AFRICAN FOOD CRISIS: THE NIGERIAN CASE STUDY

AFRINT II Micro-Level Household Report

Tunji Akande and Femi Ogundele

Nigerian Institute of Social and Economic Research (NISER)

JULY, 2009.

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TABLE OF CONTENT 1. Background Survey methodology Sampling of villages and household Survey implementation Data entry, cleaning and analysis

2. Household Demographic and Socio-Economic Characteristics Sex of household head Age of household head Ethnicity of household head Educational level of household head

3. Farm and Crop Management Type of crop grown Abandoned crops Adopted crops

4. Crop Production Technology and Farm Management Practices 4.1. Crop production conditions 4.2. Input use and production technology 4.3. Farm management practices

5. Crop Commercialization and Marketing Condition

6. Agricultural Production Technology Adoption and Diffusion

7. Households and Wealth Creation 7.1. Land resource 7.2. Labour resource 7.3. Livestock and fisheries 7.4. Consumer durable assets

8.0. State and Institutional Conditions 9.1. Extension services 9.2. Land tenure system

9. Household Income and Expenditure

10. Conclusion

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LIST OF TABLES Table1.1: Villages and Sample size in Kaduna State Table1.2. Villages and Sample size in Osun State Table 2.1: Distribution of Respondents by Socio-Economic Characteristics Table 3.1.1: Distribution of Respondents by Types of Crop Grown Last Season Table 3.1.2: Distribution of Respondents by Types of Crop Grown during Season before most Recent Table 3.1.3: Distribution of Respondents by Types of Crop Grown when Household was Formed Table 3.1.4: Distribution of Respondents by Types of Crop Grown in 2002 Table 3.2.1: Distribution of Respondents by Reasons for Abandoning Crops Grown in 2002 Table 3.2.2: Distribution of Respondents by Reasons for Adopting Crops not Grown in 2002 Table 4.1.1: Distribution of Households by Crop Production Conditions for Maize Table 4.1.2: Distribution of Households by Crop Production Conditions for Cassava Table 4.1.3: Distribution of Households by Crop Production Conditions for Sorghum Table 4.1.4: Distribution of Households by Crop Production Conditions for Rice Table 4.1.5: Distribution of Household by Types of Other food Crops and Vegetables Cultivated Table 4.1.6: Distribution of Household by Types of Non -Food Cash Crop Cultivated Table 4.2.1: Distribution of Households by Crop Production Technology for Maize Table 4.2.2: Household Distribution by Crop Production Technology for Cassava Table 4.2.3: Distribution of Households by Crop Production Technology for Sorghum Table 4.2.4: Distribution of Households by Crop Production Technology for Rice Table 4.2.5: Household Distribution by Production Technology for Other Food Crops and Vegetables Table 4.2.6: Household Distribution by Production Technology for Non-Food Cash Crop Table 4.3.1: Distribution of Households by Farm Management Practices for Maize Table 4.3.2: Distribution of Households by Farm Management Practices for Cassava Table 4.3.3: Distribution of Households by Farm Management Practices for Sorghum Table 4.3.4: Distribution of Households by Farm Management Practices for Rice Table5.1: Distribution of Households by Marketing Condition for Maize Table 5.2: Distribution of Households by Marketing Condition for Cassava Table 5.3: Distribution of Households by Marketing Condition for Sorghum Table5.4: Distribution of Households by Marketing Condition for Rice Table 5.5.1: Distribution of Households by Types of Other Food Crops and Vegetables Marketed Table 5.5.2: Distribution of Households by Marketing Condition for other Food Crops and Vegetables Table 6.1: Distribution of Households by Rural-Urban and Rural-Rural Linkages Table 7.1: Distribution of Households by Knowledge of Agricultural Techniques Table 7.2: Distribution of Households by Types of Agricultural Techniques Practice Table 7.3: Distribution of Households by Factors Limiting Technology Adoption Table 7.5: Distribution of Households by Period of Learning about Agricultural Techniques Table 7.6: Distribution of Households by Usage of other Technologies Table 8.1: Distribution of Households by Land Resource Information Table 8.2.1: Distribution of Households by Labour Resource Information Table 8.2.2: Distribution of Households by Gender Participation in Farm Activities Table 8.3: Distribution of Households by Ownership of Livestock and Fisheries Resources Table 8.4: Distribution of Households by Ownership of Consumer Durable Assets Table 9.1: Distribution of Households by the Use of Extension and Credit Facilities Table 9.2: Distribution of Households by Land Tenure System and Land Use Table 10.1.1: Distribution of Households by Sources of Income Table 10.1.2: Distribution of Households by Amount Generated from various Sources of Income Table 10.2.1: Distribution of Households by the Description of Household Expenditure Patterns Table 10.2.2: Distribution of Households by Expenditure Outlays

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LIST OF FIGURES

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CHAPTER ONE

INTRODUCTION

1.1. Background to Afrint II – African Food Crisis

Though the global food crisis may be new in some countries, it is already chronic in the African continent, where 315 million of its 900 million people live on less than $1 a day (UNDP, 2008). Within this incredibly awful picture, about 35% of the total population is malnourished due to the shortage of food. This means about 200 million people. Furthermore, the number of hunger-related deaths in the continent is about 3 million (FAO, 2008).

According to UN World Food Programme (WFP), 19 out 53 countries of Africa face serious hunger problems. Recent assessments of the performance and prospects of African economies portray a deepening crisis centred on the problem of food supplies. During the last ten years, a rapidly rising number of Africans have had an increasingly difficult time getting enough to eat. By all accounts, domestic food supplies are falling further and further behind domestic needs. Both government and consumers face serious problems in procuring the kinds and quantities of food they want at prices they can afford to pay. Chronic hunger and malnutrition are spreading, escalating quickly into famine at times of environmental and financial crisis. Covering food deficits from foreign sources has also become more difficult in the last decade. World prices of grains have risen; soaring petroleum prices before the recent decline put heavy strains on many African countries’ balances of payment and worsened their term of trade; agricultural exports have not increase sufficiently to cover rising import bills. Food aid to Africa has grown in unprecedented rates in the last decade, but it neither adequate to meet short term needs, nor is it a solution to the crisis in the long run.

Global food shortages and higher prices are more likely to cause malnutrition than outright famine, at least in the short term. It may be too early to estimate how much extra money will be needed to confront crises stemming from increasingly unaffordable food staples in poor countries. People, particularly those on the lowest incomes, will be eating less and less well. In reaction to the global food crisis, protests, strikes and riots have erupted in developing countries around the world in the wake of dramatic rises in the prices of wheat, rice, corn, oils and other essential foods that have made it difficult for poor people to make ends meet.

The food price shock now roiling world market is destabilizing governments, igniting street riots and threatening to send a new wave of hunger rippling through the world’s poorest nations. It is outpacing even the Soviet grain emergency of 1972-75, when world food prices rose 78 percent. By comparison, from the beginning of 2005 to early 2008, prices leapt 80 per cent, according to United Nation’s Food and Agriculture Organization. Much of the increase is being absorbed by middle men---- distributors, processors, even governments---- but consumers worldwide are still feeling the pinch. Africa’s enduring food crisis has been a source of serious concern to governments and non-governmental organizations at both national and international levels. The issue features constantly and prominently in international research agenda. In 2002, a Swedish team from Lund University, Sweden, drew inspiration from 5 | Page

progress being made on the Asian continent in what has been described as a state- driven, market-mediated and farmer-based process of increasing yield in food grains and staples and sought to replicate the same in Africa through capturing the dynamism in African agriculture, and illuminating questions about its driving forces, especially the role of the state and market in influencing African farmers’ production behaviour. The project that resulted in -“African food crisis-the relevance of Asian models” took place in eight African countries namely; Ethiopia, Ghana, Kenya, Malawi, Nigeria, Tanzania, Uganda and Zambia. The Nigerian study was implemented in collaboration with the International Institute of Tropical Agriculture (IITA) and Nigerian Institute of Social and Economic Research (NISER), all in Ibadan, Nigeria. As a follow up to this study, another survey was mounted in collaboration with NISER in 2007 in order to monitor progress that might have been made in Nigeria agriculture. This project is referred to as Afrint II while the 2002 study is now referred to as Afrint I. The parameters and variables defined and analysed in 2002 were also replicated in the 2007 survey in order to properly track the progress made.

Afrint II study report, therefore, comes in two volumes. The first volume is the meso- level village report while the second volume is the micro-level household report. In both volumes, analyses of agricultural intensification in Nigeria were succinctly carried out. These analyses focused on trends in the productivity of major staples (maize, cassava, sorghum and rice) in the country. In this micro-level village report, the trends in productivity were explained through yields, technological change and commercialization observed among sample farm households. Primary data collection was carried out in two states. Kaduna state in the Northern Guinea Savanna (NGS) where cereals especially maize and rice dominate other crops, and Osun state in the Humid Forest (HF) agro-ecological zone where root and tubers-mainly cassava-are more important than cereals in contributing to both household subsistence and income. The rest of this section highlights the survey methodology, sampling of villages and households, survey implementation and a brief on steps taken to ensure that the data was consistent both within sample areas and within the country.

1.2. Survey Methodology

The survey was undertaken by the Nigerian Institute of Social and Economic Research (NISER) in collaboration with the Lund University, Sweden. The two states, Kaduna in the Northern Guinea Savannah (NGS) and Osun in the Humid Forest (HF) which were covered in the 2002 survey were also considered in this current survey. These two states were purposefully selected in 2002 to meet the requirements of the overall objective of the study. Farming system in Kaduna state is cereal based with significant livestock production (particularly cattle and small ruminants), while Osun state is predominantly root crop based (mainly cassava), though maize production and rice in some parts of the state are equally important. However, livestock farming is not as important as in Kaduna state. Two sets of survey instruments were engaged in data collection system. These are a village diagnostic survey instrument and a household survey questionnaire. These instruments and the manuals were developed by the Lund team while the production and the process of administering them were coordinated by the NISER team.

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1.3. Sampling of Survey Villages and Households

The same approach followed in 2002 was adopted in this current survey for the selection of villages and households. The sampling technique employed can be described as a multistage stratified random sampling technique. The procedure comprised of the selection of Agricultural Development Project (ADP) zones after classifying them with respect to their agricultural potentials. This was done to ensure dynamism in the areas within each state. The second stage was the selection of villages while the third and final stage was the selection of households. In Nigeria, each state is divided into ADP zones for ease of extension delivery and agricultural development purposes. Thus in Kaduna state, five ADP zones were covered as compared with four zones covered in 2002. This is because a new zone has been created between 2002 and 2007 and this new zone is now refers to as the Headquarter zone. In Osun state, however, all the six ADP zones covered in 2002 were also selected in this current survey.

In terms of selection of villages, the procedure followed in selecting the villages in 2002 was also adopted though the number of villages selected in this current survey was less than that of 2002. In this survey, 14 villages were selected from Kaduna state as against 24 selected in 2002. Out of these 14 villages, five representing about 33% are new villages while the remaining nine are Afrint I villages. In Osun state on the other hand, 16 villages were selected against the 25 villages selected in 2002. Out of these 16 villages only two (about 12.5%) were new villages. The decision to retain more than 60 % of the Afrint I villages is to meet the objective of the study. It should be noted, however, that the selection of these villages as was done for Afrint I followed the identification of villages along the intensification continuum-early, transition and late and sample villages were selected along this gradient. The list of villages and the number of households selected from each village is presented in Tables 1.1 and 1.2. The Tables also contain the coordinates of all the villages selected. For the household survey, the head of the households which in most cases was also the farm manager represented the household. The selection of the households in the two states was such that more than 60% of the households was Afrint I households.

Table 1.1. Villages and Sample size in Kaduna State Zones Villages Latitude Longitude Sample size Samaru Manchock 110 05` 7 º 25 15 Jangidi Gari 110 09` 7 º 27 14 Kukum Daji 110 11` 7 º 29 14 Maigana Anchau 110 13` 7 º 45 14 Gubuchi 110 16` 8º 02 14 Kuzuntu 110 19` 8º 07 15 Birnin Gwari Dutzen Gaiya 100 45` 7 º 40 14 Kajuru 100 20` 7 º 32 15 Buruku 60 48` 7 º 14 14 Lere Kudaru 100 34` 8º 25 14 Garu 100 24` 8º 34 14 Lere 100 22` 8º 32 15 Headquarter Kujama 100 28` 7 º 38 14 Kudan 110 15` 7 º 43 14 Total 200

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Table 1.2. Villages and Sample size in Kaduna State Zones Villages Latitude Longitude Sample size Egbedore Ojo 7 º 46 4 º 22 15 Aro 7 º 46 4 º 18 15 Egbedi 7 º 44 4 º 23 15 Orolu Idiroko 7 º 58 4 º 28 13 Okiti 7 º 62 4 º 34 15 Owode Disu 7 º 60 4 º 32 17 Oriade Erin oke 7 º 43 4 º 48 12 Erimo 7 º 36 4 º 45 12

Ila Edimosi NA NA 15 Idi Ogbagbara NA NA 15 Ife North Akinlalu 7 º 30 4 º 20 15 Ashipa 7 º 31 4 º 22 15 Eleweran Kajola 7 º 18 4 º 39 15 Aiyedire Railway station 7 º 33 4 º 11 15 Osunwonyin 7 º 21 4 º 07 15 Ikoyi kuta 7 º 23 4 º 08 15 Total 234

1.4. Survey Implementation

The Nigerian Afrint II team received two sets of final instrument following some modifications. The two instruments are; the Afrint II Micro-Level Households Survey Instrument and the Afrint II Meso-Level Village Diagnostics Survey Instrument. These two instruments were processed and printed in the form that will make them comfortable to be handled by the enumerators while working on the field. Aside, preliminary consultations were made with relevant officials in the two states of KADUNA and OSUN where the survey eventually took place. Details of the initial contact and pre-survey arrangements and the actual survey including preliminary observations about the data in each state are given below.

1.4.1. Pre-Survey Arrangement and Survey Activities in Kaduna State

As part of the pre-survey arrangement in Kaduna state a member of the Nigerian Afrint II team visited the state between 6th and 8th November, 2007 to make initial contact with the officials of Kaduna State Agricultural Development Project (KADP) who assisted in the recruitment and training of enumerators. A detail discussion was held with the Director Planning, Monitoring and Evaluation of the KADP on the methodology of the survey in the state. As a result of the bulky nature of the questionnaires and for us to be able to administer the instruments in all the 14 villages that were selected across the four Agricultural Development Project Zones, 14 enumerators and four supervisors were engaged.

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Each of these enumerators was commissioned to work in a village but each of the four supervisors was required to cover 5 villages in each zone. In addition to supervising the enumerators in the villages under their control, they are expected to administer the Meso-Level Village Diagnostic Survey Instrument in each village. For effective coordination, a facilitator at the level of the KADP who assisted in monitoring the activities of the enumerators and the supervisors during the course of the survey was equally engaged. Therefore, the total number of personnel that were recruited for the exercise in the state was 19. During the course of the pre-survey visit, a tentative date of 13th – 15th November, 2007 was fixed for the training of all the officers that are going to participate in the survey. However, due to logistic problem the training could not hold as planned. Thus, the training eventually took place on 20th-23rd November, 2007. The survey kicked off in the state immediately after the training and lasted for one month. Meanwhile, in order to give room for proper coordination and good quality work, another one week was given to the Afrint II officer covering the state to go through the data collected for pre-entry data cleaning and to crosscheck with the enumerators before data entry started. In summary, a total of 200 households spread across the 14 villages were covered in Kaduna state with an average of 15 households per village.

1.4.2. Pre-Survey Arrangement and Survey Activities in Osun State

The pre survey and survey activities in Osun state were a little different from that of Kaduna state. The initial contact with the officials of Egbedore LGA was made between 6th and 9th November, 2007 during which 3 enumerators and 3 supervisors that covered the 3 selected villages in the LGA were trained to serve as test-run in the state. Aside, Nigerian Afrint II team led by one member of the NISER team visited the three selected villages in this LGA to make preliminary arrangement for the conduct of the Meso-Level Village Diagnostics Survey whenever the representative of the Afrint II visited the country. The three villages selected are Ojo, Aro and Egbedi. These three Meso-Level Village Diagnostics survey took place in the presence of the representative of the Lund team (Associate Prof. Hans) who visited the country between 13th and 18th November, 2007. Subsequently, efforts were made to establish the survey in the remaining 5 LGAs that have been selected in the state. In this regards, 13 additional villages were selected across the remaining five LGAs. An enumerator was also selected for each village while three additional supervisors were also appointed to oversee the collection of data in the five LGAs and also to administer the village diagnostic instruments. Thus, in terms of personnel requirement in the state, a total of 21 officials comprising of 16 enumerators, 4 supervisors and one facilitator participated in the survey. The survey also lasted for one month in the state with an extra one week for crosschecking of data for pre-entry data cleaning. In Osun state, a total of 234 households spread across the 16 selected villages were covered during the course of the survey.

1.5. Data Entry, Cleaning and Analysis

The template and programme for data entry was developed by the Lund team but the data entry was carried out in NISER by the data clerks. Data entry of this nature is usually considered as part of capacity building exercise for NISER staff. The Meso- Level Village Diagnostics Survey Instrument contained 550 variables as against 105

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variables in the 2002 version. Also, the Micro-Level Households Survey Instrument contained 742 variables as compared with 437 variables in the Afrint I version. A total of 434 households were selected in this survey as compared with 495 selected for the Afrint I survey. Data from these surveys were entered in SPSS. Copy of the final data set is available at the Lund University as well as NISER, Ibadan, Nigeria.

Data quality checks were done in collaboration with the Lund team and these involved the followings:

 studying the questionnaires for coverage of research questions;  obtaining a sample of completed questionnaires and cross-checking values in them against those in the data set for accuracy of data entry and the handling of zeros and missing values;  using frequencies, means, maximum and minimum values of the variables to check for outliers;  cross-checking outlier values against values in questionnaire to correct inaccurate data entry or otherwise consider variable as missing value.

The overall impression is that a lot of effort went into ensuring that the survey instruments are well designed to capture as many of the relevant explanatory variables as possible. Similarly, the high degree of accuracy of data in the completed questionnaires compared to their corresponding values in the data set point to the fact that qualified and well trained personnel were used for data collection and entry. The above strongly suggest that the data set is of reliable quality and actually reflect the production trends in Kaduna and Osun states, Nigeria.

1.6 Plan of the Report

This report has been arranged into ten sections with each section dealing with distinct issue in the agricultural production process in the country during the year of the survey in comparison with the situation in 2002. Thus, section one presented the background information for the study and highlighted information such as the survey methodology, sampling techniques, survey implementation, data entry, cleaning and analysis. Section two highlighted households’ demographic and socio-economic characteristics while section three dealt with farm and crop management in relation to types of crop grown by households. Section four took a critical look at crop production technologies and farm management practices while section five articulated the crop commercialization and marketing conditions in the country during the survey year. Section six discussed agricultural technology adoption and diffusion while section seven summarized household’s wealth creation resources. The role of state and other institutions is discussed in section eight while household income and expenditure pattern is taken care of in section nine. Section ten concluded the report.

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CHAPTER TWO

SOCIO-ECONOMIC CHARACTERISTICS AND CROP MANAGEMENT PRACTICES AMONG FARM HOUSEHOLDS

2.1 Socio-economic characteristics of farm households

In this chapter, a detail analysis of the demographic and socio-economic characteristics of the respondents (heads of households) was carried out. These characteristics include sex, age, and educational level. Though these socio-economic characteristics were not expected to deviate much from the 2002 situation (except for age) particularly among the Afrint I households, the analysis is necessary in order to provide some socio-cultural background information that may influence farm household behaviour. The result of the analysis is presented in Table 2.1. Nigerian farming households is dominated by male-headed households and age distribution of the household heads showed that majority of them fell within actively working age group of 30 to 60 years with an average age of 52 years. Being farming households, majority of the household heads only had primary education.

Table 2.1: Distribution of Respondents by Socio-Economic Characteristics (%) Socio-economic variables Kaduna state Osun state National Sex of household head male 96.0 85.3 90.7 female 4.0 14.7 9.3 Age of household head <30 1.5 0.0 0.8 30<60 72.5 70.7 71.6 60> 26.0 29.3 27.7 mean (years) 51.0 54.0 52.5 Educational level of household head 1-6 59.7 62.9 60.3 7-11 19.0 20.2 19.6 > 11 21.3 16.9 19.1 Source: Afrint II field Survey, 2007

2.2 Types of Crop Grown

This section only describes the change in farm and crop management in relation to what has changed in terms of crops grown between 2002 when Afrint I study was conducted and 2007. Generally the proportion of farmers who grew maize in the last season was the highest when compared with other crops as shown in Table 2.2. A significant proportion of the households planted cassava and other food crops and vegetables in the last season but the proportions of households that planted sorghum and rice were in each case less than 40 per cent. The only variation observed between the two states was for cassava and non-food cash crops in Osun state and other cereals (sorghum and rice) in Kaduna state. Similar situation was observed for season before the most recent season and among newly sampled households (Table 2.3 and 2.4) Comparison with 2002, however, showed that proportion of households growing various crops increased significantly (Table 2.5).

