an estimated 400,000 ha of Fadama lands. The natural vegetation is savannah and arid in nature. The region is termed Sudan Savannah, associated with shorter grasses and scattered, droughtresistant tress like Baobab, Tamarind andAcacia.
Figure 1: Map of Nigeria showing ATASP-1 Program location 9
The climate for this Zone is generally arid, while two seasons are predominant, namely rainy and dry seasons. The rains commence by early April through September, with the peak of rainfall recorded in August, with an estimated quantity of about 800 mm. The dry season lasts from October toApril, with high temperatures and low humidity. Two key wind currents are associated with the zone, namely; the south-westerlys, which dominate the rainy season and the northeasterlies (harmattan winds), which is predominant in the dry season. The mean annual o omaximum temperature is 35 C, whilst the average annual minimum is 18 C in the north. The main soil types, like in most northern states are chiefly vertisols, alisols, acrisols, ferrrasols and arensol. These soils are associated with low productivity, given the inadequate moisture retention capacity and organic matter Yields in Kano and Jigawa are estimated at between 1.952.07mt/ha for wet season rice, 1.1-1.3mt/ha for sorghum and 5.92mt/ha for cassava (FMARD, 2014). The zone is the source of numerous flowing rivers, such as Zamfara, Ka, Shalla and Hadejia; in addition to shallow water resources. The natural vegetation is mainly savannah and those that flourish in arid conditions. The zone is Sudan Savannah, associated scattered, shorter grasses and drought-resistant trees such as the baobab, tamarind and acacia. The lands are sparsely vegetated and prone to wind and rain erosion.
2.1.4 Kano-Jigawa SCPZ (Kano and Jigawa States)
A multi-stage random sampling technique was adopted in selecting the respondents for the survey The first stage involved the stratification of respondents into the three value chain actors namely, farmers, processor and fabricators in the second stage, random sampling technique was used to select 182 farmers that are Program beneficiaries, 182 non-beneficiaries and 182 non-adopter giving a total of 546 respondents across zone. In the third stage, random sampling technique was used to select 20 processors that are Program beneficiaries, 20 non-beneficiaries and 20 non-adopters giving a total of 60 processors across zone. In final stage, random sampling techniques was used to select 20 fabricators that are Program beneficiaries, 20 non-beneficiaries and 20 non-adopters giving a total of 60 fabricators across zone. The holistic sample size was determined using the Yamane sample size determination formula (Equation 1) and representative sample was drawn at 5% precision level and 95% confidence level from the available profiles of the value chain actors (Table 1), following which, individual samples across value chain actors were based on their assumed preponderance in the total sample. n=where;Sample size, N= Population size and e= level of precision Based on the above formula, a total of 666 respondents were interviewed as presented in Table 1 below. 10
Sampling Technique and Sampling Size
2.2 Survey Design
The counterfactual survey design was employed for this study. The design, involving Program beneficiaries, non-beneficiaries and control group (non-adopters). This approach is a best practice procedure aimed at effectively determining the magnitude of impact and the issue of attribution during future milestone surveys (Mid-Term Evaluation and Impact Assessment). This approach had been successfully employed by various donor- assisted Programs and Programs across the globe, including Nigeria.
2.4
Table 1: Sampling size for Program beneficiaries, non beneficiaries and control group Sample size of Program beneficiaries value actorschain Staple Crop Processing Zones (SCPZs) Farmers OmorAdani- Bida Badeggi JigawaKano- SokotoKebbi- Total Rice 21 14 22 16 73 Sorghum 14 22 16 52 Cassava 21 14 22 57 Sub-total 42 42 66 32 182 Fabricators 5 5 5 5 20 Processors 5 5 5 5 20 Sub-total 52 52 76 42 222 Non beneficiaries value actorschain Staple Crop Processing Zones (SCPZs) Farmers OmorAdani- Bida-Badeggi JigawaKano- SokotoKebbi- Total Rice 21 14 22 16 73 Sorghum 14 22 16 52 Cassava 21 14 22 57 Sub-total 42 42 66 32 182 Fabricators 5 5 5 5 20 Processors 5 5 5 5 20 Sub-total 52 52 76 42 222 Control group (non adopters) value actorschain Staple Crop Processing Zones (SCPZs) Farmers OmorAdani- Bida-Badeggi JigawaKano- SokotoKebbi- Total Rice 21 14 22 16 73 Sorghum 14 22 16 52 Cassava 21 14 22 57 Sub total 42 42 66 32 182 Fabricators 5 5 5 5 20 Processors 5 5 5 5 20 Sub total 52 52 76 42 222 Total 156 156 228 126 666 Consultant computation (2020) 11
The data processing procedure for the survey covered the development of coding guide, data entry, data management (cleaning and editing) and data analysis modules. Data coding guide was professionally undertaken by the Data Analyst. The guide provided direction to the data entry clerks on how the questionnaires were to be coded. The guide further specified the questions from which data was derived, variable name, operational definition of the variable, coding options, variable type (numeric or alpha-numeric), the columns required by variables, as well as the measurement of each variable (scale, nominal, ordinal or string). For the binary response variables, zero and one were employed for coding, while strings were used for letters and numbers where applicable. Data entry was preceded by three days intensive training for the 15 coding clerks screened for the coding exercise. Data coding was undertaking by the coding clerks under the supervision of three experienced data entry supervisors using SPSS version 24.
2.5 Data Coding, Entry and Processing
2.6 Analytical Techniques
2.6.1 Z-test Z-test is any statistical hypothesis used to determine whether two samples' means are different when variances are known and sample is large (n ≥30). It is Comparison of the means of two independent groups of samples, taken from one population with known variance. To calculate the z-score, you will find the difference between a value in the sample and the mean, and divide it by the standard deviation.
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2.4 Method of Data Collection
Data were collected using structured questionnaire covering targeted value chain actors across zone using Trained ExtensionAgents (EAs).
The analytical tools used for the study were descriptive and inferential statistics. The descriptive statistics were employed to summarise data collected. These involved the use of percentages, figures, means and frequency distribution of Program beneficiaries, nonProgram beneficiaries and control across value chain actors into a number of classes with respect to socio economic characteristics of households, production information as well as other economic characteristics of the respondents. While the inferential statistics include z tests, Farm budgeting technique and multiple regression analysis.
NFI
GI =
GM =
Farm budgeting technique
TC =
equations2 and 3: = G1 … 3 NFIWhere;=Net
GI =
13
TVC =
are
GMWhere;=Gross
is
The farm budgeting technique was also employed to determine the level of costs, returns and net revenue that accrued to value chain actors. Oluwasola (2012) affirmed that the farm budget is a detailed physical and financial plan for the operation of the farm for a certain period of time. The farm budget technique is mathematically expressed in farm income (N) Gross income (N) Total cost of production (N) GM = Gross Margin: by definiti on the difference between gross income (GI) and the total variable cost (TVC). GI - TVC …(4) Margin (? /ha) Gross Income also termed total value of production: is the total physical product multiplied by the unit price of the product. Total Variable Costs: costs incurred on variable inputs which can be contributed to specific enterprises and vary according to output such as labour, fertilizer, seeds. TC
2.6.5 Limitation of the Study
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a) Timing of the exercise should take into cognisance the farming calendar of the host communities.
Figure 5: Pear review meeting and data cleaning exercise in one of the SCPZs
Figure
b) The extension agents need to be given re-orientation to be more committed to their 3: Enumerators training in one of the SCPZs Figure 4: Data collection exercise in one of the host communities.
Figure 6: Distribution of farmers cropping enterprise across zones 3
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3.1.1 Distribution of farmers according to their cropping enterprise across zones
The distribution of farmers according to their cropping enterprises across zones is presented on Figure 6. The national result shows that 53.8% and 51.6% of beneficiaries and non-beneficiaries produce rice across zone respectively. However, the national result also shows that 24.2% alike of the beneficiaries and non-beneficiaries were in to cassava production respectively with exception Kebbi-Sokoto zone. Under sorghum production, the national result shows that 22.0% and 24.2% of beneficiaries and non-beneficiaries respectively were in to sorghum production with exception Adani-Omor zone zone. There, it can be concluded that rice is the major producing crop across all the zones.
3.1 Demographic Characteristics of farmers across zones
FINDINGSAND DISCUSSION 3.0 FARMERS
The socio-economic characteristics of farmers includes type of cropping enterprise, special need, gender, level of education, age of household head and household size.
Figure 7 presents percentage distribution of Program beneficiaries among Peoples with Special Needs (PWSNs). According to the result obtained, only 0.3 % of the peoples under this category benefitted under farming enterprises promoted by the Program, which is dismally low The result further shown a dwindling percentage allocation of Program beneficiaries among PWSNs (0.2% and 0.1%) for fabricators and processing activities respectively As grievously as this data, the findings is closely related to the United Nations (2012) reports which stated that unemployment amongst these persons is as high as 70%. Furthermore, a 2006 United States survey, found out that only 35% of working-age persons with disabilities have economic opportunities compared to those without disabilities. This findings has important policy implication when taken into cognizance the United Nations Development Program study which opined that 80% of persons with disabilities live in developing countries, Nigeria inclusive. Although, the latest National Census (2006) did not capture the true position of the disability rate, but it was estimated that about 4.8 million Nigerians are living with one form of disability or theother, (Micheal-Olomu et. al., 2018).
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3.1.2 Distribution respondents according to special needs
Figure 7: People with special needs
3.1.3 Gender of farmers
The distribution of famers across gender shows that the male gender was the dominant group, accounting for 67.6% and 80.2% for both beneficiaries and non-beneficiaries respectively as presented in Table 2. The distribution across the zones further shows that 32.4% and 19.8% of the farmers were female for both beneficiaries and nonbeneficiaries respectively This trend is not unexpected and shows the extent of gender inequality in agricultural production. Numerous researchers, including Ihugba et al (2013) and Obiora and Emodi, (2013) have all established male dominance in food crop production in Nigeria. Igboji et al. (2015) however affirmed that gender disparity has grave implications for food security within the continent. This outcome justifies the need for effective targeting of beneficiaries, with particular focus on the vulnerable female and youths.
Marital status of farmer
3.1.5 Level of education Education is a social capital which could impact positively on household ability to take good and well informed production decisions. The distribution of farmers according to their educational status shows that 65.8% and 62.0% of the beneficiaries and nonbeneficiaries respectively acquired formal education ranging from primary to tertiary level from the national result as presented in Table 2. While the other zones had above 50%. However, only 14.3% and 11.0% of the beneficiaries and non-beneficiaries respectively were without any form of formal education, the other zones had above 10% of respondents within this category It is gratifying to note that the high population of educated beneficiaries is likely to impact positively on technology adoption under the Program. However, attention is still needed to be directed at the remaining Program population without formal education through awareness creation and education. Bifarin et al. (2010) established that high educational status of farm household member's increase income, reduces poverty, while enhancing competence and entrepreneurial spirit.
Results in Table 2 show that majority of the farmers were married, put at a national total of 70.3% and 72.5% for beneficiaries and non-beneficiaries respectively. This partly explains why they have large families. Except for Kano-Jigawa zone, that recorded 40.6% and 34.46% un-married population under the beneficiaries and non- beneficiaries respectively, all the other zones indicated less than 18% achievement across board. Thus, it is imperative that the program takes cognizance of beneficiaries' status. Being married affords the farmers opportunity of getting cheap family labour for farm and non-farm activities (Mignouna et al., 2011). Furthermore, the high proportion of married farmers is an indication that most respondents are likely to have family responsibilities and commitments, especially with regards to household food provision and upkeep, educational and health demands and savings. Kassie et al (2013), also observed that it is generally believed that males are often more energetic and could readily be available for energy demanding jobs like farming. The low percentage of the participating female farmers in Program could likely be attributed to traditional land tenure system widely practiced in the country which put women in disadvantaged position. Nevertheless, inferential evidences has shown that female in the study area usually involved in several other economic activities outside farming like food vendors, hair dressing, tailoring and petty trading.
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3.1.4
Source: Field Survey (2020) 3.1.6 Age of household head (years) Table 3 details the age of farmers across zones. The results show that the age of Program beneficiaries ranged from 27 years to 61 years. Similarly for the non-beneficiaries, the least age of 29 years was obtained with maximum age of 65 years. Further review of the results show that the farmers were generally young, as reflected by mean ages of 34 years and 40 years for Program beneficiaries and non-beneficiaries respectively The effects of these results are that most of the farmers are still active with positive implications for enhance productivity and household food security The outcome further shows that younger people are involved in the Program. Abdullahi (2012) obtained mean ages of 43 years and 37 years farmers respectively The age of household head is expected to have impact on labour supply, especially for crop production. Young people are stronger and are expected to cultivate larger farms than old people.
18 Table 2: Distribution of farmers according to gender, marital status and level of education across SCPZs Variables Adani Omor (n=42) Bida Badeggi (n=42) Kano Jigawa (n=66) Kebbi Sokoto (n=32) National (n=182) ATASP1 ANonTASP1 ATASP1 Non ATASP 1 ATASP1 Non ATASP 1 ATASP1 Non ATASP 1 ATASP 1 Non ATASP 1 Gender Male 30(71.4) 33(78.6) 29(69.0) 40(95.2) 41(62.1) 48(72.7) 23(71.9) 25(78.1) 123(67.6) 146(80.2) Female 12(28.6) 9(21.4) 13(31.0) 2(4.8) 25(37.9) 18(27.3) 9(28.1) 7(21.8) 59(32.4) 36(19.8) Marital status Single 10(23.8) 8 (19.0) 13 (31.0) 11 (26.2) 18 (27.3) 20 (30.3) 13 (40.6) 11 (34.4) 54 (29.7) 50 (27.5) Married 32 (76.2) 34 (81.0) 29 (69.0) 31 (73.8) 48 (72.7) 46 (69.7) 19 (59.4) 21 (65.6) 128 (70.3) 132 (72.5) Level of education None 8(19.0) 4(9.5) 6(14.3) 3(7.1) 7(10.6) 9(13.6) 5(15.6) 4(12.5) 26(14.3) 20(11.0) Islamic education 0 0 2(4.8) 8(19.0) 22(33.3) 30(45.5) 12(37.5) 11(34.4) 36(19.8) 49(26.9) Primary School 15(35.7) 17(40.5) 18(42.9) 12(28.6) 15(22.7) 10(15.2) 3(9.4) 9(28.1) 51(28.0) 48(26.4) Junior Secondar y School 10(23.8) 8(19.0) 9(21.4) 7(16.7) 8(12.1) 6(9.1) 6(18.8) 2(6.3) 33(18.1) 23(12.6) Senior Secondar y School 4(9.5) 10(23.8) 5(11.9) 4(9.5) 10(15.2) 8(12.1) 4(12.5) 5(15.6) 23(12.6) 27(14.8) Tertiary 5(11.9) 3(7.1) 2(4.8) 8(19.0) 4(6.1) 3(4.5) 2(6.3) 1(3.1) 13(7.1) 15(8.2)
3.1.7 Household Size
This refers to the number of individuals living in a household under the household head. The distribution of respondents according to household size composition is presented in Table 3. The results show that most of household head under Program beneficiaries had minimum of 1 wife and maximum of 3 wives with an average of 1 wife per head. Similarly, non-beneficiaries had minimum of 1 wife and maximum of 4 wives with an average of 1 wife per head. The result further indicated that similar trend was observed in Kano-Jigawa and Kebbi-Sokoto zones with average of 2 wives per head. The result of the number of children less than 18 years show that most of household head under Program beneficiaries had minimum of 1 child that is less than 18 years and maximum of 6 with an average of 3 per head. Similarly, non-beneficiaries had minimum of 1 child that is less than 18 years and maximum of 4 with an average of 2 per head. The result of the number
19 of children that are 19 years and above show that most of household head under Program beneficiaries had minimum of 1 child that is 19 years and above and maximum of 1 with an average of 2 per head. The result of the number of male and female household Members show that most of household head under Program beneficiaries had minimum of 1 male and 1 female members per household head. In addition, Program beneficiaries had maximum of 7 male and 4 female members per household head with average of 3 male and 2 female members. Similarly, non-beneficiaries had also a minimum of 1 male and 1 female members per household head. However, non-beneficiaries had maximum of 9 male and 6 female members per household head with average of 4 male and 3 female members. While it is recognized that household size plays a key role in subsistence agriculture where value chain actors rely on the number of people in the family for labour source; however, high number of household has grave implication for households expenditure and food security status of the participating households. 3: Distribution of farmers according to their age and household size across SCPZs (n=42)Omor Bida(n=42)Badeggi Kano(n=66)Jigawa Kebbi(n=32)Sokoto Tota National l (n=182)
Table
ATASP1 ANonTASP1 ATASP1 ANonTASP1 ATASP1 ANonTASP1 ATASP1 ANonTASP1 ATASP1 ANonTASP1 Age of House hold Head (years) Min 28.0 30.0 25.0 31.0 30.0 27.0 33.0 29.0 27.0 29.0 Max 69.0 71.0 65.0 57.0 66.0 60.0 68.0 70.0 61.0 65.0 Mean 31.0 40.0 39.0 36.0 33.0 40.0 35.0 42.0 34.0 40.0 Number of Wife/wives Min 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 Max 2.0 2.0 1.0 2.0 4.0 4.0 3.0 4.0 3.0 4.0 Mean 1.0 1.0 1.0 1.0 2.0 2.0 1.0 2.0 1.0 1.0 Number of Children < 18 yrs Min 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 Max 8.0 10.0 13.0 9.0 11.0 7.0 9.0 5.0 6.0 4.0 Mean 3.0 4.0 6.0 4.0 3.0 2.0 4.0 1.0 3.0 2.0 Number of children 19yrs and above Min 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 Max 7.0 9.0 8.0 10.0 3.0 5.0 3.0 6.0 5.0 12.0 Mean 3.0 4.0 2.0 5.0 1.0 2.0 1.0 3.0 2.0 4.0 Number of Male Household Members Min 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 Max 9.0 7.0 10.0 6.0 9.0 5.0 8.0 6.0 7.0 9.0 Mean 4.0 3.0 5.0 3.0 4.0 3.0 4.0 3.0 3.0 4.0 Number of Female Household Members Min 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 Max 6.0 3.0 5.0 4.0 7.0 9.0 5.0 8.0 4.0 6.0 Mean 3.0 1.0 2.0 2.0 3.0 4.0 2.0 3.0 2.0 3.0 Source: Field Survey (2020)
sVariable Adani
ATASP
Non
1 ATASP 1 Non ATASP 1 ATASP 1 Non ATASP 1 ATASP 1 Non ATASP 1 Total Cost (? ) 89,681.0 90,307.0 75,302.0 84,821.0 82,194.0 97,116.0 61,794.3 68,061.0 Output (Mt/ha) 2 99 1 91 2 67 1 83 2 06 1 74 1 92 1 53 Unit Price (? ) 99 0 95 0 88 0 92 0 92 0 102 0 69 8 72 3 Income (? ) 148,401 0 122,645 0 142,296 0 124,016 0 155,664 0 136,680 0 111,590 3 95,835 3 Profit 58,720.0 32,338.0 66,994.0 39,195.0 73,470.0 39,564.0 49,796.0 27,774.3 Source: Field Survey (2020)
Table
3.2 Estimation of Farmer's Average Income Estimation of farmer's average income level from crop enterprise was carried out using the farm budgeting technique to estimate the profitability or otherwise through estimation of costs and returns that accrued to farmers. It is important to note however, that there was no production of sorghum at Adani-Omor and cassava production in Kebbi-Sokoto zones. Abdullahi (2012) affirmed that the farm budget is an important measure for determining financial viability of a farm enterprises.
