In the third quarter of 2024, Nigeria's crop production grew by around 1.2 percent compared to the same period of the previous year. During the selected period, the contribution of crop production to Nigeria's GDP experienced the highest increase in the fourth quarter of 2021. Agriculture contributes to a significant part of the country's GDP. It is a key activity for Nigeria's economy after oil. Nevertheless, agricultural activities provide a livelihood for many Nigerians, whereas the wealth generated by oil reaches a restricted share of people.

According to a survey conducted in 2019, about 50 percent of farming households in Nigeria were growing maize crops, the most common crop in the country. Cassava crops followed directly, with some 46 percent of households growing this root. In addition, other widespread crops were Guinea corn, yam, and beans, with 20 percent to 30 percent of surveyed households cultivating them.

Abstract

The programme for the World Census of Agriculture 2000 is the eighth in the series for promoting a global approach to agricultural census taking. The first and second programmes were sponsored by the International Institute for Agriculture (IITA) in 1930 and 1940. Subsequent ones up to 1990 were promoted by the Food and Agriculture Organization of the United Nations(FAO). FAO recommends that each country should conduct at least one agricultural census in each census programme decade and its programme for the World Census of Agriculture 2000 for instance corresponds to agricultural census to be undertaken during the decade 1996 to 2005. Many countries do not have sufficient resources for conducting an agricultural census. It therefore became an acceptable practice since 1960 to conduct agricultural census on sample basis for those countries lacking the resources required for a complete enumeration.

In Nigeria's case, a combination of complete enumeration and sample enumeration is adopted whereby the rural (peasant) holdings are covered on sample basis while the modern holdings are covered on complete enumeration. The project named “National Agricultural Sample Census” derives from this practice. Nigeria through the National Agricultural Sample Census (NASC) participated in the 1970's, 1980's, 1990's programmes of the World Census of Agriculture. Nigeria failed to conduct the Agricultural Census in 2003/2004 because of lack of funding. The NBS regular annual agriculture surveys since 1996 had been epileptic and many years of backlog of data set are still unprocessed. The baseline agricultural data is yet to be updated while the annual regular surveys suffered set back. There is an urgent need by the governments (Federal, State, LGA), sector agencies, FAO and other International Organizations to come together to undertake the agricultural census exercise which is long overdue. The conduct of 2006/2008 National Agricultural Sample Census Survey is now on course with the pilot exercise carried out in the third quarter of 2007.

The National Agricultural Sample Census (NASC) 2006/08 is imperative to the strengthening of the weak agricultural data in Nigeria. The project is phased into three sub-projects for ease of implementation; the Pilot Survey, Modern Agricultural Holding and the Main Census. It commenced in the third quarter of 2006 and to terminate in the first quarter of 2008. The pilot survey was implemented collaboratively by National Bureau of Statistics.

The main objective of the pilot survey was to test the adequacy of the survey instruments, equipments and administration of questionnaires, data processing arrangement and report writing. The pilot survey conducted in July 2007 covered the two NBS survey system-the National Integrated Survey of Households (NISH) and National Integrated Survey of Establishment (NISE). The survey instruments were designed to be applied using the two survey systems while the use of Geographic Positioning System (GPS) was introduced as additional new tool for implementing the project.

The Stakeholders workshop held at Kaduna on 21st-23rd May 2007 was one of the initial bench marks for the take off of the pilot survey. The pilot survey implementation started with the first level training (training of trainers) at the NBS headquarters between 13th - 15th June 2007. The second level training for all levels of field personnels was implemented at headquarters of the twelve (12) concerned states between 2nd - 6th July 2007. The field work of the pilot survey commenced on the 9th July and ended on the 13th of July 07. The IMPS and SPSS were the statistical packages used to develop the data entry programme.

Geographic coverage

State

Analysis unit

Household crop farmers

Universe

Crop farming household

Kind of data

Census/enumeration data [cen]

Sampling procedure

The survey was carried out in 12 states falling under 6 geo-political zones. 2 states were covered in each geo-political zone. 2 local government areas per selected state were studied. 2 Rural enumeration areas per local government area were covered and
4 Crop farming housing units were systematically selected and canvassed .

