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.

Nigeria Agricultural Production: Maize data was reported at 18,570.260 Tonne th in 2017. This records an increase from the previous number of 18,097.500 Tonne th for 2016. Nigeria Agricultural Production: Maize data is updated yearly, averaging 11,087.360 Tonne th from Jun 1995 (Median) to 2017, with 23 observations. The data reached an all-time high of 18,570.260 Tonne th in 2017 and a record low of 4,547.660 Tonne th in 1997. Nigeria Agricultural Production: Maize 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.B003: Agricultural Production.

GDP from Agriculture in Nigeria increased to 5785472.38 NGN Million in the fourth quarter of 2024 from 5763385.21 NGN Million in the third quarter of 2024. This dataset provides the latest reported value for - Nigeria Gdp From Agriculture - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

In the second quarter of 2023, the agricultural sector generated about ** percent of Nigeria's gross domestic product. The largest contribution was from crop production, which covered nearly ** percent of the GDP. Agriculture accounted for a significant portion of Nigeria's GDP as a key activity for the country'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.

Nigeria Agricultural Production: Groundnut data was reported at 6,217.300 Tonne th in 2017. This records an increase from the previous number of 6,054.560 Tonne th for 2016. Nigeria Agricultural Production: Groundnut data is updated yearly, averaging 3,812.610 Tonne th from Jun 1995 (Median) to 2017, with 23 observations. The data reached an all-time high of 6,217.300 Tonne th in 2017 and a record low of 2,401.140 Tonne th in 2000. Nigeria Agricultural Production: Groundnut 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.B003: Agricultural Production.

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.

Nigeria: Value added in the agricultural sector as percent of GDP: The latest value from 2023 is 22.72 percent, a decline from 23.69 percent in 2022. In comparison, the world average is 9.91 percent, based on data from 166 countries. Historically, the average for Nigeria from 1981 to 2023 is 22.9 percent. The minimum value, 12.24 percent, was reached in 1981 while the maximum of 36.97 percent was recorded in 2002.

Nigeria NG: Land under Cereal Production data was reported at 17,342,468.000 ha in 2016. This records a decrease from the previous number of 17,631,527.000 ha for 2015. Nigeria NG: Land under Cereal Production data is updated yearly, averaging 14,131,350.000 ha from Dec 1961 (Median) to 2016, with 56 observations. The data reached an all-time high of 19,410,000.000 ha in 2007 and a record low of 4,864,500.000 ha in 1981. Nigeria NG: Land under Cereal Production 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. Land under cereal production refers to harvested area, although some countries report only sown or cultivated area. Cereals include 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.; ; Food and Agriculture Organization, electronic files and web site.; Sum;

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

Estimation domains are administrative areas from which reliable estimates are expected. The sample size planned for the extended listing operation allowed reporting key structural agricultural statistics at Local Government Area (LGA) level.

Analysis unit

Agricultural Households.

Universe

Population units of this operation are households with members practicing agricultural activities on their own account (farming households). However, all households in selected EAs were observed as much as possible to ensure a complete coverage of farming households.

Kind of data

Census/enumeration data [cen]

Sampling procedure

An advanced methodology was adopted in the conduct of the listing exercise. For the first time in Nigeria, the entire listing was conducted digitally. NBS secured newly demarcated digitized enumeration area (EA) maps from the National Population Commission (NPC) and utilized them for the listing exercise. This newly carved out maps served as a basis for the segmentation of the areas visited for listing exercise. With these maps, the process for identifying the boundaries of the enumeration areas by the enumerators was seamless.

The census was carried out in all the 36 States of the Federation and FCT. Forty (40) enumeration Areas (EAs) were selected to be canvassed in each LGA, the number of EAs covered varied by state, which is a function of the number of LGAs in the state. Both urban and rural EAs were canvassed. Out of 774 LGAs in the country, 767 LGAs were covered and the remaining 7 LGAs (4 in Imo and 3 in Borno States) were not covered due to insecurity (99% coverage). In all, thirty thousand, nine hundred and sixty (30,960) EAs were expected to be covered nationwide but 30,546 EAs were canvassed.

The Sampling method adopted involved three levels of stratification. The objective of this was to provide representative data on every Local Government Area (LGA) in Nigeria. Thus, the LGA became the primary reporting domain for the NASC and the first level of stratification. Within each LGA, eighty (80) EAs were systematically selected and stratified into urban and rural EAs, which then formed the second level of stratification, with the 80 EAs proportionally allocated to urban and rural according to the total share of urban/rural EAs within the LGA. These 80 EAs formed the master sample from which the main NASC sample was selected. From the 80 EAs selected across all the LGAs, 40 EAs were systematically selected per LGA to be canvassed. This additional level selection of EAs was again stratified across urban and rural areas with a target allocation of 30 rural and 10 urban EAs in each LGA. The remaining 40 EAs in each LGA from the master sample were set aside for replacement purposes in case there would be need for any inaccessible EA to be replaced.