3.2.1 Profitability of sorghum enterprise Table 4 details the profitability analysis of sorghum enterprise per farmer across zones. The national results show that the total cost of sorghum production was N 61,794.3 per ha; N 68,061.0 per ha for the beneficiaries and non-beneficiaries respectively. The high cost of sorghum production for beneficiaries was observed at Bida-Badeggi (N 89,681.0) and Kebbi-Sokoto (N 82,194.0) Zones. Under the non-beneficiaries, high cost of sorghum production was also observed at Kebbi-Sokoto (N 97,116.0). The result shows that total output realised by farmers was 1.92Mt/ha and 1.53Mt/ha for beneficiaries and non-beneficiaries respectively when aggregated at national figure. On zonal basis, BidaBadeggi recorded the highest output (2.99MT), while Kebbi-Sokoto recorded the lowest output at 1.74MT Furthermore, the result shows that unit price of sorghum per Kg varies across the zones for beneficiaries ranges from N 88.0/Kg at Kano-Jigawa to N 99.0/ Kg at Bida-Badeggi. The national result shows that the unit price of sorghum was N 69.8 per kg for beneficiaries and N 72.3 per kg for non-beneficiaries. The result equally shows that sorghum farmer's income varies across zones for beneficiaries from N 142,296.0 per ha at Kano-Jigawa zone to N 148,401.0 per ha at Bida-Badeggi zone. The national result shows Program beneficiaries earned more income than the non-beneficiaries. The result of the profitability analysis of sorghum production indicated that the least profit realised by sorghum farmers under Program beneficiaries was observed at Bida-Badeggi zone (N 58,720.0/ha) and the highest was observed at Kebbi-Sokoto zone (N 73,470.0/ha). Similar trend was also observed under the non-beneficiaries. National result shows that on average sorghum farmers under Program beneficiaries were more profitable than the non-beneficiaries. The variance in farmer's income probably may be as a result of adoption of new technology promoted by the Program or due to localized market conditions. 4: Profitability of sorghum enterprise per farmer Sorghum Bida Badeggi (n=42) Kano Jigawa (n=66) Kebbi Sokoto (n=32) National (n=182) 1 ATASP
20
Table
21 3.2.2
National
Rice crops Adani
ATASP 1 Non ATASP 1 ATASP 1 Non ATASP 1 ATASP 1 Non ATASP 1 ATASP 1 Non ATASP 1 ATASP 1 Non ATASP 1 Total Cost (? ) 180,379.0 195,463.0 189,177.0 195,114.0 188,539.0 168,319.0 176,569.0 205,463.0 183,666.0 191,089.8 Output (Mt/ha) 6.63 4.11 5.50 5.12 6.67 5.42 6.79 5.48 6.18 5.93 Unit Price (? ) 113.0 111.0 124.0 114.0 112.0 115.0 111.0 118.0 115.0 114.5 Income (? ) 251,990.0 233,211.0 286,440.0 239,628.0 243,376.0 200,330.0 263,181.0 241,664.0 261,246.8 228,708.3 Profit (? ) 71,611.0 37,748.0 97,263.0 44,514.0 54,837.0 32,011.0 86,612.0 36,201.0 77,580.8 37,618.5 Source: Field Survey (2020)
Profitability of paddy rice Enterprise
Table 5 details the Profitability analysis of paddy rice enterprise across zones. The national result shows that the total cost of paddy rice production was N 183,666.0 per ha and N 191,089.8 per ha for the beneficiaries and non-beneficiaries respectively The highest cost of paddy rice production (N 189,177.0 per ha) for beneficiaries was observed at Bida-Badeggi Zones. Under the non-beneficiaries, high cost of paddy rice production (N 205,463.00) was observed at Kebbi-Sokoto. The national result shows that total output realised by paddy rice farmers was 6.18Mt/ha and 5.93Mt/ha for beneficiaries and non-beneficiaries respectively. However, the result of paddy rice output across zones indicated Kebbi-Sokoto and Kano-Jigawa zones recorded the highest out of 6.79MT/ha and 6.67MT/ha respectively. This is followed by Adani-Omor zone at 6.63Mt/ha. The least output was recorded at Bida-Badeggi zone (5.50Mt/ha). Furthermore, the result shows that unit price of paddy rice per Kg varies across zones from N 111 per Kg at Kebbi-Sokoto to N 124 per Kg at Bida-Badeggi. The national result shows that the unit price of paddy rice was N 115 per kg for beneficiaries and N 114.5 per kg for nonbeneficiaries. The result also shows that paddy rice farmer's income varies across zones from N 243,376.0/ha at Kano-Jigawa zone to N 286,440.0/ha at Bida-Badeggi zone. The national result shows Program beneficiaries had more income than the non-beneficiaries. The result of the profitability analysis indicated that the least profit realised by paddy rice farmers under Program beneficiaries was observed at Kano-Jigawa zone (N 54,837.0) and the highest was observed at Bida-Badeggi zone (N 97,263.0). Similar trend was also observed under the non-beneficiaries. The national result shows that on average paddy rice farmers under Program beneficiaries were more profitable than the nonbeneficiaries. The difference in level of profit and income generated by farmers may be as result difference in climatic, soils and market conditions across zones. The implication of this findings is that ATASP-1 Program had positive impact on the beneficiary's farm income. 5: Profitability of paddy rice enterprise per farmer Omor (n=42) Bida Badeggi (n=42) Kano Jigawa (n=66) Kebbi Sokoto(n=32) (n=182)
22 3.2.3
(?CosTotalt) 173,151.0 187,139.0 179,681.0 190,307.0 168,752.0 176,184.0 159,634.3 165,401.8 (Mt/Ha)Output 32.44 27.14 33.99 28.91 22.61 19.48 27.86 21.72 Unit Price (? ) 68.00 60.00 57.00 55.00 61.00 58.00 55.50 53.30 (?Income) 250,008.0 226,840.0 236,743.0 226,005.0 231,821.0 224,584.0 200,837.1 193,997.3 (?Profit) 76,857.00 39,701.00 57,062.00 35,698.00 63,069.00 48,400.00 41,202.80 28,595.50 Source: Field Survey (2020)
Profitability of Cassava enterprise Table 6 details the profitability analysis of cassava enterprise per farmer across zones. The national result shows that the total cost of cassava production was N 159,634.3/ha and N 165,401.8/ ha for the beneficiaries and non-beneficiaries respectively The difference in cost of production probably may be attributed market imperfections especially as it relat to supply of farm inputs. The study reported that the least cost of cassava production (N 168,752.0/ha) was recorded at Kano-Jigawa zone and the highest cost of cassava production (N 179,681.0/ha) was observed at Bida-Badeggi zone for beneficiaries. Under the non-beneficiaries, the least cost of cassava production (N 176,184.0/ha) was also recorded at Kano-Jigawa zone and the highest cost of cassava production (N 190,307.0/ha) was equally observed at Bida-Badeggi zone. The national result shows that total output realised by cassava farmers was 27.86Mt/ha and 21.72Mt/ha for beneficiaries and non-beneficiaries respectively. However, the result of cassava output across zone indicated that Bida-Badeggi zone recorded the highest output of 33.99Mt/ha, followed byAdani-omor zone (32.44Mt/ha) and Kano-Jigawa zone (22.61Mt/ha). Similarly, the result shows that unit price of cassava per Kg of beneficiaries varies across zones from N 57.0 per Kg at Bida-Badeggi to N 68.0 per Kg atAdani-Omor zone. The national result shows that the unit price of cassava was N 45.5/kg for beneficiaries and N 43.3/kg for non-beneficiaries. Cassava price is shown to be affected by location, type of market, and season. The result also shows that cassava farmer's income varies across zones for beneficiaries from N 231,821.0/ha at KanoJigawa zone to N 250,008.0/ha at Adani-Omor zone. The result of the cassava profitability analysis indicated that the least profit realised by cassava farmers under Program beneficiaries was observed at Bida-Badeggi zone (N 57,062.0/ha) and the highest was observed at AdaniOmor zone (N 76,857.0/ha). Similar trend was also observed under the non-beneficiaries. However, the national result shows that on average cassava farmers under Program beneficiaries more profitable and earned more income than the non-beneficiaries. The difference in level of profit generated by farmers may be as a result difference in climatic and market conditions across zones. 6: Profitability of Cassava enterprise CrCassavaop Adani Omor (n=42) Bida Badeggi (n=42) Kano Jigawa (n=66) National (n=182) 1 Non ATASP 1 ATASP 1 Non ATASP 1 ATASP 1 Non ATASP 1 ATASP 1 Non ATASP 1
ATASP
Table
Change in Output from Crop Enterprise
Table 7 presents the estimated change in output of farmers across zone for beneficiaries before and after the intervention as well as non-adopters categories. The national result revealed that beneficiaries had an average output of 46 bags of rice per ha before the intervention and non-adopters had on average output of 38 bags of rice per ha. However, the output roused to 64 bags of rice per ha after the intervention. The percentage change in output of rice per ha was 39.1%, this implies that there is 39.1% increase in output of rice produced across zones before and after the Program intervention. Similar achievements were also observed at Adani-Omor (33.3%), Bida-Badeggi (50.0%), Kano-Jigawa (59.5%) and Kebbi-Sokoto (37.7%).
23 3.3 Rate of increase of real income of beneficiaries 3.3.1
The estimated change in sorghum output across zone for beneficiaries before and after the intervention as well as non-adopters categories is also presented in Table 7. The national result revealed that beneficiaries had an average output of 37 bags of sorghum per ha before the intervention and non-adopters had an average output of 33 bags of sorghum per ha. However, the output roused to 57 bags of sorghum per ha after the intervention. The percentage change in output of sorghum per ha was 54.1%, this implies that there is 54.1% increase in output of sorghum produced across zone before and after the Program intervention. Similar achievements were also observed in Bida-Badeggi (45.2%), Kano-Jigawa (41.0%) and Kebbi-Sokoto (47.5%). it can be concluded that the Program had achieved it target of increasing output of farmers by 25%.production across zones. This was achieved through provision of inputs support and production technologies promoted by the Program.
The estimated change in cassava output across zone for beneficiaries before and after the intervention as well as non-adopters categories is also presented in Table 7. The national result revealed that beneficiaries had an average output of 6597.5Kg of cassava per ha before the intervention and non-adopters had an average output of 5391.1Kg of cassava per ha. However, the output roused to 9328.3Kg of cassava per ha after the intervention. The percentage change in output of cassava per ha was 41.4%, this implies that there is 41.4% increase in output of cassava produced across zone before and after the Program intervention. Similar achievements were also observed in Adani-Omor (30.9%), BidaBadeggi (54.2%) and Kano-Jigawa (37.0%).
The estimated change in price of cassava across zone for beneficiaries before and after the intervention as well as non-adopters categories is also presented in Table 8. The national result revealed that selling price of cassava at harvest for beneficiaries was N 6,230.8/Kg before the intervention and after the intervention 8,984.7/Kg. The percentage change in price of cassava per Kg was 44.2%, this implies that there is 44.2% increase in price of cassava produced across zone before and after the Program intervention. Similar achievements were also observed in Adani-Omor (34.9%), Bida-Badeggi (38.9%) and
24 Table 7: Change in output of crop enterprise Zones Crops NON ADOPTERS (ADOPTERS) Percentage change Boutput EFORE ATASP 1 AFTER ATASP 1 Adani-Omor (n=42) Rice (Bags) 38.0 45.0 60.0 33.3 Cassava (Kg) 5,581 2 8,450 3 11,060 2 30 9 Bida Badeggi (n=42) Rice (Bags) 32 0 38 0 57 0 50 0 Sorghum (Bags) 29 0 31 0 45 0 45 2 Cassava (Kg) 5,957 1 6,014 3 9,271 8 54 2 Kano Jigawa (n=66) Rice (Bags) 36.0 42.0 67.0 59.5 Sorghum (Bags) 33.0 39.0 55.0 41.0 Cassava (Kg) 5,311.5 6,208.1 8,504.5 37.0 Kebbi Sokoto (n=32) Rice (Bags) 44 0 53 0 73 0 37 7 Sorghum (Bags) 37 0 40 0 59 0 47 5 National (n=182) Rice (Bags) 38.0 46.0 64.0 39.1 Sorghum (Bags) 33.0 37.0 57.0 54.1 Cassava (Kg) 5,391.1 6,597.5 9,328.3 41.4
Source: Field Survey (2020) 3.3.2 Change in price of Crops Table 8 presents the change in prices of Staple crops across zone of beneficiaries before and after the intervention as well as non-adopters categories. The general price level of an agricultural commodity is influenced by a variety of market forces that can alter the current or expected balance between supply and demand. The selling prices of crop by farmers at harvest was presented in Table 8. The national result revealed that, beneficiaries sold a bag of paddy rice at N 8,503.8 before the intervention and nonadopters sold a bag of paddy rice at N 8,893.3. However, the price roused to N 12,290.60 after the intervention. The fluctuation in price of paddy rice per bag may be attributed to change in government policy which ban importation of processed rice into the country. The percentage change in price of bag of paddy was 44.5%, this implies that there is an increase of 44.5% in price paddy rice produced across zone before and after the Program intervention. Similar achievements were also observed at Adani-Omor (42.2%), BidaBadeggi (40.8%), Kano-Jigawa (28.0%) and Kebbi-Sokoto (33.3%).
before and
of
achievements were
after
was 37.4%, this
25 Kano-Jigawa (30.6%). The estimated change in price of sorghum bag across zone for beneficiaries before and after the intervention as well as non-adopters categories is also presented in Table 8. The national result revealed that, beneficiaries sold a bag of sorghum at N 6,672.9 the intervention and non-adopters sold a bag of sorghum at N 6,230.2. However, the price roused to N 9,166.3 the intervention. The percentage change in price of bag sorghum implies that there is an increase of 37.4% zone after the Program intervention. Similar also observed in BidaBadeggi (28.0%), Kano-Jigawa (44.0%) and Kebbi-Sokoto (43.1%). 6,901.3 9,012.8 30.6 Kebbi Sokoto (n=32) Rice (Bags) 6,924.1 7,070.5 9,425.3 33.3 (Bags)Sorghum 5,047.1 5,367.8 7,679.9 43.1 National (n=182) Rice (Bags) 8,893.3 8,503.8 12,290.6 44.5 (Bags)Sorghum 6,230.2 6,672.9 9,166.3 37.4 Cassava (Kg) 6,374.8 6,230.8 8,984.7 44.2
Table 8: Change in price of crops Zones Crops ADOPTERSNONUnitPrice(?) Unit(ADOPTERS)Price(?) PercentagechangepriceBEFORE AFTER Adani Omor (n=42) Rice (Bags) 10,250.0 10,522.0 14,957.2 42.2 Cassava (Kg) 8,612.2 9,293.4 12,532.2 34.9 Bida Badeggi (n=42) Rice (Bags) 9,645.6 9,322.3 13,127.6 40.8 (Bags)Sorghum 7,402.3 7,980.5 10,214.6 28.0 Cassava (Kg) 5,447.3 5,801.1 8,058.5 38.9 Kano Jigawa (n=66) Rice (Bags) 8,753.5 9,100.2 11,652.3 28.0 (Bags)Sorghum 6,241.3 6,670.5 9,604.3 44.0 Cassava (Kg) 6,687.3
Source: Field Survey (2020) 3.3.3 Change in real income of crop enterprise per hectare
in price sorghum produced across
before
The net farm income statement is a summary of revenue and expenses for a given accounting period. It is sometimes called an operating statement or a profit and loss statement. The purpose of Net Farm Income (NFI) in this study is to measure the difference between revenue and expenses of beneficiaries before and after intervention. A positive difference indicates a profit or a positive Net Farm income, and a negative value indicates a loss or a negative Net Farm Income for the given farm enterprise. The average costs incurred and the output in monetary value obtained per hectare by the beneficiaries before and after the Program was estimated for determining the net farm income. Table 9 presents the change in income of farmers across zone for beneficiaries
per
The estimated change in net income of sorghum farmers across zone is also presented in Table 9. The national result revealed that sorghum farmers under Program beneficiaries had net income of N 81,025.6/ha before the intervention while non-adopters had net income of N 95,835.3/ha. However, the net income aroused to N 111,590.3/ha after the intervention. The percentage change in the net income generated by sorghum farmers across zones was 37.7%, this implies that there is an increase of 37.7% in the net income of farmers generated from cultivation sorghum across zone before and after the Program intervention. Similar achievements were also observed in Bida-Badeggi (31.0%), KanoJigawa (26.9%) and Kebbi-Sokoto (32.0%). In general, the difference in net farm income of beneficiaries before participating in ATASP-1 over that of after participation may be attributed to the increase in farm output realized by the farmers across zone. Participant's profitability index is higher because they may have been taught better farming techniques which had impacted on their yield and hence, revenue.