Sampling deviation

No deviation

Mode of data collection

Face-to-face [f2f]

Research instrument

The NASC crop questionnaire was divided into the following sections: - Holding identification - Holding characteristics - Access to land - Access to credit and funds used - Production input utilization, quantity and cost - Sources of inputs/equipment - Area harvested - Agric machinery - Production - Farm expenditure - Processing facilities - Storage facilities - Employment in agric. - Farm expenditure - Sales - Consumption - Market channels - Livestock farming - Fish farming

Cleaning operations

The data processing and analysis plan involved five main stages: training of data processing staff; manual editing and coding; development of data entry programme; data entry and editing and tabulation. Census and Surveys Processing System (CSPro) software were used for data entry, Statistical Package for Social Sciences (SPSS) and CSPro for editing and a combination of SPSS, Statistical Analysis Software (SAS) and EXCEL for table generation. The subject-matter specialists and computer personnel from the NBS and CBN implemented the data processing work. Tabulation Plans were equally developed by these officers for their areas and topics covered in the three-survey system used for the exercise. The data editing is in 2 phases namely manual editing before the data entry were done. This involved using editors at the various zones to manually edit and ensure consistency in the information on the questionnaire. The second editing is the computer editing, this is the cleaning of the already entered data. The completed questionnaires were collected and edited manually (a) Office editing and coding were done by the editor using visual control of the questionnaire before data entry (b) Cspro was used to design the data entry template provided as external resource (c) Ten operator plus two suppervissor and two progammer were used (d) Ten machines were used for data entry (e) After data entry data entry supervisor runs fequency on each section to see that all the questionnaire were enterd

Response rate

The response rate at EA level was 100 percent, while 98.44 percent was achieved at crop farming housing units level

Sampling error estimates

No computation of sampling error

Data appraisal

The Quality Control measures were carried out during the survey, essentially to ensure quality of data. There were two levels of supervision involving the supervisors at the first level, NBS State Officers and Zonal Controllers at second level and finally the NBS Headquarters staff constituting the second level supervision.

Primary crops produced in Nigeria in 2022 amounted to nearly *** million metric tons in total. The main crops were roots and tubers, which attained a production volume of roughly ***** million metric tons. Other primary crops produced in large quantities in Nigeria were cereals, oil crops, and fruit.

Nigeria NG: Production Index: 2004-2006: Crop data was reported at 118.870 2004-2006=100 in 2016. This records a decrease from the previous number of 120.140 2004-2006=100 for 2015. Nigeria NG: Production Index: 2004-2006: Crop data is updated yearly, averaging 42.525 2004-2006=100 from Dec 1961 (Median) to 2016, with 56 observations. The data reached an all-time high of 120.140 2004-2006=100 in 2015 and a record low of 22.430 2004-2006=100 in 1961. Nigeria NG: Production Index: 2004-2006: Crop data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank.WDI: Agricultural Production Index. Crop production index shows agricultural production for each year relative to the base period 2004-2006. It includes all crops except fodder crops. Regional and income group aggregates for the FAO's production indexes are calculated from the underlying values in international dollars, normalized to the base period 2004-2006.; ; Food and Agriculture Organization, electronic files and web site.; Weighted average;

Abstract

Four federal agencies namely, National Bureau of Statistics (NBS), Central Bank of Nigeria (CBN), Federal Ministry of Agriculture & Rural Development (FMA&RD), and Federal Ministry of Commerce (FMC), jointly conducted three survey rounds through the National Survey of Agricultural Exportable crop Commodities (NSAEC). It is believed that the survey results would give both government and non-governmental agencies ample opportunity to address the paucity of reliable agricultural data in Nigeria.

The survey included 14 export crops: cashew, cocoa, coffee, garlic, ginger, groundnut, arabic gum, palm oil, rubber, sesame seeds, shea nuts, sugar cane, and tea.

This dataset is based on the third round of the National Survey of Agricultural Export Commodities. Previous rounds were conducted in 2002/2003 and 2004/2005.

The major objectives of the survey included:

i. To ascertain the spread of the cultivation of each of the fourteen export crops within Nigeria in terms of area cultivated by state.

ii. To provide national baseline data on agricultural export commodities.

iii. To provide structural data on agricultural export commodities in Nigeria.

iv. To obtain socio-economic data and demographic characteristics of holders within households.

v. To provide production estimates at national and state levels.

Geographic coverage

National and state

Analysis unit

Household

Universe

Household export crop holders

Kind of data

Sample survey data [ssd]

Sampling procedure

A 2-stage sample design was employed.

In the first stage, 192 Local Government Areas (LGAs) from the complete list of 774 LGAs were selected nationwide. Next 10 enumeration areas (EAs), demarcated by the National Population Commission during the 1991 population census, were systematically selected from each sampled LGA, for a total of 1,920 EAs.

In the second stage, 10 export crop farming housing units were systematically selected from each sampled EA (provided there were more than 10 farming housing units in the EA). Where there were 10 or less farming housing units no selection was required, and all available housing units were studied.

Sampling deviation

Of the expected 1,920 EAs only 1,855 were found to have export crops and were eventually studied. Out of the 18,550 export crop farm housing units expected to be covered, 16,310 were canvassed.

