5 research outputs found
Assessing the impact of the adoption of agroforestry technology on food production and poverty reduction among farming households in Oyo State, Nigeria
Article Details: Received: 2020-06-22 | Accepted: 2020-08-08 | Available online: 2021-03-31 https://doi.org/10.15414/afz.2021.24.01.25-34This study determines the impact of agroforestry practices on food production, income generation and poverty reduction among farming households in Oyo State, Nigeria. A multi-stage sampling technique was used to select the respondents. Both descriptive statistics such as frequencies and percentages as well as inferential statistics such as Propensity Score Matching (PSM) and Foster Greer Thorbecke (FGT) analysis were used in the study. It was discovered that the propensity score distribution and common support for propensity score estimation shows the results from the covariate balancing tests both before and after matching in which the treatment (adopters) and comparison (non-adopters) groups are said to be balanced. The result of the impact of the adoption of agroforestry practices on farmers’ income from the PSM analysis shows that the adoption produces a positive and significant impact on the farmers’ income, while the result of the impact of the adoption on farmers’ output was found to be negative, though not significant. This could be attributed to improper adoption or practices of the technologies by the farmers. It was also discovered that about 27% of the adopters fell below the poverty line (102.21) and can therefore be described as poor. FGT poverty index was then used to show the extent of poverty among the farming households and it was found that the adopters of agroforestry technology were faring better than the non-adopters of agroforestry technology.Keywords: agroforestry technology, food production, poverty reduction, Propensity Score Matching (PSM), Foster Greer Thorbecke (FGT) ReferencesADAMS, W.M. et al. (2004). Biodiversity conservation and the eradication of poverty. Science, (306), 1146.ADEOLA, A.O. (2015). Principles and Practice of Agroforestry. YEMPET PUBLISHERS, Akure.ADEPOJU, A.O. et al. (2010). Households’ Vulnerability to Poverty in Ibadan Metropolis, Oyo State, Nigeria. Journal of Rural Economics and Development, 20, pp. 1–14.AJAYI, O.C. et al. (2012). Role of externality in the adoption of smallholder agroforestry: Case studies from Southern Africa and Southeast Asia. In S. Sunderasan (Ed.). Externality: Economics, Management and Outcomes, NY: NOVA Science Publishers, pp. 167–188.AKINWALERE, B.O. (2016). Agroforestry Practices among Farmers in SouthWest Nigeria: An Analysis of Benefits. Asian Journal of Agricultural Extension, Economics & Sociology, 10(2), 1–9.ALI, A. et al. (2010). The Adoption of Genetically Modified Cotton and Poverty Reduction in Pakistan. J. Agric. Econ., 61(1), 175–192.AMONUM, J.I. et al. (2019). Adoption Level of Agroforestry Practices in Katsina State, Nigeria. Asian Research Journal of Agriculture, 11(2), 1–10.BEEGLE, K. et al. (2016). Poverty in a rising Africa. World BankPublications. https://doi.org/10.1596/978-1-4648-0723-7CHARLES, A. et al. (2019). Addressing the climate change and poverty nexus: a coordinated approach in the context of the 2030 agenda and the Paris agreement. Rome. FAO.DANAAN, V.V. (2018). Analysing Poverty in Nigeria through Theoretical Lenses. Journal of Sustainable Development, 11(1), 20–31.GARRITY, D. et al. (2011). More trees on farms. Farm. Matt., 27(2), 8–9.GRIGGS, D. et al. (2013). Policy: sustainable development goals for people and planet. Nature, (495), 305–307.GUO, S. et al. (2010). Advanced quantitative techniques in the social sciences: Propensity score analysis: Statistical methods and applications. Sage Publications, Inc.FFOSTER J. E. et al. (1984). A class of decomposable poverty indices. Econometrica, (5), 761–766.IDUMAH, F.O. et al. (2019). Determinants of Yam Production and Resource use Efficiency under Agroforestry System in Edo State, Nigeria. Tanzania Journal of Agricultural Sciences, 18(1), 35–42.IDUMAH, F.O. et al. (2018). Balancing Food Production and Forest Conservation in Nigeria: The Agroforestry Option. IOSR Journal of Agriculture and Veterinary Science (IOSR–JAVS), 11(11), pp. 63–68.IDUMAH, F.O. et al. (2014). Contribution of agroforestry to food production and income generation in Sapoba forest area, Edo State, Nigeria. Journal of Horticulture and Forestry, 6(8), pp. 64–71.INSTITUTE FOR FOOD SECURITY, ENVIRONMENTAL RESOURCES AND AGRICULTURAL RESEARCH(IFSERAR). Federal University of Agriculture, Abeokuta (FUNAAB), Cartographic, Laboratory, 2016.JAMA, B. et al. (2006). Role of Agroforestry in Improving Food security and Natural Resource Management in the Drylands: A Regional Overview. Journal of the Drylands, 1(2), 206–211.KANDJI, S.T. et al. (2006). Opportunities for linking climate change adaptation and mitigation through agroforestry systems. In Garrity DP, Okono A, Grayson