Details of sampling procedure implemented in the NASC (LISTING COMPONENT). A stratified two-phase cluster sampling method was used. The sampling frame was stratified by urban/rural criteria in each LGA (estimation domain/analytical stratum).

First phase: in each LGA, a total sample of 80 EAs were allocated in each strata (urban/rural) proportionally to their number of EAs with reallocations as need be. In each stratum, the sample was selected with a Pareto probability proportional to size considering the number of households as measure of size.

Second phase: systematic subsampling of 40 EAs was done (10 in Urban and 30 in Rural with reallocations as needed, if there were fewer than 10 Urban or 30 Rural EAs in an LGA). This phase was implicitly stratified through sorting the first phase sample by geography.

With a total of 773 LGAs covered in the frame, the total planned sample size was 30920 EAs. However, during fieldwork 2 LGAs were unable to be covered due to insecurity and additional 4 LGAs were suspended early due to insecurity. For the same reason, replacements of some sampled EAs were needed in many LGAs. The teams were advised to select replacement units where possible considering appurtenance to the same stratum and similarity including in terms of population size. However about 609 EAs replacement units were selected from a different stratum and were discarded from data processing and reporting.

Sampling deviation

Out of 774 LGAs in the country, 767 LGAs were covered and the remaining 7 LGAs (4 in Imo and 3 in Borno states) were not covered due to insecurity (99% coverage).

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The NASC household listing questionnaire served as a meticulously designed instrument administered within every household to gather comprehensive data. It encompassed various aspects such as household demographics, agricultural activities including crops, livestock (including poultry), fisheries, and ownership of agricultural/non-agricultural enterprises.

The questionnaire was structured into the following sections: Section 0: ADMINISTRATIVE IDENTIFICATION Section 1: BUILDING LISTING Section 2: HOUSEHOLD LISTING (Administered to the Head of Household or any knowledgeable adult member aged 15 years and above).

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.

Sampling error estimates

Given the complexity of the sample design, sampling errors were estimated through re-sampling approaches (Bootstrap/Jackknife)

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.

As of 2023, Niger registered the agricultural sector's highest contribution to the GDP in Africa, at over ** percent. Comoros and Ethiopia followed, with agriculture, forestry, and fishing accounting for approximately ** percent and ** percent of the GDP, respectively. On the other hand, Botswana, Djibouti, Libya, Zambia, and South Africa were the African countries with the lowest percentage of the GDP generated by the agricultural sector. Agriculture remains a pillar of Africa’s economy Despite the significant variations across countries, agriculture is a key sector in Africa. In 2022, it represented around ** percent of Sub-Saharan Africa’s GDP, growing by over *** percentage points compared to 2011. The agricultural industry also strongly contributes to the continent’s job market. The number of people employed in the primary sector in Africa grew from around *** million in 2011 to *** million in 2021. In proportion, agriculture employed approximately ** percent of Africa’s working population in 2021. Agricultural activities attracted a large share of the labor force in Central, East, and West Africa, which registered percentages over the regional average. On the other hand, North Africa recorded the lowest share of employment in agriculture, as the regional economy relies significantly on the industrial and service sectors. Cereals are among the most produced crops Sudan and South Africa are the African countries with the largest agricultural areas. Respectively, they devote around *** million and **** million hectares of land to growing crops. Agricultural production varies significantly across African countries in terms of products and volume. Cereals such as rice, corn, and wheat are among the main crops on the continent, also representing a staple in most countries. The leading cereal producers are Ethiopia, Nigeria, Egypt, and South Africa. Together, they recorded a cereal output of almost *** million metric tons in 2021. Additionally, rice production was concentrated in Nigeria, Egypt, Madagascar, and Tanzania.

Nigeria Agricultural Production: Yam data was reported at 46,912.650 Tonne th in 2017. This records an increase from the previous number of 45,409.800 Tonne th for 2016. Nigeria Agricultural Production: Yam data is updated yearly, averaging 30,343.870 Tonne th from Jun 1995 (Median) to 2017, with 23 observations. The data reached an all-time high of 46,912.650 Tonne th in 2017 and a record low of 22,522.500 Tonne th in 2001. Nigeria Agricultural Production: Yam 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.B003: Agricultural Production.