Mode of data collection

Face-to-face [f2f]

Research instrument

Agricultural Holding Questionnaire:

Section I: Holding Identification Section Ii: Access to Land
Section Iii: Source of Funds
Section Iv: Export Crop Farming Section Vii: Market Channel Section Viii: Quantity Sold Section X: Quantity Consumed
Section Xi: Use of Fertilizer
Section Xii: Use of Pesticides Section Xiii: Use of Improved Seedling/Seed

Some modifications were made on the 2003 questionnaire.

Cleaning operations

All questionnaires were retrieved from the field by the enumerators and submitted to the sub-offices. Next the questionnaires were organized according to EAs and were taken to the NBS state offices and finally to the zonal offices. Three NBS zonal headquarters (Ibadan, Kaduna and Enugu) were chosen for the last destination of retrieval of the questionnaires. In the case of southwest and north-central zones were merged together for the submission their records at NBS zonal headquarters in Ibadan. Northwest and northeast zones were combined to submit their records at NBS zonal headquarters in Kaduna. Finally, the southeast and southern zones were joined together to submit their records to NBS zonal headquarters in Enugu.

The completed questionnaires were collated and edited manually:

a. Office editing and coding were done by the editor using visual control of the questionnaire before data entry b. Imps was used to design the data entry template provided as an external resource c. Six operators plus two supervisor and two programmers were used d. Six machines were used for data entry e. After data entry, supervisors run frequencies on each section to see that all the questionnaire were entered f. Conversion programs were written to convert the data to SPSS also provided as an external resource

Response rate

On a national basis, 100% response rate was acheived at the LGA level and 96.61% at the EA level. While 87.92% was acheived at the export crop farming housing units level.

Sampling error estimates

No sampling error estimate

Nigeria's agricultural sector experienced a growth of 1.76 percent in the fourth quarter of 2024, compared to the previous quarter. However, in relation to the fourth quarter of the previous years under study, this represented a decline. Nonetheless, the overall growth rate reflects the ongoing importance of agriculture to Nigeria's economy, despite challenges facing the sector. Agriculture remains one of the crucial sources of employment and livelihood for many Nigerians. Employment trends in agriculture While agriculture continues to play a considerable role in Nigeria's economy, its share of total employment has been generally fluctuating recently. In 2023, the agricultural sector accounted for approximately 34 percent of the total employment. While this maintained the above 30 percent share observed since 2000, it represented a further decline. By extension, this trend suggests a slow but steady shift in the labor market, especially over the last three decades, with more workers moving into the services sector which now accounts for around 47.8 percent of total employment. The workforce transition from agriculture to services can be attributed mainly to rural-urban migration, technological advancement, and a rising informal sector. Land use and crop production Nigeria's agricultural landscape is characterized by extensive land use, with approximately 36.9 million hectares of arable land and 7.7 million hectares under permanent crops as of 2022. Crop production, a key component of the agricultural sector, saw growth of 1.2 percent in the third quarter of 2024. Roots and tubers are the main agricultural products grown in the country, besides cereals and oil crops. Overall, the sector is important to Nigeria’s economic diversification.

Abstract

An 'agricultural export crop' is a crop which is currently grown in country and has export potential. An 'agricultural export commodity' is the product of any export crop. For example, palm oil and palm kernel are two by-products of the oil palm.

A 'holding' is the total land area devoted to the cultivation of any of the 14 export crops included in this survey (rubber, coffee, cocoa, sesame seed, garlic, tea, ginger, gum arabic, cashew nut, oil palm, groundnut, cotton, sugarcane and shea nut) by an individual called a farmer. A 'holder' is the person who owns a holding and is therefore entitled to the proceeds from the holding.

The major objectives of the survey were as follows:

i. To ascertain the spread of the cultivation of each of the 14 export crops within Nigeria in terms of areas cultivated by state.

ii. To ascertain the export potential of these commodities with respect to their outputs.

iii. Ascertain the quantities of commodities being exported.

iv. To provide structural data on agricultural export commodities such as size of holdings, access to land and credit, availability of processing, and storage facilities among others.

v. To provide socio-economic and demographic data on agricultural export commodity holders.

Geographic coverage

National and state

Analysis unit

Household

Universe

Household export crop farmers

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey covered farming households in all states of the federation and the Federal Capital Territory (FCT) involved in the 14 selected export crops. The number of LGAs allocated to each state for sampling varied from a minimum of 3 to a maximum of 9. The number of LGAs per state was based on the number of export crops grow, the intensity of cultivation, and corresponding output in the state.

A total of 192 LGAs were mapped out for sampling nationwide and in each LGA 10 enumeration areas (EAs) were listed for sampling. This brought the total number of EAs initially slated for sampling nationwide to 1,920.

In each EA, 10 Housing Units (HUs) were to be selected, which brought the total number of HUs covered in the survey to 19,200.

