Ayedun Bamikole1*, Abdoulaye Tahirou2 and Okuneye Peter Adebola1
1Department of Agricultural Economics and Farm Management, Federal University of Agriculture, Abeokuta, Nigeria
2Senior Agricultural Economist, Socioeconomic Unit, International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria.
*Corresponding Author: Ayedun Bamikole, Department of Agricultural Economics and Farm Management, Federal University of Agriculture, Abeokuta, Nigeria.
Received: November 25, 2019; Published: December 31, 2019
Cassava is a major food crop in sub-Saharan Africa. Increases in its productivity and processing can be a driver for higher food security and commercialization of its products. The study assessed the effect of adopting production and processing technologies and profitability of cassava in southern Nigeria. Poverty status of the users and non-users of the technologies was also estimated. Data were obtained using structured questionnaires from 480 farming households from the three southern geographical zones of Nigeria using a multistage sampling technique. Data were analyzed using descriptive statistics, budgetary analysis, P-Alpha Measures of Poverty (FGT) and Logit model. Results showed that of all production technologies disseminated, awareness and adoption of improved cassava varieties both in intervention villages (IVs) and non-intervention villages (NIVs) were the highest compared to other technologies. The IVs had 93% awareness rate and 72% adoption rate, while NIVs had 81% awareness rate and 64% adoption rate on improved cassava varieties. On processing technologies among farm households, grating machine had the highest level of awareness and adoption rate in both IVs and NIVs. However, apart from grater, presser, fryer and grinder which were common before interventions by ICP, participants in training (PARTI) were more exposed to other machines and adopted more of them than any other groups.
On budgetary analysis, the return per capital outlay (RPN) for improved practice was 3.1 compared to that of local that was 2.3. The implication was that by investing N1 (one naira) in production, local cassava producer made a N2.3 gain on average, while the improved cassava variety producer would make N3.1; with the difference being attributed to the relative use of both improved cassava varieties and various management techniques extended to and used by the farmers. Poverty status estimation revealed that 57.4% of farm households from IVs and 46.6% of farm households from NIVs were above the poverty line. The percentage of households below poverty was lower for IV (42.6%) than for NIV (53.4%) if compared along village type’s line. When compared along participation in training, it was lower for participants (45.9%) than for non-participants (52.3%); and when compared along adoption status for improved variety line, it was lower for adopters (45.9%) than non-adopters (51.7%) and in case of adoption status for the grater machine, it was lower for adopters (45.3%) than non-adopters (59%). Poverty depth index and poverty severity estimates also buttressed that respondents that were from intervention villages, which participated in extension training and adopted new technologies, had lower poverty values than their counterparts. The Logit model revealed that adoption of a grater machine (P < 0.01), non-farm income (P < 0.05), medical expenses (P < 0.01), social contribution (P < 0.05), and level of education (P < 0.01) had a poverty reducing effect among the households. The study concluded that the technologies adopted impacted positively on farmers’ yields and varieties of different products made from cassava and reduced the poverty in the study area. The study, therefore recommended increased promotion of the technologies through farm demonstration by relevant stakeholders and agricultural institutions for enhanced livelihoods.
Keywords: Food Security; FGT; Productivity; Poverty Status
Citation: Ayedun Bamikole., et al. “Effects of Adoption of Cassava Technologies on Farmers from Southern Zones of Nigeria". Acta Scientific Nutritional Health 4.1 (2020): 152-164.
Copyright: © 2020 Ayedun Bamikole. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.