Table 2.2: Distribution of Respondents by Types of Crop Grown Last Season (%) Crops Kaduna state Osun state National Maize 92.0 98.3 95.2

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Cassava 16.0 96.2 56.1 Sorghum 66.0 5.6 35.8 Rice 52.5 14.5 33.5 Other food crops and vegetables 56.8 79.1 67.9 Non-food cash crops 21.3 72.5 46.9 Source: Afrint II field Survey, 2007 Note: Multiple responses, percentage may not add up to 100.

Table 2.3: Distribution of Respondents by Types of Crop Grown during Season before Most Recent Crops Kaduna state Osun state National Maize 92.0 97.4 94.7 Cassava 17.5 95.3 56.4 Sorghum 66.7 4.3 35.5 Rice 52.5 13.4 32.9 Other food crops and vegetables 52.5 79.1 65.8 Non-food cash crops 21.5 72.5 47.0 Source: Afrint II field Survey, 2007 Note: Multiple responses, percentage may not add up to 100.

Table 2.4: Distribution of Respondents by Types of Crop Grown When Household was formed Crops Kaduna state Osun state National Maize 87.5 96.1 91.8 Cassava 9.1 92.2 50.7 Sorghum 56.8 6.8 31.8 Rice 36.9 26.2 31.6 Other food crops and vegetables 37.8 76.7 57.3 Non-food cash crops 15.3 69.6 42.5 Source: Afrint II field Survey, 2007

Table 2.5: Distribution of Respondents by Types of Crop Grown in 2002 Crops Kaduna state Osun state National Maize 84.5 84.2 84.3 Cassava 15.5 81.6 48.5 Sorghum 64.0 4.3 34.2 Rice 48.5 5.1 26.8 Other food crops and vegetables 46.5 72.2 59.4 Non-food cash crops 15.7 65.7 40.7 Source: Afrint II field Survey, 2007

2.3 Adopted and Abandoned Crops

The fact that there have been significant changes in the proportion of households growing different crops between 2002 and now is an indication that some households must have adopted some crops while others might have also abandoned some. The decision to adopt or abandon a particular crop by households may be due to any of the economic reasons (marketing problems or profitability), agronomic reasons (management problems) and labour problems.

2.3.1 Abandoned Crops

For all the crops, economic reason was rated highest for all the households who have had any reasons to abandon any of the crops grown in 2002 except for rice as seen in Table 2.6. The main economic factor is non-profitability of these crops. For households who have abandoned rice, they have done so mainly for agronomic reasons. Probably, the crop did not grow well and the yield is low compared to other staples. Also, households that abandoned non-food cash crops have done so mainly

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for labour reason as their cultivation is always labour intensive. The only variation was observed for maize and rice for Kaduna and Osun respectively. While all the households that abandoned maize in Kaduna state have done so for economic reason, all the households that abandoned rice in Osun state have done so for agronomic reason.

2.3.2 Adopted Crops

Economic reason has being the main factor underlying the adoption of crops not grown by households in 2002 as presented in Table 2.7. These households now found these crops more profitable and thus, enhanced their income. However, a significant proportion of these households have adopted some crops such as maize, sorghum and rice for agronomic reasons that they now grow well and with higher yield compared with the situation in 2002.

Table 2.6: Distribution of Respondents by Reasons for Abandoning Crops grown in 2002 Crops Kaduna state Osun state National Econ. Agron. Lab. Econ. Agron. Lab. Econ. Agron. Lab. Maize 100.0 0.0 0.0 95.8 4.2 0.0 97.9 2.2 0.0 Cassava 44.4 11.1 44.4 96.3 3.7 0.0 70.4 7.4 22.2 Sorghum 68.4 15.8 15.8 66.7 33.3 0.0 67.6 24.5 7.9 Rice 44.4 11.1 44.4 0.0 100.0 0.0 22.2 55.5 22.2 Other food & 52.6 42.1 5.3 94.1 5.9 0.0 73.4 24.0 2.7 vegetables Non-food cash 9.7 0.0 90.9 87.5 12.5 0.0 48.6 6.2 45.5 crops Source: Afrint II field Survey, 2007

Table 2.7: Distribution of Respondents by Reasons for Adopting Crops not Grown in 2002 Crops Kaduna state Osun state National Econ. Agron. Lab. Econ. Agron. Lab. Econ. Agron. Lab. Maize 45.7 52.2 2.2 71.4 28.6 0.0 58.5 40.4 1.1 Cassava 62.5 25.0 12.5 76.5 24.5 0.0 69.5 24.3 6.2 Sorghum 46.4 39.3 14.3 50.0 50.0 0.0 48.2 44.7 7.1 Rice 46.2 42.3 11.5 50.0 50.0 0.0 48.1 46.2 5.8 Other food & 73.3 23.3 3.3 93.8 6.2 0.0 83.6 14.7 1.2 vegetables Non-food cash 53.3 20.0 26.7 70.6 29.4 0.0 61.9 24.7 13.3 crops Source: Afrint II field Survey, 2007 Note: Multiple responses, percentage may not add up to 100.

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CHAPTER THREE

CROP PRODUCTION TECHNOLOGY AND FARM MANAGEMENT PRACTICES

Adequate utilization of inputs and improved farm management practices is required for increased productivity and improved performance in the agricultural sector. Thus, as part of the food security programme and agricultural sector reform in the country since 2002, a number of policies and initiatives have been implemented. These policies and initiatives were directed at improving input use and farm management practices for the purpose of increasing the performance of the sector. This section, therefore, examine households crop production conditions, input use, and management practices by farming households in comparison with the situation in 2002.

3.1 Crop Production Conditions

The crop production conditions for maize, cassava, sorghum and rice were as presented in Tables 3.1, 3.2, 3.4 and 3.5 respectively. It is obvious from these tables that planting of food crops in pure stand is mainly practised in the north (Kaduna) while intercropped system is the common practice in the south (Osun). Contrary to expectation, however, irrigation was not a common practice among cereal (maize, sorghum and rice) growing households in Nigeria and as a result they normally did not have more than one crop in the year. In other words, cereal cultivation in the country has been mainly rainfed. This situation was observed for both states. Thus, except in planting their land to other crops most of the cereal growing households did not put their land for any other specific use in addition to cereal cultivation. For those who utilized their land for other crops in addition to cereal cultivation, planting of other food crops has always been the usual practice.

In terms of average area cultivated by households to different staple food crops in the most recent season, maize recorded 2.5ha, cassava 1.7ha, sorghum 1.5ha and rice 2.1ha. The average cultivated areas for and sorghum were fairly higher in Kaduna than in Osun. However, the area under rice in each household was the same in both states. For cassava, the average area cultivated in recent season was higher in Osun. The area cultivated to maize by households in the most recent season decreased significantly when compared to the season before the recent season but increased for cassava, sorghum and maize. When compared with two seasons before the recent season, average area decreased for maize and cassava but stagnated for sorghum and rice. For the newly sampled households, the comparison of the area cultivated to maize with the time household was formed showed that area cultivated increased as indicated by about 50 per cent of the households but the proportion of households who claimed that area cultivated in recent season increased when compared with 2002 was less than 50 per cent. For cassava, sorghum and rice, proportion of newly sampled households that indicated increased area cultivation was less than 50 per cent in each case and when compared with 2002, similar results were equally obtained.

Even though the average total output obtained in the most recent season for maize and sorghum were higher than what was obtained during the season before the most recent season, it was lower when compared with what was obtained by households

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two seasons before the recent season. In the case of rice, the average output obtained in the recent season was lower than what the households obtained during the season before the most recent one and two seasons before the recent season.

Comparison of yield levels in recent season with the time household was formed for newly sampled households showed that yield levels for maize and rice have increased as indicated by about 58 per cent in each case when compared with when household was formed. The proportions of households which indicated increased yield in recent season for cassava and sorghum compared to when household was formed were less than 40 per cent. Except for maize where about 60 per cent of the households indicated increased yield in recent season compared to 2002, the proportion of households indicating increased yield for other staple food crops was less than 50 per cent each case

Utilization of the output realised by households in the recent season pointed to increased commercialization of most of these crops. The proportion of output sold ranged from 43 per for maize, 49 per cent for cassava to a high of 65 per cent for rice. Only sorghum appeared to be produced mainly for home consumption as the proportion sold in the recent season was less than 30 per cent. The proportion of work done by the farm managers who in most cases are also the household heads varied accordingly with respect to the crop in question. For maize and sorghum, about 60 to 65 per cent of the farm work was done by the farm managers whereas, for rice, the proportion was less than 50 per cent. In the case of cassava, the proportion of work done by the farm manager was about 55 per cent. In most cases, the male members of the households and the spouses of the household heads also assisted in farm work.

The production conditions for other food crops and vegetables and non-food cash crops in the recent season were different from that of the major staples earlier discussed. For other food crops and vegetables, yam, cocoyam and vegetables for local markets which are mostly cultivated in the south (Osun), the proportions of households which cultivated them in recent season were significantly high and more than 60 per cent for each crop. Millet which is only cultivated in the north (Kaduna) also witnessed wide cultivation as indicated by 55 per cent of the respondents. Banana and fruits for local market also witnessed wide cultivation across the country as shown in Table 3.6.

Many of the non-food cash crops listed in Table 3.6 are not cultivated in the north except for cotton and sugar cane but a significant number of them were cultivated in the south in the recent season. For cotton and sugar cane, the proportion of households in the north that cultivated the crops in recent season was less than half. For crops cultivated mainly in the south, only cocoa recorded a wide cultivation as indicated by 76 per cent of the respondents. The proportion of households from the south that cultivated cashew nuts and fruits and vegetables for export market, was less than 50 per cent. Other non-food cash crops cultivated but not in significant proportions include tobacco, coffee, flowers and spices such as ginger and vanilla.

The proportion of work done by the farm manager averaged 60 per cent for other food crops and vegetables and non-food cash crops respectively. Cultivation of these crops on pre-arranged contract with private traders is not a common practice. While other

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male and female members of the households were involved in the cultivation of other food crops and vegetables, only the spouse of the manager and other male members of the household were mainly involved in the cultivation of non-food cash crops.

Table 3.1: Distribution of Households by Crop Production Conditions for Maize Production conditions Kaduna Osun National Cropping system in most recent season Pure stand 70.9 17.7 45.4 Intercropped 28.6 82.3 55.4 proportion of land irrigated yes 28.0 1.3 14.7

Whether take more than one maize crop year 0.7 yes 0.0 1.3

Uses of land in addition to maize no specific use 71.0 19.7 45.3 for other crops 17.5 76.0 46.7 for grazing 9.0 3.0 6.0 other uses 2.5 1.3 1.9 Other crops for which land is used after harvest other food crops 84.5 75.2 79.9 vegetables 9.5 20.4 14.9 others 6.0 4.3 5.2 Average area under maize leading to the most recent harvest 3.1 1.9 2.5 Average area under maize during season before most recent season 4.1 2.3 3.2 Average area under maize two season before most recent season 3.5 2.5 3.0 Change in area cultivated compared to when household was formed Did not grow maize at that time 19.8 1.0 10.4 Area decreased since then 10.8 15.5 13.6 Area unchanged 21.6 29.1 25.3 Area increased since then 47.7 54.4 51.1 Change in area cultivated in the most recent season compared to 2002 Did not grow maize in 2002 17.5 1.7 9.6 Area decreased since then 8.5 12.4 10.5 Area unchanged 30.0 31.8 30.9 Area increased since then 44.0 54.0 49.0 Average total production of maize after the most recent harvest 3643.0 1532.5 2587.8 Average total production of maize during the harvest before most recent 1641.6 2448.3 3255.0 season Average total maize production two season ago 3749.6 1788.4 2769 Change in maize yield today compared to when household was formed Did not grow maize at that time 21.6 1.0 11.3 Yield have decreased 9.0 37.0 23.0 Yield unchanged 8.1 9.0 8.5 Yield have increased 61.3 53.0 57.3 Change in yield today compared to 2002 Did not grow maize at that time 13.5 8.5 11.0 Yield have decreased 16.5 27.2 21.9 Yield unchanged 8.5 8.0 8.2 Yield has increased 61.5 56.3 58.9 Average quantity of maize by usage in most recent season Home consumption 1216.5 419.2 817.8 Payment for hired labour 491.5 461.2 476.4 Sale 1552.1 804.6 1178.4 Other uses (seed, animal feed, brewing, gifts etc) 350.8 197.8 274.3 Average proportion of maize production work done by the manager 67.8 50.4 59.1 Persons involved in maize production Nobody else 1.5 9.2 5.3

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Spouse of farm manager 37.5 46.8 42.1 Other male members of the household 60.5 42.2 51.4 Other female members 0.5 1.9 1.2 Source: Afrint II field Survey, 2007

Table 3.2: Distribution of Households by Crop Production Conditions for Cassava Production conditions Kaduna Osun National Cropping system Pure stand 69.4 19.1 44.2 Intercropped 30.6 80.9 55.8 Average area under pure stand during the past year 1.2 2.1 1.7 Average area under pure stand the year before last 1.2 2.7 1.4 Average area under pure stand two years ago 1.0 2.7 1.9 Area of cassava cultivated today compared to when household was formed Did not grow cassava at that time 46.2 0.0 23.1 Area decreased since then 0.0 12.8 6.4 Area unchanged 30.8 22.3 26.5 Area increased since then 23.1 64.9 44.0 Area cultivated in the most recent season compared to 2002 Did not grow cassava in 2002 24.3 2.6 13.5 Area decreased since then 13.5 17.7 15.6 Area unchanged 43.2 20.3 31.8 Area increased since then 18.9 59.4 39.2 Change in cassava yield today compared to when household was formed Did not grow cassava at that time 91.9 7.8 49.9 Yield have decreased 0.9 29.4 15.1 Yield unchanged 2.7 10.8 6.7 Yield have increased 4.5 52.0 28.2

Change in yield today compared to 2002 Did not grow cassava at that time 85.5 1.0 43.2 Yield have decreased 2.0 33.5 17.6 Yield unchanged 3.0 9.3 6.1 Yield has increased 9.5 56.2 32.9 Ranking of cassava by most important usage Home consumption 25.0 46.8 35.9 Payment for hired labour 14.7 16.2 15.5 Sale 63.3 34.8 49.1 Other uses (seed, animal feed, brewing, gifts etc) 0.5 2.0 1.7 Average proportion of cassava production work done by the manager 57.8 49.9 53.9 Persons involved in cassava production Nobody else 19.4 12.9 16.1 Spouse of farm manager 29.0 44.6 36.8 Other male members of the household 51.6 42.1 46.8 Other female member of the household 0.0 0.5 0.2 Source: Afrint II field Survey, 2007 ** raking has multiple responses

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Table 3.3: Distribution of Households by Crop Production Conditions for Sorghum Production conditions Kaduna Osun National Cropping system in most recent season Pure stand 60.9 71.4 66.1 Intercropped 38.3 28.6 33.5 proportion of land irrigated yes 1.8 0.0 9.0 no 98.2 100.0 99.6 Whether take more than one sorghum crop year –yes 0.0 0.0 0.0

Uses of land in addition to sorghum no specific use 75.0 23.1 49.1 for other crops 2.5 61.5 31.7 for grazing 21.7 0.0 10.9 other uses 0.8 15.4 8.1 Other crops for which land is used after harvest other food crops 78.6 66.7 72.65 vegetables 7.1 26.7 16.9 others 14.3 6.7 10.5 Average area under sorghum leading to the most recent harvest 2.3 0.7 1.5 Average area under sorghum during season before most recent season 2.3 0.6 1.4 Average area under sorghum two season before most recent season 2.3 0.7 1.5 Change in area most recent season cultivated compared to when household was formed Did not grow sorghum at that time 1.8 90.7 46.2 Area decreased since then 8.8 1.9 5.3 Area unchanged 29.8 2.8 16.3 Area increased since then 59.6 4.7 32.2 Average total production of sorghum after the most recent harvest 1372.7 474.7 923.7 Change in area cultivated in the most recent season compared to 2002 Did not grow sorghum in 2002 5.6 16.7 5.9 Area decreased since then 11.3 8.3 9.8 Area unchanged 44.4 50.0 47.2 Area increased since then 38.7 25.0 31.9 Average total production of sorghum during the harvest before most recent season 1412.7 337.3 875.0 Average total sorghum production two season ago 1458.8 440.8 949.8 Change in sorghum yield today compared to when household was formed Did not grow sorghum at that time 3.3 75.0 39.1 Yield have decreased 13.1 15.9 14.5 Yield unchanged 13.1 4.5 8.8 Yield have increased 70.5 4.5 37.5 Change in yield today compared to 2002 Did not grow sorghum at that time 4.7 73.7 39.2 Yield have decreased 22.8 15.8 19.8 Yield unchanged 12.6 5.3 8.9 Yield has increased 59.8 5.3 32.5 Average quantity of sorghum by usage in most recent season Home consumption 611.8 237.2 424.5 Payment for hired labour 181.8 157.7 169.8 Sale 381.2 52.8 217.0 Other uses (seed, animal feed, brewing, gifts etc) 205.0 75.0 140.0 Average proportion of sorghum production work done by the manager 69.9 61.9 65.9

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Persons involved in sorghum production Nobody else 2.0 0.0 1.0 Spouse of farm manager 37.0 90.9 63.9 Other male members of the household 61.0 9.1 35.0 Source: Afrint II field Survey, 2007

Table 3.4: Distribution of Households by Crop Production Conditions for Rice Production conditions Kaduna Osun National proportion of land irrigated yes 14.6 0.0 7.3 no 85.4 100.0 92.7 Whether take more than one rice crop year yes 1.8 13.3 7.5 no 98.2 86.7 92.5 Uses of land in addition to rice no specific use 75.5 36.4 55.9 for other crops 14.3 52.3 33.3 for grazing 9.2 2.3 5.7 other uses 1.0 9.1 5.0 Other crops for which land is used after harvest other food crops 71.4 33.3 52.4 vegetables 14.3 50.0 32.1 others 14.3 16.7 15.5 Average area under rice leading to the most recent harvest 2.2 2.1 2.1 Average area under rice during season before most recent season 1.7 2.1 1.9 Average area under rice two season before most recent season 1.9 2.3 2.0 Change in area cultivated compared to when household was formed Did not grow rice at that time 23.4 22.5 22.9 Area decreased since then 6.4 12.5 9.4 Area unchanged 27.7 22.5 25.1 Area increased since then 42.6 42.5 42.5 Change in area cultivated in the most recent season compared to 2002 Did not grow rice in 2002 14.7 0.0 7.3 Area decreased since then 3.2 0.0 1.6 Area unchanged 44.2 64.5 54.3 Area increased since then 37.9 35.5 36.7 Average total production of rice after the most recent harvest 2289.1 4307.3 3298.2 Average total production of rice during the harvest before most recent season 2235.5 7302.9 4769.2 Average total rice production two season ago 2272.7 4598.4 3435.6 Change in rice yield today compared to when household was formed Did not grow rice at that time 21.3 2.9 12.1 Yield have decreased 10.6 26.5 19.1 Yield unchanged 14.9 8.8 11.9 Yield have increased 53.2 61.8 57.5 Change in yield today compared to 2002 Did not grow rice at that time 14.7 8.8 11.9 Yield have decreased 18.9 0.0 9.4 Yield unchanged 14.7 44.1 29.4 Yield has increased 51.6 47.1 43.3 Average quantity of rice by usage in most recent season Home consumption 596.1 448.4 522.2 Payment for hired labour 182.0 1405.7 793.8 Sale 1220.3 2811.2 2015.8 Other uses (seed, animal feed, brewing, gifts etc) 292.5 318.0 305.3 Average proportion of rice production work done by the manager 64.3 25.8 45.1 Persons involved in rice production Nobody else 6.3 9.1 7.7 Spouse of farm manager 27.8 51.5 39.6

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Other male members of the household 62.0 39.4 50.7 Other female member of the household 3.8 0.0 1.9 Source: Afrint II field Survey, 2007

Table 3.5: Distribution of Household by Types of Other food Crops and Vegetables Cultivated Other Food Crops and Vegetables Kaduna Osun National Banana 27.3 82.3 54.8 Beans 34.5 35.7 33.6 Peas 18.2 5.5 11.5 Irish potatoes 27.3 3.1 15.2 Sweet potatoes 47.3 32.9 40.1 Millet 55.5 - 55.5* Groundnut 43.6 19.0 31.3 Yam 55.0 89.4 72.5 Cocoyam 56.5 71.4 63.9 Vegetables for local markets 48.6 92.8 70.7 Fruits for local markets 19.6 77.0 48.3 Others 16.8 26.8 21.8 Proportion of work done by the farm manager 67.9 55.1 61.5 Grow crop on pre-arranged contract with 1.7 2.1 1.9 private trader persons involved in production nobody else 3.2 19.4 11.3 spouse of farm manager 27.4 48.5 37.9 other male member of the household 69.5 31.1 50.3 other female member of the household 0.0 1.0 0.5 Source: Afrint II field Survey, 2007 * only produced in the north

Table 3.6: Distribution of Household by Types of Non -Food Cash Crop Cultivated Non-Food Cash Crop Kaduna Osun National Cotton 48.9 1.5 25.2 Sugar cane 48.9 8.5 28.7 Cashew nut - 47.7 47.7* Cocoa - 76.0 76.0* Tobacco - 6.9 6.9* Coffee - 1.0 1.0 Tea - - - Sisal - - - Pyrethrum - - - Fruits and Vegetables for export market 44.4 16.7 30.6 Flowers - 1.0 1.0 Others 13.3 15.0 14.1 Spices, like ginger and vanilla 17.8 1.0 9.4 Proportion of work done by the farm manager 77.0 48.7 62.9 Grow crop on pre-arranged contract with 1.8 6.0 3.9 private trader persons involved in production nobody else 17.4 2.6 10.0 spouse of farm manager 34.8 60.9 47.9 other male member of the household 45.7 33.9 39.8 other female member of the household 2.2 2.6 2.4 Source: Afrint II field Survey, 2007 * only cultivated in the south

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3.2 Input Use and Production Technology

The use of improved seeds and application of adequate quantity of fertilizer coupled with application of other production technologies such as irrigation and use of tractor or animal traction is a necessary condition for increased yield and high factor productivity. The utilization of farm inputs and application of technologies for the cultivation of various crops under investigation by households was examined for the current season. These were also compared with the situation when household was formed for newly sampled households and with 2002 for all the households. The results of the analysis for the various crops are presented on Tables 3.7, 3.8, 3.9 and 3.10 for maize, cassava, sorghum and rice respectively.