Sampling deviation

192 LGAs were selected nationwide, but due to logistical problems only 182 LGAs were sampled.

Mode of data collection

Face-to-face [f2f]

Research instrument

Holding Questionnaire:

Section I: Holding Identification Section Ii: Access to Land
Section Iii: Source of Funds
Section Iv: Export Crop Farming Section Vii: Market Channel Section Viii: Quantity Sold Section X: Quantity Consumed
Section Xi: Use of Fertilizer
Section Xii: Use of Pesticides Section Xiii: Use of Improved Seedling/Seed

Cleaning operations

The completed questionnaires were collated and edited manually:

(a) Office editing and coding was done by the editor using visual control of the questionnaire before data entry (b) Imps was used to design the data entry template provided as an external resource (c) Six operators plus two supervisors and two programmers were used (d) Six machines were used for data entry (e) The data entry staff used 20 days to do the entries (f) The supervisor used 5 days to check the entries

Response rate

On a national basis, the 2005 survey achieved a response rate of about 77.66% at the Housing Unit level.

Sampling error estimates

No sampling error estimate

Abstract

The main objective of the Pilot Survey was to test the adequacy of the survey instruments, equipments and administration of questionnaires, data processing arrangement and report writing. The Pilot survey conducted in July 2007 covered the two NBS survey system-the National Integrated Survey of Households (NISH) and National Integrated Survey of Establishment (NISE). The survey instruments were designed to be applied using the two survey systems while the use of Geographic Positioning System (GPS) was introduced as additional new tool for implementing the project.

The programme for the World Census of Agriculture 2000 is the eighth in the series for promoting a global approach to agricultural census taking. The first and second programmes were sponsored by the International Institute for Agriculture (IITA) in 1930 and 1940. Subsequent ones up to 1990 were promoted by (FAO). Food and Agriculture Organization of the United Nations recommends that each country should conduct at least one agricultural census in each census programme decade and its programme for the World Census of Agriculture 2000 for instance corresponds to Agricultural Census to be undertaken during the decade 1996 to 2005. Many countries do not have sufficient resources for conducting an agricultural census. It therefore became an acceptable practice since 1960 to conduct agricultural census on sample basis for those countries lacking the resources required for a complete enumeration.

In Nigeria's case, a combination of complete enumeration and sample enumeration is adopted whereby the rural (peasant) holdings are covered on sample basis while the modern holdings are covered on complete enumeration. The project named "National Agricultural Sample Census" derives from this practice. Nigeria through the National Agricultural Sample Census (NASC) participated in the 1970's, 1980's, 1990's programmes of the World Census of Agriculture. Nigeria failed to conduct the Agricultural Census in 2003/2004 because of lack of funding.

The NBS regular annual agriculture surveys since 1996 had been epileptic and many years of backlog of data set are still unprocessed. The baseline agricultural data is yet to be updated while the annual regular surveys suffered set back. There is an urgent need by the Governments (Federal, State, LGA), sector agencies, FAO and other International Organizations to come together to undertake the agricultural census exercise which is long overdue. The conduct of 2006/2008 National Agricultural Sample Census Survey is now on course with the pilot exercise carried out in the third quarter of 2007.

The National Agricultural Sample Census (NASC) 2006/08 is imperative to the strengthening of the weak agricultural data in Nigeria. The project is phased into three sub-projects for ease of implementation; the Pilot Survey, Modern Agricultural Holding and the Main Census. It commenced in the third quarter of 2006 and to terminate in the first quarter of 2008. The pilot survey was implemented collaboratively by National Bureau of Statistics.

The Stakeholders workshop held at Kaduna on 21st-23rd May 2007 was one of the initial bench marks for the take off of the Pilot Survey. The Pilot Survey implementation started with the first level training (Training of Trainers) at the NBS Headquarters between 13th - 15th June 2007. The second level training for all levels of field personnels was implemented at Headquarters of the twelve (12) concerned states between 2nd - 6th July 2007. The field work of the Pilot Survey commenced on the 9th July and ended on the 13th of July 07. The CSpro and SPSS were the statistical packages used to develop the data entry programme. The results of the survey are presented in chapter three of this report.

The owner-like possession was the most common system nationwide with a figure of 2,083,503 (holding) followed by family land 962,233 (holding) while squatter was the least system used 40,473 (holding). Distribution of holding by type of land showed that three types of land-upland, lowland and irrigated were mostly used with irrigated land being the highest 5,825,531 holding followed by lowland 5,320,782 holding and upland 3,070,911 holdings with the highest holding within the age group of 25-44 years. In all states, 2,392,725 males were involved in crop farming while 540,070 females were also paticipating. Out of the 11 major crops reported, cassava recorded the highest number of farms 2,649,098 farms, next was maize 2,199,352 and yam 2,042,440 farms while the least was cotton 46,287 farms. Other crops were Beans, Cocoyam, Groundnut, Guinea corn, melon, Millet and Rice.

