Abstract

The Nigerian agricultural sector is characterized by low level of technology adoption which in turn contributes to the low agricultural productivity in the country. This is indeed worrisome given the plethora of interventions by successive governments, multi-lateral and donor agencies working to implement several programmes aimed at promoting technology adoption among farmers. This study examines factors which influence adoption of modern agricultural production technologies among African Development Bank-Community Based Agriculture and Rural Development Programme (AfDB-CBARDP) beneficiaries in Nigeria. To achieve this objectives, Multi stage sampling technique was employed where a total of 1020 farmers/Project beneficiaries across the 5 Project Implementing Units were selected. The data was estimated using the logit regression. The use of the logit model for this analysis is consistent with the literature on adoption (see for instance Griliches, 1957). Result of the maximum likelihood estimates of the Logit regression model has indicated that the relationship between income and improved technology adoption was shown to be positive and statistically significant. Farming experience was also positively related to adoption of the improved technologies and statistically significant at 1% level. The study also reveals that adoption of improved farming technologies increases with credit availability. Farm size on the other hand was negatively related to adoption of fertilizer technology but positively related to seed, post-harvest and livestock improvement technologies at 1% significant level. Correspondingly, the coefficients for improved seed and livestock technologies were positively related to the farmer’s age at 5% significant level. The findings of the study further revealed that profitability of the enterprise is the major reason for technology adoption by the beneficiaries and is considered very important (3.7*). Output/yield and product marketability was the second and most important reasons for technology adoption having a weighted mean scores value of 3.1* and 3.3* respectively. Likewise, among the bundles of technology disseminated under crop sub sector, varietal attributes related to early maturity was adjudged to be important motive for the adoption (2.7*). Inaccessibility of the technology or high cost of production were cited prominently as the main reasons for non-adoption of a particular technology (*Reason ≥2.5). These findings have important implication. The availability of modern agricultural production technologies to end users, and the capacities of end users to adopt and utilize these technologies should always be consider when scaling up innovation practices.

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