For the newly sampled households, 87 per cent grew maize, 69 per cent grew cassava, 49 per cent grew sorghum and 73 per cent grew rice when the household was formed. Since irrigation was not a usual practice among the respondents, over 95 per cent of the households did not apply irrigation when the household was formed. The only exception was for the cultivation of lowland irrigated rice as reported by 40 per cent of respondents in Osun state where this technology was applied. As regards the use of improved varieties when the household was formed, the planting of traditional variety was very predominant particularly among households that grew maize, sorghum and rice. Application of pesticides when the household was formed was practised by less than 20 per cent of the households for all the four crops except for rice where about 32 per cent of the household claimed they applied pesticides when household was formed. The main method of land preparation when the household was formed was hoe as indicated by an average of 80 per cent of the respondents for each of the crop.

The used of improved inputs and modern technologies by newly sampled households in most recent season did not show a significant improvement compared to when household was formed. About 43 per cent of the households were still using traditional maize variety, 47 per cent still planting old cassava varieties, and 87 per cent still using traditional sorghum variety, while about 60 per cent are still planting traditional rice varieties. In spite of the presidential initiative on rice designed to push the adoption of NERICA in Nigeria, less than 30 per cent of the households planted NERICA or its descendants in the most recent season. The low use of improved seed varieties cannot be completely divulged from the channel through which households acquired their seed. The main source of seed planted in the most recent season was own stock as indicated by 35 per cent for maize, 58 per cent for sorghum and 37 per cent for rice growing households. A significant proportion of the maize and sorghum growing households also acquired their seed from the market while another significant proportion of rice growing households acquired their seed from the government extension agents and non-governmental organizations (NGOs). The use of artificial fertilizer in most recent season compared to when household was formed has not recorded much significant improvement. Except for the rice and maize growing households where 50 and 41 per cent claimed increased use of fertilizer in recent season compared to when household was formed, fertilizer use has either stagnated or declined among the sorghum and cassava growing households. The situation of fertilizer use in recent season in Nigeria appeared worse when compared

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with 2002 as only 25 per cent of the rice and 44 per cent of maize growing households indicated increased use.

This puts into question the rationale for the huge amount of money being spent on fertilizer subsidy in the country. Similarly, the method of land preparation in 2007 had not shown any significant improvement compared to 2002 as farmers still relied on hoe cultivation with very little use of oxen ploughing and tractor. Application of pesticides in recent season, however, showed significant improvement compared to 2002 for sorghum and rice cultivation as indicated by an average of 50 per cent of the households. Little progress was made by maize growing households while cassava growing households could not make any significant progress.

In terms of input use and technology for the production of other food crops and vegetables and non-food cash crops the result was mixed (see Tables 3.11 and 3.12). Area devoted for these two categories of crops averaged 2ha in recent season. For non-food cash crops, 47 per cent of the respondents indicated that there has been substantial increase in area devoted to cultivation of these crops in recent season compared to when household was formed while about 45 per cent of the respondents also claimed that the overall land devoted to cultivation of these crops has increased compared to 2002. The use of fertilizer was not impressive as less than 50 per of the household growing other food crops and vegetables and less than 40 per cent of non- food cash crops growing households applied fertilizer in the most recent season. One- third of the respondents in either case, however, used animal manure as substitute for artificial fertilizer in the most recent season. The practice of the use of green manure is still very low among the respective households but application of pesticides was higher among non-food cash crops growing households. There was no gender specialization in the production of these crops as both men and women are equally involved in the production.

Table 3.7: Distribution of Households by Crop Production Technology for Maize Description of technology when household was formed Kaduna Osun National Grew maize when household was formed Yes 76.6 97.3 86.9 Proportion of maize land irrigated when H/h was formed None 92.7 93.0 92.9 ¼ 3.6 1.8 2.7 ½ 2.7 1.8 2.7 3/4 0.9 2.6 1.7 All or nearly all 0.0 0.9 0.4 Variety of maize planted when household was formed Traditional 60.4 56.8 58.6 Improved (OPV, composite) 28.8 38.7 33.7 Hybrid 10.8 4.5 7.6 Application of pesticides when household was formed Yes 18.0 14.6 16.3 Method of land preparation when household was formed Hoe cultivation 90.1 89.1 89.6 Oxen ploughing 8.1 7.3 7.7 Tractor ploughing 1.8 3.6 5.7 Description of technology in most recent season Proportion of maize land irrigated in most recent season None 94.8 96.4 95.6 ¼ 3.6 0.9 2.3 ½ 0.5 1.4 0.9

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3/4 1.0 0.5 0.7 All or nearly all 0.0 0.9 0.4 Variety of maize planted in most recent season Traditional 48.7 36.4 42.5 Improved (OPV, composite) 22.1 56.1 29.2 Hybrid 29.2 7.5 18.3 Acquiring of seed used in most recent season Own stock 47.1 23.6 35.3 Other farmers or neighhours 9.8 2.6 6.2 Purchased in the market 20.2 47.6 33.9 From extension agents, Ngo or other formal organizations 22.8 26.2 24.5 Comparing fertilizer use in recent season with when Household was formed 18.0 43.9 30.9 No fertilizer applied at that time 27.0 16.8 21.9 Amount decreased since then 8.1 3.7 7.7 Amount unchanged since then 46.8 35.5 41.1 Amount increased since then Average amount spent on artificial fertilizer in most recent season 225.21 56.9 141.06 Fertilizer use in most recent season compared to 2002 No fertilizer applied in 2002 13.6 45.6 29.6 Amount decreased since then 20.6 9.3 14.9 Amount unchanged 8.0 14.7 11.3 Amount increased since then 57.8 30.4 44.1 Method of land preparation in most recent season Hoe cultivation 64.8 58.8 61.8 Oxen ploughing 23.1 40.4 31.9 Tractor ploughing 12.1 0.9 6.5 Use of Pesticides in most recent season 45.0 20.1 32.5 Source: Afrint II field Survey, 2007

Table 3.8: Household Distribution by Crop Production Technology for Cassava Crop production technology Kaduna Osun National Used of new varieties today compared to when household was formed 23.7 83.7 53.7 Used of new varieties today compared to what parent was using 25.0 85.9 55.5 Purchase or received stem cuttings from formal agency or NGO 15.6 33.5 24.6 Average amount spent on fertilizer in the most recent season US$ 56.5 52.1 54.3 Change in fertilizer used in most recent season compared to 2002 No fertilizer applied at that time 66.7 86.6 76.6 Amount decreased since then 11.1 7.0 9.0 Amount unchanged since then 13.9 3.2 8.5 Amount increased since then 8.3 3.2 5.6 Use of pesticides on cassava during the most recent season 12.1 19.5 15.8 Main method of land preparation during the most recent season Hoe cultivation 97.3 57.3 77.3 Oxen ploughing 2.7 41.3 22.0 Others 0.0 1.4 0.7 Grow cassava when household was formed 46.7 90.8 68.7 Change in fertilizer use today compared to when household was formed No fertilizer applied at that time 90.0 77.4 83.7 Amount decreased since then 0.0 7.1 3.5 Amount unchanged since then 0.0 4.8 2.4 Amount increased since then 10.0 10.7 10.3 Used pesticides when household was formed 22.2 9.3 15.7 Method of land preparation when household was formed Hoe cultivation 100.0 88.2 94.1 Oxen ploughing 0.0 0.0 0.0 Tractor ploughing 0.0 7.5 3.7 Others 0.0 4.3 2.1

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Source: Afrint II field Survey, 2007

Table 3.9: Distribution of Households by Crop Production Technology for Sorghum Description of technology when household was formed Kaduna Osun National Grew maize when household was formed 87.9 9.1 48.5

Proportion of Sorghum land irrigated when H/h was formed None 98.2 100.0 99.1 ¼ 0.0 0.0 0.0 ½ 0.0 0.0 0.0 All or nearly all 1.8 0.0 0.9 Variety of sorghum planted when household was formed Traditional 98.3 100.0 99.2 Improved 0.0 0.0 0.0 Hybrid 1.7 0.0 0.8 Application of pesticides when household was formed 17.0 0.0 8.9 Method of land preparation when household was formed Hoe cultivation 98.3 100.0 99.1 Oxen ploughing 1.7 0.0 0.9 Tractor ploughing 0.0 0.0 0.0 Description of technology in most recent season Proportion of sorghum land irrigated in most recent season None 100.0 100.0 100.0 ¼ 0.0 0.0 0.0 ½ 0.0 0.0 0.0 All or nearly all 0.0 0.0 0.0 Variety of sorghum planted in most recent season Traditional 89.6 84.6 87.1 Improved 3.7 15.4 9.5 Hybrid 6.7 0.0 3.4 Acquiring of seed used in most recent season Own stock 79.4 38.5 58.9 Other farmers or neighbours 3.2 0.0 1.6 Purchased in the market 14.0 61.5 37.8 From extension agents, Ngo or other formal organizations 2.9 0.0 1.9 Comparing fertilizer use in recent season with when Household was formed No fertilizer applied at that time 30.2 90.0 60.1 Amount decreased since then 12.7 0.0 6.3 Amount unchanged since then 7.9 10.0 8.9 Amount increased since then 49.2 0.0 24.6 Fertilizer use in most recent season compared to 2002 No fertilizer applied in 2002 25.0 75.0 50.0 Amount decreased since then 16.9 0.0 8.5 Amount unchanged 11.8 0.0 5.9 Amount increased since then 46.3 25.0 35.7 Method of land preparation in recent season compared to 2002 Hoe cultivation 72.0 84.6 78.3 Oxen ploughing 22.7 0.0 11.3 Tractor ploughing 5.3 15.4 10.4 Use of Pesticides in most recent season 25.0 100.0 62.5 Source: Afrint II field Survey, 2007

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Table 3.10: Distribution of Households by Crop Production Technology for Rice Description of technology when household was formed Kaduna Osun National Grew rice when household was formed 66.0 80.0 73.0

Type of rice production system when household was formed Upland rice (rainfed)-proportion of land 34.0 70.9 52.5 Lowland rainfed rice-proportion of land 66.0 34.7 50.3 Lowland irrigated rice-proportion of land - 40.0 40.0* Variety of rice planted when household was formed Traditional 83.9 77.4 80.6 Improved 16.1 22.6 19.4 Application of pesticides when household was formed 30.3 33.3 31.8 Method of land preparation when household was formed Hoe cultivation 97.4 78.1 87.8 Oxen ploughing 2.6 6.3 4.4 Tractor ploughing 0.0 15.6 7.8 Description of technology in most recent season Type of rice grown during the most recent season upland rice (rainfed) 42.3 60.1 51.2 lowland rainfed rice 57.7 54.3 56.0 lowland irrigated rice 0.0 31.6 15.8 Variety of rice planted in most recent season Traditional 77.9 39.4 58.7 Improved 22.1 60.6 41.3 Plant any NERICA or NERICA descendants 3.2 52.9 28.5 Acquiring of seed used in most recent season Own stock 56.6 17.6 37.1 Other farmers or neighbours 19.2 17.6 18.4 Purchased in the market 21.2 2.9 12.1 From extension agents, NGO or other formal organizations 3.0 61.8 32.4 Comparing fertilizer use in recent season with when Household was formed No fertilizer applied at that time 26.3 32.1 29.2 Amount decreased since then 13.2 3.6 8.4 Amount unchanged since then 5.3 17.9 11.6 Amount increased since then 52.6 46.4 49.5 Average amount spent on artificial fertilizer in most recent season 64.9 81.7 73.3 Fertilizer use in most recent season compared to 2002 No fertilizer applied in 2002 22.2 0.0 11.1 Amount decreased since then 24.1 24.0 24.0 Amount unchanged 12.0 68.0 40.0 Amount increased since then 41.7 8.0 24.9 Method of land preparation when household was formed Hoe cultivation 75.0 84.9 79.9 Oxen ploughing 11.1 0.0 5.6 Tractor ploughing 13.9 9.1 11.5 Others 0.0 6.1 3.0 Use of Pesticides in most recent season 44.2 54.5 49.3 Source: Afrint II field Survey, 2007 * only applied in Osun state

Table 3.11: Household Distribution by Production Technology for Other Food Crops and Vegetables Production Technology and Input Use Kaduna Osun National Average total area devoted to crop in most recent season 2.5 1.3 1.9 Whether land is irrigated-yes 4.9 3.5 4.2

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Used chemical fertilizer in most recent season 69.1 24.6 46.9 Used animal manure in most recent season 52.7 9.1 30.9 Used green manure in most recent season 11.9 12.1 12.0 Applied pesticides in most recent season 56.0 21.5 38.8 Source: Afrint II field Survey, 2007 Table 3.12: Household Distribution by Production Technology for Non-Food Cash Crop Production Technology and Input Use Kaduna Osun National Average total area devoted to crop 1.9 1.9 1.9 How much of the land was irrigated (ha) 1.7 0.6 1.1 Used chemical fertilizer in most recent season 55.9 13.9 34.9 Used animal manure in most recent season 55.9 3.8 29.9 Used green manure in most recent season 23.7 10.1 16.9 Applied pesticides in most recent season 44.8 55.4 50.1 Only men or women responsible for production of these crops 57.9 56.4 57.1 Change in overall land devoted to crop since household was formed less land under cash crop now 16.2 3.9 10.0 no change 41.9 43.3 42.6 more land under cash crop now 41.9 52.9 47.4 Change in overall land devoted to crop since 2002 less land under cash crop now 15.1 1.3 8.2 no change 43.4 50.0 46.7 more land under cash crop now 41.5 48.7 45.1 Source: Afrint II field Survey, 2007

3.3 Farm Management Practices

In the face of unpredictable change in weather and climatic conditions and prevalence of pests and diseases, increased use of improved inputs and modern technologies coupled with good farm management practices remain the best option of achieving maximum output and increased productivity on farm. Such farm management practices include; crop rotation, intercropping with nitrogen fixing crops, bush fallowing, the use of animal manure, conservation or minimum/zero tillage, breaking of hard pan, the use of green manure and soil and water conservation. This study investigated these management practices both in the recent season (2007) and when the newly sampled households were formed and the results are presented in Tables 3.13, 3.14, 3.15 and 3.16 for maize, cassava, sorghum and rice growing households.

Where available arable land is declining or limited, one practical way of maintaining and achieving maximum output from a given piece of land is crop rotation. Until recently, this farm management technique was not a common practice in Nigeria. However, as a result of urbanization and increasing demand for land for industrial use and other purposes, most of the fertile arable lands in the country have been encroached upon. Thus, one of the ways by which Nigerian farmers now ensure maximum utilization of the available arable lands is through crop rotation. For the newly sampled households the practice of crop rotation was widely common when the household was formed. This practice was particularly common among the rice and sorghum growing households where more than 60 per cent of the respondents reported the practice as and when their households were formed. About 50 per cent of maize and cassava growing households were also engaged in the practice of crop rotation when their households were formed. The result, however, presented a wide divergent in the practice between the north and the south with the practice more predominant in the south (Osun state). Similar trend was observed in 2007 except in the case of cassava growing households where close to about 60 per cent of the

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households adopted the practice. The practice did not record any significant improvement among the maize growing households where less than half of the respondents adopted crop rotation practice.

Intercropping with nitrogen fixing crops is one way of replenishing the soil with one of the most important micro-nutrients (nitrogen) which is required for healthy growth of crops. These crops harbour some nitrogen fixing bacterial in their root noodles which helps in fixing nitrogen into the soil. Apart from assisting other crops in getting this micro-nutrient, output realise of these nitrogen fixing crops also contribute to increased productivity of land. This management practice was not widely common among the newly sampled households when their households were formed except for sorghum growing households where 55 per cent of the respondents claimed to be practicing it when their households were formed. It should, however, be noted that the common practice in rice cultivation is mono-cropping. As a result, only about 6 per cent of the rice growing households reported the practice when their households were formed. However, due to increasing difficulty of accessing fertilizer by farmers in the country, the practice is gradually gaining ground among rice growing households as reported by 13 per cent of the respondents who adopted this management practice in 2007. Except for sorghum growing households where close to half of the respondents engaged in the practice in 2007, the percentage of maize and cassava growing households who engaged in the practice in 2007 was less than 40 per cent.

The practice of bush fallowing is a way of allowing arable land that has been put into cultivation for a number of cropping seasons some resting time for it to regenerate its lost fertility. This is normal practice where arable land is abundant and the pressure on land is very low. Generally, this practice is very common in the south as indicated by respondents in Osun state and presented in the tables for the various crops. For the newly sampled households, about 55 per cent of maize growing households engaged in the practice when their households were formed. For the remaining crops, the percentage of households engaging in the practice when their households were formed was less than 50 per cent. In 2007, however, it was only among the sorghum growing households that more than 50 per cent of the respondents engaged in the practice. This further underscores the increasing decline in arable land in the country.

Conservation tillage, otherwise known as minimum tillage, is a farm management practice that requires very little impact on the soil surface in order not to tamper with the organic matter layer of the soil. This is usually practised on land with thin or tiny layer of organic matter. Though this management practice exists both in the northern and southern parts of the country, the practice is not widely common among the farmers. For example, among the newly sample households, only rice growing households had 25 per cent of the households engaged in the practice when their households were formed. The practice among maize, cassava and sorghum growing households was less than 20 per cent as indicated by the respondents. Even in recent season (2007) the practice did not record any significant improvement among the farmers as it was only among rice growing households that about a quarter of the respondents reported the practice.

Where the land contains a very hard impervious layer of top or sub soil, breaking the hard pan is usually a practice in which case these hard surfaces are exhumed and broken into pieces at the on-set of the raining season to allow free percolation of air

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and water. This is usually a common practice in the northern part of the country but it is gradually spreading into the south.

The survey of newly sampled households showed that the practice was only common among the rice growing households when their households were formed as indicated by about 45 per cent of the respondents. Less than 20 per cent of the respondents for the maize, cassava and sorghum growing households indicated the practice when their households were formed. In 2007, about one-third of the rice and cassava growing households adopted the practice. The practice has not assumed any significant scale among the maize and sorghum growing households.