Geographic coverage

State

Analysis unit

Household based

Universe

Household

Kind of data

Sample survey data [ssd]

Sampling procedure

12 states were purposely selected in the country. 2 states from each of the 6 geo-political zones. 2 LGAs per selected state were studied. 2 Rural EAs per LGA were covered and 5 Housing Units were systematically selected and canvassed for GHS data.

Sampling deviation

No Deviation

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire for the Private Farmers (Holding) is a structured questionnaire based on household characteristics with some modifications and additions. The questionnaire contains the following sections. Holding identification Holding Characteristics Access to Land Access to Credit and Funds Used Production input utilization; quantity and cost Sources of inputs/equipment Area Harvested. Agric Machinery. Production. Farm Expenditure. Processing Facilities. Storage Facilities. Employment in Agric. Farm Expenditure. Sales. Consumption. Market Channels. Livestock Farming. Fish Farming.

Cleaning operations

The data editing is in 2 phases namely manual editing before the questionnaires were scanned. This involved using editors at the various zones to manually edit and ensure consistency in the information on the questionnaire. The second editing is the computer editing, this is the cleaning of the already scanned data. The subject-matter specialists and computer personnel from the NBS and CBN implemented the data processing work. Tabulation Plans were equally developed by these officers for their areas and topics covered in the three-survey system used for the exercise.

The data editing is in 2 phases namely manual editing before the data entry were done. This involved using editors at the various zones to manually edit and ensure consistency in the information on the questionnaire. The second editing is the computer editing, this is the cleaning of the already enterd data. The completed questionnaires were collated and edited manually

(a) Office editing and coding were done by the editor using visul contro of the questionnaire before data entry (b) Cspro was used to design the data entry template provided as external resource (c) Ten operator plus two suppervissor and two progammer were used (d) Ten machines were used for data entry (e) After data entry data entry supervisor runs fequency on each section to see that all the questionnaire were enterd

Response rate

On state basis, 100 percent response rate was acheived at EA level .

While 99.6 percent was recorded at housing units level.

Sampling error estimates

No computation of sampling error

Data appraisal

The Quality Control measures were carried out during the survey, essentially to ensure quality of data. There were two levels of supervision involving the supervisors at the first level, NBS State Officers and Zonal Controllers at second level and finally the NBS Headquarters staff constituting the second level supervision.

Nigeria NG: Production Index: 2014-2016: Crop data was reported at 120.890 2014-2016=100 in 2022. This records an increase from the previous number of 118.310 2014-2016=100 for 2021. Nigeria NG: Production Index: 2014-2016: Crop data is updated yearly, averaging 46.655 2014-2016=100 from Dec 1961 (Median) to 2022, with 62 observations. The data reached an all-time high of 120.890 2014-2016=100 in 2022 and a record low of 19.310 2014-2016=100 in 1961. Nigeria NG: Production Index: 2014-2016: Crop data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank.WDI: Agricultural Production Index. Crop production index shows agricultural production for each year relative to the base period 2014-2016. It includes all crops except fodder crops. Regional and income group aggregates for the FAO's production indexes are calculated from the underlying values in international dollars, normalized to the base period 2014-2016.;Food and Agriculture Organization, electronic files and web site.;Weighted average;

Abstract

An 'agricultural export commodity' is defined as an exportable crop that is currently grown in country and has great potential for generating foreign exchange for the nation. The 14 crops under consideration in Nigeria are rubber, coffee, cocoa, sesame seed, garlic, tea, ginger, gum arabic, cashew nut, oil palm, groundnut, cotton, sugarcane and shea nut.

Nigeria is earning some foreign exchange from the 14 export crops covered in the survey.

The objective of the survey is to provide a national baseline data on agricultural commodities. Furthermore, the annual survey, among others will help to:

  1. Provide structural data on agricultural export commodities in Nigeria, 

  2. Obtain socio-economic data and demographic characteristics of holders within households, and

  3. Provide production estimates at national and state levels.

Geographic coverage

National, state, and sector (urban/rural).

Analysis unit

Household

Universe

Household export crop farmers and modern agricultural export crop holders.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling design employed a two-phase, two-stage sample selection procedure.

Phase 1, stage 1: The listing exercises were conducted during phase 1, stage 1. A total of 192 Local Government Areas (LGAs) were selected throughout the federation and 10 enumeration areas (EAs) were selected in each LGA, totaling 1,920 EAs throughout the country including the Federal Capital Territory (FCT). Most of these LGAs were selected based on the information that they were producing one or more of the 14 selected export crops. No less than three LGAs were selected from each state and FCT.