M, Parrott S (Eds) World Agroforestry into the Future (Edn) World Agroforestry Centre (ICRAF). Nairobi, Kenya.KAREEM, I.A. et al. (2017) Evaluation of selected agroforestry practices and farmers’ perception of climate change in Ogun State, Nigeria. Forest Research Engineering: International Journal, 1(1), 9–16.KENNEDY, N. et al. (2016). Adoption of soil and water conservation practices in central Haiti. J. Soil Water Conserv., 71(2), 83–90.MADUKA, S.M. (2007). Role of Agroforestry Products in Household Income and Poverty Reduction in Semi-Arid Areas of Misungwi District, Mwanza, Tanzania. A dissertation submitted in partial fulfilment of the requirements for the degree of Master of Sciencein Forestry of Sokoine University of Agriculture, Morogoro, Tanzania.MAREN, O. et al. (2011). Climate Change Adaptation using Agroforestry Practices: A Case Study from Costa Rica. Stefano Casalegno (Ed.) Global Warming Impacts – Case Studies on the Economy, Human Health, and on Urban and Natural Environments. https://doi.org/10.5772/241727MUTUA, J. et al. (2014). Conservation Agriculture with Trees: Principles and Practice. A simplified guide for Extension Staff and Farmers. World Agroforestry Centre, (ICRAF), Nairobi, Kenya.OLAJUYIGBE, S. (2016). Potential role of traditional agroforestry in climate change mitigation in rural communities of Oyo State Nigeria. In Conference Paper presented at the 38th Annual Conference of the Forestry Association of Nigeria, held at Port Harcourt, Rivers State, Nigeria.OSOWOLE, O.I. (2011). An Analysis of Rural Poverty In Oyo State: A Principal Component Approach. JORIND, 9(2), 100–104. www.ajol.info/journals/jorindOWOMBO, P.T. et al. (2017). Determinants of agroforestry technology adoption among arable crop farmers in Ondo state, Nigeria: an empirical investigation. AgroforestSyst., (91), 919– 926. https://doi.org/10.1007/s10457-016-9967-2OZOWA, B. (2005). Making the Most of Agricultural Investment. PDF adobe acrobat document at www.ifad.org/agri_investment.pdf Retrieved in November, 2011.RAHMAN, S.A. et al. (2010). SustainableForest Management for Poverty Reduction Through Agroforestry Options:Lesson from the Remote Uplands of Eastern Bangladesh. Libyan Agriculture Research Center Journal International, 1(3), 134–141.RUBIN, D. R. (2001). Using Propensity Scores to Help Design Observational Studies: Application to the Tobacco Litigation. Health Services & Outcomes Research Methodology, 2, 169–88.SARVADE, S. et al. R. (2014). Role of Agroforestry in Food Security. Popular Kheti, 2(2), 25–29.SILESHI, G.W. (2012). Can Integration of Legume Trees Increase Yield Stability in Rain-fed Maize Cropping Systems in South Africa? Agronomy Journal, (104), 1392–1398.THOEMMES, F.J. et al. (2011). A Systematic Review of Propensity Score Methods in the Social Sciences. Multivariate Behavioral Research, 46(1), 90–118.THORNTON, P. K. et al. (2006). Mapping climate vulnerability and poverty in Africa. Report to the Department for International Development, ILRI, Nairobi, Kenya, pp 171.TIWARI, P. et al. (2017). Agroforestry for Sustainable Rural Livelihood: A Review. International Journal of Pure Applied Biosciences, 5(1), 299–309. http://dx.doi.org/10.18782/2320-7051.2439NATIONAL HUMAN DEVELOPMENT REPORT OF THE UNITED NATIONS DEVELOPMENT PROGRAMME. (2019). Inequalities in Human Development in the 21st Century Briefing note for countries on the 2019 Human Development Report. Retrieved on http://hdr.undp.org/sites/all/themes/hdr_theme/country-notes/NGA.pdfUNITED NATIONS DEVELOPMENT PROGRAMME, HUMAN DEVELOPMENT REPORTS, GDP per capita (2011 PPP$).WORLD BANK. (2018). Poverty and Equity Brief in Sub-Saharan Africa, Nigeria. April, 2018. https://databank.worldbank.org/data/download/poverty/33EF03BB-9722-4AE2-ABC7-AA2972D68AFE/Archives-2018/GlobalPOVEQ_NGA. pdfWorld BankWORLD BANK. (2001). Attacking poverty. World development report 2000/2001 (draft copy). West African, USA, 352 p
Wetland importance and dependence among households around the Ogun River Basin, Nigeria
Wetland is particularly important in developing countries for economic purposes. This study examines livelihood activities, wetland dependence and its determinants among wetland households. Primary data were collected from households in a two stage random sampling procedure. Both descriptive and quantitative methods were employed for data analysis. Results show that support for dry season production, all year round water supply, and fishing were the first, second and third most important benefits of wetland to households. Socio-economic factors have influences on wetland dependence. This study concludes that wetland support dry season farming and is heavily depended upon for income by households in wetland communities. It is therefore recommended that skills acquisition centres should be established in wetland communities to engage youths particularly male in other employment apart from wetland related ones so as to reduce dependence on wetlands and thus take pressure off them