Green manure is an art of incorporating plant residues into the soil as a way of enriching soil fertility. This is usually done when these plants (weeds) are very succulent preferably before flower stage. This practice is also common across the country. However, a survey of newly sampled households showed that the practice was only widely common among rice growing households when their households were formed. This was indicated by 43 per cent of the respondents. The percentage of respondents practicing the management technique when their households were formed for maize, cassava and sorghum growing households was less than 20 per cent.

Climate change and the associated weather variables such as rainfall patterns is increasingly making rainfed agriculture very difficult as this is exposing farmers in the country to a number of unpredictable risks with the attendant effects on farm planning and profit of the farmers. Where large scale irrigation facilities are lacking another way of managing the effects of unpredictable change in weather condition is through soil and water conservation. While soil conservation is the prevention of the washing away of the top fertile layer of the soil, water conservation involves a way of retaining the soil moisture content. The practice of soil conservation include tree planting and cover crops, terrace and contours while the practice of water conservation includes mulching, cover crops, agro-forestry and rain water harvesting. In spite of the importance of this management practice, very few farmers in Nigeria engaged in it. A survey of newly sample households showed that the proportion of the households that engaged in the practice when their households were formed was less than 10 per cent. Even in the most recent season (2007), the proportion of households that engaged in the practice was still less than 10 per cent for all the crops.

Animal manure is normally used by farmers to replenish soil nutrient particularly where access to artificial fertilizer have proven to be very difficult. The animal dung is applied early enough to allow the decomposition of some of the elements before planting of crops so as to prevent heat generated during decomposition from damaging the crops. This practice appeared to be in vogue particularly in the northern part of Nigeria where livestock farming is a wide scale practice. Nevertheless, household survey in 2007 showed that only about half of the newly sampled households engaged in the practice when their households were formed. The situation was the same for the application of the technique even in 2007 cropping season. The only exception was among the sorghum growing households since the crop is mainly cultivated in the north.

Meanwhile, one farm management practice that is gradually gaining ground among the cereal growing households in Nigeria is the use of pesticides and herbicides. This

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management practice is in response to the wave of increasing farm wage rate (cost of labour) in the country. Household survey revealed that at least 50 per cent of the households on the average applied pesticides and herbicides on their farms in 2007 cropping season.

Table 3.13: Distribution of Household by Farm Management Practices for Maize Farm management practices when household was formed Kaduna Osun National Used or applied crop rotation 41.4 56.8 49.1 Intercropped with nitrogen fixing crops 22.5 50.6 36.5 Fallowing 39.1 70.3 54.7 Animal manure 53.2 11.0 32.1 Conservation tillage 1.8 10.3 6.0 Breaking the hard pan 21.6 16.3 18.9 Green manure/residue incorporation 11.7 20.8 16.2 Soil and water conservation 9.9 3.7 6.8 Farm management practices during the most recent season Used or applied crop rotation 45.5 54.8 50.1 Intercropped with nitrogen fixing crops 14.4 33.9 24.1 Fallowing 20.7 62.1 41.4 Animal manure 59.5 7.5 33.5 Conservation tillage (minimum tillage) 11.0 20.9 15.5 Breaking the hard pan 32.5 14.8 23.6 Green manure/residue incorporation 17.0 32.8 24.9 Soil and water conservation 0.00 0.0 0.0 Source: Afrint II field Survey, 2007

Table 3.14: Distribution of Household by Farm Management Practices for Cassava Farm management practices when the household was formed Kaduna Osun National Used or applied crop rotation 40.0 59.7 49.8 Intercropped with nitrogen fixing crops 22.2 36.4 29.3 Fallowing 10.0 69.5 39.7 Animal manure 50.0 8.2 29.1 Conservation tillage (zero or minimum tillage) 0.0 23.9 11.9 Breaking the hard pan 30.0 18.1 24.0 Green manure/residue incorporation 22.2 36.5 29.3 Soil and water conservation 0.0 8.2 4.1 Pesticides or herbicides 52.3 52.3* Farm management practices during the most recent season Used or applied crop rotation 44.1 72.3 58.2 Intercropped with nitrogen fixing crops 35.5 39.2 37.3 Fallowing 23.3 85.7 54.5 Animal manure 44.4 12.9 28.6 Conservation tillage (zero or minimum tillage) 3.3 16.7 10.0 Breaking the hard pan 48.4 19.2 33.8 Green manure/residue incorporation 23.3 25.0 24.1 Soil and water conservation 10.0 7.2 8.6 Pesticides or herbicides 16.7 - 16.7 Source: Afrint II field Survey, 2007 * only practiced in one state

Table 3.15: Distribution of Household by Farm Management Practices for Sorghum Farm management practices when household was formed Kaduna Osun National Used or applied crop rotation 41.4 100.0 70.7 Intercropped with nitrogen fixing crops 22.5 87.5 55.0 Fallowing 39.1 54.5 46.8 Animal manure 53.2 - 53.2* Conservation tillage 1.8 - 1.8* Breaking the hard pan 21.6 - 21.6*

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Green manure/residue incorporation 11.7 11.7 11.7* Soil and water conservation 9.9 - 9.9* Farm management practices during the most recent season Used or applied crop rotation 44.1 83.3 63.4 Intercropped with nitrogen fixing crops 20.9 75.0 47.9 Fallowing 16.4 77.8 47.1 Animal manure 49.6 25.0 37.3 Conservation tillage 13.3 - 13.3* Breaking the hard pan 32.6 1.0 16.3 Green manure/residue incorporation 14.1 66.7 40.4 Soil and water conservation 12.1 - 12.1* pesticides/herbicides 30.4 66.7 48.5 Source: Afrint II field Survey, 2007 * only practiced in one state

Table 3.16: Distribution of Household by Farm Management Practices for Rice Farm management practices when household was formed Kaduna Osun National Used or applied crop rotation 30.3 96.7 63.5 Intercropped with nitrogen fixing crops 0.00 11.1 5.5 Fallowing 12.1 85.7 48.9 Animal manure 31.3 5.3 18.3 Conservation tillage 3.1 47.4 25.2 Breaking the hard pan 51.4 36.8 44.1 Green manure/residue incorporation 0.0 86.7 43.3 Soil and water conservation 12.5 0.0 6.2 Farm management practices during the most recent season Used or applied crop rotation 35.8 87.9 61.8 Intercropping with nitrogen fixing crops 14.7 11.8 13.2 Fallowing 7.4 61.8 34.6 Animal manure 30.9 8.0 19.4 Conservation tillage 10.8 44.1 27.4 Breaking the hard pan 43.2 17.6 30.4 Green manure/residue incorporation 12.8 18.2 15.5 Soil and water conservation 13.8 2.9 8.3 Integrated pest management 6.4 20.6 13.5 Pesticides/herbicides 44.0 88.2 66.1 Source: Afrint II field Survey

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CHAPTER FOUR

CROP COMMERCIALIZATION AND MARKETING CONDITIONS

Though this survey focused mainly on the small scale farmers, the rate of commercialization of crop outputs among the households is a good indicator of development of smallholder agriculture in Nigeria. It was against this background that this study examined the market and marketing conditions for the selected crops among the sampled households in 2007 in comparison with the situation in 2002 and what obtained when households were formed for the newly sample households. The results of this analysis are presented in Tables 4.1, 4.2, 4.3 and 4.5 for maize, cassava, sorghum and rice growing households respectively.

Investigation revealed that maize, cassava and rice received increased commercialization as the proportion of households reported selling these crops in 2007 was more than 80 per cent in each of the crops. Sorghum production in the country appeared to be mainly for the purpose of home consumption as the proportion of households that offered the crop for sale in 2007 was less than 40 per cent. Except for cassava which is normally marketed at farm gate and village markets probably due to the bulky nature of the product and the difficulty it could pose by transporting it over a long distance, majority of grain growing households marketed their crops in the markets outside the village. This was attested to by 57 percent of the maize growing households, 44 per cent of the sorghum growing households and 63 per cent of the rice growing households. It is assumed that most of the cereal crops are sold in form of grains; some maize growing households could also sell some of their output fresh in form of cobs. In the case of cassava, however, more than 90 per cent of the households sold their output in form of tubers in 2007. In other words, less than 10 per cent of cassava growing households added value to their output. It was found expedient for cassava farmers to sell the crop as tubers because there was a glut in the cassava market in that year. An attempt to sell the cassava as processed products would have meant additional costs that would not have been recovered. Selling tubers involved less loss to the farmers who would not have to take the risk of loss posed by poor rural roads and transportation vehicles.

Since most of the outputs of these crops are sold in the market outside the village, there is no doubt that poor post harvest handling will lead to quality deterioration which will subsequently affect the price received by the farmers. This situation holds true for some of the produce in more than 50 per cent of the rice and cassava growing households but for one-third and 40 per cent of the maize and sorghum growing households respectively. Except in Osun state where about 40 per cent of the rice growing households grew the crop on pre-arranged contract with private trader in 2007 the practice of contract farming has not been a common among maize, sorghum and cassava growing households.

The quantity of the various crops offered for sale by households in the 2007 season and in each of the two seasons before 2007 varied. For the maize and sorghum growing households, average quantity of crops sold in 2007 season was higher than the previous season but lower than quantity sold two seasons before 2007. Cassava growing households have always witnessed increasing sale of produce as the average quantity of produce sold by the households was higher than what was sold during

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season before the most recent season and two seasons ago. Rice producing households, however, witnessed a decline in the average quantity of produce sold in 2007 as the quantity sold averaged 2479kg against 2585kg sold per household during the season before 2007 season. Average quantity sold in 2007 was higher than what obtained in two seasons ago. The quantity of produce sold by households in the most recent season might have been driven by the improvement in the margin between the lowest and highest prices received for the various crops during the season. The margin between the lowest and the highest price received for rice was more than 100 percent as prices rose from N44 per kg to about N96/kg. For sorghum, the margin was about 50 per cent as prices moved from N31 per kg to about N50 per kg. Maize and cassava prices margin were 40 and 30 per cent respectively.

Commercialization of produce by the newly sampled households when the households were formed was only pronounced among the maize and rice growing households as reported by 57 and 65 per cent of the respondents respectively. Aside, 42 per cent of the cassava growing households sold their produce when their households were formed while the proportion of sorghum growing households that sold their produce when their households were formed was just 23 per cent. Comparing the quantity of produce sold in recent season with when household was formed, 54 and 76 per cent of maize and rice growing households respectively also claimed that more produced was sold compared with 42 and 33 per cent by the cassava and sorghum growing households respectively. Also comparing the price received in the most recent season for produce with when household was formed, an average of 65 per cent of the maize, sorghum and rice growing households claimed that better price was received in 2007 compared to when their households were formed. The only exception was cassava where only 40 per cent of the respondents reported increased price. About 36 per cent of the households claimed there was no significant change in price while about 23 per cent claimed that cassava price has actually decreased. The increased price level recorded for most crops in recent season compared to when household was formed for the newly sampled households could be traced to increased market outlets for these crops. More than 60 per cent of the households agreed that market access for their produce in 2007 was actually better than when households were formed. An average of one-third of the households, however, did not see any significant improvement in the market outlets for their produce in recent season when compared with where their households were formed.

In 2002, more than three-quarter of the maize and cassava growing households sold their produce while about 57 of the sorghum and rice growing households offered their produce for sale. Comparing quantity sold in the most recent season with 2002, the proportions of households that reported increase in quantity sold vary between 57 per cent for cassava growing households and 66 per cent for the rice growing households. Maize and sorghum growing households recorded the same proportion of 58 per cent. In terms of price movement, 90 and 75 per cent of the sorghum and maize growing households reported that price had increased compared to 2002. For the rice growing households, 60 per cent also claimed that price had increased while 43 per cent of the sorghum growing household also held the same opinion. This could be merely due to food price inflation in the country. In terms of change in market access, the market access for grains seems to have improved when compared with the situation in 2002. Improved market access was reported by 70 per cent of maize growing households, 100 per cent of the sorghum growing households and 66 per cent

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of rice growing households. For the cassava growing households, however, less than 50 per cent of them reported increased market access underscoring the structural constraints and market imperfection that still characterize cassava market in Nigeria.

In the past, other food crops and vegetables were produced mainly for home consumption but some of these crops are now being produced in commercial quantities. Analysis of households by level of commercialization of these crops showed that vegetables for local markets, yam and banana were produced in commercial quantities and marketed in 2007 (see Tables 4.5, 4.6 and 4.7). This was reported by 65 per cent of the households for vegetables, 54 per cent for yam, 44 per cent for banana and 42 per cent for fruits for local market. Others that have also assumed substantial levels of commercialization include cocoyam and beans. The most profitable of these crops are yam and vegetables for local market as indicated by 23 per cent of the households.

Comparing the marketing conditions for these crops in 2007 with the situation when household was formed for the newly sampled households, 76 per cent of the households claimed that the quantity sold in 2007 was more than what was sold when their households were formed. Aside, 89 per cent also agreed that the overall market access for these crops was better than when their households were formed. Similar result was obtained when the households were requested to compare marketing conditions for these crops in 2007 with the situation in 2002. About 78 per cent of the households claimed more quantities of these crops were sold in 2007 compared to 2002 while another 88 per cent believed that the market access was better compared to the situation in 2002.

For the non-food cash crops, cocoa was rated as the most profitable by 38 per cent of the households in 2007. However, 77 per cent of the households claimed that the price received for these crops was better in 2007 compared to the time the households was formed for the newly sampled households. Another 76 per cent indicated that the overall market access for these crops was better than the situation when their households were formed. The comparison of price received and market access for these crops with the situation in 2002 yielded similar result as indicated by 77 per cent of the households.

Table 4.1: Distribution of Households by Marketing Condition for Maize Marketing conditions Kaduna Osun National Selling of maize following most recent harvest 78.4 81.3 79.8 Paying of lower price by traders due to post-harvest quality deterioration No 57.1 68.1 62.6 Yes for some produce 37.1 25.0 31.0 Yes for most produce 5.9 6.9 6.4 Main market outlet for maize At farm gate 10.6 15.2 12.9 Village market 19.4 37.3 28.3 Market outside the village 67.6 46.6 57.1 Farmers groups or organization 2.4 0.5 1.5 Others 0.0 0.5 0.2 Growing of maize on pre-arranged contract with private trader 2.9 1.1 2.0 Average quantity of maize sold after most recent harvest 1915.3 1290.7 1603.0 Average lowest price received after most recent harvest 25.0 29.1 27.0 Average highest price received after most recent harvest 28.7 45.5 37.1

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Selling maize after the harvest before the most recent one 80.5 78.9 79.7 Average quantity sold after the harvest before most recent one 2266.4 926.1 1596.2 Selling maize after harvest two seasons before the most recent one 70.0 79.7 74.9 Average quantity sold two harvests before the most recent one 2344.8 895.6 1620.2 Selling maize at the time household was formed 39.6 75.0 57.3 Change in quantity sold since household was formed Less maize sold 52.3 17.1 34.7 No significant change 7.2 8.5 7.9 More maize sold 40.5 74.4 54.4 Price received today better or worse than when household was formed Price has decreased 33.3 10.1 21.7 No significant price change 3.6 5.0 4.3 Price has increased 63.1 84.9 74.0 Change in market outlets since household was formed market access is worse now 12.7 5.2 8.9 market access unchanged 22.7 4.3 13.5 market access is better now 65.5 90.4 77.9 Selling maize after the harvest in 2002 70.2 85.2 77.7 Changes in quantity sold since 2002 Less maize sold 18.5 18.3 18.4 No significant change 28.5 12.8 20.6 More maize sold now 53.0 68.9 70.0 Price received today compared to 2002 Price has decreased 9.5 8.3 9.0 No significant change 24.1 7.8 15.9 Price has increased 66.3 83.9 75.1 Changes in market outlet since 2002 market access is worse now 10.0 7.3 8.6 market access unchanged 35.0 7.3 21.2 market access is better now 55.0 85.3 70.2 Source: Afrint II field Survey, 2007

Table 4.2: Distribution of Households by Market and Marketing Condition for Cassava Marketing conditions Kaduna Osun National Selling of cassava in the past years starting from today 81.8 86.0 83.9 Form of selling cassava mainly sold as tubers 96.7 87.7 92.2 mainly sold in processed form 3.3 12.3 7.8 Average total quantity of cassava sold in the most recent season 2126.5 4794.3 3460.4 Average lowest price received during this period 167.7 48.3 108.0 Average highest price received during this time 186.2 65.9 126.0 Paying of lower price by traders due to post-harvest quality deterioration No 22.7 54.1 38.5 Yes for some produce 72.7 36.6 54.6 Yes for most produce 4.5 9.3 6.9 Main market outlet for cassava At farm gate 40.7 36.3 38.5 Village market 50.8 20.2 35.5 Market outside the village 6.3 43.0 24.7 Farmers groups or organization 3.1 0.5 1.8 Growing of cassava on pre-arranged contract with private trader 9.7 2.2 5.9 Sold cassava during season before most recent season 82.9 84.4 83.7 Average quantity of unprocessed cassava sold during season before 2042.4 3729.7 2886.1 recent season Sold cassava two years ago 10.5 81.8 46.2 Average quantity of unprocessed cassava sold two season before most 1340.4 3587.9 2464.2 recent season Selling cassava at the time household was formed 3.0 80.6 41.8

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Change in quantity sold since household was formed Less cassava sold 6.2 26.9 16.5 No significant change 68.8 15.1 42.0 More cassava sold 25.0 58.1 41.5 Price received for unprocessed cassava today better or worse than when household was formed Price has decreased 0.0 45.7 22.9 No significant price change 64.3 7.6 36.0 Price has increased 35.7 46.7 41.1 Change in market outlets since household was formed market access is worse now 0.0 24.4 12.2 market access unchanged 44.4 12.2 28.3 market access is better now 55.6 63.3 59.5 Selling cassava after the harvest in 2002 63.2 87.2 75.2 Changes in quantity sold since 2002 Less cassava sold 6.5 37.3 21.9 No significant change 29.0 13.3 21.2 More cassava sold now 64.5 49.4 56.9 Price received today compared to 2002 Price has decreased 0.0 71.3 35.6 No significant change 38.7 4.2 21.5 Price has increased 61.3 24.6 42.9 Changes in market outlet since 2002 market access is worse now 0.0 43.1 21.6 market access unchanged 54.8 6.6 30.7 market access is better now 45.2 50.3 47.7 Source: Afrint II field Survey, 2007

Table 4.3: Distribution of Households by Marketing Condition for Sorghum Marketing conditions Kaduna Osun National Selling of sorghum following most recent harvest 59.3 12.6 35.9 Paying of lower price by traders due to post-harvest quality deterioration No 45.6 35.7 40.7 Yes for some produce 48.1 42.9 45.5 Yes for most produce 6.3 21.4 13.8 Main market outlet for sorghum At farm gate 17.9 33.3 25.6 Village market 27.4 25.0 26.2 Market outside the village 46.3 41.7 44.0 out-grower scheme 5.3 - 5.3* Farmers groups or organization 3.2 3.2* Growing of sorghum on pre-arranged contract with private trader 2.4 - 2.4 Average quantity of sorghum sold after most recent harvest 991.6 362.5 677.0 Average lowest price received after most recent harvest 34.7 28.5 31.6 Average highest price received after most recent harvest 50.1 46.1 48.1 Selling sorghum after the harvest before the most recent one 70.1 69.2 69.7 Average quantity sold after the harvest before most recent one 302.0 515.3 408.7 Selling sorghum after harvest two seasons before the most recent one 60.5 64.3 62.4 Average quantity sold two harvests before the most recent one 1004.9 500.3 752.6 Selling sorghum at the time household was formed 32.8 12.6 22.7 Change in quantity sold since household was formed Less sorghum sold now 16.3 35.7 26.0 No significant change 37.8 42.9 40.4 More sorghum sold 45.9 21.4 33.6 Price received today better or worse than when household was formed Price has decreased 0.0 0.0 0.0 No significant price change 22.0 42.9 32.5 Price has increased 78.0 57.1 67.5 Change in market outlets since household was formed

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market access is worse now 0.0 7.1 3.5 market access unchanged 25.0 42.9 34.0 market access is better now 75.0 50.0 62.5 Selling sorghum after the harvest in 2002 59.1 52.9 56.0 Changes in quantity sold since 2002 Less sorghum sold now 23.4 33.3 28.4 No significant change 26.4 0.0 13.2 More sorghum sold now 50.0 66.7 58.4 Price received today compared to 2002 Price has decreased 1.1 0.0 0.5 No significant change 19.1 0.0 9.5 Price has increased 79.8 100.0 90.0 Changes in market outlet since 2002 market access is worse now 2.1 0.0 market access unchanged 18.9 0.0 market access is better now 78.9 100.0 Source: Afrint II field Survey, 2007