Phase 1, stage 2: Ten (10) export crop farming housing units were selected in each EA using a systematic selection approach during phase 1, stage 2. All households in each export crop farming housing unit were administered the holding questionnaires.

Phase 2, stage 1: During phase 2, stage 1 the crop cutting exercise were conducted, which included the farm survey, laying yield plots, and harvesting. All 10 EAs in each LGA, covered in the first phase, were selected for crop cutting exercises.

Sampling deviation

No deviation.

Mode of data collection

Face-to-face [f2f]

Research instrument

Federal Republic of Nigeria The National Survey on Agricultural Export Commodities was conducted by the Central Bank of Nigeria in collaboration with the National Bureau of Statistics, Federal Ministry of Agriculture and Rural Development, and Federal Ministry of Commerce.

Holding Questionnaire:

Section I: Holding Identification Section Ii: Access to Land
Section Iii: Source of Funds
Section Iv: Export Crop Farming Section Vii: Market Channel Section Viii: Quantity Sold Section X: Quantity Consumed
Section Xi: Use of Fertilizer
Section Xii: Use of Pesticides Section Xiii: Use of Improved Seedling/Seed

Cleaning operations

The completed questionnaires were collated and edited manually:

(a) Office editing and coding was done by the editor using visual control of the questionnaire before data entry (b) Imps was used to design the data entry template provided as an external resource (c) Six operators plus two supervisors and two programmers were used (d) Six machines were used for data entry (e) The data entry staff used 20 days to do the entries (f) The supervisor used 5 days to check the entries (g) A conversion program was written to convert the data to SPSS which was also provided as an external resource

Response rate

The 2003 Nigeria AGREXP survey achieved a response rate of about 74.86% at the Housing Unit level.

Reasons for non-response was not given.

Sampling error estimates

No sampling error estimate

Data appraisal

In order to ensure high quality data, a two-phase quality check was put in place. During the first phase, the officers skim-checked 10 listing forms and selected 10 holding questionnaires in selected EAs in each state and FCT.

During the second phase, 10 listing forms from 10 holding questionnaires were chosen to be spot-checked from selected EAs in each state and FCT.

Farmers were randomly selected and visited on their farms to authenticate the data entries made by enumerators.

Abstract

NASC is an exercise designed to fill the existing data gap in the agricultural landscape in Nigeria. It is a comprehensive enumeration of all agricultural activities in the country, including crop production, fisheries, forestry, and livestock activities. The implementation of NASC was done in two phases, the first being the Listing Phase, and the second is the Sample Survey Phase. Under the first phase, enumerators visited all the selected Enumeration Areas (EAs) across the Local Government Areas (LGAs) and listed all the farming households in the selected enumeration areas and collected the required information. The scope of information collected under this phase includes demographic details of the holders, type of agricultural activity (crop production, fishery, poultry, or livestock), the type of produce or product (for example: rice, maize, sorghum, chicken, or cow), and the details of the contact persons. The listing exercise was conducted concurrently with the administration of a Community Questionnaire, to gather information about the general views of the communities on the agricultural and non-agricultural activities through focus group discussions.

The main objective of the listing exercise is to collect information on agricultural activities at household level in order to provide a comprehensive frame for agricultural surveys. The main objective of the community questionnaire is to obtain information about the perceptions of the community members on the agricultural and non-agricultural activities in the community.

Additional objectives of the overall NASC program include the following: · To provide data to help the government at different levels in formulating policies on agriculture aimed at attaining food security and poverty alleviation · To provide data for the proposed Gross Domestic Product (GDP) rebasing

Geographic coverage

Communities (in Enumerated Areas).

Analysis unit

Community

Universe

The population units are communities encompassing the designated enumeration areas, where household listing was performed.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Focus group interviews were performed in communities overlapping with in the EAs selected for the extended listing operation. Accordingly, a focus group discussion in a total of 26,555 communities were undertaken to administer the community level questionnaire. It is important to note here that the results from the community survey are unweighted results and all the tables produced from the community level data are only from the 26,555 communities interviewed.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The NASC community listing questionnaire served as a meticulously designed instrument administered within every community selected to gather comprehensive data. It encompassed various aspects such as agricultural activities in the community, infrastructures, disaster, etc. The questionnaire was structured into the following sections:

• Identification of the community • Respondent Characteristics (Name, Sex, age) • Agricultural Activities in the Community • Disasters and Shocks • Community Infrastructure and Transportation • Community Organizations • Community Resources Management • Land Prices and Credit • Community Key Events • Labour

Cleaning operations

Data processing of the NASC household listing survey included checking for inconsistencies, incompleteness, and outliers. Data editing and cleaning was carried out electronically using the Stata software package. In some cases where data inconsistencies were found a call back to the household was carried out. A pre-analysis tabulation plan was developed and the final tables for publication were created using the Stata software package.