The national result revealed that, paddy rice farmers under Program beneficiaries had income of N 201,036.8/ha before the intervention while non-adopters had net income of N 228,708.5/ha. However, the net income roused to N 261,246.7/ha after the intervention. The variation in net income generated by paddy rice farmers may be attributed to their differences in level of output produce across zones, because where output increases credibly, income generation is equally expected to change in the same direction. The percentage change in net income generated by paddy rice farmers across zones was 29.9%, this implies that there is an increase of 29.9% in the net income generated from cultivation of paddy rice across zone before and after the Program intervention. Similar achievements were also observed at Adani-Omor (25.1%), BidaBadeggi (31.0%), Kano-Jigawa (33.3%) and Kebbi-Sokoto (27.7%).
The estimated change in net income of cassava farmers across zone is also presented in Table 9. The national result revealed that cassava farmers under Program beneficiaries had net income of N 72,385.9/ha before ATASP-1 intervention while non-adopters had net income of N 93,997.3/ha. However, the net income moved to N 100,837.0/ha after the intervention. The percentage change in net income generated by cassava farmers across zones was 39.3%, this implies that there is an increase of 39.3% in the net income generated from cultivation cassava across zone before and after the Program intervention. Similar achievements were also observed in Adani-Omor (30.3%), BidaBadeggi (30.7%) and Kano-Jigawa (27.9%).
26 before and after the intervention as well as non-adopters categories. Substantial amount of income has been generated by the farmers from the outputs obtained.
Rice
124,016.0 112,112.3 142,296.0 26.9
Source: Field Survey (2020)
136,680.0 117,905.1 155,664.0
3.4.1 Impact of ATASP-1 on output of farmers across zone
Rice
200,330.0 185,312.2 243,376.0 33.3 Sorghum
27 Table 9: Change in income/ha of farmers Zone Crops NON ADOPTERS(?) ADOPTERS ATASP 1 inchPercentageangeincome/haBEFORE AFTER Adani Omor (n=42) Rice (Bags) 233,211.0 201,352.3 251,990.0 25.1 Cassava (Kg) 126,840.0 115,141.1 150,008.0 30.3 Bida Badeggi (n=42) Rice (Bags) 239,628.0 218,605.5 286,440.0 31.0 Sorghum (Bags) 122,645.0 113,258.3 148,401.0 31.0
241,664.0 206,058.9 263,181.0 27.7 Sorghum
3.4 Comparative Analysis of Output, Prices of Crops and Income of farmers
124,584.0 103,025.6 131,821.0 27.9
The Comparative analysis of output of crop farmers per ha was estimated using Z-test to test hypothesis whether changes observed in output of crop farmers per ha was as result of ATASP-1 intervention as presented in Table 10. The Z-Test is used to test the hypothesis that there is no significant difference in output of crop farmers before and after intervention. The result shows that paddy rice farmers before intervention on average realised output of 46 bag/ha which higher than the non-adopters group (38 bags/ha). The comparative analysis of output realised by paddy rice farmers before and after intervention across zone shows that Z- calculated is greater than Z-critical, thus implying that there was significant difference (P<0.01) in the number of output realised by farmers across zones. Therefore, the null hypothesis is rejected in favour of the alternative, there is significant difference in output of paddy rice farmers before and after intervention. However, the result shows that sorghum farmers before intervention on average realised output of 37 bag/ha which higher than the non-adopters group 33 bags/ha. In the same vein, the comparative analysis of output realised by sorghum farmers before and after intervention across zone shows that Z- calculated is greater than Z-critical, thus implying that there significant difference (P<0.05) in the number of output realised by sorghum farmers across zones. Therefore, the null hypothesis is rejected in favour of the alternative, there is significant difference in output of sorghum farmers before and after intervention.
Kebbi Sokoto (n=32) (Bags) (Bags) 32.0 National (n=182) Rice (Bags) 228,708.5 201,036.8 261,246.7 29.9 Sorghum (Bags) 95,835.3 81,025.6 111,590.3 37.7 Cassava (Kg) 93,997.3 72,385.9 100,837.0 39.3
Cassava (Kg) (n=66) (Bags) (Bags) Cassava (Kg)
126,005.0 104,614.4 136,743.0 30.7 Kano-Jigawa
CROPS ENTERPRISE (n=182) NON ADOPTERS ADOPTERS ATASP -1 Z BStatistic EFORE AFTER
Furthermore, the result shows that cassava farmers before intervention on average realised output of 6,597.5Kg/ha which higher than the non-adopters group 5,391.1Kg/ha. The comparative analysis of output realised by cassava farmers before and after intervention across the zones shows that Z- calculated is greater than Z-critical, thus implying that there was significant difference (P<0.001) in the number of output realised by cassava farmers across the zones. Therefore, the null hypothesis is rejected in favour of the alternative, there is significant difference in output of cassava farmers before and after intervention. This implies that ATASP-1 intervention had impacted on the level of output produce by farmers across zones. Impact output farmers zone Output 46 64 33 37 57 1.8347 Cassava (Kg) 5,391 1 6,597 5 9,328 1567 Field Survey (2020) *** Significant at P<0 001 ** Significant at P<0 01 * Significant at P<0 05 Impact of ATASP-1 on selling price of crops at harvest by farmers across zone
Table 10:
ATASP 1 on
*** Source:
of
0
0 2 1983** Sorghum (Bags)
3.4.2
3 3
*
0
28
0
The comparative analysis of selling price of crops was estimated using Z-test to test hypothesis whether changes observed in prices of crops was as result of ATASP-1 intervention (Table 11). There is no significant difference in prices of crops cultivated by farmers before and after intervention. The result shows that price of paddy rice before intervention was N 8,503.8 per bag which is higher than the non-adopters group (N 8,893.3). The comparative analysis of price paddy rice per bag sold during harvest before and after intervention across zone shows that Z- calculated is greater than Z-critical, thus implying that there was significant difference (P<0.001) in the price of a bag of paddy rice across zones. Therefore, the null hypothesis is rejected in favour of the alternative which stated that, there is significant difference in price of paddy rice before and after intervention. In addition, the result shows that the price of a bag of sorghum before intervention was N 6,672.9 which is higher than the non-adopters group (N 6,230.2). In the same vein, the comparative analysis of price sorghum before and after intervention across zone shows that Z- calculated is greater than Z-critical, thus implying that there was significant difference (P<0.05) in the price of a bag of sorghum across zones. Therefore, the null hypothesis is rejected in favour of the alternative which stated that, there is significant difference in the price of sorghum before and after intervention.
Rice (Bags) 38 0
Furthermore, the result shows that price of cassava before intervention was N 6,230.8Kg which is higher than the non-adopters group (N 6,374.8). The comparative analysis of price of cassava before and after intervention across zone shows that Z- calculated is greater than Z-critical, thus implying that there was significant difference (P<0.01) in the price cassava across zones. Therefore, the null hypothesis is rejected in favour of the
across
0
The comparative analysis of net income generated by crop farmers per ha was estimated using paired Z-test to test hypothesis whether changes observed in the net income of crop farmers per ha was as result of ATASP-1 intervention (Table 12). There is no significant difference in the net income of crop farmers before and after intervention. The result shows that paddy rice farmers before intervention on average had net income of N 37,618.5 which is less than the non-adopters group (N 40,025.3). The comparative analysis of net income realised by paddy rice farmers before and after intervention across zone shows that Z- calculated is greater than Z-critical, thus implying that there was significant difference (P<0.01) in the net income realised across zones. Therefore, the null hypothesis is rejected in favour of the alternative which stated that, there is significant difference in the net income of paddy rice farmers before and after intervention. However, the result shows that sorghum farmers before intervention on average realised a net income of N 27,774.3 which is less than the non-adopters group. In the same vein, the comparative analysis of net income realised by sorghum farmers before and after intervention across zone shows that Z- calculated is greater than Zcritical, thus implying that there was significant difference (P<0.01) in the net income realised by sorghum farmers across zones. Therefore, the null hypothesis is rejected, in favour of the alternative which stated that there is significant difference in net income realised by sorghum farmers before and after intervention. Furthermore, the result shows that cassava farmers before intervention on average realised net income of N 28,595.5 which is less than the non-adopters group. The comparative analysis of the net income realised by cassava farmers before and after intervention across zone shows that Z- calculated is greater than Z-critical thus implying that there was significant difference (P<0.01) in the net income realised by cassava farmers across zones. Therefore, the null hypothesis is rejected, in favour of the alternative which stated that there is significant difference in net income of cassava farmers before and after intervention. This implies that ATASP-1 intervention had impacted on the level of income of farmers across zones.
*
Rice (Bags)
***
*** Sorghum
29 alternative which stated that, there is significant difference in the price of cassava before and after intervention. This implies thatATASP-1 intervention had impacted on the price of crops produce by farmers across zones. Impact ATASP 1 selling price of crops at harvest by farmers across zone Price 8,893.3 8,503.8 12,290.6 3.8269 (Bags) 6,230.2 6,672.9 9,166.3 1.9241 (Kg) 6,374.8 6,230.8 8,984.7 2.4659 Field Survey (2020) Significant at P<0.001 Significant at P<0.01 Significant at P<0.05 3.4.3 Impact of ATASP-1 on net income of farmers across zone
CROPS ENTERPRISE (n=182) NON ADOPTERS ADOPTERS ATASP 1 Z BStatistic EFORE AFTER
Table 11:
* Cassava
on
** Source:
**
30 Table 12: Impact ATASP 1 on net income of farmers across zone CROPS ENTERPRISE (n=182) NON ADOPTERS ADOPTERS ATASP 1 Z BStatistic EFORE AFTER Net Income Rice (Bags) 40,025.3 37,618.5 77,580.75 2.1416** Sorghum (Bags) 28,215 2 27,774 3 49,796.0 2 2958** Cassava (Kg) 30,314 5 28,595.5 41,202 8 2.9818** Source: Field Survey (2020) *** Significant at P<0 001 ** Significant at P<0 01 * Significant at P<0 05 3.5 Factors Influencing Profitability of Crop Enterprise Among beneficiaries Across Zone Multiple regression analysis was used to determine the factors influencing profitability of crop enterprise among beneficiaries of ATASP-1 Program across zones. The socioeconomic factors which formed the independent variables include, age of farmers, household size, level of education, farming experience, farm size, cost of production, extension contact and adoption of improved technology. In order to compare and assess in detail the necessary parameters, four linear forms were fitted to the data The national linear regression model was chosen as lead equation based on its conformity with 2econometric and significant criteria such as the magnitude of R (0.937), F-ratio (114.305, P<0.01) number of significant variables and agreement with a priori expectation as presented in Table 13. The regression coefficients of multiple 2determination reveal R of 0.705, 0.691, 0.813, 0.671 and 0.937 for Adani-Omor, BidaBadeggi, Kano-Jigawa, Kebbi-Sokoto and national result respectively, meaning that 70.5%, 69.1%, 81.3%, 67.1% and 93.7% variability in profit generated by farmers from crop enterprise at Adani-Omor, Bida-Badeggi, Kano-Jigawa, Kebbi-Sokoto and National result respectively was accounted for by the explanatory variables include in the model. The F-value was significant at P<0.01 level of probability indicating a goodness of fit of the regression across zone. The coefficient of age (0.088) was positive and statistically significant (P<0.05) except at Bida-Badeggi zone. This implies that positive relationship exists between the age of the farmers and profit realised from crop production in the study area. The situation indicates that middle age farmers are more skillful than the young farmers, hence the a priori expectation was met. This is in line with the observation of Ja'afar-Furo et al.(2011), that the more energetic a person is, the more the ability to take risk and diversify his/her livelihood strategies and vice versa. The farming experience of the beneficiaries of ATASP-1 Program also showed positive coefficient (0.079) and statistically significant (P<0.001) across zone. This means that increase in the years of farming experience led to a corresponding increase in the output of the farmers and thereby increase profit. This is true because farmers who have higher farming experience are likely to be more knowledgeable in the combination of resources. This is in line with the apriori expectation because crop farmers with high level of farming experience obtained increased yield due to higher efficiency in resource use. They are technically, economically and allocatively more efficient than others who have low level of farming experience.
In the same vein, the coefficient of household size (0.098) indicate a positive relationship and statistically significant (P<0.05) across zone. This indicates that household size have a positive influence on the output of farmers in the study area. The implication is that members of the household contribute significantly to family labour supply which leads to increase in rice yield and profit level. It was therefore against popular expectation that large household size would provide necessary labour for the enterprise which reduces the cost since family labour is not paid (Lowder et al., 2014).
31
Extension contact involves the application of scientific research and new knowledge to agricultural practices through farmer education. The field of extension encompasses a wide range of communication and learning activities organized for farmers by professionals of agriculture. Agricultural extension contact for this study was measured in terms of the number of times the famers were taught by extension agent. The coefficient for extension contact was positive (0.074) and significant at (P<0.001). This implies that any increase in frequency of extension contacts will bring about increase in adoption of technologies. This is in agreement with priori expectation. Extension is the major medium for agricultural innovations dissemination to farmers from the research. The coefficient of farm size was found to be positive (0.041) and significantly (P<0.001) related with the beneficiaries profit generated from crop production. This means that farm size is positively related with level of farm income. Therefore, any increase in farm size will lead to increase in output resulting to increased profit. This implies that any increase in farm size will lead to an increase in output there by bringing about more revenue and profit to the farmer. The result is in agreement with the findings of Muzari et al. (2012) where they found a positive relationship between income and output of AgipGreen River Program crop farmers in Rivers State, Nigeria.
In the same vein, the coefficient of adoption of improve technologies promoted by the Program was positive (0.054) and significant (P<0.001). This implies that any increase in adoption of improve technologies will lead to a corresponding increase in profit of farmers across zones. On the other hand, the coefficient for total cost of crop production
Education is a social capital which could impact positively on household ability to take good and well informed production decisions. For this study, education was used as a proxy for management and was measured by years of schooling. This variable is expected to relate positively with the efficiency The coefficient of educational level was found to be positive (0.058) and significant (P<0.05) except at Adani-Omor and KebbiSokoto zones. This implies that increased level of education will lead to increase in the profit of the beneficiaries. Education produces labour force that is more skilled and adaptable to the need of changing economy. It helps to unlock the natural talents and inherent enterprising qualities of the farmers. It enhances the farmer's ability to understand and evaluate new production techniques. This translates into higher crop output and productivity (Mugwe et al., 2012).