Table 4.4: Distribution of Households by Marketing Condition for Rice Marketing conditions Kaduna Osun National Selling of rice following most recent harvest 87.0 84.4 85.7 Paying of lower price by traders due to post-harvest quality deterioration No 42.5 27.6 35.1 Yes for some produce 50.0 62.1 56.0 Yes for most produce 7.5 10.3 8.9 Main market outlet for rice At farm gate 5.9 12.5 9.2 Village market 21.8 56.3 39.0 Market outside the village 64.4 31.3 62.9 out-grower scheme 5.9 0.0 2.9 Farmers groups or organization 2.0 0.0 1.0 Growing of rice on pre-arranged contract with private trader 39.4 39.4* Average quantity of rice sold after most recent harvest 1719.5 3238.8 2479.2 Average lowest price received after most recent harvest 26.7 61.8 44. 3 Average highest price received after most recent harvest 30.7 162.7 96.7 Selling rice after the harvest before the most recent one 78.0 74.3 76.2 Average quantity sold after the harvest before most recent one 1815.7 3356.0 2585.9 Selling rice after harvest two seasons before the most recent one 75.0 83.3 79.2 Average quantity sold two harvests before the most recent one 1897.7 2506.4 2202.1 Selling rice at the time household was formed 46.7 83.3 65.0 Change in quantity sold since household was formed Less rice sold 6.3 10.0 8.2 No significant change 31.3 0.0 15.5 More rice sold 62.5 90.0 76.3 Price received today better or worse than when household was formed Price has decreased 0.0 13.3 6.7 No significant price change 31.3 26.7 29.0 Price has increased 68.8 60.0 64.4 Change in market outlets since household was formed market access is worse now 3.2 3.4 3.3 market access unchanged 22.6 34.5 28.6 market access is better now 74.2 62.1 68.1 Selling rice after the harvest in 2002 72.6 40.5 56.6 Changes in quantity sold since 2002 Less rice sold 19.6 7.1 13.3 No significant change 27.2 14.3 20.8 More rice sold now 53.3 78.6 65.9 Price received today compared to 2002

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Price has decreased 5.2 42.9 24.0 No significant change 17.7 14.3 16.0 Price has increased 77.1 42.9 60.0 Changes in market outlet since 2002 market access is worse now 3.3 30.8 17.0 market access unchanged 10.9 23.1 17.0 market access is better now 84.8 46.2 66.0 Source: Afrint II field Survey, 2007

Table 4.5: Distribution of Household by Types of Other Food Crops and Vegetables Marketed Other Food Crops and Vegetables Kaduna Osun National Banana 15.1 72.9 44.0 Beans 43.6 17.6 30.6 Peas 1.9 2.7 2.3 Irish potatoes 0.0 1.2 0.6 Sweet potatoes 33.0 20.5 26.8 Millet 39.2 0.5 19.9 Groundnut 43.1 12.6 27.9 Yam 38.2 69.8 54.0 Cocoyam 32.4 44.4 38.4 Vegetables for local markets 56.6 79.0 67.8 Fruits for local markets 18.4 64.6 41.5 Most Profitable of the Crops Banana 5.7 32.5 19.1 Beans 35.8 2.6 19.2 Peas 0.9 1.0 0.9 Irish potatoes 0.0 0.5 0.2 Sweet potatoes 0.9 0.5 0.7 Millet 0.9 0.5 0.7 Groundnut 9.4 0.5 4.9 Yam 15.1 30.4 22.7 Cocoyam 0.0 1.0 0.5 Vegetables for local markets 31.1 15.2 23.2 Fruits for local markets 0.0 12.0 6.0 Source: Afrint II field Survey, 2007

Table 4.6: Distribution of Households by Marketing Condition for Other Food Crops and Vegetables Marketing conditions Kaduna Osun National Crop sales compared to when household was formed crop not grown at that time 11.5 4.2 7.9 less is sold now 13.5 9.4 11.5 no change in 5.8 3.1 4.5 more is sold now 69.2 83.2 76.2 Change in overall market access since household was formed crop not grown at that time 5.6 3.1 4.4 market access is worse now 3.7 1.6 2.7 market access unchanged 7.4 1.6 4.5 market access is better now 83.3 93.8 88.6 Crop sales compared to 2002 crop not grown at that time 10.4 2.7 6.6 less is sold now 11.3 9.2 10.2 no change in 6.6 2.7 4.7 more is sold now 71.7 85.3 78.5 Market access today compared to 2002 crop not grown in 2002 8.6 0.6 4.6 market access is worse now 2.9 1.7 2.3 market access unchanged 9.5 1.1 5.3 market access is better now 79.0 96.6 87.8

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Source: Afrint II field Survey, 2007

Table 4.7: Distribution of Households by Marketing Condition for Non-Food Cash Crops Marketing conditions Kaduna Osun National Which of the crops is most profitable cotton 47.3 1.5 24.4 sugarcane 43.6 8.5 26.1 cashew nut 5.5 47.7 26.6 cocoa 0.0 76.0 38.0 tobacco 0.0 6.9 3.4 coffee 0.0 1.0 0.5 fruits and vegetables, mainly for export 1.8 16.7 9.2 flowers 0.0 1.0 0.5 spices, like ginger and vanilla 0.0 1.5 0.7 Others 1.8 15.0 8.4 Price received today compared with when household was formed crop not grown at that time 18.2 11.7 14.8 worse price today (price has decreased) 0.0 4.1 2.0 no significant change 7.3 5.3 6.3 better price today (price has increased) 74.5 78.9 76.7 Change in market access compared with when household was formed crop not grown at that time 18.2 11.4 14.8 market access is worse now 0.0 1.1 0.5 market access unchanged 15.8 2.3 9.0 market access is better now 66.0 85.2 75.6 Price received today compared with 2002 crop not grown at that time 22.6 7.9 15.3 worse price today (price has decreased) 0.0 4.9 2.4 no significant price change 3.8 3.7 3.8 better price today 9price has increased) 73.6 83.5 76.5 Change in overall market access for most profitable non food cash crops since 2002 crop not grown in 2002 22.6 8.6 15.6 market access is worse now 0.0 1.8 0.9 market access unchanged 9.4 2.5 6.0 market access is better 66.0 87.1 76.5 Source: Afrint II field Survey, 2007

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CHAPTER FIVE

AGRICULTURAL PRODUCTION TECHNOLOGYADOPTION AND DIFFUSION

Agricultural production technologies may not make much impact on farm level productivity unless such technologies are put into use by the farmers. But for a peasant farmer to adopt a technology, he/she must first have the knowledge of the technology, and be convinced that such technology will not only increase his/her productivity but that it is going to be cost efficient. This study also investigated the knowledge of the sampled households in 2007 as regards the various farm practices, whether they adopted any of the farm practices and the major factor inhibiting the adoption of those practices which the households could not adopt. The results of these analyses are as shown in Tables 5.1, 5.2 and 5.3. The study also traced the path of technology diffusion in the country by examining the major source of information for the various technology adopted by the households and the major period during which these technologies were adopted. These are presented in Tables 5.4 and 5.5.

As regards the households’ knowledge of technologies in 2007, those technologies which were well known to the households included, intercropping, intercropping with nitrogen fixing fertilizer, improved fallowing and application of chemical fertilizer. At least, more than half of the households reported the knowledge of these technologies in 2007. Other technologies of which households reported they had appreciable knowledge are fallowing, animal manure, soil and water conservation, the use of pesticide and herbicides, and rain water harvesting as indicated by about 45 per cent of the households. In spite of the households’ knowledge of these technologies, very few of the technologies were actually put into practice in 2007. Technologies that assumed significant practice among the households included crop rotation, intercropping, bush fallowing, the use of chemical fertilizer and application of pesticides and herbicides, as reported by more than 50 per cent of the households. For those technologies that were not adopted by the households, three major limiting factors were implicated. The households could not see the relevance of the technology to their agricultural production; technology is labour consuming; or such technology involved additional cost which the households could not afford.

Analysis of agricultural technology diffusion and sources of technology information seriously underscores the limited impact of the agricultural extension system in the country and spatial differences in the effectiveness of extension service delivery in Nigeria, with the north more effective than the south. In general, most of the households rely mainly on their parent and neighbouring farmers for technology information. In Kaduna state, it was only in the case of improved fallowing, zero or minimum tillage, improved planting practices, integrated pest management, agro- forestry and the use of pesticides and herbicides that households received information regularly from the extension agents or NGOs. In Osun state, however, households received information from the extension agents only in respect of integrated pest management and irrigation practices. In terms of the time period during which farmers learnt about these technologies, it was obvious that most farming households in Kaduna state had not learnt about any new technology in the last five years as most of the households reported they learnt these technologies more than five years ago. This indicates that the Presidential Initiative Programme which was designed to further promote agricultural technology adoption among the farming households in

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Nigeria did not yield the desired results, as Kaduna state was among the pilot states for the implementation of the programme in the country. Similar situation was observed in Osun state except for the case of integrated soil nutrient management, integrated pest management and rainwater harvesting where households reported that these technologies were learnt within the last five years. Application of other technologies such as facilities for drying produce, storage technology and other post harvest management practices, such as seed treatment, showed that households have not significantly moved away from their usual traditional practices as presented in Table 5.6. About 40 per cent of the households are still drying their produce on the ground and 65 per cent storing their produce in bags inside house as against 3 per cent that stored their produce in the granary. Though most of these produce are treated by insecticides to prevent mould or insect attack as reported by over 60 per cent of the households, the proportion of produce lost due to poor storage alone is about 10 per cent. The total post harvest loss could be as high as 30 per cent when loss due to other post harvest handlings is added to storage loss.

Table 5.1: Distribution of Household by Knowledge of Agricultural Techniques in 2007 Agricultural Techniques Kaduna Osun National Crop rotation 61.8 5.1 33.5 Intercropping 69.9 75.0 72.5 Intercropping with nitrogen fixing crops 43.5 90.7 67.1 Fallowing 43.5 52.8 48.2 Improved fallowing 18.0 84.5 51.3 Animal manure 69.0 22.0 45.5 Zero or minimum tillage 38.5 38.0 38.2 Breaking the hard pan 40.9 31.1 36.0 Green manure 34.7 19.0 26.9 Chemical fertilizer 85.5 42.7 64.1 Soil and water conservation 27.0 67.0 47.0 Improved planting practices 31.8 12.7 22.3 Integrated soil nutrient management 9.5 31.6 20.6 Integrated pest management 11.0 3.4 7.2 Agro-forestry 15.7 14.2 14.9 Pesticides/herbicides 58.8 28.2 43.5 Rainwater harvesting 17.6 70.1 43.9 Irrigation 25.0 12.1 18.6 Source: Afrint II field Survey, 2007

Table 5.2: Distribution of Household by Types of Agricultural Techniques Practice in 2007 Agricultural Techniques Kaduna Osun National Crop rotation 43.5 62.7 53.1 Intercropping 42.5 96.6 69.6 Intercropping with nitrogen fixing crops 20.6 36.4 28.7 Fallowing 29.0 78.3 53.6 Improved fallowing 7.0 11.9 9.5 Animal manure 67.0 12.6 39.8 Zero or minimum tillage 16.0 23.2 19.7 Breaking the hard pan 39.0 16.2 37.5 Green manure 14.0 34.6 24.3 Chemical fertilizer 85.5 56.4 70.9 Soil and water conservation 13.1 8.6 10.9 Improved planting practices 30.2 26.3 28.3 Integrated soil nutrient management 1.0 0.5 0.7 Integrated pest management 8.0 7.3 7.6 Agro-forestry 5.0 10.1 7.5

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Pesticides/herbicides 51.8 70.6 61.2 Rainwater harvesting 1.5 1.5 1.5 Irrigation 20.6 4.9 12.8 Source: Afrint II field Survey, 2007

Table 5.3: Distribution of Household by Factors Limiting Technology Adoption Agricultural Techniques Major Limiting Factor- Major Limiting Factor- Kaduna Osun Crop rotation do not find it relevant involve extra cost Intercropping too labour consuming already practicing it Intercropping with nitrogen too labour consuming involve extra cost fixing crops Fallowing too labour consuming do not find it relevant Improved fallowing not relevant do not find it relevant Animal manure involve other extra cost which do not find it relevant I cannot afford Zero or minimum tillage do not find it relevant involve extra cost Breaking the hard pan do not find it relevant do not find it relevant Green manure too labour consuming involve extra cost Chemical fertilizer too labour consuming involve extra cost Soil and water conservation do not find it relevant do not find it relevant Improved planting practices too labour consuming do not find it relevant Integrated soil nutrient involve extra cost do not find it relevant management Integrated pest management involve extra cost do not find it relevant Agro-forestry do not find it relevant do not find it relevant Pesticides/herbicides too labour consuming and extra involve extra cost cost Rainwater harvesting do not find it relevant do not find it relevant Irrigation involve other extra cost do not find it relevant Source: Afrint II field Survey, 2007

Table 5.4: Distribution of Household by Source of Information on Technology Agricultural Techniques Major Source of Information Major Source of Information Kaduna Osun Crop rotation from parent/ family member not practice in the state Intercropping from parent /family member from parent and family member Intercropping with nitrogen from parent/family member from parent or family member fixing crops Fallowing from parent /family member from parent or family member Improved fallowing from extension agent/NGO from parent or family member Animal manure from parent/family member from parent or family member Zero or minimum tillage from extension agent/NGO from parent and family member Breaking the hard pan from parent/family member extension agent Green manure from parent/family member from parent or family member Chemical fertilizer from parent/extension agent from parent or family member Soil and water conservation from parent/extension agent from parent or family member Improved planting practices from extension agent/NGO from extension agent Integrated soil nutrient from fellow farmers from parent or family member management Integrated pest management from extension agent/NGO from extension agent Agro-forestry from extension agen/NGO over the radio and television Pesticides/herbicides from extension agent/NGO over the radio and television Rainwater harvesting from parent/family member from parent or family member Irrigation from parent/family member from extension agent Source: Afrint II field Survey, 2007

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Table 5.5: Distribution of Household by Period of Learning about Agricultural Techniques Agricultural Techniques Major period of Learning Major period of learning Kaduna Osun Crop rotation more than five years ago more than five years ago Intercropping more than five years ago more than five years ago Intercropping with nitrogen more than five years ago more than five years ago fixing crops Fallowing more than five years ago more than five years ago Improved fallowing more than five years ago more than five years ago Animal manure more than five years ago more than five years ago Zero or minimum tillage more than five years ago more than five years ago Breaking the hard pan more than five years ago more than five years ago Green manure more than five years ago more than five years ago Chemical fertilizer more than five years ago more than five years ago Soil and water conservation more than five years ago more than five years ago Improved planting practices more than five years ago more than five years ago Integrated soil nutrient more than five years ago within the last five years management Integrated pest management more than five years ago within the last five years Agro-forestry more than five years ago more than five years ago Pesticides/herbicides more than five years ago more than five years ago Rainwater harvesting more than five years ago within the last five years Irrigation more than five years ago more than five years ago Source: Afrint II field Survey, 2007

Table 5.6: Distribution of Households by Usage of other Technologies Other Technologies Kaduna Osun National Drying facilities used in drying produce none, drying on the ground 43.5 34.5 39.0 tarmac road 14.0 1.7 7.9 bags, tarpaulins, mats 22.0 27.1 24.5 concrete drying floor 18.5 36.2 27.4 others 2.0 0.4 1.2 Storage of produce bag inside house 64.5 66.1 65.3 in a grainery 3.5 2.6 3.0 bags in a proper store 29.5 30.4 29.9 others 2.5 0.8 1.7 System of storing bags in the house where it is done in bags straight on the floor 37.0 17.5 27.3 in bags on pallets on the floor 48.5 69.5 59.0 in bags under the ceiling 1.0 11.7 6.4 others 13.5 1.3 7.4 Treatment of seed with insecticides to prevent mould or 77.0 54.6 65.8 insect attack Average proportion of post harvest loss due to storage 9.8 9.4 9.6 Source: Afrint II field Survey, 2007

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CHAPTER SIX

HOUSEHOLD WEALTH CREATION

One of the factors that can enhance farm level productivity in households is available wealth creation opportunities and potentials. These include land resources, labour resources, livestock and fisheries resources and other households’ durable assets. This study also investigated the situation of these resources among the sampled households in 2007 and the various findings are discussed below.

6.1. Land Resource

The average total area of land cultivated to all crops by the households in 2007 is 6ha with the households in the north having relatively higher farm sizes than those in the south (Table 6.1). The potential to expand cultivated area is equally higher in the north and almost double that of the south. This shows that the frontier for arable land cultivation will be exhausted earlier in the south compared with the northern part of the country. This can be traced to rapid rate of urbanization in the south compared with the north. Average area of land irrigated also showed that irrigation is a common phenomenon in the north but for those who irrigated their land the major source of irrigation was privately owned well or privately owned river diversion. In other words, reliance on public irrigation facilities has been limited among the households. The fact that the frontier for arable land is approaching exhaustion is further corroborated by the change in the land cultivated particularly by the newly sampled households since household was formed. About 70 per cent of these households indicated that more land is cultivated now compared with when households were initially established. In terms of change in area of land irrigated compared to when household was formed, very insignificant proportion of the households indicated increased irrigated area as majority claimed they did not practice irrigation when household was formed, unlike they were doing now.

Table 6.1: Distribution of Households by Land Resource Information Land Information Kaduna Osun National Average total area of land cultivated during the most recent season 7.2 5.0 6.1 Potential for area expansion (area that would have been cultivated) 3.7 2.0 2.9 Average total area of land irrigated 2.5 0.5 1.5 Source of irrigation where land is irrigated privately owned well 26.2 100.0 63.1 privately owned river diversion 28.6 0.0 14.3 community owned irrigation system 2.4 0.0 1.2 government owned scheme 0.0 0.0 0.0 others 42.9 0.0 21.4 Change in total area of land cultivated since household was formed less land is cultivated 9.4 10.6 10.0 no change 27.1 10.6 18.9 more land is cultivated now 63.5 78.8 71.2 Change in total area of land irrigated since household was formed no land was irrigated at that time 83.3 99.0 91.2 less land is irrigated 1.1 0.0 0.5 no change 5.6 0.0 2.8 more land is irrigated 10.0 1.0 5.5 Source: Afrint II field Survey, 2007

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6.2. Labour Resource

Labour constitutes the major input into smallholder agriculture in Nigeria. As a result of rural-urban migration, availability of farm labour has become very limited in the rural areas where most of the agricultural production activities take place. This has led to increased farm wage rate with its attendant effects on production. This study investigated the labour resource available for households and how this resource was utilized by the various households in 2007. The result is presented in Tables 6.2, 6.3 and 6.4 for the use of family labour, the use of hired labour and gender participation in farming activities respectively.

6.2.1 Household and the use of Family Labour Resource

The use of family labour by households depends on the availability of the able bodied members in the households, their relative health status, engagement in other non-farm activities and involvement of non-residence household members in farm activities. This study investigated the performance of these variables across the households in 2007 and the result is as shown in Table 6.2. The table shows that farming households in Nigeria had an average of 9 able-bodied men and women who are residing with the head of the household and this usually comprised of 5 male and 4 female. The average number of dependants comprising children below 15 years and adults above 60 years was 3 and 4 respectively. Out of these household members, a few of them are suffering from long term illness particularly in the north as reported by an average of 2 for each category in Kaduna state. From an average of 5 able workers in the households, about 4 of them are actively involved in farm work showing that at least one member is either working outside farm or simply not participating in farm work due to illness. The same observation was recorded when compared with the situation in 2002.

Expectedly, the number of household members that depended on the produce and income from the farm in 2007 corresponds with the number of household members who participated actively in farming during the year. Since the survey was targeted at farming households, it was not surprising that farming was the main occupation for about 96 per cent of the household heads but there were still about 4 per cent of the households who engaged in other non-farm activities as their main occupation. At least 3 members of the households in 2007 took employment outside the farm out of which an average of 2 members involved in micro-businesses, seasonal farm employment outside the farm (serving as farm labourers) and seasonal non-farm employment. Meanwhile, an average of 2 non-residence members of the households also participated regularly in farm work during the year. The increasing number of household members taken non-farm seasonal employment is an indication of agricultural labour out-migration even within the rural areas in the country.