Nigeria NG: Cereal Yield: per Hectare data was reported at 1,443.600 kg/ha in 2016. This records an increase from the previous number of 1,443.500 kg/ha for 2015. Nigeria NG: Cereal Yield: per Hectare data is updated yearly, averaging 1,192.300 kg/ha from Dec 1961 (Median) to 2016, with 56 observations. The data reached an all-time high of 1,655.500 kg/ha in 1981 and a record low of 607.800 kg/ha in 1966. Nigeria NG: Cereal Yield: per Hectare data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank.WDI: Agricultural Production and Consumption. Cereal yield, measured as kilograms per hectare of harvested land, includes wheat, rice, maize, barley, oats, rye, millet, sorghum, buckwheat, and mixed grains. Production data on cereals relate to crops harvested for dry grain only. Cereal crops harvested for hay or harvested green for food, feed, or silage and those used for grazing are excluded. The FAO allocates production data to the calendar year in which the bulk of the harvest took place. Most of a crop harvested near the end of a year will be used in the following year.; ; Food and Agriculture Organization, electronic files and web site.; Weighted average;

Nigeria GDP: Basic Prices: Agriculture: Crop Production data was reported at 21,096,105.254 NGN mn in 2017. This records an increase from the previous number of 18,883,081.499 NGN mn for 2016. Nigeria GDP: Basic Prices: Agriculture: Crop Production data is updated yearly, averaging 1,204,704.922 NGN mn from Dec 1981 (Median) to 2017, with 37 observations. The data reached an all-time high of 21,096,105.254 NGN mn in 2017 and a record low of 12,817.213 NGN mn in 1981. Nigeria GDP: Basic Prices: Agriculture: Crop Production data remains active status in CEIC and is reported by National Bureau of Statistics of the Federal Republic of Nigeria. The data is categorized under Global Database’s Nigeria – Table NG.A007: GDP: by Industry: Current Price: Annual.

Abstract

In the recent past, three survey projects had been conducted by the Technical Committee of the Consultative Committee on Agricultural Export Commodities Statistics (CCAECS). The survey projects include: Pilot test 2002/2003, 2004/2005 and 2005/2006. The projects were jointly carried out by four federal agencies namely: National Bureau of Statistics (NBS), Central Bank of Nigeria (CBN), Federal Ministry of Agriculture & Rural Development (FMA&RD) and Federal Ministry of Commerce (FMC).

Obviously, the results obtained from these joint projects would add value to agricultural production in the country. It is believed that the survey results would give both government and non-governmental agencies ample opportunity to address the ugly situation of dearth of reliable statistical data on export crops.

The survey covered the following fourteen crops: Cashew, Cocoa, Coffee, Cotton, Garlic, Ginger, Groundnut, Gum Arabic, Oil palm, Rubber, Sesame seed, Sheanuts, Sugar cane and Tea.

This report is based on the 2005/06 survey result which is the third edition of the series and the most recent conclusive project.

The major objectives of the survey include: i. To ascertain the spread of the cultivation of each of the fourteen export crops within Nigeria in terms of area cultivated by state. ii. To provide a national baseline data on agricultural export commodities. iii. To provide structural data on agricultural export commodities in Nigeria. iv. To obtain socio-economic data and demographic characteristics of holders within households. v. To provide production estimates at national and state levels.

Geographic coverage

National Coverage

Analysis unit

Households

Universe

Household export crop holder

Kind of data

Sample survey data [ssd]

Sampling procedure

The first frame was the list of 774 LGAs nationwide. The second frame was the list of EAs demarcated by the National Population Commission during the 1991 population census. 192 LGAs were selected nationwide. A 2-stage sample design was employed.

In the first stage,10 EAs were systematically selected from each sampled LGA. Of the expected 1,920 EAs, only 1,855 were found to have export crops and were eventually studied.

In the second stage,10 export crop farming housing units were systematically selected from each sampled EA (provided there were more than 10 farming housing units in the EA). Where there were 10 or less farming housing units, no selection was required and all available housing units were studied.

Out of the 18,550 export crop farming housing units expected to be covered, 16,310 were canvassed.

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

The completed questionnaires were collated and edited manually (a) Office editing and coding were done by the editor using visual control of the questionnaire before data entry (b) Imps was used to design the data entry template provided as external resource (c) Six operator plus two supervisors and two progammers were used (d) Six machines were used for data entry (e) After data entry, supervisor ran frequencies on each section to see that all the questionnaire was entered (f) Conversion program was written to convert the data to spss also provided as external resource

Response rate

On national basis, 100 percent response rate was acheived at LGA level and 96.61 percent at EA level while 87.92 percent was acheived at export crop farming housing units level.