32 per ha was negative (-0.085) and significant at P<0.001. The implication of this negative effect for farmers is that if total cost of production increases will lead to corresponding decrease in profitability of the crop enterprise across zones. Table 13: Factors influencing profitability of crop enterprise among beneficiaries across zone Variables Adani Omor (n=42) Bida Badeggi (n=42) Kano Jigawa (n=66) Kebbi Sokoto (n=32) National (n=182) Constant 0.147 (1.928)* 0.2180 (2.147)** 0.038 (3.147)*** 0.602 (1.818)* 0.199 (2.697)** Age 0.028 (1.847)* 0.015 (0.012) NS 0.083 (1.691)* 0.044 (2.677)** 0.088 (1.904)* Farming experience 0.196 (2.867)** 0.012 (3.511) *** 0.077 (2.822)** 0.092 (2.435)** 0.079 (4.282)*** Household size 0.011 (2.561)** 0.0412 (1.914)* 0.041 (2.497)** 0.074 (3.145)*** 0.098 (2.2147)* Educational level 1.089 (0.699)NS 0.028 (2.325)** 0.089 (2.997) ** 1.031 (0.303)NS 0.058 (1.913)* Extension contact 0.209 (2.285)** 0.096 (3.012)*** 0.055 (1.955)* 0.011 (1.951)* 0.074 (2.428)** Farm size 0.210 (3.207)*** 0.063 (1.928)* 0.0747 (3.024)*** 0.074 (2.824)** 0.041 (3.646)*** Adoption of improved technology 0.270 (2.382)** 0.028 (1.917)* 0.087 (3.811) *** 0.021 (1.677)* 0.054 (3.963)*** Cost of production 0.047 ( 3.622)*** 0.062 ( 2.357)** 0.093 ( 3.701)*** 0.058 ( 2.439)** 0.085 ( 3.951)*** F value 45.366* 24.021* 68.141* 50.088* 114.305** R2 0.705 0.691 0.813 0.671 0.937 Source: Field Survey (2020) Values in parenthesis are T statistics Note: *** Significant at P<0.001, ** Significant at P<0.01 and * Significant at P<0.05, NS= Not Significant 3.6 Effect of Good Agronomic Practices (GAP) Technologies among farmers
The perceived effect of Good Agronomic Practices (GAP) Technologies among farmers was presented on Table 14. The national result shows that 57.7% and 36.8% of beneficiaries and non-beneficiaries agreed that GAP had enhance labour saving among farming communities. The result revealed that, 47.6% and 33.3% of beneficiaries and non-beneficiaries respectively agreed that Good Agronomic Practices enhance labour savings among farmers at Adani-Omor zones. However, 64.3% and 38.1% of beneficiaries and non-beneficiaries respectively agreed that Good Agronomic Practices enhance labour savings among farmers at Bida-Badeggi zone. Furthermore, similar trend was also observed at Kano-Jigawa and Kebbi-Sokoto zones. In addition 53.8% and 40.7% of beneficiaries and non-beneficiaries respectively agreed that GAP has increase their yield. Furthermore, on soil moisture retention, 60.4% of the beneficiaries and 41.8% of non- Program beneficiaries agreed adoption of GAP improve soil moisture retention capacity in their communities. Moreover, 61.0% of beneficiaries and 41.8% of non-beneficiaries agreed that GAP has improve their capacity towards controlling soil erosion, 75.3% of the beneficiaries and 65.9% of non- Program beneficiaries agreed GAP enhancement of soil fertility. However, 81.9% of the beneficiaries and 69.8% of non- Program beneficiaries agreed GAP had improved their climate change adaptability
According to Noltze, et al., (2012), Good Agricultural Practices improve agricultural productivity and agro ecosystem resilience, involving different agronomic and
Table 14:
ATASP 1 Non ATASP 1 ATASP 1 Non ATASP 1 ATASP 1 Non ATASP 1 ATASP 1 Non ATASP 1 ATASP 1 Non ATASP 1 Labour saving Agree 20(47.6) 14(33.3) 27(64.3) 16(38.1) 38(57.6) 22(33.3) 20(62.5) 15(46.9) 105(57.7) 67(36.8) Not sure 12(28.6) 18(42.9) 5(11.9) 18(42.9) 18(27.3) 20(30.3) 4(12.5) 11(34.4) 39(21.4) 67(36.8) Disagree 10(23.8) 10(23.8) 10(23.8) 8(19.0) 10(15.2) 24(36.4) 8(25.0) 6(18.8) 38(20.9) 48(26.4) Higher yield Agree 26(61.9) 20(62.5) 22(33.3) 20(47.6) 35(53.0) 24(36.4) 15(46.9) 10(31.3) 98(53.8) 74(40.7) Not sure 9(21.4) 14(33.3) 20(30.3) 12(28.6) 20(30.3) 18(27.3) 10(31.3) 13(40.6) 59(32.4) 57(31.3) Disagree 7(16.7) 8(25.0) 24(36.4) 10(23.8) 11(16.7) 24(36.4) 7(21.9) 9(28.1) 25(13.7) 51(28.0) Soil moisture retention Agree 26(61.9) 17(40.5) 30(71.4) 19(45.2) 40(60.6) 27(40.9) 14(43.8) 13(40.6) 110(60.4) 76(41.8) Not sure 10(23.8) 12(28.6) 10(23.8) 15(35.7) 19(28.8) 19(28.8) 13(40.6) 10(31.3) 52(28.6) 56(30.8) Disagree 6(14.3) 13(31.0) 2(4.8) 8(19.0) 7(10.6) 20(30.3) 5(15.6) 9(28.1) 20(11.0) 50(27.5) Soil erosion control Agree 20(47.6) 16(38.1) 25(59.5) 20(47.6) 49(74.2) 30(45.5) 17(53.1) 10(31.3) 111(61.0) 76(41.8) Not sure 17(40.5) 14(33.3) 16(38.1) 10(23.8) 11(16.7) 22(33.3) 5(15.6) 20(62.5) 49(26.9) 66(36.3) Disagree 5(11.9) 12(28.6) 1(2.4) 12(28.6) 6(9.1) 14(21.2) 10(31.3) 2(6.3) 22(12.1) 40(22.0) Enhancement of soil fertility Agree 32(76.2) 28(66.7) 30(71.4) 26(61.9) 55(83.3) 49(74.2) 20(62.5) 17(53.1) 137(75.3) 120(65.9) Not sure 5(11.9) 8(19.0) 9(21.4) 7(16.7) 10(15.2) 11(16.7) 6(18.8) 10(31.3) 30(16.5) 36(19.8) Disagree 5(11.9) 6(14.3) 3(7.1) 9(21.4) 1(1.5) 6(9.1) 6(18.8) 5(15.6) 15(8.2) 26(14.3) Climate change adaptation Agree 30(71.4) 22(52.4) 33(78.6) 28(66.7) 60(90.9) 56(84.8) 26(81.3) 21(65.6) 149(81.9) 127(69.8) Not sure 7(16.7) 10(23.8) 9(21.4) 8(19.0) 3(4.5) 6(9.1) 3(9.4) 5(15.6) 22(12.1) 29(15.9) Disagree 5(11.9) 10(23.8) 0(0) 6(14.3) 3(4.5) 4(6.1) 3(9.4) 6(18.8) 11(6.0) 26(14.3)
Source: Field Survey (2020) Values in parenthesis are percentages 3.7 Effectiveness of support for Good Agronomic Practices (GAP) among farmers
The proportion of farmers that receive inputs support from ATASP-1 is presented in Figure iv. The national result shows that majority (81.9%) of the Program beneficiaries received inputs support from ATASP-1 while only 18.1% claimed that they did not received any input support from ATASP-1. The result also shows that 89.4% of the farmers under Kano-Jigawa zone and 84.4% of the farmers under Kebbi-Sokoto zone received input support from ATASP-1. Furthermore, the result indicated that the proportion of farmers that received input support from the Program under Bida-Badeggi and Adani-Omor zones was put at 78.6% and 71.4% respectively The implication of the finding is that the distribution mechanism used for input support was effective since more than 70% of beneficiaries received inputs support across zone. According to Mumba et al., (2012), adoption of good agricultural practices will enhance farmers with economic and social conditions.
33 management components with synergistic relationships. Another economic benefit of adoption of GAP is that it can lead to the reduction of some production costs. Improved agricultural practices that reduce wastage or result in more efficient use of labor or other farm inputs can reduce average costs which are an economic incentive for farmers to adopt such practices. Effect of Good Agronomic Practices (GAP) technologies among farmers Variables Adani Omor (n=42) Bida Badeggi (n=42) Kano Jigawa (n=66) Kebbi Sokoto (n=32) National (n=182)
Table
34
Figure 8: Proportion of farmers that received input support from ATASP-1 Type of Inputs Support needed by farmers across zones
3.8
Kano Jigawa (n=66) Kebbi Sokoto (n=32) National (n=182) Frq % Frq % Frq % Frq % Frq % Seeds 8 19.0 4 9.5 14 21.2 4 12.5 30 16.5 Fertilizer 4 9.5 9 21.4 19 28.8 8 25.0 40 22.0 Agro chemicals 7 16.7 4 9.5 11 16.7 6 18.8 28 15.4 Access to credit 10 23.8 12 28.6 12 18.2 9 28.1 43 23.6 Regular capacity building 8 19.0 5 11.9 5 7.6 2 6.3 20 11.0 Storage facilities 5 11.9 8 19.0 5 7.6 3 9.4 21 11.5 Source: Field Survey (2020)
Type
The type of inputs support required by farmers across zones is presented in Table 15. The national result shows that 16.5% of the farmers preferred seeds support, 22.0% requested for fertilizer support, 15.4% requested for agro-chemical support, 23.6% requested for credit support, 11.0% requested for regular capacity building and 11.5% requested for storage facilities support. The result across zone shows that 21.2 % of farmers at KanoJigawa zone and 19.0% of farmers atAdani-Omor zone requested for seed support, while 28.8% of farmers from Kano-Jigawa zone, 21.4% of farmers from Bida-Badeggi zone and 25.0% of farmers from Kebbi-Sokoto requested for fertilizer support. Furthermore, the result shows that 28.6% of farmers from Bida-Badeggi coveted credit support while 11.9% of the farmers from Adani-Omor craved storage facilities support. This implies that seeds, fertilizer and agro-chemical were the major input needed by farmers to enhance their productivity. This outcome is likely to be due to the several agro-input interventions implemented under closed and on-going government and development Programs interventions across the country. 15: Type of inputs support required by famers across zones of inputs Omor (n=42) (n=42)
Bida Badeggi
Adani
35
3.10 Constraints militating against wealth creation among farmers
Figure v presents the impact of good agricultural practice on beneficiary's income under survey. The pattern across the items under the national result shows that 56.1% of farmers that adoption of good agricultural practice reported their income has improved very well, while only 14.8% reported that adoption of good agricultural practice reported their income do not improved at all. Under Adami-Omor zone (64.3%), Bida-Badeggi Zone (57.1%), Kebbi-Sokoto zone (59.4%) and Kano-Jigawa Zones (48.5) of farmers that adoption of good agricultural practice reported that their income has improved very well. This implies that good agricultural practice promoted by the Program had impacted positively on farmers' income.
3.9 Impact of Good Agricultural Practice on beneficiaries' income
Figure 9: Impact of Good Agricultural Practice on beneficiary's income
The constraints militating against wealth creation among beneficiaries is presented in Table 16. The national result shows that majority (56.0%) of farmers faced with constraint of poor record keeping, 27.5% of the farmers faced with constraint of poor understanding of technology (GAP) requirements while 16.5% of the farmers faced with constraint of insufficient awareness on improve technology across zones. However, 44.5% and 55.5% of farmers faced with constraint associated with human factor and physical/Climatic factors respectively The result also shows 36.3% of the farmers complained of conflict and 35.2% of the farmers complained of low prices for their farm produce across zones. Furthermore, 68.7% of the farmers faced with constraint of lack of effectiveness of extension services. Other constraint militating against wealth creation among ATASP-1 beneficiaries across zone includes: problem of pest and diseases (18.1%), poor roads network (20.30%), inadequate capital (17%), inadequate land (18.1%) and inadequate export market (26.40%).
Knowledge: Frq (%) Frq (%) Frq(%) Frq(%) Frq(%) Insufficient awareness 10(23.8) 2(4.8) 10(15.2) 8(25.0) 30(16.5) Poor understanding of technology (GAP) requirements 12(28.6) 10(23.8) 18(27.3) 10(31.3) 50(27.5) Poor record keeping 20(47.6) 30(71.4) 38(57.6) 14(43.8) 102(56.0)
Production Constraints Product market: Long distance to market 6(14.3) 8(19.0) 10(15.2) 9(28.1) 33(18.1) Low prices for farm produce 14(33.3) 16(38.1) 23(34.8) 11(34.4) 64(35.2) High transport cost 12(28.6) 8(19.0) 13(19.7) 2(6.3) 35(19.2)
Source: Field Survey (2020)
Social: Socio cultural (Religious belief/Tradition ) 10(23.8) 5(11.9) 9(13.6) 9(28.1) 33(18.1) shortage of labour, 6(14.3) 9(21.4) 10(15.2) 8(25.0) 33(18.1) insufficient networking with stakeholders, 12(28.6) 10(23.8) 21(31.8) 7(21.9) 50(27.5) Conflict 14(33.3) 18(42.9) 26(33.3) 8(25.0) 66(36.3)
Environmental: Human factors 20(47.6) 21(50.0) 30(45.5) 10(31.3) 81(44.5)
Physical/Climatic factors 22(52.4) 21(50.0) 36(54.5) 22(68.8) 101(55.5)
36 Table 16: Constraints militating against wealth creation among farmers Constraints AdaniOmor(n=42) BaBidadeggi(n=42) JigKanoawa(n=66) SoKebbikoto(n=32) National(n=182)
Lack of market/demand for product 10(23.8) 10() 20(30.3) 10(31.3) 50(27.5) Extension services: Unavailability of extension services 8(19.0) 4(9.5) 6(9.1) 3(9.4) 21(11.5) Lack of effectiveness 28(66.7) 23(54.8) 55(83.3) 19(59.4) 125(68.7) Long distance to the extension workers 6(14.3) 15(35.7) 5(7.6) 10(31.3) 36(19.8) Others: Problem of pest and diseases 7(16.7) 8(19.0) 10(15.2) 8(25.0) 33(18.1) Poor roads network 11(26.2) 6(14.3) 13(19.7) 7(21.9) 37(20.3) Inadequate capital 8(19.0) 10(23.8) 8(12.1) 5(150.6) 31(17.0) Inadequate land 10(23.8) 6(14.3) 15(22.7) 2(6.3) 33(18.1) Inadequate large export market 6(14.3) 12(28.6) 20(30.3) 10(31.3) 48(26.4)
Figure 14: Well flooded transplanted rice field in one of the production clusters
Figure 11: supervision of wash bore drilling
Figure 10: Land preparation in one of the Rice field
Figure 12: Nursery establishment in one of the production clusters
Figure 13: Rice transplanting in progress in one of the production cluster
Figure 16: A well-established rice field
Figure 15: A well-established rice field
Figure 17: Some of the sorghum variety promoted by the Project through collaboration with the Research Institutes.
37
FINDINGSAND DISCUSSION 4.0 PROCESSORS
The distribution of processors across gender is presented in Table 17. The national result shows that the female gender was the dominant group, accounting for 60.0% and 44.5% for both beneficiaries and non-beneficiaries respectively The distribution across the SCPZs further shows female dominance in all the zones, except at Adani-Omor where the male group accounted for 80.0% and 60.0% for beneficiaries and non- Project beneficiaries alike. This finding is in line with Manza andAtala (2014) who reported that 70% of the respondents were female among rice processors in southern Borno state, Nigeria.
4.1 Socio-economic Characteristics' of Processors across SCPZs.
4.1.1 Gender of processor
The distribution of processors according to their educational status is presented in Table 17. The national result shows that 20.0% and 250.5% of the beneficiaries and nonbeneficiaries respectively acquired primary education, 45.0% and 50.0% of the beneficiaries and non-beneficiaries respectively acquired Secondary/TC II education and only 10.0% and 15.0% of the beneficiaries and non-beneficiaries respectively acquired tertiary education. However, only 5.0% and 20.0% of the beneficiaries had nonformal education and Qur'anic education respectively Ahmed (2011) state that level of education significantly enhances processors 'ability to make accurate and meaningful management decisions which could also enhance knowledge of improved techniques. Aboki et al. (2013) argues that education in agricultural value chain will assist to accept and test innovations that are available, and enhance the ability to make informed and accurate management decisions. 38 4
The socio-economic characteristics of processors includes gender, level of education, age of household head, household size and years of experience in agro-processing.
4.1.2 Level of education of processors
Table Distribution of processors across gender and level of education
Source: Field Survey (2020) 4.1.3
4.1.4 Household size of Processors
The distribution of processors according to household size composition is presented in Table 18. The national result shows that most of household head under Program beneficiaries had minimum of 1 male and 1 female members per household head. In addition, Program beneficiaries had maximum of 9 male and 10 female members per household head with average of 4 male and 5 female members. Similarly, nonbeneficiaries had also a minimum of 1 male and 1 female members per household head. However, non-beneficiaries had maximum of 11 male and 12 female members per household head with average of 5 male and 6 female members. The implication is that large household size may likely enhance the family labour supply, hence supporting favorably, productive capacities of the processors. According to the findings of Loevinsohn et al. (2008), there is a positive and significant relationship between household size and processors' efficiency in production. Nevertheless, the absolute number of people in a certain family cannot be used to justify the potential for productive work. This is because it can be affected by other important factors namely; age, sex and health status. Essentially, it is the composition of the household that determine labour supply for the successful accomplishment of processing operations.