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Table 6.2: Distribution of Households by Labour Resource Information in 2007 Labour Information Kaduna Osun National Average no of household members who reside with the household head 16-60years(male) 7.0 3.0 5.0 16-60years (female) 4.0 3.0 4.0 15years and less 3.0 3.0 3.0 61years and above 5.0 2.0 4.0 Average number of household members who are able workers 5.0 4.0 5.0 Average number of household members suffering from long term illness 16-60 years 2.0 0.0 2.0* 15year and below 2.0 0.0 2.0* 61years and above 1.0 0.0 1.0* Average number of household members working on the farm 16-60 years 4.0 4.0 4.0 15year and below 3.0 2.0 3.0 61years and above 1.0 2.0 2.0 Average number of household members working on the farm in 2002 16-60 years 4.0 4.0 4.0 15year and below 3.0 2.0 3.0 61years and above 1.0 2.0 2.0 Average number of dependants on produce and income of the farm 16-60 years 4.0 4.0 4.0 15year and below 3.0 3.0 3.0 61years and above 1.0 2.0 2.0 Main occupation of head of households farming 96.5 94.7 95.6 non-farm 3.5 4.8 4.2 do not work (retired) 0.0 0.4 0.2 Average number of adult household members (16-60years) on regular 3.0 3.0 3.0 employment outside the farm Average number of adult household members regularly involved in some 2.0 2.0 2.0 kinds of micro business Average number of adult household members regularly involved in large 2.0 2.0 2.0 scale business Average number of adult household members that take seasonal 1.0 2.0 2.0 employment outside farm Average number of adult household members that take seasonal non- 1.0 2.0 2.0 farm employment Average number of non-resident adult family members that work 2.0 2.0 2.0 regularly on the farm Source: Afrint II field Survey, 2007 * only reported in one state

6.2.2 Households and the Use of Hired and Exchange labour

In the face of decreasing availability of family labour in the country, farmers are left with only two options of hired and exchange labour. Investigation revealed that about 74 per cent of the sampled household engaged hired labour in 2007. The use of hired labour for various farming operations varied between the two states in the study. However, the use was particularly common for planting, weeding, fertilizer application and transporting of crops as indicated by more than 50 per cent of the households in each case. These operations are often regarded as labour intensive in crop production. The use of exchange labour was also reported by about 23 per cent

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of the households. Exchange labour was particularly used for land preparation, weeding and crop harvesting as indicated by at least 20 per cent of the households.

Table 6.3: Distribution of Households by the Use of Hired and Exchange Labour Hired labour use Kaduna Osun National Regularly use hired labour 67.0 80.9 73.95 Land preparation 52.5 3.4 27.9 Planting 45.5 75.9 60.7 Weeding 64.5 49.1 56.8 Fertilizing 42.5 74.2 58.4 Watching crops 24.0 49.1 36.6 Harvesting 57.0 19.2 38.1 Transporting crops 67.0 49.1 58.1 Tending livestock 30.5 31.8 31.2 Others 5.0 4.3 Exchange labour Use Use exchanged labour 21.0 25.2 23.1 Land preparation 17.0 26.9 22.0 Planting 14.5 21.5 18.0 Weeding 25.0 24.8 23.4 Fertilizing 7.0 6.4 6.7 Watching crops 2.0 9.8 5.9 Harvesting 22.5 23.2 22.8 Transporting crops 13.0 9.1 10.5 Tending livestock 1.0 2.1 1.5 Others 0.0 3.9 1.9 Source: Afrint II field Survey, 2007

6.2.3 Gender and Sex Role Distribution of Labour Resource in Farming

The household dynamics and crop production activities in Nigeria recognize sex role distribution in family labour use and engagement in various farming operations. Generally tedious and energy sapping farm operations such as bush clearing, tilling of land and weeding are mostly carried out by men while women engage in less energy demanding operations such as planting, harvesting, transporting of crops and tending of livestock. In few cases, however, operation like fertilizer application is jointly carried out by both male and female. Thus, the result of our investigation on gender participation in farm activities among the sampled households in 2007 is presented in Table 6.4. About 92 per cent of the households reported that men mainly participated in land preparation. Planting could be done mainly by men as indicated by about 44 per cent of the household or jointly as reported by about 36 per cent of the households. About 63 per cent of households agreed that weeding is done mainly by men. Fertilizer application and harvesting were performed jointly by both male and female as indicated by 58 and 60 per cent of the households respectively. Transporting of crops and tending of livestock were mainly done by women as reported by at least 40 per cent of the households.

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Table 6.4: Distribution of Households by Gender Participation in Farm Activities Farming Activities Kaduna Osun National Land Preparation mainly men 88.0 95.2 91.6 mainly women 0.5 1.3 0.9 equal participation 11.5 3.5 7.5 Planting mainly men 29.0 58.0 43.5 mainly women 35.5 5.2 20.4 equal participation 35.5 36.8 36.2 Weeding mainly men 54.5 72.3 63.4 mainly women 1.0 3.9 2.4 equal participation 44.5 23.8 34.2 Fertilizing mainly men 47.5 23.2 35.4 mainly women 4.0 9.4 6.7 equal participation 48.5 67.4 57.9 Watching of crops mainly men 78.0 35.8 56.9 mainly women 9.5 21.4 15.4 equal participation 12.5 42.8 27.7 Harvesting mainly men 46.0 15.0 30.5 mainly women 1.5 14.6 7.8 equal participation 52.5 70.4 61.4 Transporting mainly men 49.5 14.3 31.9 mainly women 13.5 39.0 26.3 equal participation 37.0 46.8 41.9 Tending livestock mainly men 57.8 7.7 32.8 mainly women 18.5 33.8 26.1 equal participation 23.7 58.5 41.1 Source: Afrint II field Survey, 2007

6.3. Livestock and Fisheries Resources

One of the major ways by which farming households in Nigeria augment their protein intake is the rearing of chicken and small ruminants such as sheep and goats for the primary purpose of home consumption though, these animals can also be offered for sale in times of serious financial needs by the households. Homestead fisheries and fish farming is not common among the smallholder farmers in Nigeria. However, some farmers may have unrestricted access to fisheries resources such as small rivers, lake or ponds within their communities. Investigation by this study revealed that an average farming household in Nigeria has at least 7 sheep or goats, 23 pigs, two cows or oxen and 14 poultry birds. Regular sale of livestock produce is not very common as only 4 per cent of the households reported having regular sale in 2007. However, close to half of the households reported regular sale of animals such as sheep and goats. Sale of livestock for draught or transport is particularly common in the north but the proportion of households that sold this category of animal in 2007 was less than 10 per cent. Similarly, stall feeding of cattle is mainly practiced in the north as

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indicated by 22 per cent of the households in Kaduna state against only 2 per cent recorded in Osun state in the south. For those who owned cattle in 2007, two main methods of feeding them were identified by this study. In the north, the commonest method is stall feeding as indicated by 70 per cent of the households in Kaduna state, while in the south it is by allowing animals to graze on communal open grazing land as reported by more than 90 per cent of the households. Thus, cultivation of fodder crops is more prominent in the north probably for the purpose of stall feeding their animals. Since stall feeding is usually practised in the north, only households in Kaduna state reported practising stall feeding of animals when their households were formed. Thus, the main method of keeping cattle when household was formed by the newly sampled households is stall feeding as indicated by 61 per cent of the households in Kaduna state. Virtually, all the newly sampled households did not own any graded or cross-bred milk cow when their households were formed. Similarly only insignificant proportion (1.7%) of the households reported they own fish pond in 2007 and these households are mainly from the south (Osun state). Aside, access of households to fish water or household fishing in the water was highly limited. The few ones that had access or did actually fish from the water did so mainly for home consumption, though 50 per cent of the households in this category in Osun state also did that for commercial purposes as shown in Table 6.5.

Table 6.5: Distribution of Households by Ownership of Livestock and Fisheries Resources Livestock and Fisheries Resources Information Kaduna Osun National Average number of livestock own cow 3.0 0.0 3.0* oxen 3.0 0.0 3.0* goat/sheep 5.0 8.0 7.0 camels/donkey 0.0 0.0 0.0 pigs 5.0 40.0 23.0 poultry 13.0 15.0 14.0 Regular sale of livestock produce 6.5 2.3 4.4 Regular sale of animals 44.7 49.2 46.9 Sale of livestock for draught or transport 7.5 0.5 4.0 Stall-feeding of cattle 21.7 1.9 11.8 Keeping of cattle stall feeding (zero grazing, tethered) 70.7 0.0 70.7 private own grazing land 15.5 6.7 11.1 communal (open) grazing land 13.8 93.3 53.6 Cultivation of fodder crops 11.5 1.1 6.3 Stall-feeding of cattle when household was formed 16.2 0.0 16.2* Method of keeping cattle when household was formed stall feeding (zero grazing, tethered) 61.0 NA 61.0* private own grazing land 14.6 NA 14.6* communal (open) grazing land 24.4 NA 24.4* Average number of graded or cross-bred milk cow owned 2.0 0.0 2.0* Owned graded or cross-bred milk cow when household 1.1 0.0 1.1 was formed Owned fish pond 0.0 1.7 1.7* Access to fish water or fishing in the water 0.5 0.9 0.7 Purpose of fishing household uses/own consumption 100.0 50.0 75.0 commercial purposes 0.0 50.0 50.0* other purposes 0.0 0.0 0.0 Source: Afrint II field Survey, 2007 * only reported in one state

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6.4. Household Ownership of other Consumer Durable Assets

The ownership of consumer durable assets by farming households is not only an enhancement of the socio-economic status of the households but could also boost farm level productivity and reduce rural–urban drift. Where social infrastructure is provided in the rural areas, its multiplier effects are usually high with the impacts much felt in the agricultural sector. Investigation of the households’ ownership, access and use of consumer durable assets in 2007 is presented in Table 6.6. Ownership of these assets varies significantly between the two states and across various assets reflecting the levels of rural social infrastructural provision in the two states. It should be noted, however, that Osun state is still a relatively young state as it was created out of the old Oyo state in 1992 compared to Kaduna state which has been in existence since 1976. Thus, ownership of wired electricity/power electronics was higher among farming households in Kaduna state compared with Osun state with an average of 51 per cent for the two states. Since mobile phone is a recent phenomenon in Nigeria, ownership of this asset was almost equal by households in both states averaging 46 per cent but those who did not own this asset at least had access to one as indicated by 54 per cent of the households. Ownership of diesel power generator and access to pipe borne water by farming households in Nigeria is still very limited as indicated by 14 and 12 per cent of the households respectively. However, ownership of television set, radio and tape recorder was widely reported among the households in 2007 as indicated by 54, 93 and 75 per cent of the households respectively. About 62 per cent of the households also reported ownership of bicycle in 2007 but this is particularly higher for Kaduna state probably due to longer distance of farms to homestead and poor conditions of farm roads. This asset has also been recognized by at least 54 per cent of the households as the most advanced means of own transport. Sewing machine is one of the assets that could generate income for households but less than one-third of the households in the two states reported ownership of the asset. Ownership of kerosene stove was widely reported by households in both states with an average of 70 per cent of the households claiming ownership of the asset in 2007. This improvement is very significant as it will reduce pressure on the forest land for firewood. However, sustainability becomes another important issue in the face of the current economy downturn which may limit the capacity of these households to acquire the fuel required to power their stove and may thereby revert to the use of firewood and coal. Where electricity is not available and the farming households cannot bear the cost of diesel or petrol-powered generator, the least cost available option is battery torch which ownership was reported by about 93 per cent of the households.

In terms of the type of dwelling units, most farming households in Nigeria reside in mud houses with corrugated iron roof as reported by 72 per cent of the respondents. Given the above scenarios, the ranking of the households wealth relative to other households in the village showed that about 41 per cent of these households were below average wealth while 6 per cent of them were actually ranked very poor. About 14 and 2 per cent of the households were ranked to be above average wealth and very wealthy respectively. The proportion of households in the average wealth

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category is just 37 per cent. The proportion of household ranked below average wealth and very poor is a pointer to the prevalence of poverty among the farming households in the country.

Table 6.6: Distribution of Households by Ownership of Consumer Durable Assets Consumer Durable Assets Kaduna Osun National Ownership of the following consumer durable assets wired electricity/power 68.5 32.5 50.5 mobile or stationary telephone 44.5 47.9 46.2 diesel power generator or similar 21.5 7.7 14.6 water pipe to house 8.0 17.1 12.6 TV-set 61.5 46.8 54.2 radio 95.0 90.2 92.6 tape recorder 88.5 61.5 75.0 bicycle 80.5 43.8 62.2 sewing machine 35.7 15.0 25.3 kerosene stove or other modern stove 66.0 74.7 70.4 battery torch 92.5 92.6 92.5 Access to mobile or stationary telephone where one is not owned 61.6 45.5 53.6 Most advanced means of own transport foot 7.5 24.7 16.1 bicycle 19.5 10.8 15.2 donkey/horse 0.0 0.4 0.2 motor bike 59.0 47.2 53.1 car, tractor, truck 14.0 16.9 15.4 Type of dwelling unit mud house with thatched roof 6.6 5.6 6.1 mud house with corrugated iron roof 78.8 64.5 71.7 block/brick house with corrugated iron roof or other modern roof 14.6 29.9 22.3 Ranking of household wealth relative to other households in the village very poor 2.5 9.6 6.1 below average wealth 34.5 47.4 40.9 average wealth 36.5 37.7 37.1 above average 23.5 4.8 14.2 very wealthy 3.5 0.4 1.9 Source: Afrint II field Survey, 2007

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CHAPTER SEVEN

STATE AND INSTITUTIONAL CONDITIONS

The roles of state institutions such as extension, credit and land development institutions are very germane in agricultural development of any country. Where these institutions are weak or none existence, it has negative implication for technology diffusion, input use, agricultural production expansion and productivity. The effectiveness of these institutions is assessed in this study from the households perspectives in terms of ability of the households to secure the services of these institutions and the results of the analyses are presented in Table 7.1 and 7.2.

From the tables, it is obvious that extension delivery in Nigeria has not been very effective as only 22 per cent of the households regularly received government extension services in 2007. About half of the households rarely received extension services while close to one-third of the households never received extension services during the year. Similar trend was observed for the non-governmental extension services. However, it was observed that extension services in the country is 100 per cent subsidized as only 7 per cent of the households claimed ever paying for any form of services received either from government or non-governmental extension agents. Meanwhile, the capacity for social capital formation among the farming households in Nigeria is very weak as less than half of the households sampled belonged to members of any local farmer group or association. Also, formal credit institutions are either lacking or accessing loan from the existing ones has been very difficult. As a matter of fact, less than 20 per cent of the households were able to obtain agricultural credit in 2007.

7.1 Extension Credit Services

Table 7.1: Distribution of Households by the Use of Extension and Credit Facilities Extension and Credit Facilities Kaduna Osun National Government extension services during the last year never 33.0 22.3 27.7 rarely 46.0 55.4 50.4 regularly 21.0 22.3 21.7 Non-governmental extension services during the last year never 61.8 57.3 59.5 rarely 30.2 30.8 30.5 regularly 8.0 12.0 10.0 Payment for extension services (government or non-govt) 8.0 5.6 6.8 Membership of any local farmer group or association 33.5 54.3 43.9 Obtain any form of agricultural input credit 16.1 17.5 16.8 Source: Afrint II field Survey, 2007

7.2 Land Use and Land Tenure System

Land is the most critical input into agricultural production but what appeared to even be more critical is the control that individual farming households exert over their land. This depends on the land tenure system operating in the communities or villages and land tenure system varies across the country. The land tenure system, to a large extent, determines how land can be acquired in a community and the use to which such land can be put. The control a farmer has over his land usually determines the

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kind of crops which the farmer can cultivate. Thus where a farmer has absolute control over his land, such land can be put into cultivation of cash crops with a longer maturity period but with higher return per hectare. Investigation of land use and land tenure system among the sampled households in 2007 pointed to the fact that the frontier for arable land in the country is approaching near exhaustion as shown in Table 7.2. For the newly formed households, the major means of obtaining land when households were formed was through inheritance of land already under cultivation, as reported by 50 and 30 per cent of households in Kaduna and Osun state respectively. Only one-fifth of the households were allocated virgin land when households were formed. Meanwhile, most of the land being cultivated by households was individually owned by the farming households, as indicated by about 86 per cent of the respondents. But a rather interesting find is that most of these households (88%) claimed they had full control over their land, while only 12 per cent required permission. Ownership of formal title or land registration was not a common practice among farming households in Nigeria as less than one-third of the households registered their land. The major means of expanding farm size in the village now is by clearing virgin land as indicated by about half of the households and for the new generation (children), the major means by which they could obtain land is by inheriting land already under cultivation.

Table 7.2: Distribution of Households by Land Tenure System and Land Use Land Tenure Arrangement and Land Use Kaduna Osun National How land was obtained when household was formed allocated virgin land 12.3 27.9 20.1 allocated family land under fallow 17.9 25.0 21.5 inherited land already under cultivation 50.0 29.8 39.9 purchased land 10.4 3.8 7.1 borrow/rented land 9.4 13.5 11.5 Status of most land now being cultivated individually owned by farm household 86.8 84.6 85.7 use right allocated by communal/clan/government 0.5 3.4 1.9 rented/borrowed from other individuals/families 12.7 12.0 12.4 Control over all the land now cultivate full control 89.9 85.9 87.9 need permission 10.1 14.1 12.1 Ownership of formal title or registration of land 29.4 27.2 28.3 Alternative ways of expanding farm size in the village clearing virgin land 22.5 79.4 50.9 turning grazing land into cultivation 9.5 6.0 7.8 bringing fallow land into permanent cultivation 16.1 62.0 39.5 renting/borrowing land 52.5 18.8 35.6 buying land 63.0 16.7 39.9 Means of obtaining land by children in the village in future they will be allocated land virgin land 11.0 33.2 22.1 they will be allocated family land under fallow 11.0 28.4 19.7 they will inherited land already under cultivation 61.5 28.4 44.9 they will rent/borrow land 12.5 5.6 9.1 they will purchased land 4.0 4.3 4.1 Source: Afrint II field Survey, 2007

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CHAPTER EIGHT

HOUSEHOLD INCOME AND EXPENDITURE PATTERN

8.1 Sources of income

Apart from farm income, farming households also derived income from other non- farm sources such as leasing of machinery or equipment, working as agricultural or farm labour, micro-business, rent, pension and remittances from absent household members. This study, however, revealed that the two major sources of income for farming households in Nigeria are the sale of staple food and the sale of non-food cash crops. These two sources constituted farm income sources with highest cash for the households as shown in Table 8.1. The relative importance of each source, however, differs between the two states. While, the sale of staple food constituted the major source with highest income in the north, the sale of non-food cash crops constituted the major source with highest contribution in the south as reported by 61 and 43 per cent of the households respectively.

8.2 Farm production expenditure patterns of farm households

In order to completely capture intra-household dynamics with respect to household economic and farm decision, this study also examined the expenditure patterns of the farming households in Nigeria and the results are presented in Tables 8.2 and 8.3. Table 8.2 presented the household expenditure patterns on farm input and other farm operations or activities during the year while Table 8.3 showed the household expenditure outlay on food and other households’ needs. The expenditure patterns varied considerably between the two states. Thus, while 42 per cent of the households in the Kaduna state did not incur any cash outlay on seed in 2007, virtually all the households in Osun state claimed they had low or moderate cash outlay on seed. In other words cash outlay on seed by farming households in Nigeria has been very negligible as most farmers usually rely on previous year stock set aside for planting. Expenditure outlay on chemical fertilizer was very significant in the north but households in the south had very low or small expenditure outlay on chemical fertilizer. This, again, is a reflection of the soil fertility level and the type of crops mainly planted in the two regions. Thus, in the north with very low soil fertility and where very high fertilizer demanding crops (mainly cereals) are planted, the cash outlay on fertilizer was very significant compared with the south where the soil fertility is relatively higher and root and tuber crops which are less fertilizer demanding are planted. Cash outlay on pesticides was also very significant in the north compared with the south. The result of cash expenditure on hired labour was diffused in both states but in terms of land rent, majority of the households claimed they did not incur any cash outlay on land rent in 2007. Similarly, majority of the households did not incur any cash outlay on hiring of equipment for land preparation during the year. The result of cash outlay on transport in both states was equally diffused while majority of the households did not incur cash outlay on irrigation during the year.

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8.3 Food-related expenditure of households

The type of food bought by households in 2007 followed the traditional food consumption patterns in the country. Thus, food which feature prominently in the consumption pattern of the households but is not produced in sufficient quantities by the households attracted significant attention of households while those which the households produced in sufficient quantities were not purchased in significant proportion by households. Therefore, in Kaduna state where cereals feature prominently in the consumption pattern and produced in sufficient quantities, the proportion of households that purchased them was very small. But food such as cassava, beans, banana, Irish and sweet potatoes, vegetables and groundnut which are not usually produced in sufficient quantities were purchased by more than 50 per cent of the households. Similarly, in the south where roots and tubers form the bulk of the food delicacy and are produced in sufficient quantities by the households, the proportion of households that purchased this category of food in 2007 was less than 50 per cent. Meanwhile, one recent development has been the increasing proportion of households that purchased banana and plantain during the year. This was indicated by more than 70 per cent of the households in both states who claimed purchasing the crops.