In 2021, Nigeria had approximately 68.6 million hectares of agricultural land. Agriculture 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. In fact, agricultural production ranks among the ten main export categories from Nigeria.

Kaduna state agricultural production data for a set of crops for the period 1999 to 2014.

Dataset of agricultural production estimates for Cross River state, Nigeria for 2000 to 2016.

Nigeria's agricultural sector contributes to a significant part of the country's GDP. Between July and September 2021, the agriculture contributed to almost 30 percent of the total GDP, an increase by about six percentage point compared to the previous quarter.

Agriculture is a key activity for Nigeria's economy after oil. Nevertheless, agricultural activities provide livelihood for many Nigerians, whereas the wealth generated by oil reach a restricted share of people.

Agriculture, forestry, and fishing, value added (annual % growth) in Nigeria was reported at 1.1284 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Nigeria - Agriculture, value added (annual % growth) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Achieving zero hunger is intricately linked to sustainable agricultural production and the workings of a farming system. With land being the most important resource in smallholder agriculture in developing countries; including Nigeria; the effect of legal land ownership is a sine qua non for the process of achieving zero hunger in Nigeria. This study examined Nigeria’s attempt at making agricultural land both accessible and utilizable for smallholders in Nigeria through the Presidential Technical Steering Committee on Land Reforms in 2009. The aim was to explore the extent to which land ownership had become legalized; so that it had positive investment incentives for smallholder farmers to improve their investment portfolio on their holdings. A secondary dataset of 4,032 respondents obtained from the Living Standard Survey Integrated Survey on Agriculture (LSMS/ISA) of the 2018/2019 season, was used for the study. Data analysis included descriptive statistics and a 2-stage least square model. The apriori being that legal land ownership provided a perception of security that would enhance farm-level investment; which would therefore increase production output and hence food security. The findings revealed that although land titling was low (~12%) within the agricultural system; its return on production output was highly significant (5.3; p 

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 based of fish farmers

Universe

The survey covered all de jure household members (usual residents), who were into fish production

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 3 Fishing farming housing units were systematically selected and canvassed .

Sampling deviation

There was deviations from the original sample design

Mode of data collection

Face-to-face [f2f]

Research instrument

The NASC fishery questionnaire was divided into the following sections: - Holding identification: This is to identify the holder through HU serial number, HH serial number, and demographic characteristics. - Type of fishing sites used by holder. - Sources and quantities of fishing inputs. - Quantity of aquatic production by type. - Quantity sold and value of sale of aquatic products. - Funds committed to fishing by source and others

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 enterd data. 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) 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

Both Enumeration Area (EA) and Fish holders' level Response Rate was 100 per cent.

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

This Data Article houses secondary data, consisting of the available historic and current farm production data in Nigeria such as crop type, yields, prices, crop production inputs’ (e.g. labour, fertilizer, pesticide, seed, cash capital) as well as the Nigerian food consumption, ethanol demand, and international commodity (crop/food) trade (import and export) data. The data were collected from reputable online databases such as FAOSTAT, World Bank, IMF, USDA, NBS, IITA, etc., and through personal research visits to Nigerian government agencies such as Federal and State Ministries of Agricultural and Rural Development, State Agricultural Development Agency (ADP) in Nigeria, National (Nigerian) Bureau of Statistics (NBS) and others; and were assembled, screened, processed (tabulated them according to GAMS table requirements), and applied via General Algebraic Modelling System (GAMS) to analyse the Nigerian Biofuels (bioethanol production) Potential, assessing its policy impacts on domestic (Nigerian) food and energy securities, job creation, rural development, and the economy. Ndukwe Agbai Dick collected all the data, processed and applied them through GAMS to analyse the Nigerian Biofuels Potential during his PhD research studies at Newcastle University, England, between October 2010 and September, 2014. The research visit took place between March 1st and June, 2012. Research findings from the analysis of these data using GAMS have been partly documented in paper titled "Analysis of the Inherent Energy-Food Dilemma of the Nigerian Biofuels Policy using Partial Equilibrium Model: The Nigerian Energy-Food Model (NEFM)", which has been peer-reviewed and recommended for publication with major revisions in a reputable international high impact journal - Renewable and Sustainable Energy Reviews (RSER). Of course, the NEFM and results generated from it has been peer-reviewed and validated, acceptance for publication, and is now available online on the Renewable and Sustainable Energy Reviews Journal's website - a high impact and reputable international journal with impact factor of 9.184.