17:
Age of household head (years) Age factor is very important in agro-processing activities due to its influence on the decision making process with respect to adoption of improved technologies and other production-related decisions. Table 18 details the age of processors across SCPZs. The national results show that the age of Program beneficiaries ranged from 24 to 69 years with mean age 35 years. Similarly, for the non-beneficiaries, the minimum age of 27 years was obtained with maximum age of 70years. Further review of the results show that the processors were generally young, as reflected by mean ages of 35 years and 38 years for Program beneficiaries and non-beneficiaries respectively. The outcome further shows that younger people are more involved in the Program activities. This is expected to have positive influence because of high physical energy demand associated with the production process.
39
Tertiary 1(20.0) 1(20.0) 1(20.0) 1(20.0) 1(20.0) 2(10.0) 3(15.0) Non Formal 1(20.0) 1(20.0) 1(5.0) 1(5.0) Qur’anic 1(20.0) 1(20.0) 3(60.0) 4(20.0) 1(5.0)
TCSecondary/II 4(80.0) 3(60.0) 1(20.0) 2(40.0) 3(60.0) 2(40.0) 1(20.0) 3(60.0) 9(45.0) 10(50.0)
Variables Adani Omor Bida Badeggi Kano Jigawa Kebbi Sokoto National ATASP Non ATASP ATASP Non ATASP ATASP Non ATASP ATASP Non ATASP ATASP Non ATASP Gender Male 4(80.0) 3(60.0) 1(20.0) 3(60.0) 1(20.0) 2(40.0) 2(40.0) 3(60.0) 8(40.0) 11(55.5) Female 1(20.0) 2(40.0) 4(80.0) 2(40.0) 4(80.0) 3(60.0) 3(60.0) 2(40.0) 12(60.0) 9(44.5) Level of education Primary 1(20.0) 1(20.0) 1(20.0) 2(40.0) 2(40.0) 1(20.0) 1(20.0) 4(20.0) 5(25.0)
40 4.1.5 Experience of Processors Experience is another important socio-economic factor that can bring about increase in productivity. Experience influences individuals? perception and understanding of the management requirements and consequently improve production. The distribution of processors according to years of experience is presented in Table 18. The national result shows that most of processors under Program beneficiaries and non-beneficiaries had minimum of 4 years and 2 years' experience respectively However the result shows that beneficiaries and non-beneficiaries had maximum of 22 years and 19 years respectively
Source: Field Survey (2020) 4.2 Type of crops processed across SCPZs The type of crops processed across zone is presented in Table 19. The national result indicated that 55.0% of beneficiaries and 20.0% of non-beneficiaries were into sorghum processing. However, the result across zones shows that 80% of beneficiaries at BidaBadeggi and Kano-Jigawa zones were into sorghum processing when compared with the other zones. Further, the national result indicated that, 80.0% of beneficiaries and 50.0% of non-beneficiaries were into rice processing. The result across zones shows that most of beneficiaries and non-beneficiaries were into rice processing. Majority (45%) of the respondents were also into cassava processing across zone with exception of KebbiSokoto zone. The national result also indicated that 50.0% of beneficiaries and 35.0% of non-beneficiaries were into maize processing. In the same vein, the result across zones shows that all of beneficiaries at Kano-Jigawa zone were into groundnut processing and
The average years of processors' experience was put at for beneficiaries and non-beneficiaries. This shows that Project beneficiaries had more processing than the non-beneficiaries, implying that they are more likely to take better decisions increase their of Female Household 4.0 2.0 Max 16.0 15.0 14.0 16.0 13.0 17.0 19.0 21.0 22.0 19.0 Mean 7.0 5.0 9.0 7.0 6.0 4.0 8.0 6.0 11.0 9.0
9 years for
output and income. Table 18: Distribution of processors across age, household size and experience Variables Adani Omor Bida Badeggi Kano Jigawa Kebbi Sokoto National ATASP1 Non ATASP 1 ATASP 1 Non ATASP 1 ATASP 1 Non ATASP 1 ATASP 1 Non ATASP 1 ATASP 1 Non ATASP 1 Age of House hold Head (years) Min 27.0 28.0 24.0 28.0 29.0 28.0 29.0 27.0 24.0 27.0 Max 69.0 67.0 66.0 70.0 67.0 68.0 65.0 67.0 69.0 70.0 Mean 37.0 43.0 39.0 40.0 39.0 37.0 39.0 44.0 35.0 38.0 Number of Male Household Members Min 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 Max 7.0 5.0 6.0 8.0 12.0 10.0 8.0 13.0 9.0 11.0 Mean 3.0 2.0 3.0 4.0 6.0 5.0 `4.0 7.0 4.0 5.0 Number
11 years
years of
Members Min 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 Max 9.0 6.0 12.0 5.0 7.0 5.0 10.0 5.0 10.0 12.0 Mean 4.0 3.0 6.0 2.0 3.0 2.0 4.0 2.0 5.0 6.0 ExperienceMin 4.0 6.0 4.0 5.0 4.0 3.0 5.0 2.0
experience
that would
41 80.05% were into sesame processing at Kebbi-Sokoto zone. Furthermore the national result shows that 55.0% of beneficiaries and 25.0% of non-beneficiaries were into cowpea processing across zones. According to Julius and Job (2012) agro-processing is one of the most important sub-sector of the manufacturing sector, with food and beverages representing the largest component of processed commodities in Nigeria.
The type of value chain activities undertaken by respondents across zone is presented in Table 20. The national result indicated that 75.0% of beneficiaries and 35.0% of nonbeneficiaries were into rice milling. However, 65.0% of beneficiaries and 45.0% of nonbeneficiaries were into seed processing package and storage. The result also indicated that 85.0% of beneficiaries and 40.0% of non-beneficiaries were into production of Pop sorghum. Further, the national result indicated that, 60.0% of beneficiaries and 55.0% of non-beneficiaries were into production of high quality rice flour. Similarly, the result shows that 80.0% of beneficiaries and 45.0% of non-beneficiaries were into production of Cassava chin -chin and doughnut across zone. On the other hand, 40.0% of beneficiaries and 20.0% of non-beneficiaries were into processing of cassava into garri across Adani-Omor and Bida-Badeggi zones. However, only 40.0% of beneficiaries and 30.0% of non-beneficiaries were into production of cassava fufu with exception of KanoJigawa and Kebbi-Sokoto zones.
Source: Field Survey (2020), values in ( ) parenthesispareercentages 4.2.1 Types of value chain activities undertaken across SCPZs by Processors
Table 19: Type of crops processed across SCPZs Type of crops Adani Omor Bida Badeggi Kano Jigawa Kebbi Sokoto Total ATASP 1 Non ATASP 1 ATASP 1 Non ATASP 1 ATASP 1 Non ATASP 1 ATAS P 1 Non ATASP 1 ATAS P 1 Non ATASP 1 Sorghum 4(80) 1(20) 4(80) 1(20) 3(60) 2(40) 11(55) 4(20) Rice 5(100) 4(80) 4(80) 4(80) 4(80) 1(20) 3(60) 1(20) 16(80) 10(50) Cassava 3(60) 2(40) 3(60) 2(40) 3(60) 2(40) 9(45) 6(30) Maize 5(100) 2(40) 1(20) 3(60) 4(80) 2(40) 10(50) 7(35) G/nut 1(20) 1(20) 5(100) 1(20) 3(60) 1(20) 9(45) 3(15) Sesame 2(40) 2(40) 4(80) 3(60) 6(30) 5(25) Cowpea 3(60) 2(40) 4(80) 1(20) 4(80) 2(40) 11(55) 5(25)
Source: Field Survey (2020) *Multiple response exist 4.3 Usefulness of Support Received fromATASP-1 by the Processors
42 Table 20: Types of value chain activities undertaken across SCPZs Variables Adani Omor Bida Badeggi Kano Jigawa Kebbi Sokoto Total ATASP1 ANonTASP1 ATASP1 ANonTASP1 ATASP1 ANonTASP1 ATASP1 ANonTASP1 ATASP1 ANonTASP1 Value chain activities* Rice Milling 4(80) 1(20) 4(80) 4(80) 4(80) 1(20) 3(60) 1(20) 15(75.0) 7(35.0) storagpackagprocesSeedsingeande 4(80) 4(80) 3(60) 2(40) 3(60) 2(40) 3(60 .0) 1(20.0) 13(65.0) 9(45.0) Production of Pop Sorghum 3(60) 2(40) 5(100) 2(40) 3(60) 3(60) 4(80) 1(20) 17(85.0) 8(40.0) Production of high quality rice flour 4(80.0) 3(60. 0) 5(100) 3(60.0) 1(20.0) 2(40.0) 2(40 .0) 3(60.0) 12(60.0) 11(55.0) Processing of Cassava into garri 4(80.0) 2(40. 0) 4(80.0) 2(40.0) 8(40.0) 4(20.0) Production of Cassava chin chin doughandnut 4(80.0) 3(60. 0) 4(80.0) 2(40.0) 4(80.0) 3(60.0) 16(80.0) 9(45.0) Production of cassava fufu 4(80) 2(40) 4(80.0) 4(80.0) 8(40.0) 6(30.0)
The distribution of beneficiaries' perception on the Usefulness of support received from ATASP-1 is presented in figure 18. The result show that majority (75.0%) of the Program beneficiaries perceived that support received from ATASP-1 inform of capacity building as very useful and has increase their ability to assess their needs, participate in planning, implementation and manage economic activities. Therefore, it is evident that the Program capacity building activity has done favorably well. Note withstanding, some Project beneficiaries still have negative feelings about this component, even though insignificant. For instance, 5.0% of the respondents did not comprehend the importance of the capacity building i.e. the capacity building is not useful to them at all. Linkages between major institutional actors in agricultural knowledge and information system are widely recognized as essential for an effective flow of technology and information between research, extension and farmers. The result shows that there is an increase of 50.0% linkages created by the Program. It should be noted that the types and nature of linkage between actors with better knowledge and information system directly influenced the production and productivity of farmers. Furthermore, the result shows that 85.0% of the beneficiaries reported that access to market information is very useful because the market information has increased their efficiency towards overcoming issues of market failure based on asymmetric access to basic market information. Conclusively, it can be inferred that ATASP-1 support has impacted positively on the processors capacity, linkages and access to market information across zones.
4.4 Change in level of patronage among beneficiaries before and afterATASP-1
43
The result of change in beneficiary level of patronage before and after ATASP-1 Intervention is presented in figure 19. The level of patronage among beneficiaries at Adani-Omor zone was put at 22.0% before ATASP-1 Intervention. However, after the intervention the level of patronage among beneficiaries increases to 36.0% with percentage change increase of 63.6%. Under Bida-Badeggi zone, the percentage change was put at 53.3%. Furthermore, the level of patronage among beneficiaries has increased by 58.3% and 57.9% at Kano-Jigawa and Kebbi-Sokoto zones respectively. The national result further indicated that before intervention the level of patronage was 20.0% and after intervention the level of patronage has increased to 31.8%. When comparing the level of patronage before and after intervention at national scale, there is 59.0% increase in the level of patronage among Project beneficiaries across zones.
Figure 19: Change in level of patronage among beneficiaries before and after ATASP-1 Intervention
Figure 18: Usefulness of support received from ATASP-1 by Processors
44 4.5 Change in Quantity (kg/Mt) of Output Processed Per Annum across SCPZs
Source: Field Survey (2020)
Table 21: Change in Quantity (kg/Mt) of Output Processed Per Annum across SCPZs SCPZs NON ADOPTERS (ADOPTERS) Before After Percentage change Adani Omor 12,058.1 10,122.0 14,774.2 46.0 Bida Badeggi 14,154.2 15,365.0 21,011.1 36.7 Kano Jigawa 13,301.1 12,074.0 18,212.2 50.8 Kebbi Sokoto 10,901.2 16,911.0 22,041.0 30.3 National 12,603.5 13,618.0 19,009.5 41.0
Table 21 presents the estimated change in output (Kg/Mt) at the four staple crop processing across zones for beneficiaries before and after the intervention as well as nonadopters categories. The national result revealed that beneficiaries had an average output of 13,618.0Kg/Mt per annum before the intervention and non-adopters had an average output of 12,603.5Kg/Mt per annum. However, the output roused to 19,009.5Kg/Mt per annum after the intervention. The percentage change in output was 41.0%, this implies that there is 41.0% increase in output of the processing activities across the zones. Under Adani-Omor, the result shows that beneficiaries had an average output of 10, 122.0Kg/Mt per annum before the intervention and non-adopters had an average output of 12,058.1Kg/Mt per annum. However, the output roused to 14,774.2Kg/Mt per annum after the intervention. The percentage change in output was 46.0%, this implies that there is 46.0% increase in output before and after the Program intervention. In the same vein, the result from Bida-Badeggi zone shows that beneficiaries had an average output of 15,365.0Kg/Mt per annum before the intervention and non-adopters had an average output of 14,154.2Kg/Mt per annum. However, the output increased to 21,011.1Kg/Mt per annum after the intervention. The percentage change in output was thus 36.7%, this implies that there is 36.7% increase in output. Similarly, the estimates of change in processors output at Kano-Jigawa zone shows that beneficiaries had an average output of 12,074.0Kg/Mt per annum before the intervention and non-adopters had an average output of 13,301.1Kg/Mt per annum. However, the output aroused to 18,212.2Kg/Mt per annum after the intervention. The percentage change in output was 50.8%, this implies that there is 50.8% increase in output. Under Kebbi-Sokoto zone, the result indicate that beneficiaries had an average output of 16,911.0Kg/Mt per annum before the intervention and non-adopters had an average output of 10,901.2Kg/Mt per annum. However, the output roused to 22,041.0Kg/Mt per annum after the intervention. The percentage change in output was 30.3%, this implies that there is 30.3% increase in output. It can be concluded that the Program had achieved it target of increasing output of processors by 25% across zones. This was achieved through provision of training, inputs support and provision of processing technologies promoted by the Program.
The estimated change in monthly income of processors across zone is presented in Table 22. The national result shows that processors under the Program beneficiaries had monthly income of N 44,917.3 before the intervention while non-adopters had monthly income of N 60,496.0. The monthly income of the beneficiaries aroused to N 65,313.3 after the intervention. The percentage change in the monthly income across zones was put at 46.0%, this implies that there is an increase of 46.0% in the monthly income generated from processing enterprise across zone before and after the Program Underintervention.Adani-Omor,
the result shows that beneficiaries had an average monthly income of N 41,304.0 before the intervention and non-adopters had an average monthly income of N 57,589.0. However, this average monthly income increases to N 66,017.0 after the intervention. The percentage change in average monthly income was 59.8%, this implies that there is 59.8% increase in average monthly income of processors before and after the Program intervention. Furthermore, the result under Bida-Badeggi zone shows that beneficiaries had an average monthly income of N 37,808.0 before the intervention and non-adopters had an average monthly income of N 42,547.0. However, the monthly income aroused to N 71,244.0 after the intervention. The percentage change in the average monthly income was consequently put at 35.5%, this implies that there is 35.5% increase in average monthly income against the Project target of 25% increased. In the same vein, the estimate of change in average monthly income at Kano-Jigawa zone shows that beneficiaries had an average monthly income of N 35,981.0 before the intervention and non-adopters had an average monthly income of N 64,037.0. However, this monthly income roused to N 82,481.0 after the intervention. The percentage change in average monthly income was put at 48.7%, this implies that there is 47.8% increase in average monthly income of beneficiaries. Similarly, under Kebbi-Sokoto zone, the result indicate that beneficiaries had an average monthly income of N 62,576.0 before the intervention and non-adopters had an average monthly income of N 47,960.0 However, the monthly income increase to N 87,511.0 after the intervention. The percentage change in the average monthly income was put at 39.8%, this implies that there is 39.8% increase in average monthly income of beneficiaries. It can be concluded that the Program had achieved it target of increasing output of processors by 25% across zones. This was achieved through provision of support and type of processing technologies promoted by the Program. Akenbor and Okoye (2011) averred that improve access to agricultural technology, information, and capital would lead to greater value and quality of processed output.
45 4.6 Change in processors monthly income
The result under Kano-Jigawa zone shows that 24.3% of the beneficiaries were satisfied with storage of Sorghum grains and flour for enhanced shelf life technology, 21.6% were satisfied with production of Sorghum flour using hammer mill with Cyclone technology and 16.2% were satisfied with Effective Sorghum drying techniques (i.e of Solar dryer).
The result further shows that only 10.% and 5.4% of the beneficiaries were satisfied with production of Pop Sorghum technology and production of composite flour using Soya bean flour and sorghum flour technology, respectively.
Extended by ATASP-1
The national result shows that 22.4% of the beneficiaries across zones were satisfied with production of Sorghum flour using hammer mill with cyclone technology, 19.4% of the beneficiaries across zones were satisfied with effective Sorghum drying techniques (i.e of Solar dryer), 16.3% of the beneficiaries across zones were satisfied with seed processing, packaging and storage technology as well as storage of Sorghum grains and flour for enhanced shelf life. Furthermore, only 13.3% of the beneficiaries across zones were satisfied with production of composite flour using Soya bean flour and sorghum flour technology.
The result under Kebbi-Sokoto zone shows that 25.8% of the beneficiaries were satisfied with production of composite flour using Soya bean flour and sorghum flour technology, 19.4% of the beneficiaries were satisfied with effective Sorghum drying techniques (i.e of Solar dryer) and production of Sorghum flour using hammer mill with cyclone technologies. The result also indicated that 12.9% of the beneficiaries were satisfied with storage of Sorghum grains and flour for enhanced shelf life technology and production of Pop Sorghum technology. However, only 9.7% of the beneficiaries were satisfied with seed processing, packaging and storage technology.