Effect of rural infrastructure on profitability and productivity of cassava-based farms in Odogbolu local government area, Ogun state, Nigeria
Infrastructural development in Nigeria has been historically linked to the
development of agriculture, exploitation of natural resources and public
policies. This study examined the effect of rural infrastructures on
profitability and productivity of cassava-based farms in Odogbolu local
government area of Ogun state, Nigeria. The study was based on a
cross-sectional survey of 120 cassava farmers selected with a multistage
random sampling technique from 10 villages. Descriptive statistics were used
to generate the composite rural infrastructure index which revealed that 5
out of the 10 sampled villages were under-developed. Economic efficiency in
the developed and under-developed areas shows that farmers in the developed
areas are better off compared to their counterparts in the under-developed
areas. Farm size, years of farming experience and infrastructural development
index (INF) were statistically significant with negative influence on
productivity of cassava-based farmers. The significance and indirect
relationship of the years of farming experience and infrastructural
development index at p<0.05 and farm size (p<0.01) regarding the total factor
productivity (TFP) implied that these variables decrease TFP. Similarly, the
negative sign of the coefficient of INF of -0.742 at p<0.05 shows that the
under-development of infrastructural facilities observed in the study area is
capable of jeopardizing efforts at improving the productivity of
cassava-based farmers. Therefore, farmer in the developed areas can generally
produce more output at lower cost if there is an improvement in
infrastructural facilities in the study area
WETLANDS ATTRIBUTES AND INFLUENCES ON FOOD SECURITY OF HOUSEHOLDS AROUND OGUN RIVER OF NIGERIA
The physical and ecological attributes of wetlands are important in their economic and biological usefulness. To this end, this research answers questions such as: what are the attributes of the wetland in the study area? Do the wetland attributes have influence on food security status of the households? The study was conducted in the wetlands of Ogun River and its tributaries located in the South-western Nigeria. Primary data were collected through the use of personally administered questionnaire and interview. Two stage sampling technique was used in selecting 633 households included in this study. Data were analyzed using descriptive techniques; United States Department of Agriculture (USDA) food security module and binary Logit model. The result revealed that wetlands of upper Ogun have abundance of all wetland attributes examined. Food security situation in households with children was not different from those without children. Majority of wetland residents’ households were not food secure leaving about a quarter as food secured. All the eight wetland attributes examined in this study had potential of increasing food security among wetland households as food security was constituently higher in wetlands with abundance of these attributes as against where they are limited. Socio-economic characteristics and wetland attributes have influence on food security status of households. The study therefore recommends that wetlands that are deep and free flowing with unobstructed water ways should be developed by government, international development agencies and non-governmental organizations so as to improve food security status in wetlands areas
The composition and determinants of rural non-farm income diversification in Nigeria
Farming has been considered as main source of income for rural households in Nigeria, despite their involvement in other income generating activities. Focusing on income derivable from farming alone may be partially responsible for the ineffective poverty reduction strategies in Nigeria. Using the National Living Standard Survey data collected by the National Bureau of Statistics, this paper investigated the composition and determinants of non-farm incomes of rural households in Nigeria. The results show that the share of farm, non-farm wage (NFW)- and self-employment (NFS) incomes in total household incomes were 24.3%, 43.0% and 23.7% respectively. Households whose heads are male (0.647), had formal education (0.522), increased the likelihood of households’ participation in NFW activities, while access to credit (-0.307) and having larger farm size (-0.221) decreased it. Access to credit (0.379); community participation (0.103); larger family size (0.193) and possession of capital assets (0.069) increased the likelihood of participation in NFS-employment activities, while having larger farm size (-0.211) decreased it. The study concludes that policy targeting poverty reduction should focus on providing enabling environment for poor households’ access to non-farm activities in the study area