Though some of the farming households own livestock, the proportion of households that purchased animal produce in 2007 was very significant averaging 80 per cent for different categories of animal produce such as meat, milk, fish and eggs. Apparently reflecting the level of poverty among the farming households in Nigeria, the proportion of households that borrowed money to cover households expenditure in 2007 was more than 50 per cent. Yet, the proportion of households that cultivated the habit of saving money every year for future needs was very significant with an average of 73 per cent. As a way of coping with food scarcity particularly during lean seasons, a significant proportion of households in the south (Osun state) usually skipped either breakfast or lunch. This practice is, however, not common among the farming households in the north.

Table 8.1: Distribution of Households by Sources of Income Sources of Income Kaduna Osun National Sale of staple food 53.5 31.8 42.7 Sale of other food crops 16.7 10.7 13.7 Sale of non-food cash crop 13.6 46.8 30.2 Sale of animal and animal produce 3.0 3.4 3.2 Leasing out machinery or equipment 3.0 1.7 2.3 Work on others’ farm/agricultural labour 1.0 4.7 2.9 Non-farm salaried employment 8.5 0.9 4.7 Micro-business 0.5 31.8 16.1 Large scale business 0.0 10.7 5.3 Rent/interest 0.0 46.8 23.4 Pension 0.0 3.4 1.7 Remittances from absent household members 0.0 1.7 0.9 Farm income Sources with Highest Cash for the Household Sale of staple food 61.0 42.7 51.9 Sale of other food crops 19.5 12.3 15.9 Sale of non-food cash crop 14.0 43.2 28.6 Sale of animal and animal produce 4.5 1.8 3.2 Leasing out machinery or equipment 1.0 42.3 13.6 Source: Afrint II field Survey, 2007

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Table 8.2: Distribution of Households by the Description of Household Expenditure Patterns Description of Household Expenditure Kaduna Osun National Seed no cash outlay 42.0 0.0 21.0 low/small cost 15.5 100.0 57.8 moderate cost 30.0 0.0 15.0 very significant cost 12.5 0.0 6.2 Chemical fertilizer no cash outlay 13.5 25.0 19.2 low/small cost 10.5 46.1 28.3 moderate cost 26.5 23.3 24.9 very significant cost 49.5 5.6 27.6 Pesticides no cash outlay 22.1 27.8 24.9 low/small cost 13.6 24.4 19.0 moderate cost 24.1 32.9 28.5 very significant cost 40.2 15.0 27.6 Hired labour no cash outlay 24.5 32.5 28.5 low/small cost 17.0 25.1 21.1 moderate cost 28.5 22.9 25.7 very significant cost 30.0 19.5 24.8 Land rented no cash outlay 53.5 13.4 33.5 low/small cost 7.0 11.6 9.3 moderate cost 18.0 41.8 29.9 very significant cost 21.5 33.2 27.4 Machinery/implements for land preparation no cash outlay 55.3 77.0 66.2 low/small cost 4.0 8.7 6.3 moderate cost 15.1 11.3 13.2 very significant cost 25.6 3.0 14.3 Transport no cash outlay 14.8 13.3 14.1 low/small cost 21.4 39.9 30.6 moderate cost 32.1 36.9 34.5 very significant cost 31.6 9.9 20.7 Land improvement/Irrigation no cash outlay 71.6 93.1 82.4 low/small cost 1.5 2.1 1.8 moderate cost 8.6 3.0 5.8 very significant cost 18.3 1.7 10.0 Source: Afrint II field Survey, 2007

Table 8.3.: Distribution of Households by Expenditure Outlays Expenditure Outlays Kaduna Osun National Type of food Purchase During Past Year maize 18.0 19.2 18.6 cassava 54.3 16.7 35.5 sorghum 27.5 15.8 21.7 rice 53.5 79.8 66.7 banana 77.5 76.2 76.9 beans 62.5 23.2 42.9 peas 29.5 10.8 20.2 Irish potatoes 56.5 10.8 33.7 sweet potatoes 58.5 22.9 40.7 millet 46.0 13.3 29.7 groundnut 50.8 59.1 54.9 vegetables 72.9 43.7 58.3

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Animal produce/food purchase during past year milk 83.0 87.7 85.4 meat 89.5 93.0 91.3 fish 92.0 96.1 94.1 egg 77.3 81.1 79.2 Borrowed money in the past years to cover expenditures 55.8 47.2 51.5 Able to save some money every year for future needs 65.5 79.7 72.6 Number of meals household generally eat during the lean season breakfast 87.5 0.0 43.8 lunch 68.0 4.3 36.2 dinner 98.0 100.0 99.0 Number of meal household generally eat during non-lean season breakfast 96.0 100.0 98.0 lunch 82.5 5.6 44.1 dinner 97.0 97.4 97.2 Source: Afrint II field Survey, 2007

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CHAPTER NINE

TECHNOLOGY, PRODUCTIVITY AND COMMERCIALIZATION

9.1 Analytical Framework

In order to properly address the many and varied research questions in this study, the use of linear production function and logistic regression (binary and multinomial) were adopted. Although the questions thrown up in the study varied, but yet in order to address trends in technology, productivity and commercialization at household level, the central explanatory variables remain those related to the farmer, markets and the state. This common trend running through the research provided the basis for using a single analytical framework for the econometric analysis of survey data, even as the application of linear production and logistic models became necessary.

The general empirical model is simply specified as:

TYC = f(F(1-n), M(1-n), S(1-n) ) 1

Where, TYC could be any of technology, yield or commercialization and F, M and S are vectors of farm and household characteristics, market and state factors capable of explaining them. The composition of these factors varies from one model to another but the same for all the crops.

Apart from being dependent variables, technology, yield and commercialization are related and, therefore, also explain each other. For example, users of new technologies are expected to have higher yield and market their excess products. In the various analyses, they have been used interchangeably both as dependent and explanatory variables bearing in mind that such specification may sometimes present econometric problems of endogeneity. We have in the interim concentrated on the gains which will accrue from using them in the manner to explain causalities.

Given this general analytical framework, subsequent sections deal with specific model. Nevertheless, since most of the variables are common to the different models and were derived from the same dataset, a brief description of them, which applies wherever they are used in this report, is given in section 10.2. In section 10.3, parameters are estimated for technology using a binary logistic regression. Section 10.4 contains the estimation of parameters for yield using linear production function and in section10.5, estimate of parameters were carried out using both linear regression and a multinomial logistic regression.

9.2. Description of Variables

As indicated earlier, the variables use in the various econometric regressions are grouped under three main sub-heads. These include the household and farm variables, the market variables and the state/institutional variables. The household and farm variables include age of household heads (farm managers), household size, education level of household head, the use of family and hired labour, the use of fertilizer, the use of improved variety of seeds, farm size, output and yield of crop, and membership of cooperative or social organization.

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The market variables on the other hand include whether farmer sold crop in 2007 and quantity of crop offer for sale, market outlet, change in market access, lowest and highest price received in 2007, effect of quality deterioration on price and previous year sale while the state or institutional variables include extension service delivery, use of available extra land in the community, contract farming and the use of credit. Detail description and measurement of variables is presented in Table10.1.

Table 9.1: Description and Measurement of Variables Farm households variables Age of household head (same person as farm manager in more than 99% of cases) in years Household size (no of household members who regularly sleep in the household) Education level of household head (measured in years of schooling) Use of hired labour (dummy variable; 1 for use and 0 otherwise) Family labour use (measured as number of household members who are working on the farm) Farm size (area cultivated to crop in 2007in hectare) Fertilizer use (amount spent on fertilizer per crop in dollars) Yield of crops ( output/area cultivated to crop) Member of cooperative organization (farmers belonging to any social organization or cooperative group) Use of improved variety (dummy variable; 1 for improved variety and 0 otherwise) Output of crop in 2007 (measured in kg)

Market variables Commercialization (quantity of crop offer for sale or intend to sell in 2007) Market access (dummy variable; 1 for improved market access and 0 otherwise) Market outlet (dummy variable; 1 for farm gate and 0 otherwise) Lowest price received for crop in 2007 ($/100kg) Highest price crop in 2007 ($/100kg) Effect of quality deterioration on price of crop (dummy variable; 1 for receiving lower price and 0 otherwise) Previous year sale (dummy variable; 1 for selling crop in previous season and 0 otherwise)

State Variables Extension services (dummy variable; 1 for receiving extension services and 0 otherwise) State dummy (1 for Kaduna state and 0 for Osun state) Use of extra land willing to put under cultivation of crop (hectare) Contract farming (dummy variable; 1 for growing crop in pre-arranged contract with traders and 0 otherwise Use of credit (dummy variable; 1 if farmers obtain any form of agricultural credit iput and 0 otherwise

9.3 Technology Adoption

Binary Logistics Regression

In order to capture some of the developments in agricultural technology adoption at the household level, questions requiring farmers to recall events in 2002 and compared them with the current situation were included in the micro-level diagnostic survey instrument. To remain realistic, the questions were mainly qualitative and as such, the analysis was done using binary logistic regression technique.

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The logit model is of the form:

* Yn = 1 {if I n  I n for all the n, n=1, 2, 3, .………… N observations}

or Yn = 0 {if I n < I *n } 2

Where:

Yn = use improved seed variety (1 for use and 0 for none use) in 2007

In = Di    j X jn 3

 j = unknown parameter for the covariates, j= 1, 2, 3, ....….., J

Xjn = the jth explanatory variable (for farm and household, market and state) for the nth observation, n=1, 2, 3, .….N;  i = unknown parameter for categorical variables D i = the ith categorical variable

The result of the binary logistic regression analysis for maize and cassava is presented in Table 10.2. Similar analysis for sorghum and rice produced spurious results due to collinearity or because the dependent variables did not vary. The results for maize and cassava are not too good as only yield of maize in 2007 and market access for cassava were only significant. Even then, the signs of these variables depart radically from a priori expectation. Meanwhile, the result indicated that increased yield of maize enhanced technology adoption while improved market access for cassava in 2007 compared with 2002 enhanced cassava technology adoption. Education, the use of fertilizer, contact with extension agent and membership of cooperative organizations which are expected to exert significant influence on technology adoption were not only insignificant but were also wrongly signed. This result was not surprising as only 29 and 18 per cent of the farmers planted improved and hybrid maize varieties respectively in 2007 (see Table 4.2.1) while 55 per cent of the households planted improved cassava variety in 2007 compared with what parents were using.

Table 9.2: Determinants of Technology Adoption Variables maize Cassava Coeff. sig. t Coeff. sig. t (std. err) (std. err) age of respondents -0.01 0.85 0.01 0.61 (0.04) (0.02) household size -0.18 0.10 0.06 0.25 (0.11) (0.05) farm size 0.07 0.82 -0.31 0.11 (0.32) (0. 19) education of -0.02 0.80 0.06 0.33 respondents (0.10) (0.06) family labour use 0.37 0.08 0.01 0.95 (0.21) (0.11) use of hired labour 1.31 0.18 1.06 0.15 (0.21) (0.75) fertilizer use 0.003 0.38 - -

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(0.004) yield 0.001 0.02 - - (0.004) commercialization - - - - state dummy - - -3.65 0.00 (0.83) market access 0.01 0.99 0.81 0.03 (0.64) (0.38) contract farming - - - - extension services 0.31 0.67 -0.40 0.35 (0.74 (0.43) member of coop 1.27 0.34 0.05 0.92 (1.34) (0.66) constant 3.89 0.20 2.38 0.21 (3.08) (1.9) pseudo R2 0.31 0.06 0.39 0.00 Log likelihood -21.26 -40.41 Dependent variable: Use of improved variety

9.4 Determinants of Productivity

Applying equation 1 as the basic empirical model, linear production functions were specified and analysed for maize, sorghum and rice with farm and household, market and state as the vectors of the explanatory variables. This analysis could not be carried out for cassava as the output for cassava was not determined for 2007. However, two models were estimated for each of the crop. The first model is the prototype model with all the explanatory variables while the second is the constrained model with only those variables retained after a stepwise backward regression procedure. In the prototype model for maize, four variables were found to be highly significant as shown in Table 9.3. These variables are farm size (area cultivated to maize in 2007), available family labour, the use of fertilizer (proxy by amount spent on fertilizer for maize in 2007), and commercialization (proxy by dummy for sale of maize in 2007). These variables were also found to be significant in the constrained model as shown in Table 10.4. The use of improve maize varieties which is one of the critical yield enhancing technologies was not significant as only 29 per cent of the households planted improved maize varieties in 2007 (Table 4.2.1). In the case of sorghum the only significant variable is area cultivated to sorghum in 2007 (farm size) an indication that yield increases was only obtained through land extensification as the two most critical yield enhancing technologies (fertilizer and the use of improved varieties were not significant).This result was nor surprising as none of the households planted improved sorghum varieties in 2007 while only 36 per cent of the households claimed that the use of fertilizer has improved when compared with 2002 (Table 4.2.3). As for rice, four variables (the use of improved varieties, growing of crops on pre-arranged contract, the use of extra land for rice cultivation and the state dummy were found to be significant. The most critical yield enhancing input for rice (fertilizer) was not significant because of low usage as only 25 per cent of the households claimed that the use of fertilizer has increased since 2007 (Table 4.2.4). An average of $73 per hectare was incurred on fertilizer use by rice growing households in 2007 which is less than half the amount required for procuring a 50kg bag of fertilizer in Nigeria at that time at the rate of N2, 500 per bag. ($1:120). However, all the regression equations show some reasonable level of fitness as

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indicated by the adjusted R-square of 0.52, 0.61 and 0.47 for maize sorghum and rice respectively.

Table 9.3: Determinants of Productivity Variables maize sorghum rice Coeff. sig. t Coeff. sig. t Coeff. sig. t (std. err) (std. err) (std. err) log of age of respondents -0.06 0.72 0.40 0.35 -0,22 0.55 (0.18) (0.42) (0.38) log of household size 0.01 0.87 0.24 0.31 0.01 0.93 (0.09) (0.23) (0.18) log of farm size 0.74 0.00 0.85 0.00 -0.14 0.32 (0.06) (0.13) (0.14) log of family labour 0.19 0.02 0.12 0.54 0.04 0.76 (0.80) (0.19) (0.16) log of use of fertilizer 0.39 0.00 0.08 0.46 0.01 0.93 (0.06) (0.12) (0.11) commercialization 0.56 0.00 - - - - (dummy) (0.18) use of improved variety 0.03 0.61 0.16 0.31 1.26 0.00 (dummy) (0.06) (0.15) (0.25) contract farming 0.17 0.57 0.80 0.20 1.74 0.00 (dummy) (0.30) (0.61) (0.51) extension services 0.11 0.13 0.05 0.71 0.12 0.43 (dummy) (0.07) (0.16) (0.15) membership of coop. 0.26 (dummy) -0.14 0.14 0.15 0.58 0.26 (0.27) (0.23) (0.09) use of credit 0.17 0.20 -0.06 0.83 0.02 0.92 (dummy) (0.13) (0.32) (0.24) use of hired labour 0.02 0.80 0.23 0.32 0.02 0.91 (dummy) (0.10) (0.23) (0.21) use of extra land -0.01 0.41 -0.01 0.75 -0.09 0.01 (dummy) (0.01) (0.03) (0.03) state dummy 0.19 0.17 - - 1.34 0.00 (0.14) (0.39) Constant 4.95 0.00 3.92 0.03 10.69 0.00 (0.77) (1.71) (1.67) R2 0.56 0.00 0.71 0.00 0.57 0.00 Adjusted R2 0.52 0.61 0.47

Dependent variable: log of crop yield

Table 9.4: Determinants of Productivity-Constrained Model Variables maize sorghum rice Coeff. sig. t Coeff. sig. t Coeff. sig. t (std. err) (std. err) (std. err) log of household size flog of arm size 0.72 0.00 0.56 0.00 (0.05) (0.08) log of family labour 0.14 0.01 (0.05) log of fertilizer use 0.44 0.01 (0.04) commercialization 0.43 0.00

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(dummy) 0.22) use of improved variety 1.23 0.00 (dummy) (0.19) contract farming 1.47 0.00 (dummy) (0.48) use of extra land 0.10 0.00 (dummy) (0.02) state dummy 1.46 0.00 (0.26) Constant 4.90 0.00 6.64 0.00 10.08 0.00 (0.22) (0.08) (0.41 R2 0.46 0.00 0.26 0.45 0.00 Adjusted R2 0.45 0.25 0.42

Dependent variable: crop yield

9.5 Determinants of Crop Commercialization

In the empirical models, commercialization has been defined in terms of the quantity of crops that was offer to sale in 2007. This, therefore, makes the use of linear regression approach very relevant in examining factors that determine the level of crop commercialization in 2007 and like the case of productivity analysis; the constrained model was also estimated. In examining factors that affects rate of commercialization (whether increased or decrease rate of commercialization), however, the use of multinomial logistic regression was found to be more appropriate. This is because, the design of the micro-level households’ survey instrument provided for case specific responses in respect of how has the amount of crop sold changed since 2002. Therefore, the multiple choices of less is sold, no significant change in quantity sold and more is sold provided the multiple responses for the dependent variable (change in quantity of crop sold) and a very convenience comparison (no significant change) as the base category. The result of the prototype and the constrained models for the determinants of commercialization are presented in Tables 10.5 and 10.6. These models were estimated for all the crops covered in this study (maize, cassava, sorghum and rice). The result of the determinants of maize commercialization as presented in Table 9.5 shows that the average lowest price received in 2007 (N27/kg) exert significant and negative influence on the level of maize commercialization during the year. This may be due to the fact that most farmers market their output fresh at harvest thereby causing glut in market and often result in lower prices. Similarly, the receipt of lower prices due to deterioration in maize quality also affects maize commercialization significantly during the year (though the level of significant is very high 7%). From Table 4.1, about 37 per cent of the households reported to have received lower price for some or most of their produce due to deterioration in quality. This further underscores the important of post harvest handling the value chain addition for our agricultural produce in Nigeria. Expectedly, however, increased farm size and output exert positive and significant impact on maize commercialization. The coefficient of the state dummy was also significant and negative showing that maize commercialization was more prominent among households in Osun state than in Kaduna state. The distribution of households by marketing conditions for maize as reported in Table 4.1 shows that 81 per cent of the households in Osun state were found to be selling maize in 2007 as compared to 78 per cent in Kaduna state. However, the average quantity of maize sold during the year was slightly higher (1900kg/household) for Kaduna when compared with

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(1300kg/household) for Osun state. In the result of the constrained model presented in Table 9.6, the effect of lower price due to quality deterioration became insignificant in the long run. This could be due to the fact that a significant proportion of maize marketed are sold fresh and the fact that there are now modern farm-level storage techniques (storage can) being promoted by the ADPs across the country. In the case of cassava, only output was found to exert positive and significant impact on the level of commercialization in 2007. The growing of cassava on pre-arranged contract and the state dummy were only significant at 7 per cent.