46 Table 22 : Change in processors’ monthly income SCPZs NON ADOPTERS (N) (ADOPTERS) Before (N) After (N) Percentage change Adani Omor 57,589.0 41,304.0 66,017.0 59.8 Bida Badeggi 42,547 0 37,808 0 71,244 0 35 5 Kano Jigawa 64,037 0 35,981 0 82,481 0 48 7 Kebbi Sokoto 47,960.0 62,576.0 87,511.0 39.8 National 60,496.0 44,917.3 65,313.3 46.0 Source: Field Survey (2020) 4.7 Perception of beneficiaries awareness on sorghum Processing Technologies
Table 23 shows the perception of beneficiary's awareness on sorghum processing technologies extended by ATASP-1. The findings indicated that 26.7% of beneficiaries under Bida-Badeggi zone were satisfied with production of Sorghum flour using hammer mill with cyclone technology, additional 23.3% were also satisfied with effective Sorghum drying techniques (i.e of Solar dryer), 16.7% were satisfied with seed processing, packaging and storage technology and 13.3% were satisfied with production of Pop Sorghum technology. However, only 10.0% of the beneficiaries were satisfied with storage of Sorghum grains and flour for enhanced shelf life technology as well as production of composite flour using Soya bean flour and sorghum flour technology
Table Perception of beneficiary’s awareness on sorghum processing technologies extended by ATASP 1
4.8 Perception of Beneficiaries awareness on Rice Processing Technologies Extended by ATASP-1 Table 24 shows the perception of beneficiary's awareness on rice processing technologies extended by ATASP-1. The findings indicated that 25.8% of the beneficiaries under Adani-Omor zone were satisfied with production of extruded rice snacks technology, 19.4% of the beneficiaries were satisfied with improved rice processing technology and production of rice beverages. still 12.9% of the beneficiaries were satisfied with production of high quality rice flour technology as well as production of rice flour based products. While only 9.7% of the beneficiaries were satisfied with seed processing package and storage technology.
The result under Bida-Badeggi zone shows that 23.3% and 26.7% of the beneficiaries were satisfied with improved rice processing technology and production of rice beverages respectively In the same vein, about 16.7% and 13.3% of the beneficiaries were satisfied with seed processing package and storage technology and production of rice flour based products respectively While only 10.0% of the beneficiaries were satisfied with production of high quality rice flour technology The result under Kano-Jigawa zone shows that 24.3% of the beneficiaries were satisfied with production of high quality rice flour technology, 21.6% of the beneficiaries were satisfied with seed processing package and storage technology as well as production of rice beverages. In addition, 16.2% and 10.8% of the beneficiaries were satisfied with improved rice processing technology and production of rice flour based products respectively. While only 5.3% of the beneficiaries were satisfied with production of extruded rice snacks technology.
23:
47
Source: Field Survey (2020) Sorghum Processing Technologies Bida Badeggi Kano Jigawa Kebbi Sokoto National Seed processing, packaging and storage 5(16.7) 8(21.6) 3(9.7) 16(16.3) Effective Sorghum drying techniques (i.e of Solar dryer) 7(23.3) 6(16.2) 6(19.4) 19(19.4) Storage of Sorghum grains and flour for enhanced shelf life 3(10.0) 9(24.3) 4(12.9) 16(16.3) Production of Pop Sorghum 4(13.3) 4(10.8) 4(12.9) 12(12.2) Production of Sorghum flour using hammer mill with Cyclone 8(26.7) 8(21.6) 6(19.4) 22(22.4) Production of composite flour using Soya bean flour and sorghum flour 3(10.0) 2(5.4) 8(25.8) 13(13.3)
The result under Kebbi-Sokoto zone shows that 16.3% and 20.9% of the beneficiaries were satisfied with improved rice processing technology and production of high quality rice flour technology respectively, 18.6% of the beneficiaries were satisfied with seed processing package and storage as well as production of extruded rice snacks technology
48 The result further indicated that 11.6% and 14.0% of the beneficiaries were satisfied with production of rice flour based products and production of rice beverages technology Furthermore,respectively. the national result shows that 21.1% and 19.9% of the beneficiaries across zones were satisfied with production of rice flour based products technology and production of rice beverages technology respectively In the same vein, 18.4% and 14.9% of the beneficiaries across zones were satisfied with improved rice processing technology and production of extruded rice snacks technology respectively The result equally shows that 17.7% of the beneficiaries across zones were satisfied with production of high quality rice flour technology and 17.0% of the beneficiaries across zones were satisfied with seed processing package and storage technology
Table 24: Perception of beneficiaries’ awareness on rice processing technologies extended by ATASP 1 Rice Processing Technologies Adani-Omor Bida-Badeggi Kano-Jigawa Kebbi-Sokoto National Seed processing package and storage 3(9 7) 5(16 7) 8(21 6) 8(18 6) 24(17 0) Improved rice processing technology 6(19.4) 7(23.3) 6(16.2) 7(16.3) 26(18.4) Production of high quality rice flour 4(12.9) 3(10.0) 9(24.3) 9(20.9) 25(17.7) Production of rice flour based products 4(12 9) 4(13 3) 4(10 8) 5(11 6) 17(21 1) Production of rice beverages 6(19.4) 8(26.7) 8(21.6) 6(14.0) 28(19.9) Production of extruded rice snacks 8(25.8) 3(10.0) 2(5.4) 8(18.6) 21(14.9)
Source: Field Survey (2020) 4.9 Perception of Beneficiaries awareness on Cassava Processing Technologies Extended byATASP-1 Table 25 shows the perception of beneficiary's awareness on cassava processing technologies extended by ATASP-1. The findings indicated that 23.1% and 20.5% of the beneficiaries under Adani-Omor zone were satisfied with processing of Cassava into garri and starch technology, respectively In addition, 17.9% of beneficiaries were satisfied with production of cassava fufu, 15.4% of the beneficiaries were satisfied with production of high quality cassava flour technology, and 10.3% production of Cassava chin -chin and doughnut. While only 7.7% and 5.1% of the beneficiaries were satisfied with production of Cassava/bean crisp and eggroll and processing of Cassava into chips and chunks, respectively The result under Bida-Badeggi zone shows that 22.6% of the beneficiaries were satisfied with processing of Cassava into garri and starch technology respectively. In the same vein, about 16.1% of the beneficiaries were satisfied with production of high quality
49 cassava flour and fufu technology. However, 12.9% of the beneficiaries were satisfied with production of Cassava chin -chin and doughnut technology. While only 6.5% of the beneficiaries were satisfied with processing of Cassava into chips and chunks and 3.2% of the beneficiaries were satisfied with production of Cassava/bean crisp and eggroll.
Table 25: Perception of beneficiaries awareness on cassava processing technologies extended by ATASP -1 Cassava Processing Technologies Adani Omor Bida Badeggi Kano Jigawa National Processing of Cassava into garri 9(23 1) 7(22 6) 9(28 1) 33(24.3) Production of high quality cassava flour 6(15.4) 5(16.1) 6(18.8) 21(15.4) Processing of Cassava and starch 8(20.5) 7(22.6) 8(25.0) 31(22.8) Production of Cassava chin chin and doughnut 4(10 3) 4(12 9) 5(15 6) 18(13 2) Production of cassava fufu 7(17 9) 5(16 1) 1(3 1) 16(11 8) Processing of Cassava into chips and chunks 2(5.1) 2(6.5) 2(6.3) 8(5.9) Production of Cassava/bean crisp and eggroll 3(7.7) 1(3.2) 1(3.1) 9(6.6) Field Survey (2020)
The result under Kano-Jigawa zone shows that 28.1% and 25.0% of the beneficiaries were satisfied with processing of Cassava into garri and starch technology, respectively However, 18.8% of the beneficiaries were satisfied with production of high quality cassava flour technology and 15.6% of the beneficiaries were satisfied with production of Cassava chin -chin and doughnut technology In addition, only 3.1% of the beneficiaries were satisfied with production of cassava fufu technology, 6.3% of the beneficiaries were satisfied with processing of Cassava into chips and chunks technology and 3.1% of the beneficiaries were satisfied with production of Cassava/bean crisp and eggroll Furthermore,technology.thenational
Source:
result shows that 24.3% and 22.8% of the beneficiaries across zones were satisfied with processing of Cassava into garri and starch technology respectively. In the same vein, 15.4% of the beneficiaries across zones were satisfied with production of high quality cassava flour technology, 13.2% of the beneficiaries across zones were satisfied with production of Cassava chin -chin and doughnut technology and 11.8% of the beneficiaries across zones were satisfied with production of cassava fufu technology. However, result shows that only 5.9% of the beneficiaries across zones were satisfied with processing of Cassava into chips and chunks technology and 6.6 % of the beneficiaries across zones were satisfied with seed Production of Cassava/bean crisp and eggroll technology
Source: Field Survey (2020) *Multiple responses
50 4.10 Constraints militating against processing among beneficiaries
The constraints militating against processing among ATASP-1 beneficiaries is presented in Table 26. Under Adani-Omor zone, the findings indicated that 29.6% of the beneficiaries reported lack of power supply as their major constraint, 22.2% of the beneficiaries reported lack of capital and 14.8% of the beneficiaries reported inadequate market information. Other constraints reported by beneficiaries include inadequate water supply (14.8%) low patronage (11.1%) and limited access to raw materials (7.4%). Further down Bida-Badeggi zone, the result shows that lack of capital (25.0%) and inadequate market information (22.2%) were the major constraints faced by beneficiaries. In addition, 16.7% of the beneficiaries were faced with problem of inadequate power supply, low patronage (13.9%), limited access to raw materials (11.1%) and inadequate water supply (11.1%).
In Kebbi-Sokoto zone, the result shows that inadequate water supply (25.8%), lack of capital (22.6%), inadequate power supply (19.4%), low patronage (12.9%) and inadequate market information (12.9%) were the major constraints faced by beneficiaries. Other constraints faced by beneficiaries include limited access to raw materials (6.5%). The national result shows that lack of capital (23.9%), inadequate water supply (19.7%) and inadequate power supply (18.8%) were the major constraints faced by beneficiaries across zone. Other constraints faced by beneficiaries across zones include inadequate market information (14.5%), low patronage (12.8%) and limited access to raw materials (10.3%). The findings support that of Adeyemo and Okoruwa (2018) whom pointed out that access to inputs, capital and credit were among the major problems encountered by processors. Table 26: Constraints militating against processing among beneficiaries Constraints* AdaniOmor BaBidadeggi JigKanoawa SoKebbikoto National Lack of capital 6(22.2) 9(25.0) 6(26.1) 7(22.6) 28(23.9) Low patronage 3(11.1) 5(13.9) 3(13.0) 4(12.9) 15(12.8) Limited access to raw materials 2(7.4) 4(11.1) 4(17.4) 2(6.5) 12(10.3) Inadequate market information 4(14.8) 8(22.2) 1(4.3) 4(12.9) 17(14.5) Inadequate power supply 8(29.6) 6(16.7) 2(8.7) 6(19.4) 22(18.8) Inadequate water supply 4(14.8) 4(11.1) 7(30.4) 8(25.8) 23(19.7) Total 27(100.0) 36.0(100.0) 23(100.0) 31(100.0) 117(100.0)
Under Kano-Jigawa zone, the result shows that inadequate water supply (30.4%), lack of capital (26.1%) and limited access to raw materials (17.4%) were the major constraints faced by beneficiaries. Other constraints faced by beneficiaries include, low patronage (13.0%), inadequate power supply (8.7%) and inadequate market information (4.3%).
Figure 23: Final processing process: Garri frying.
Figure 24: Final processing process: Garri frying. Figure 25: Final processed product on display at the market centre.
Figure 22: Pressing of grated cassava and fermentation process at the village Garri processing centre.
Figure 26: Rice mill in operation 51 Figure 20: Cassava peeling at the village Garri processing centre. Figure 21: Cassava grating in progress in one of the village 4 Garri processing centre.
Product diversification in to various ways from sorghum
FINDINGS AND DISCUSSION FABRICATORS
5.1 Socio-economic characteristics' of the respondents. The socio-economic characteristics of processors includes gender, level of education, age of household head, household size and years of experience in fabrication.
5.1.1 Gender and Level of education of fabricators
The distribution of fabricators across gender is presented in Table 27. The national result shows that the male gender was the dominant group, accounting 100.0% for both beneficiaries and non-beneficiaries respectively. The distribution of fabricators according to their level of education is presented in Table 27. There is considerable variation in the education level of fabricators. The national result shows that only 5.0% of both beneficiaries and non-beneficiaries do not attained any form of education. The result also shows that 15.0% and 5.0% of the beneficiaries and non-beneficiaries respectively acquired primary education respectively, 40.0% and 25.0% of the beneficiaries and non-beneficiaries acquired secondary/TC II education respectively and 10.0% and 20.0% of the beneficiaries and non-beneficiaries acquired tertiary education respectively However, 15.0% of both beneficiaries had non-formal education and 15.0% and 30.0% of the beneficiaries and non-beneficiaries acquired Qur'anic education respectively. However, a review of the breakdown across zones reveal that for the beneficiaries, the secondary/TC II education had the largest proportion while uneducated individuals present 20.0% at Adani-Omor. Aboki et al. (2013) argues that education in agricultural value chain will assist to accept and test innovations that are available, and enhance the ability to make informed and accurate management decisions.
5.0
52 5
Gender Male 5(100 0) 5(100 0) 5(100 0) 5(100 0) 5(100 0) 5(100 0) 5(100 0) 5(100 0) 5(100 0) 5(100 0)
Secondary/TC II 2(40 0) 1(20 0) 3(60 0) 2(40 0) 1(20 0) 3(60 0) 1(20 0) 8(40 0) 5(25 0) Tertiary 1(20 0) 3(60 0) 1(20 0) 1(20 0) 2(10 0) 4(20 0) Non Formal 1(20 0) 1(20 0) 2(40 0) 1(20 0) 1(20 0) 3(15 0) 3(15 0) Qur’anic 1(20.0) 1(20 0) 2(40 0) 2(40 0) 3(60 0) 3(15.0) 6(30.0)
The distribution of fabricators according to household size composition is presented on Table 28. The national result shows that most of household head under Program beneficiaries had minimum of 1 male members per household head and maximum of 12 male members per household head with average of 5 male members per household head. In addition, the non-Program beneficiaries had minimum of 1 male members per household head and maximum of 10 male members per household head with average of 4 male members per household head. Further review of the results across zone show that the fabricators household head under Kano-Jigawa zone had the highest average of male members per household head presenting 6 and 5 for beneficiaries and non-beneficiaries Similarlyrespectively.,the national result shows that most of household head under Program beneficiaries had minimum of 1 female members per household head and maximum of 7 female members per household head with average of 3 female members per household head. In addition, the non-Program beneficiaries had minimum of 1 male members per household head and maximum of 9 female members per household head with average of 4 female members per household head. Further review of the results across zone show that the fabricators household head under Kano-Jigawa zone had the highest average of
53 Table 27: Gender and Level of education across SCPZs Variables Adani Omor Bida Badeggi Kano Jigawa Kebbi Sokoto National ATASP ANonTASP ATASP ANonTASP ATASP ANonTASP ATASP ANonTASP ATASP ANonTASP
Source: Field Survey (2020) 5.1.2 Age of household head (years) Table 28 details the age of fabricators across SCPZs. The national results show that the age of Program beneficiaries ranged from 26 to 55 years with mean age 30 years. Similarly for the non-beneficiaries, the minimum age of 28 years was obtained with maximum age of 68years. Further review of the results show that the fabricators were generally young, as reflected by mean ages of 30 years and 32 years for Program beneficiaries and non-beneficiaries respectively. The outcome under Kano-Jigawa zone further shows mean age of 28 year and 30 years for beneficiaries and non-beneficiaries. It can be concluded that younger people are more involved in the Program.
Level of education No school at all 1(20 0) 1(20 0) 1(5 0) 1(5 0) Primary 1(20.0) 1(20.0) 1(20.0) 1(20.0) 3(15.0) 1(5.0)
5.1.3 Household size of fabricators
Table 28: Age, household size and experience of fabricators across SCPZs Adani Omor Bida Badeggi Kano Jigawa Kebbi Sokoto National ANon-TASP1 ANon-TASP1 ATASP1 ANon-TASP1 House Head 2.0 3.0 4.0 3.0 2.0 3.0 4.0 Experience Min 3.0 2.0 2.0 2.0 4.0 2.0 6.0 4.0 2.0 2.0 Max 21.0 29.0 25.0 27.0 19.0 27.0 21.0 20.0 29.0 25.0 Mean 13.0 10.0 12.0 11.0 13.0 10.0 9.00 8.0 14.0 12.0
ATASP1 ANon-TASP1 Age of
54 female members per household head presenting 3 and 4 for beneficiaries and nonbeneficiaries respectively. While it is recognised that household size plays a key role in subsistence agriculture where value chain actors rely on the number of people in the family for labour source; however, high household population has grave implication for technology adoption and food security status of the participating households.
