INDEX OF SOYBEAN TECHNOLOGY ADOPTION AND MULTIVARIATE CORRELATIONS IN SMALLHOLDER SYSTEMS

Godfrey Onuwa () and Oludare Adedire
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Godfrey Onuwa: Department of Agricultural Extension and Management, Federal College of Forestry, Jos, Nigeria.
Oludare Adedire: Department of Statistics, Federal College of Forestry, Jos, Nigeria.

Big Data In Agriculture (BDA), 2023, vol. 6, issue 1, 22-25

Abstract: This study aims to critically highlight appropriate soybean production techniques that enhance levels of agricultural productivity. Therefore, it analyzed soybean production technologies and multivariate correlations in smallholder systems at Jos East, Plateau State, Nigeria. The respondents (120) were selected via multistage techniques. Descriptive statistics, adoption index and multivariate correlation techniques were used to analyze data collected via questionnaires. Soybean production technologies mainly applied by farmers in the area include planting on ridge (81%), improved varieties (80%) and appropriate harvest date (51%); most (67.5%) have a low adoption index of ≤0.36. The correlation coefficients of the multivariate factors (farm output, adoption cost, and adoption index) were significant at rxz (-0.64,), ryz (0.79) and rxy (-0.75), respectively. The identified constraints are barriers to technology adoption. Therefore, the study recommends improved input supply and subsidies, improved advisory services, credit access and market linkages.

Keywords: Adoption Constraints; Cost of Adoption; Agricultural Practices/Technologies; Correlation Analysis; Index of Adoption; Soybean Productivity. (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:zib:zbnbda:v:6:y:2023:i:1:p:22-25

DOI: 10.26480/bda.01.2023.22.25

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