Table 9.5: Determinants of Commercialization Variables maize cassava sorghum rice Coeff. sig. t Coeff. sig. t Coeff. sig. t Coeff. sig. t (std. err) (std. err) (std. err) (std. err) log of lowest -0.42 0.00 -0.13 0.69 -0.87 0.10 -0.32 0.52 price (0.12) (0.33) (0.52) (0.51) log of highest 0.19 0.20 0.31 0.36 0.56 0.22 0.25 0.52 price (0.14) (0.34) (0.45) (0.40) deterioration -0.16 0.07 -0.26 0.23 -0.10 0.63 - - (dummy) (0.08) (0.22) (0.27) market outlet 0.02 0.89 -0.20 0.11 - - 0.98 0.25 (dummy) (0.15) (0.12 (0.81) contract farming 0.25 0.43 1.41 0.07 0.19 0.77 -0.45 0.33 (dummy) (0.32) (0.78) (0.67) (0.46) previous year sale -0.22 0.16 - - -0.06 0.89 -0.11 0.83 (dummy) (0.15) (0.46) (0.54) log of output in 0.92 0.00 0.67 0.00 0.88 0.00 0.89 0.00 recent year (06) (0.12) (0.23) (0.10 use of variety 0.001 0.98 0.55 0.12 -0.92 0.00 -0.37 0.13 (dummy) (0.05) (0.36) (0.22) (0.24) sex of respondent -0.07 0.62 -0.12 0.68 -0.04 0.95 0.04 0.93 (dummy) (0.15) (0.29) (0.93) (0.50) education of 0.01 0.19 0.02 0.28 -0.03 0.31 0.04 0.02 respondent (years) (0.01) (0.02) (0.03) (0.02) log of farm size 0.13 0.03 - - 0.04 0.84 0.0003 0.99 (0.06) (0.22) (0.17) state dummy -0.55 0.00 -0.77 0.07 - - -0.40 0.12 (0.12) (0.42) (0.26) const. -1.82 0.01 3.22 0.01 0.06 0.97 1.59 0.21 (0.71) (1.24) (2.12) (1.2) R2 0.60 0.00 0.78 0.00 0.59 0.00 0.74 0.00 Adj. R2 0.58 0.74 0.49 0.67 Dependent variable: log of output sold in 2007

While the growing of cassava on pre-arranged contract was found to impact positively on the level of commercialization, the negative sign of the state dummy indicated that there was significant difference on the level commercialization between the two states with Osun state having the highest level of cassava commercialization. Both the proportion of households that offer cassava for sale in 2007 and the average quantity sold per household were higher for Osun state than Kaduna state (Table 4.1). In the constrained model, only output and the state dummy were found to be significant. The non-significant of the dummy representing the growing of cassava on pre-arranged contract may be due to the relatively low proportion of households (5.9%) who engaged in this practice in 2007. In the case of sorghum, output and the planting of improved varieties were found to significantly affect commercialization. While increased output was found to exert positive influence on commercialization, the type

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of varieties of sorghum planted was found to exert negative influence. This may be due to the fact that majority of the sorghum growing households (87%) planted the traditional variety in 2007 (Table 4.2.3). In the constrained model, these two variables were also found to be highly significant. Output and educational level of the head of households were two major determinants of rice commercialization in 2007. In the constrained model, however, only output was found to be significant. The dropping of the educational level of household heads/farm managers could be due to the fact that about 60 per cent of the household heads had only six years or less of schooling meaning that most of them did not proceed beyond primary school. Surprisingly, two variables expected to have exerted significant impact on the level of crop commercialization (i.e. highest price received during the year and previous year sale) were not significant in any of the equations. This underscores the structural imperfection and underdevelopment of our market system which make it difficult for farmers to speculate and predict the market so as to be able to keep their produce over a period that will allow them to benefit from the increased price movement during the year. Thus, the increased marketing margin mainly accrued to the middlemen.

Table 9.6: Determinants of Commercialization –Constrained Model Variables maize cassava sorghum rice Coeff. sig. t Coeff. sig. t Coeff. sig. t Coeff. sig. t (std. err) (std. err) (std. err) (std. err) lowest price 0.42 0.00 (0.09) deterioration 0.11 0.16 (0.08) contract 0.41 0.37 farming (0.45) previous year sale output in 0.93 0.00 0.95 0.00 0.79 0.00 0.86 0.00 recent year (0.05) (0.08) (0.14) (0.06) use of -0.68 0.00 variety (0.16) education of 0.02 0.09 respondent (0.01) farm size 0.17 0.00 (0.05) state -0.54 0.00 -0.98 0.00 dummy (0.09) (0.23) const. -1.45 0.00 0.47 0.44 (0.45) (0.61) R2 0.61 0.00 0.58 0.49 0.00 0.62 0.00 Adj. R2 0.60 0.57 0.48 0.61 Dependent variable: log of output sold in 2007

9.6. Factors Affecting Rate of Commercialization

Multinomial logit

In statistics, economics and genetics a multinomial logit model is a regression model which generalizes logistics regression by allowing more than two discrete outcomes. Multinomial logit regression is used when the dependent variable in question is nominal (a set of categories which cannot be ordered in any meaningful way) and consists of more than two categories. For example, multinomial logit regression

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would be appropriate when trying to determine what factors predict the variation in amount of crop sold-rate of commercialization (less, unchanged and more sales).

Multinomial logit regression is appropriate in cases where the response is not ordinal in nature as in ordered logit. Ordered logit regression is used in cases where the dependent variable in question consists of a set number (more than two) of categories which can be ordered in a meaningful way (for example, highest degree, social class) while multinomial logit is used when there is no apparent order. The multinomial logit model assumes that data are case specific; that is, each independent variable has a single value for each case. The multinomial logit model also assumes that the dependent variable cannot be perfectly predicted from the independent variables for any case. As with other types of regression, collinearity is assumed to be relatively low, as it becomes difficult to differentiate between the impacts of several variables if they are highly correlated. The independence of irrelevant alternatives must either be included in the error structure, or assumed to exist. This assumption states that the odds do not depend on other alternatives that are not relevant.

Model Specification and Estimation Procedure

When using multinomial logistic regression, one category of the dependent variable is chosen as the comparison category (in this case quantity of crop sold unchanged was chosen) while the estimation is carried out for less or more quantity of crop sold as indication of decreased or increased commercialization respectively.

The Model

4

and

5

Where for the ith individual, yi is the observed outcome (rate of commercialization) and Xi is a vector of explanatory variables. The unknown parameters β j was typically estimated by maximum likelihood using STATA package.

The explanatory variables used in this study included:

1. Dummy for the sale of crop in 2007 (1 if crop is sold and 0 other wise)

2. Total amount of crop sold (kg)

3. Dummy for the effect of quality deterioration on price (1 if received lower price and 0 otherwise)

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4. Dummy for the growing of crop on pre-arrange contract (1 if crop is grown on pre- arranged contract and 0 otherwise)

5. Dummy for the comparison between current price and 2002 (1 if price is better than 2002 and 0 otherwise)

6. Dummy for change in market access compared to 2002 (1 for access is better now and 0 otherwise)

7. Output of crop in 2007 (kg)

8. Dummy for comparison of current yield with 2002 (1 if yield has increased and 0 otherwise)

9. Dummy for membership of cooperative organization (1if belong to any organization and 0 otherwise)

10. Dummy for change in area cultivated to crop compared to 2002 (1 if area increased since then and 0 otherwise)

11. Dummy for state (1 if state if Kaduna and 0 for Osun)

For the maximum likelihood estimation, a convenient form for the density that generalizes the method used for binary outcome models was used. The density for ith individual is written as: m yil yim yij f (yi)  Pil ...Pim   Pij 6 j1

Where yi1...yim are m indicator variables with yij =1 if yi  j and yij =0 otherwise.

For each individual, exactly one of y1, , y2 ,...ym will be nonzero. For example, if

yi  3 , then yi3  1, the other yij =0, and upon simplification, f( yi  pi3 , as expected. The likelihood function for a sample of N independent observations is the N m product of the N densities, so L = P yij . The maximum likelihood estimator i11 j ij  (MLE),  , maximizes the log-likelihood function:

 N m InL ( ) = yij InFj (X i ,) 7 i11j

 and as usual  ~N( , [ - E{ 2 InL( ) /  }]1 ) . 8

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9.6.1. Factors Affecting Rate of Commercialization of Maize

The multinomial logit model was fitted into the data for all the four crops covered in these studies. However, only the data for maize presented some reasonable results. The results for cassava and rice were very spurious as none of the explanatory variables either significantly enhanced or reduced the rate of commercialization. Also the result for rice was not good enough as most of the explanatory variables dropped due to collinearity (i.e. no significant variation in responses) and therefore, the result was also spurious. Nevertheless, the result for maize provided an insight into which of these variables could best predict whatever changes observed in the amount of crop sold between 2002 and 2007. Thus, only the multinomial logistic regression for maize is presented in this section as shown in Table 9.6. The regression result shows some reasonable level of fitness with a pseudo R-square of 0.42 and a log likelihood ratio of -51.15 which was also highly significant. The result presented in Table 10.7 shows that if no significant change in amount of maize sold is chosen as the natural base category, it is possible to examine factors that could have either enhanced or abated changes in the amount of maize sold since 2002 (rate of commercialization) as compared with the base category. Thus, the two most critical factors that has contributed to reduced commercialization since 2002 is the reduction in output of maize which is significant at 5 per cent and by implication the declining yield which is also significant at 10 per cent. These two variables carried negative signs indicating that further decline will continue to reduce the rate of maize commercialization. This result slightly differs from the descriptive analysis where about 59 per cent of the households claimed that maize yield has increased when compared to 2002 (Table 4.1.1). Even though average output of maize was slightly higher in 2007 compared with the preceding year (2003), it declined significantly when compared with the output in two seasons before.

As regards factors that have enhanced the rate of commercialization of maize, two factors were found to have contributed significantly. The first one is willingness or intention to sell maize. This factor can also be refers to as the objective of production which could either be attainment of household food security or commercialization Where the objective of production is mainly to ensure household food security, the tendency is that the rate of commercialization will be very low as less of the output will be offer for sale and vice versa. The second factor as shown in Table 9.7 is price. This factor has always been regarded as the main driver of commercialization as shown by its positive contribution to commercialization rate. Farmers react rationally and positively to price increase by increasing their output (output supply response) and negatively by cutting down on output whenever price falls. From Table 4.1, about 70 per cent of the household claimed they now market more maize compared with 2002 while 75 per cent adduced this to the fact that the price received has increased when compared with 2002. This greatly underscores the need for a sustainable price policy that can guarantee remunerative prices for farmers in the country.

Factors which are expected to drive commercialization but which were found not to be significant in the model include improvement in market access, growing of crop on pre-arranged contract with traders and membership of farmer group or organization. Even though 70 per cent of the households reported that market access is better compared to 2002 (Table 4.1), they were not able to benefit from the improved market access due to the declining yield level occasion by low use of improved maize

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varieties which invariably reduced the quantity of maize available for sale. Where crops are grown on pre-arranged contract with the traders or buyers, it reduces the risk faced by farmers due to price volatility and by implication, enhances commercialization. Meanwhile, in this case, only 2 per cent of the farmers engaged in the practice of contract farming as indicated in Table 4.1. Also, membership of farmer group or organization is expected to enhance crop marketing as such organization should provide platform for market linkages and information dissemination. However, the result of the descriptive analysis presented in Table 10.8 shows that only 45 per cent of the maize farmers belong to farmers group or organization while 40 per cent of those who are members of farmers group actually sold maize or had the intension of selling maize in 2007. It is obvious that the farmers group or organizations have not really been effective as a veritable organ for promotion of crop commercialization in the country.

Table 9.7: Multinomial Logistic Regression for Rate of Maize Commercialization Less maize is sold now More maize is sold now variable coeff. std. error sig. t coeff. std. error sig. t sold maize in 2007 0.47 1.40 0.73 20.93 1.41 0.00 total amount of maize sold 0.001 0.001 0.19 -0.001 0.001 0.51 effect of quality deterioration -0.73 1.17 0.53 0.62 0.89 0.18 growing maize on contract -1.50 5.72 1.00 31.42 4.07e+07 1.00 price compared to 2002 1.78 1.14 0.12 3.85 1.07 0.00 change in market access 1.38 1.18 0.24 0.39 0.98 0.68 output of maize in 2007 -0.001 0.001 0.04 -0.0001 0.002 Total yield compared to 2002 -1.18 1.02 0.06 -0.67 0.92 membership of cooperative -0.05 0.95 0.58 0.98 0.81 0.22 area compared to 2002 1.09 1.01 0.37 1.17 0.90 0.19 state dummy 1.09 1.51 0.47 -0.61 1.15 0.54 Constant 0.49 1.39 0.72 21.86 - - Pseudo R2 = 0.47; Log likelihood = -51.154036; LR chi2(22)= 90.47; Prob > chi2 = 0.00 Base category (no significant change in amount of crop sold) Dependent variable: how has the amount of crop sold changed since 2002?

Table 9.8: Percentage Distribution of Maize farmers by Member of Farmer Group or Organization sold maize or intended members o farmers group or organization Total to sell No Yes Yes 40.6 39.7 80.3 No 14.2 5.5 9.7 Total 54.8 45.2 100.0

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CHAPTER TEN

CONCLUSION

Using an explorative descriptive analysis, this study evaluated the micro-level impact of recent developments in Nigerian agriculture (crop sub-sector) in the wave of various reforms and development that took place in the sector between 2002 and 2007. In addition to characterizing household demographic and socio-economic status, the study succinctly examined the dynamics and drivers of household crop production technology and farm management practices between 2002 and 2007. Aside, the study also investigated crop commercialization and marketing conditions in the country during this period while efforts were made to also examine the drivers of agricultural technology adoption and diffusion in the country. Other issues investigated by the study include the role of state and other agricultural support institutions, household’s wealth creation and household’s income and expenditure pattern in 2007.

The findings of the study are quite revealing but with mixed results. While some appreciable progress has been made in terms of the increasing proportion of households now growing crops that were not hitherto cultivated, a significant proportion of the households has also abandon some crops mainly for economic reason of non-profitability. In terms of crop production conditions, only one cropping season is still prevalent among the farming households as staple food crops production in the country is mainly rainfed with little or no irrigation practices depending on farmers’ location across the country. Area cultivated to various crops still very small averaging 2 ha but more worrisome is the fact that area cultivated to different crops declined significantly in 2007 compared with 2002 and even among the newly sampled households when compared with when household was formed. Aside, output for crop like rice also declined when compared with the situation in 2002. Though utilization of output pointed towards increased commercialization, the proportion of output sold was less than 50 per cent for all crops except for cassava.

Probably in a bid to combat transitory food insecurity, the proportion of households growing other food crops and vegetables have risen significantly compared with 2002 and among these category of crops, banana/plantain and fruits and vegetables for local market are very prominent. Meanwhile, cultivation of non-food cash crops recorded a decline in 2007 except for cocoa probably due to existence of old plantation.

The used of improved inputs and modern technologies by newly sampled households in most recent season did not shown a significant improvement compared to when household was formed. About 43 per cent of the households were still using traditional maize variety, 47 per cent still planting old cassava varieties, and 87 per cent still using traditional sorghum variety while about 60 per cent are still planting traditional rice varieties. In spite of the presidential initiative on rice designed to push the adoption of NERICA in Nigeria, less than 30 per cent of the households planted NERICA or its descendants in 2007. Fertilizer use had either stagnated or declined and the situation of fertilizer use in 2007 in Nigeria appeared worse when compared with 2002 as only 25 per cent of the rice and 44 per cent of maize growing households indicated increased use. Similarly, the method of land preparation had not shown any significant improvement compared to 2002 as farmers still relied on hoe cultivation

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with very little use of oxen ploughing and tractor. Application of pesticides in 2007, however, showed significant improvement particularly among rice and sorghum growing households when compared with 2002.

Apparently to cope with decreasing availability of arable land farmers now engaged in the practice of crop rotation which can be described as a recent phenomenon and is fast replacing the traditional bush fallowing system widely practice in the country. Except for sorghum growing households, the proportion of households that engaged in bush fallowing in 2007 was less than 50 per cent. Despite the advantage of intercropping with nitrogen fixing crops, this management practice did not record wide practice among Nigerian farmers in 2007. Other management practices that were engaged by significant proportion of the households in 2007 include, minimum tillage, breaking the hard pan, green manure, and soil and water conservation. However, the practice of animal manure application and the use of pesticides and herbicides witnessed significant improvement in 2007.

Maize, cassava and rice witnessed increased commercialization in 2007 but sorghum production in the country appeared to be mainly for home consumption as the proportion of households that offered the crop for sale in 2007 was less than 40 per cent. Market access also appeared to have improved significantly as only cassava growing households that mainly sold their produce at farm gate. Most of the farmers now market either in the village market or in markets outside the village. This development, however, also poses the problem of quality deterioration as a result of poor handling in transit. In terms of average quantity of output sold in 2007, rice growing households recorded significant decline compared with average quantity offered for sale in 2002 but the situation improved for cassava, sorghum and maize and a few of other crops such as vegetables for local markets, yam and banana.

The knowledge of various agricultural technologies among the households in 2007 was quite high. Those technologies which are well known to the households included, intercropping, intercropping with nitrogen fixing fertilizer, improved fallowing and application of chemical fertilizer. At least, more than half of the households reported the knowledge of these technologies. In spite of the households’ knowledge of these technologies, very few of them actually put them into practice in 2007. Those technologies that assumed significant practice among the households included crop rotation, intercropping, bush fallowing, the use of chemical fertilizer and application of pesticides and herbicides which are reported by more than 50 per cent of the households. For those technologies that were not adopted by the households, three major limiting factors include technology not relevant to their agricultural production, labour consuming or such technologies involved additional cost which the households could not afford. Analysis of agricultural technology diffusion and sources of technology information showed that most of the households relied mainly on their parent and neighbouring farmers for technology information. This underscores the limited impact of the agricultural extension system in the country and spatial differences in the effectiveness of extension service delivery in Nigeria with the north more effective than the south. Application of other technologies such as facilities for drying produce, storage technology and other post harvest management practice such as seed treatment showed that households have not significantly moved away from their usual traditional practices. Though more than 60 per cent of the households

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treated their produce with insecticides to prevent mould or insect attack, the proportion of produce lost due to poor storage alone is about 10 per cent. Analysis of households’ wealth creation resources with respect to land indicated that the potential to expand cultivated area is higher in the north and almost double that of the south meaning that the frontier for arable land cultivation will be exhausted earlier in the south compared with the northern part of the country. This can be traced to rapid rate of urbanization in the southern part of the country compared with the north. Average area of land irrigated also showed that irrigation is a common phenomenon only in the north but for those who irrigated their land the major source of irrigation was privately owned well or privately owned river diversion. In other words, reliance on public irrigation facilities has been limited among the households.

Farming households in Nigeria relied mainly on family labour as the major source of farm labour and this is implied by an average of 9 able-bodied men and women who are residing with the head of the households as at the time of the survey in 2007. Out of these household members, a few of them are suffering from long term illness but from an average of 5 able workers in the households, at least 4 of them are actively involved in farm work. Investigation revealed that about 74 per cent of the sampled household engaged hired labour in 2007. Their use was more restricted to operations are often regarded as labour intensive such as planting, weeding, fertilizer application and transporting of crops. The use of exchange labour was also widely reported among the households during the year. The household dynamics and crop production activities in Nigeria recognize sex role distribution in family labour use and engagement in various farming operations. Generally tedious and energy seeping farm operations such as bush clearing, tilling of land and weeding are mostly carried out by men while women are allow to engage in less energy demanding operations such as planting, harvesting, transporting of crops and tending of livestock. In few cases, however, operation like fertilizer application is jointly carried out by both male and female.

Livestock are usually kept by farming households in Nigeria for home consumption. Investigation by this study reveals that an average farming household in Nigeria owned significant number of small ruminants such as sheep or goats, and poultry birds. However, regular sale of livestock produce is not very common as only 4 per cent of the households reported having regular sale in 2007.

Ownership of consumer durable assets varied significantly among households between the two states and across various assets reflecting the levels of rural social infrastructural provision in the two states. A significant proportion of households recorded higher ownership for most assets in Kaduna which was considered to be an older state with relatively higher level of infrastructural provision than Osun state..

The role of state institutions and their effectiveness was assessed in this study from the perspectives of the households’ ability to secure their services at the right time and at lowest cost possible. It was obvious from the analysis that extension delivery in Nigeria has not been very effective as only 22 per cent of the households regularly received government extension services in 2007. About half of the households rarely received extension services while close to one-third of the households never received extension services during the year. Meanwhile, the capacity for social capital formation among the farming households in Nigeria is very weak as less than half of

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the households belong to members of any local farmer group or association. Also, formal credit institutions are either lacking or accessing loan from the existing ones has been very difficult. As a matter of fact, less than 20 per cent of the households were able to obtain agricultural credit in 2007.

Investigation of land use and land tenure system among the sampled households in 2007 pointed to the fact that the frontier for arable land in the country is approaching near exhaustion. For the newly formed households, the major means of obtaining land when household was formed is mainly through inheriting of land already under cultivation. Meanwhile, most of the land being cultivated by households are individually owned by the farming households as indicated by about 86 per cent of the respondents but more interestingly is the fact that most of these households (88%) claimed they have full control over their land. Ownership of formal title or land registration is however, not a common among farming households in Nigeria. The major means of expanding farm size in the village now is by clearing virgin land as indicated by about half of the households and for the new generation (children), the major means by which they could obtain land is by inheriting land already under cultivation

Household expenditure patterns on farm input and other farm operations or activities during the year varied considerably between the two states and expenditure on food by households in both states also followed the traditional food consumption patterns in the country. Apparently reflecting the level of poverty among the farming households in Nigeria, the proportion of households that borrowed money to cover households expenditure in 2007 was more than 50 per cent. Yet, the proportion of households that cultivated the habit of saving money every year for future needs is very significant with an average of 73 per cent. As away of coping with food scarcity particularly during lean season, a significant proportion of households in the south (Osun state) usually skip either breakfast or lunch.

REFERENCES

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