Variables
5.1.4 Experience
(years) Min 28.0 29.0 26.0 29.0 27.0 28.0 27.0 28.0 26.0 28.0 Max 64.0 65.0 55.0 66.00 58.0 62.0 64.0 68.0 55.0 68.0 Mean 30.0 31.0 29.0 32.0 28.0 30.0 31.0 32.0 30.0 32.0 Number of Male Household Members Min 3.0 1.0 3.0 3.0 5.0 4.0 2.0 1.0 1.0 1.0 Max 7.0 5.0 9.0 8.0 12.0 10.0 7.0 6.0 12.0 10.0 Mean 3.0 2.0 4.0 3.0 6.0 5.0 3.0 2.0 5.0 4.0 Number of Female Household Members Min 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 Max 5.0 8.0 6.0 4.0 6.0 9.0 7.0 4.0 7.0 9.0 Mean 2.0 4.0 3.0
5.2
hold
Source: Field Survey (2020) Usefulness of Support Received from ATASP-1 by Fabricators
ATASP1
The distribution of fabricators according to their experience is presented in Table 28. The national result shows that most of the fabricators under Program beneficiaries had minimum of 2 years' experience and maximum of 29 years with average of 14 years' experience in fabrications. In addition, the non-Program beneficiaries had minimum of 2 years' experience and maximum of 25 years' experience with average of 12 years' experience. Further review of the results across zone show that the fabricators under Adani-Omor and Kano-Jigawa zones had the highest average of 13 and 10 years' experience for beneficiaries and non-beneficiaries respectively.
The distribution of beneficiaries perception on the usefulness of support received from ATASP-1 is presented in Figure 27. The result shows that 89.0% of the beneficiaries had access to market information which increased their efficiency towards overcoming issues of market failure based on asymmetric access to basic price information. In terms of linkage to other stakeholders, the result shows that 73.0% of fabricators had linkages with other stakeholders created by the Program the result shows that 62.0% of the Program beneficiaries had received support inform of capacity building which increase their ability to assess their needs, participate in planning, implementation and manage economic activities.
ATASP1 ANon-TASP1 ATASP1
Figure 27: Usefulness of Support Received from ATASP-1 by Fabricators
Figure 28: Change in level of patronage due to ATASP-1 intervention
5.3 Change in level of patronage
The result of change in beneficiary's level of patronage before and after ATASP-1 intervention is presented in Figure 28. The level of patronage among beneficiaries at Adani-Omor zone before intervention was put at 39.0%. However, after the intervention the level of patronage among beneficiaries has increased to 61.0% with percentage change of 56.4%. Under Bida-Badeggi zone, the percentage change was put at 62.5%. Furthermore, the level of patronage among beneficiaries had also increased by 54.5% and 63.6% at Kano-Jigawa and Kebbi-Sokoto zones respectively. The national result across zone further indicated that before intervention the level of patronage was 37.0% and after intervention the level of patronage has increased to 58.8%. Comparing the level of patronage before and after intervention across zones, there is 58.8% increase in the level of patronage among fabricators.
55
The estimated change in yearly income of fabricators across zone is presented in Table 29. The National result shows that fabricators under Program beneficiaries had yearly income of N 268,915.3 before the intervention while non-adopters had yearly income of N 249,197.0. However, the yearly income roused to N 358,583.8 after the intervention.
Under Adani-Omor, the result shows that beneficiaries had an average yearly income of N 259,885.0 before the intervention and non-adopters had an average yearly income of N 241,935.0. However, the average yearly income increase to N 341,885.0 after the intervention. The percentage change in average yearly income was 31.6%, this implies that there is 31.6% increase in average yearly income of fabricators before and after the Program
The percentage change in the yearly income across zones was 33.3%, this implies that there is an increase of 33.3% in the yearly income generated from fabrication across zone before and after the Program intervention.
56 5.4
under Bida-Badeggi zone shows that beneficiaries had an average yearly income of N 247,200.0 before the intervention and non-adopters had an average yearly income of N 211,613.0. However, the yearly income roused to N 323,200.0 after the intervention. The percentage change in the average yearly income was 30.7%, this implies that there is 30.7% increase in average yearly income against the national target of 25% increased. In the same vein, the estimate of change in average yearly income at Kano-Jigawa zone shows that beneficiaries had an average yearly income of N 307,985.0 before the intervention and non-adopters had an average yearly income of N 300,049.0. However, the yearly income roused to N 419,170.0 after the intervention. The percentage change in average yearly income was put at 36.1%, this implies that there is 36.1% increase in average yearly income of beneficiaries. Similarly, under Kebbi-Sokoto zone, the result indicate that beneficiaries had an average yearly income of N 260,591.0 before the intervention and non-adopters had an average yearly income of N 243,191.0. However, the yearly income increase to N 350,080.0 after the intervention. The percentage change in the average yearly income was put at 34.3%, this implies that there is 34.3% increase in average yearly income of beneficiaries. It can be concluded that the Program had achieved it target of increasing income of fabricators by 25% across zones. This was achieved through provision of support and type of technologies promoted by the Program.
Change in yearly income of fabricators
Furthermore,intervention.theresult
The result under Bida-Badeggi zone shows that fabricators before intervention on average had yearly income of N 247,200.0 which is less than the non-adopters group (N 211,613.0). The comparative analysis of yearly income realised by fabricators under Bida-Badeggi zone before and after (N 323,200.0) intervention shows that Z- calculated is greater than Z-critical, thus implying that there was significant difference (P<0.01) in the yearly income realised. Therefore, the null hypothesis is rejected in favour of the alternative which stated that, there is significant difference in the yearly income of fabricators under Bida-Badeggi zone before and after intervention.
Source: Field Survey (2020) 5.5
57 Table 29: Change in yearly income of fabricators SCPZs Yearly Income (N) (NON ADOPTERS) Yearly Income (N) (ADOPTERS) Percentage change BEFORE AFTER Adani Omor 241,935.0 259,885.0 341,885.0 31.6 Bida Badeggi 211,613.0 247,200.0 323,200.0 30.7 Kano Jigawa 300,049.0 307,985.0 419,170.0 36.1 Kebbi Sokoto 243,191.0 260,591.0 350,080.0 34.3 National 249,197.0 268,915.3 358,583.8 33.3
Comparative analysis of fabricators' yearly income
The result under Kano-Jigawa zone shows that fabricators before intervention on average had yearly income of N 307,985.0 which is less than the non-adopters group (N 300,049.0). The comparative analysis of yearly income realised by fabricators under Kano-Jigawa zone before and after (N 419,170.0) intervention shows that Z- calculated is greater than Z-critical, thus implying that there was significant difference (P<0.001) in the yearly income realised. Therefore, the null hypothesis is rejected in favour of the alternative which stated that, there is significant difference in the yearly income of fabricators under Kano-Jigawa zone before and after intervention.
The comparative analysis of yearly income generated by fabricators was estimate using Z-test to test hypothesis whether changes observed in the yearly income of fabricators was as result of ATASP-1 intervention as presented in Table 30. There is no significant difference in the yearly income of fabricators before and after intervention. The result underAdani-Omor zone shows that fabricators before intervention on average had yearly income of N 259,885.0 which is less than the non-adopters group (N 241,935.0). The comparative analysis of yearly income realised by fabricators under Adani-Omor zone before and after (N 341,885.0) intervention shows that Z- calculated is greater than Zcritical, thus implying that there was significant difference (P<0.01) in the yearly income realised. Therefore, the null hypothesis is rejected in favour of the alternative which stated that, there is significant difference in the yearly income of fabricators underAdaniOmor zone before and after intervention.
on quality of
respectively
2. 5139** National 249,197.0 268,915.3 358,583.8 2.9626** Source: Field Survey (2020) 5.6 Effect of
The result under Kebbi-Sokoto zone shows that fabricators before intervention on average had yearly income of N 260,591.0 which is less than the non-adopters group (N 243,191.0). The comparative analysis of yearly income realised by fabricators under Kebbi-Sokoto zone before and after (N 350,080.0) intervention shows that Z- calculated is greater than Z-critical, thus implying that there was significant difference (P<0.01) in the yearly income realised. Therefore, the null hypothesis is rejected in favour of the alternative which stated that, there is significant difference in the yearly income of fabricators under Kebbi-Sokoto zone before and after intervention.
The
The national result across zone shows that fabricators before intervention on average had yearly income of N 268,915.3 which is less than the non-adopters group (N 249,197.0).
Bida
58
The comparative analysis of yearly income realised by fabricators across zones before and after (N 358,583.8) intervention shows that Z- calculated is greater than Z-critical, thus implying that there was significant difference (P<0.01) in the yearly income realised. Therefore, the null hypothesis is rejected in favour of the alternative which stated that, there is significant difference in the yearly income of fabricators across zones before and after intervention. This implies that ATASP-1 intervention had impacted on yearly income of fabricators across zones. Yearly Income(N) (NON ADOPTERS) Yearly Income(N) (ADOPTERS) T statistic BEFORE AFTER Adani Omor 241,935.0 259,885.0 341,885.0 2.3690** Badeggi 211,613.0 247,200.0 323,200.0 2.78415** Kano Jigawa 300,049.0 307,985.0 419,170.0 3. 1596*** Kebbi Sokoto 243,191.0 260,591.0 350,080.0 training fabrication distribution of fabricators based on effectiveness of training received is presented in Figure 29. The result shows that 80.0% of beneficiaries under Adani-Omor Zone rated the quality of training they received as excellent and only 20% of the beneficiaries rated the quality of training they received as very good. However, under Bida-Badeggi zone, the result shows that 60.0% of beneficiaries rated the quality of training they received as excellent and only 20% rated the quality of training they received as very good and good In the same vein, the result shows that 60.0% of beneficiaries under KanoJigawa zone rated the quality of training they received as excellent and 40% of the beneficiaries rated the quality of training they received as very good. Furthermore, the result shows that 40.0% of beneficiaries rated the quality of training they received as excellent and very good, while only 20% rated the quality of training they received as good.
Table 30: Comparative analysis of fabricators yearly income SCPZs
Similarly, under Kano-Jigawa zone, the result also shows that lack of capital (40.0%) and inadequate power supply (40.0%) were the major constraints faced by beneficiaries. Other constraints faced by beneficiaries include low patronage (20.0%).
Moreover, the national result across zones shows that 60.0% of beneficiaries rated the quality of training they received as excellent and 30.0% as very good, while only 10% rated the quality of training they received as good. There is overwhelming evidence to suggest that the training offered by ATASP-1 has contributed positively to the quality of the fabricated equipment of the Project beneficiaries.
59
Further down Kebbi-Sokoto zone, the result shows that inadequate power supply (40.0%), is the major constraints faced by beneficiaries. Other constraints faced by beneficiaries include lack of capital (20.0%), low patronage (20.0%) and limited access to raw materials (20.0%).
Source: Field Survey (2020) Constraints militating against fabrication among beneficiaries across zone
Figure 29: Effect of training on quality of fabrication
The constraints militating against fabricators among beneficiaries is presented in Table 31. Under Adani-Omor zone, the findings indicated that 40.0% of the beneficiaries reported inadequate power supply as their major constraint. However, other constraints reported by beneficiaries include lack of capital (20.0%), limited access to raw materials (20.0%) and inadequate market information (20.0%).
Under Bida-Badeggi zone, the result shows that lack of capital (40.0%) and inadequate power supply (40.0%) were the major constraints faced by beneficiaries. In addition, 20.0% of the beneficiaries were faced with problem of limited access to raw materials (20.0%).
Likewise, the national result indicated that inadequate power supply (40.0%), lack of capital (30.0%), limited access to raw materials (15.0%), low patronage (10.0%) and inadequate market information (5.0%) were the major constraints faced by beneficiaries across zones.
5.7
60 Table 31: Constraints militating against fabrication among beneficiaries Constraints* AdaniOmor BaBidadeggi JigKanoawa SoKebbikoto National Lack of Capital 1(20.0) 2(40.0) 2(40.0) 1(20.0) 6(30.0) Low Patronage 1(20.0) 1(20.0) 2(10.0) Access to Raw Materials 1(20.0) 1(20.0) 1(20.0) 3(15.0) Market Information 1(20.0) 1(5.0) Inadequate Power Supply 2(40.0) 2(40.0) 2(40.0) 2(40.0) 8(40.0) Total 5(100.0) 5(100.0) 5(100.0) 5(100.0) 20(100.0) Source: Field Survey (2020) Figure 30: One of the programme beneficiary in his workshop constructing thresher component Figure 31: Final machine coupling by one of the ATASP 1 beneficiary fabricator Figure 32: Rice parboiling unit in operation fabricated by ATASP 1 beneficiary. Figure 33: Final coupling of rice thresher fabricated by ATASP 1 beneficiary Figure 34: Threshers ready for sell
CONCLUSIONAND RECOMMENDATION
The program did not capture peoples with special needs members of the society Rice is the most dominant crop cultivated across the zones.
The study revealed that sorghum yielded more output per hectare at Bida Badeggi zone while profit recorded per hectare was more at Kebbi-Sokoto zone. The highest and lowest production cost was observed at Kano-Jigawa and Bida-Badeggi zones
There is variability of output, price and profitability of crop enterprises across the four Staple Crop Processing Zones.
6.0
Ricerespectivelyyielded more output per hectare at Kebbi-Sokoto, while Bida-Badeggi recorded the highest profitability on the same commodity per hectare. On the other hand, the least cost of production was recorded at Kebbi-Sokoto zone, while the highest cost of production was observed at Bida-Badeggi zone. Cassava output per hectare was more at Bida-Badeggi zone, whileAdani-Omor recorded the highest profitability per hectare from the same crop. The least production cost was at Kano-Jigawa, and the highest cassava production cost was recorded at Bida-Badeggi Inzone.all cases, output and net income of Project beneficiaries has surpass the 25% benchmark Projected increments observed in the Project document. Output and profitability of crop enterprises per hectare was more among Program beneficiaries than non-Program beneficiaries. The study noted that there are more women involved in processing activities than men across the staple crop processing zones.
6
The percentage of rice and cassava processors are higher and are the most dominant value 61
6.1 Conclusion In view of the foregoing analysis, this study concluded that: The Project farmers are predominantly young between the ages of 35 to 40 Majority of the beneficiaries have formal education.
6.2 Recommendation
chain processing activity across the zones.
The Program has impacted positively on the output and income of its beneficiaries.
The capacity and patronage of the fabricators increased tremendously as a result of ATASP-1 intervention.
In view of the conclusions derived, the study wishes to make the following recommendations:
Since the study has identified disparities in productivity and profitability on the same crop enterprises across the zones, it is highly recommended that the Program conduct additional study to identify the possible reasons responsible for this variations with a view to proffer solutions. The Program should be more inclusive and accessible especially to persons with special Theneeds.Program should render production input support to farmers, as well as provide capacity building, market linkages and credit supply to all beneficiaries.
To reduce drudgery associated in farm operations and processing of agricultural commodities, the Project should upscale its intervention through mechanisation.
62
Patronage of agro processing business has increased significantly as a result of the ATASP-1 intervention. The study equally observed that fabrication business is a male dominated enterprises.
Akenbor, C. O and Okoye, E. I (2011). An empirical investigation of value-chain analysis and competitive advantage in the Nigerian manufacturing industry, African Research Review, 5 (6), 188-198, doi: http://dx.doi.org/10.4314/afrrev.v5i6.16
Amodu, M. Y., Owolabi, J. O. and Adeola, S. S. (2011). Resource Use Efficiency in Part-time Food Crop Production. Nigerian Journal of Basic and Applied Science. 19(1): 102-110.