Forecast: Sugar Crops Production in Nigeria 2023 - 2027 Discover more data with ReportLinker!

According to the results of a survey conducted in 2019, agricultural activities in Nigeria were more widespread in North than in South. Especially, **** percent of households living in the North East of the country declared to practice crop farming. Similarly, **** percent of households in the same region owned or rose livestock. On the other hand, the South West of Nigeria recorded the lowest percentage of households participating in agricultural activities. In total, crop farming was practiced by about ** percent of Nigerian households.

Abstract

The major objectives of the survey include: i. To ascertain the spread of the cultivation of each of the fourteen export crops within Nigeria in terms of area cultivated by state. ii. To provide a national baseline data on agricultural export commodities. iii. To provide structural data on agricultural export commodities in Nigeria. iv. To obtain socio-economic data and demographic characteristics of holders within households. v. To provide production estimates at national and state levels.

Geographic coverage

National coverage

Analysis unit

State, household, individual

Universe

Households that export crops from the nationally sampled area

Kind of data

Sample survey data [ssd]

Sampling procedure

192 LGAs were selected nationwide. A 2-stage sample design was employed. In the first stage, 10 EAs were systematically selected from each sampled LGA. Of the expected 1,920 EAs, only 1,855 were found to have export crops and were eventually studied. In the second stage, 10 export crop farming housing units were systematically selected from each sampled EA (provided there were more than 10 farming housing units in the EA). Where there were 10 or less farming housing units, no selection was required and all available housing units were studied.

Mode of data collection

Face-to-face [f2f]

Research instrument

Agricultural Holding Questionnaire SECTION I: HOLDING IDENTIFICATION SECTION II: ACCESS TO LAND
SECTION III: SOURCE OF FUNDS
SECTION IV: EXPORT CROP FARMING SECTION VII: MARKET CHANNEL SECTION VIII: QUANTITY SOLD SECTION X: QUANTITY CONSUMED
SECTION XI: USE OF FERTILIZER
SECTION XII: USE OF PESTICIDES SECTION XIII: USE OF IMPROVED SEEDLING/SEED

Cleaning operations

Data editing proceeded as such: (a) Office editing and coding were done by the editor using visul contro of the questionnaire before data entry (b) Imps was used to design the data entry template provided as external resource (c) Six operator plus two suppervissor and two progammer were used (d) Six machines were used for data entry (e) After data entry data entry supervisor runs fequency on each section to see that all the questionnaire were enterd (f) Conversion progarm was written to convert the data to spss also provided as external resource

Response rate

Nationally, a 100 percent response rate was acheived at LGA level and 96.61 percent at EA level while 87.92 percent was acheived at export crop farming housing units level.

Sampling error estimates

No sampling error estimate

Socio-economic situation and problems of farmers, information about cultivation and selling of crops as well as attitudes towards extension-workers and modern methods of cultivation.

Issues: Years at school; number of wives; bride price; number of people to feed in household; ownership of consumer goods; memberships and amount of contributions; use of savings; poultry and cattle owner- ship; farm size; distance to farmland; access to farmland; mode of acquisition of farmland; changes in farm size; mode of additional acquisition of farmland or reasons for reduction of farmland; changes in quality of farmland and reasons for changes; comparison of quality of own farmland with others and reasons for differences; number of cultivated crops; number of crops cultivated with fertilizer, chemicals and im- proved seeds; proportion of sold crops; proceeds from selling crops; expenditure for fertilizer, chemicals, improved seeds, tractors and hired labour as well as total expenses; source of instructions for using fertilizer and chemicals; difficulties with instructions and reasons for problems; knowledge and use of modern methods of cultivation; preference for modern or traditional methods of cultivation; main problems of using modern methods; number of workdays on the farmland performed by family members and other workers; kind of work which requires other people´s help; own work on other men´s fields and reason for this activities; place to purchase fertilizer, chemicals and seeds; additional sources of income and kind of activities; income from non-agricultural activities; contacts to extension-worker as well as frequency and place of contacts; perceived improvement by activities of extension-worker; advantages or disadvantages by activities of extension-worker in comparison to other farmer and reason for disadvantage; person for discussion of farm problems; frequency of discussing farm problems with other people as well as own role in these discussions; expectations towards adviser in farm problems; detailed informations about cultivation, use of fertilizer, chemicals and improved seeds as well as the proceeds from different products culti- vated.

The file contains additional informations about the presence of other persons during the interview and the name of the interviewer.

Forecast: Primary Fibre Crops Production in Nigeria 2023 - 2027 Discover more data with ReportLinker!