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Federal Ministry of Agriculture and Rural Development (FMARD) (2012). Implementation Strategy on the Agricultural Transformation Agenda, Committee Draft Report, Abuja, Nigeria. 63
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C O N S T E C H N I C A L T E A M A T A S P1 Mr. Akintunde Akinwale P. Survey Co-ordinator Mr. Chukwuma Ejiogu Mrs. Falmata Zanna G Member Member Mr. Romanus Egba Zonal Program Co ordinator Adani-Omor SCPZ Engr. Ibrahim Manta Alh. Auwalu Ado Shehu Dr. Aliyu Addaji Zonal Program Co ordinator Bida-Badeggi SCPZ Zonal Program Co ordinator Kano-Jigawa SCPZ Zonal Program Co ordinator Kebbi-Sokoto SCPZ Mr. Ugochukwu Nnanna Member IBRAHIM M. ARABI National Program Co-ordinator
FEDERAL MINISTRY OF AGRICULTURE AND R URAL DEVELOPMENT AGRICULTURAL TRANSFORMATION AGENDA SUPPORT PROGRAM PHASE-1 (ATASP-1) Survey Questionnaire for the Income and Profitability Assessment of ATASP -1 Beneficiaries in Nigeria Farmers Questionnaire: A.2 Cropping Enterprise: 1 Sorghum 2 Rice 3 Cassava (B) Socio economic characteristics of farmers B 1Household structure and Details Gender Special Needs Age of HH Head (years) Marital Status Education level of HH Head Number of Household Members [ ] Yes [ ] No Wife/wives Children < 18 yrs children 19yrs and above Other HH Members A 1 Background Information SCPC Cropping Zone: Interview Date: State: LGA: Community: Cluster: Name of Farmer: Name of Group: Name of Group Leader: Phone Number of Farmer: Name of Enumerator: Phone Number of Enumerator: GPS Coordinate:Latitude: [ ] Longitude: [ ] Questionnaire Number: [ ] 67
Number of Household Members by Gender: Male: Female: Education level: 0 = none ; 1= Koranic ; 2 = primary, 3 = junior secondary school, 4 = senior secondary school, 5 = tertiary, 6 = other (specify) Gender: 1 = Male, 2 = Female; Marital Status: 1 = Married, 2 = Single, 3 = Others B2 Farmer’s Plot Details B2.1 Cropping practices used: 1 Sole Cropping 2 Mixed Cropping B2.2 Total size of your farm holding (ha): Before ATASP 1: After ATASP 1: B2.3 could you please provide the following details about your farm size and experience Crop 1Mode of acquisition Size of land (ha) Before ATASP -1 After ATASP -1 Cassava Rice Sorghum 1Mode: 1 = Inheritance 2=Purchase 3 = Rent 4=Lease 5 =Gift 6=Others (specify) Others: B3 Extension Contact B3.1 Did extension staff visit you last growing season? [ ] No, [ ] Yes B3.2 If yes, how OFTEN did extension staff visit you last cropping season _ B3.3 Did you participate in the Innovation Platform? [ ] No, [ ] Yes B3.4 Did you participate in demonstration plots? [ ] No, [ ] Yes B3.5 Did you participate in farmers’ field day? [ ] No, [ ] Yes B4.Credit information for the last cropping season Access to credit Ease of Access If Yes 1Source of credit Credit required (N) Credit received (N) Nature of credit 2What was the money used for? Level of loan repayment (%) 0 No 1 Yes 1 Prompt 2 Delaye d 1 Cash 2 Kind 68
1Source of credit: 1 = credit program, 2 = commercial bank, 3 = cooperatives 4 = NGO, 5 = traders, 6 = agricultural bank 7 = family and friends 8 = other (specify) 2What money was used for : 1 = input purchase, 2 = agricultural activity, 3 = commerce, 4 = health care, 5 = purchase of food, 6 = social functions, 7 = other expenses (specify) C. Production information C1 Inputs used S/NO DESCRIPTION Total Cost of Production (? ) 1 Sorghum Cost of Production 2 Rice Cost of Production 3 Cassava Cost of Production C2. Output from Crop Enterprise S/No Crops (NONADOPTERS) (ADOPTERS) ABEFORETASP-1 AAFTERTASP-1 1 Rice (Bags) 2 Sorghum (Bags) 3 Cassava (Kg) C3. Crop enterprise pricing for Rice, Sorghum and Cassava S/No Crops Unit Price (? ) (NONADOPTERS) Unit Price (? ) (ADOPTERS) ABEFORETASP-1 AAFTERTASP-1 1 Rice (Bags) 2 (SorghumBags) 3 Cassava (Kg) D1.1.Are you aware of any of the following technologies for crops production (Sorghum, Rice and Cassava)? [ ] No [ ] Yes D1 2 S/N Technologies Disseminated Awareness Status 1Source of awareness Practiced any of Technologies 2Perception of usefulness 1 Improved input 2 Extension Support 69
3 Land Preparation 4 Soil Conservation 5 Record Keeping 6 Others (specify) 1Awreness Source: ATASP_1 = 1, ADP = 2, NGOs = 3, Other Farmers = 4, Others (Specify) = 5 2Perception of Usefulness: Very Useful = 4, Useful = 3, Rarely Useful = 2, Not Useful = 1 Awareness Status: 0 = No, 1 = Yes Technology Practiced: 0 = No, 1 = Yes E1. Indicate Frequency of practicing these extended technologies on sorghum, rice and cassava production S/N TECHNOLOGIES Frequency of practice (code) 1 Improved Input 2 Extension Support 3 Land Preparation 4 Soil Conservation 5 Record Keeping Frequency of Practice: 5 = Regularly, 4 = often, 3 = sometime, 2 = rarely, 1 = never F. Reasons for Adoption of Good Agronomic Practices (GAP) Technologies were based on theGAfollowing:P Rank (Code) Labour saving Higher yield Soil moisture retention Soil erosion control Enhancement of soil fertility Climate change adaptation Others (specify) Rank Code: 3 = Agree, 2 = Not sure, and 1 = Disagree G. Constraints to adoption of Good Agronomic Practices (GAP) Technologies Constraints Rank (Code) Knowledge: Insufficient awareness Poor understanding of technology (GAP) requirements, 70
Poor record keeping, Environmental: Human factors Physical/Climatic factors Social: Socio cultural (Religious belief/Tradition ) shortage of labour, insufficient networking with stakeholders, Conflict Production Constraints Product market: Long distance to market Low prices for rice Low price for cassava Low price for sorghum High transport cost Lack of market/demand for product Extension services: Unavailability of extension services Lack of effectiveness Long distance to the extension workers Others: Problem of pest and diseases Poor roads network Inadequate capital Inadequate land Inadequate large export market Rank Code: 5 = very severe, 4 = severe, 3 = mildly severe, 2 = not severe, 1 = not a problem H. ATASP -1 Support to Beneficiaries H.1 Have you received any input support from ATASP 1? 0 No 1 Yes H.2 In what areas would you want ATASP 1 to support you from the items below? 1 Seeds 2 Fertilizer 3 Agro chemicals 4 Access to credit 5 Regular capacity building 6 Storage facilities H.3 How has the following GAP activities contributed to your farm income? 71
1 Very well 2 Fairly well 3 Not at all I. Which of the following assets owned do you own? (Please tick as applicable) Before ATASP -1 After ATASP -1 I Radio ii Television iii Refrigerator iv GSM Handset v Bicycle vi Motorcycle vii Car vii House viii Storage Facility ix Water Pump x Tractor / Implements xi Farming Tools xii Crop Processing Machine xiii Power Generator xiv Spraying Equipment xv Land Extension xvi Livestock xvii Others (Specify) I Radio ii Television iii Refrigerator iv GSM Handset v Bicycle vi Motorcycle vii Car viii House ix Storage Facility x Water Pump xi Tractor / Implements xii Farming Tools xiii Crop Processing Machine xiv Power Generator xv Spraying Equipment xvi Land Extension xvii Livestock xviii Others (Specify) 72
FEDERAL MINISTRY OF AGRICULTURE AND RURAL DEVELOPMENT AGRICULTURAL TRANSFORMATION AGENDA SUPPORT PROGRAM PHASE -1 (ATASP-1) Survey Questionnaire for the Income and Profitability Assessment of ATASP -1 Beneficiaries in Nigeria Fabricators Questionnaire: (B) DEMOGRAPHIC DATA 2.1) Gender Male Female 2.2) Household Size (Number) Male members = ; Female members = ;Total = 2.3) Age of Beneficiary/Farmer (Years) 1 Below 30 yrs 2 30 59 yrs 3 Above 60 yrs 2.4) Highest Education Attained: 0 = No school at all 1 = Primary 2 = Secondary/TC 3II= Tertiary education 4 = Non-Formal education 5 = Qur’anic A.1 Background Information SCPC Cropping Zone: Interview Date: State: LGA: Community: Cluster: Name of Fabricator: Name of Group: Name of Group Leader: Phone Number of Fabricator: Name of Enumerator: Phone Number of Enumerator: GPS Coordinate:Latitude: [ ] Longitude: [ ] Questionnaire Number: [ ] 73
CHECKLISTS FOR FABRICATORS 1. Fabricated equipment extended by ATASP 1 S/N List of Technologies Participation in training (Tick) 1Source of Training How long have you been in Fabrication (Yrs) Are you in Production? (Yes = 1, No = 0) Total Number produced Total Number sold Sorghum: 1 tMechanizedhresher 2 cStoverrusher 3 cStoverhopper 4 Hammer Mill 5 Planter Rice: 7 whMechanizedandeeders 8 Hand planter 9 htpRicearboilinganks/oustingrail 10 TRicehresher 11 tSRiceteaminganks Cassava: 12 pCassavaresser 13 sCassavaifter 14 rCassavaoasting tray 15 Cassava burr mill 74
16 Cassava combine dryer 17 Cassava grater 18 Cassava peeler 19 Cassava cabinet dryer 20 Cooling bin 1Source: ATASP 1 = 1, ADP = 2, NGOs = 3, Other Processors Fabricators = 4, 5 = Others (Specify) 1. How useful are the following support received from ATASP 1? S/No Support Received Received (1= yes, 0 = No) Usefulness of Support 1 Capacity building 2 Linkage to other stakeholders 3 Market information Usefulness of Support: 3 = Very Useful; 2 = Useful; 1 = Not Useful 3. Patronage and Income from Fabrication Enterprise: i. Did you experience increase in patronage due to ATASP 1 intervention? [ ] 1 = Yes [ ] 0 = No Other Trainers: 75
ii. Number of customers before and after ATASP 1 Intervention Number of Customers (NON ADOPTERS) Number of Customers (ADOPTERS) BEFORE ATASP -1 AFTER ATASP -1 iii. Yearly income before and after ATASP 1 intervention Monthly Income (? ) (NON ADOPTERS) Monthly Income (? ) (ADOPTERS) BEFORE ATASP -1 AFTER ATASP -1 4. How has ATASP 1 training improved the quality of your fabrication operation? 1 = Excellent, 2 = Very Good, 3 = Good, 4 = Fair 5 = Poor 5. What are the constraints to the production of ATASP 1 fabricated equipment? (Please tick as applicable) 1 Lack of Capital 2 Low Patronage 3 Access to Raw Materials 4 Market Information 5 Inadequate Power Supply 6 Other (Specify) 76
6. Which of the following assets do you own? (Please tick as applicable) Before ATASP 1 After ATASP 1 I Radio ii Television iii Refrigerator iv GSM Handset v Bicycle vi Motorcycle vii Car viii House ix Storage Facility x Water Pump xi Tractor / Implements xii Farming Tools xiii Crop Processing Machine xiv Power Generator xv Spraying Equipment xvi Land Extension xvii Livestock xviiiOthers (Specify) I Radio ii Television iii Refrigerator iv GSM Handset v Bicycle vi Motorcycle vii Car viii House ix Storage Facility x Water Pump xi Tractor / Implements xii Farming Tools xiii Crop Processing Machine xiv Power Generator xv Spraying Equipment xvi Land Extension xvii Livestock xviiiOthers (Specify) 77
AGRICULTURE AND RURAL DEVELOPMENT AGRICULTURAL TRANSFORMATION AGENDA SUPPORT PROGRAM PHASE-1 (ATASP-1) Survey Questionnaire for the Income and Profitability Assessment of ATASP -1 Beneficiaries in Nigeria Processor Questionnaire: (B) DEMOGRAPHIC DATA 2.1 Gender Male Female 2.1a Needs 0 No 1 Yes 2.2 Household Size (Number) Male members = ; Female members = ;Total = 2.3 Age of Beneficiary/Farmer (Years) 1 Below 30 yrs 2 30 59 yrs 3 Above 60 yrs 2.4) Highest Education Attained: 0 = No school at all 1 = Primary 2 = Secondary/TC 3II= Tertiary education 4 = Non Formal education 5 = Quor’anic A.1 Background Information SCPC Cropping Zone: Interview Date: State: LGA: Community: Cluster: Name of Processor: Name of Group: Name of Group Leader: Phone Number of Processor: Name of Enumerator: Phone Number of Enumerator: GPS Coordinate:Latitude: [ ] Longitude: [ ] Questionnaire Number: [ ] 78
CHECKLISTS FOR PROCESSORS 1. Awareness and usage of Processing Technologies extended by ATASP -1 S/N List of Technologies Awareness of (TechnologiesYes=1,No=0) 1Sources of tawarenessofechnologies 2Extent of usage of Technologies (OthersSpecify) Sorghum 1 Seed processing, packaging and storage 2 Effective Sorghum drying techniques (i.e of Solar dryer) 3 Storage of Sorghum grains and flour for enhanced shelf life 4 Production of Pop Sorghum 5 Production of Sorghum flour using hammer mill with Cyclone 6 Production of composite flour using Soya bean flour and sorghum flour 7 Other: Specify Rice1 Seed processing package and storage 2 Improved rice processing technology 3 Production of high quality rice flour 4 Production of rice flour based products 5 Production of rice beverages 6 Production of extruded rice snacks 7 Other: Specify Cassava1Processing of Cassava into garri 2 Production of high quality cassava flour 3 Processing of Cassava and starch 79
3 Production of Cassava chin chin and doughnut 4 Production of cassava fufu 5 Processing of Cassava into chips and chunks 6 Production of Cassava/bean crisp and eggroll 7 Other: Specify 1Source: ATASP 1 =1, ADP =2, NGOs =3, Other processors =4, Others (specify) =5 2Extent of usage of Technologies: Always = 3, Sometime = 2, Never = 1 2. What support have you received from ATASP 1? S/No Support Received Received (1 = Yes. 0 = No) Usefulness of Support 1 Capacity building 2 Linkage to other stakeholders 3 Market information Usefulness of Support: 3 = Very Useful; 2 = Useful; 1 = Not Useful 3. What crops and value chain are you involved in? 4 Output from processing enterprise (Per Annum) Kg/Mt 5. What was the level of patronage before ATASP 1? ………………………. Code: Good = 3, Fair = 2, Poor = 1 6. What is the level of patronage after ATASP 1 intervention Code: Good = 3, Fair = 2, Poor = 1 80
7. Quantity of output Processed before and after ATASP 1 Intervention (NON ADOPTERS) (ADOPTERS) BEFORE ATASP 1 AFTER ATASP 1 Output (Kg Per annum) 8. Monthly income from processing before and after ATASP 1 intervention Monthly Income (? ) (NON ADOPTERS) Monthly Income (? ) (ADOPTERS) BEFORE ATASP 1 AFTER ATASP 1 9. What is your perception of the processing technologies extended by ATASP -1? S/N Processing Technologies Satisfied Fairly Satisfied Not Satisfied Sorghum 1 Seed processing, packaging and storage 2 Effective Sorghum drying techniques (i.e of Solar dryer) 3 Storage of Sorghum grains and flour for enhanced shelf life 4 Production of Pop Sorghum 5 Production of Sorghum flour using hammer mill with Cyclone 6 Production of composite flour using Soya bean flour and sorghum flour 7 Other: Specify Rice 1 Seed processing package and storage 2 Improved rice processing technology 3 Production of high quality rice flour 4 Production of rice flour based products 5 Production of rice beverages 81
6 Production of extruded rice snacks 7 Other: Specify Cassava1Processing of Cassava into garri 2 Production of high quality cassava flour 3 Processing of Cassava and starch 3 Production of Cassava chin chin and doughnut 4 Production of cassava fufu 5 Processing of Cassava into chips and chunks 6 Production of Cassava/bean crisp and eggroll 7 Others: Specify 10 Has the nutritional quality of your processed products improved under ATASP 1? Yes = 1 [ ] No = 0 [ ] Do not know 99 [ ] 11. What are the constraints to the usage of ATASP 1 Processing technologies? (Please tick as applicable) 1 Capital 2 Low Patronage 3 Access to Raw Materials 4 Market Information 5 Inadequate Power Supply 6 Water Supply 7 Other (Specify) 82
12. Which of the following assets do you own? (Please tick as applicable) Before ATASP 1 After ATASP 1 I Radio ii Television iii Refrigerator iv GSM Handset v Bicycle vi Motorcycle vii Car viii House ix Storage Facility x Water Pump xi Tractor / Implements xii Farming Tools xiii Crop Processing Machine xiv Power Generator xv Spraying Equipment xvi Land Extension xvii Livestock xviii Others (Specify) I Radio ii Television iii Refrigerator iv GSM Handset v Bicycle vi Motorcycle vii Car viii House ix Storage Facility x Water Pump xi Tractor / Implements xii Farming Tools xiii Crop Processing Machine xiv Power Generator xv Spraying Equipment xvi Land Extension xvii Livestock xviii Others (Specify) 83
NATIONAL OFFICE No. 15, Lord Luggard Street, Asokoro, Abuja FCT, Nigeria info@atasp1.gov.ng,08137208947,atasp1_hq@atasp1.gov.ng08036551491www.atasp1.gov.ngFacebook/ATASPNigeriaTwitter@ataspnigeria ZONAL OFFICES BIDA-BADEGGI SCPZ Farm Institute, Ministry of Agriculture and Rural Development, KM 12, Bida Lemu Express way, Bida, Niger State b badeggi scpz@atasp1 gov ng, ataspbidazone@yahoo com 08132756066 KANO-JIGAWA SCPZ No 9, Ahmadu Bello Way, Servicom Center, Kano, Kano State k jigawa scpz@atasp1 gov ng 08036923665, 08052683453 KEBBI-SOKOTO SCPZ KM 11, Kalgo Junction, Bernin Kebbi Jega Road, Bernin Kebbi, Kebbi State k sokoto scpz@atasp1 gov ng, kbsoatasp1@gmail com 07037777213 ADANI-OMOR SCPZ ADP Complex, KM 41, Enugu Onitsha Express way, Kwata Junction, Awka, Anambra State a omor scpz@atasp1 gov ng 07081037456 PROGRAM PARTNERS:
