ANALYSIS OF PRODUCTION AND INVESTMENT OF FARMERS IN SOYABEAN ENTERPRISE IN TARABA STATE, NIGERIA

This study analyzed the production and investments of farmers in soybean (Glycine max) enterprise in Taraba State. The specific objectives of the study were to describe the socioeconomic characteristics of soybean farmers, identify the soybean varieties produced by the farmers, investigate the performance indices of producers, evaluate the determinants of profit efficiency and estimate the technical efficiency of soybean producers and their determinants in the study area. Multistage techniques were adopted for the study. Data were collected with the aid of a structured questionnaire. Data were analyzed using descriptive statistics, Stochastic Frontier Production function, and Tobit Regression. The results showed that females (54%) dominated the soybean enterprise with a mean farm size of 2.78 hectares. It was found that 44.4% of the respondents cultivated the TGX 1448–2E variety. 75.2% of the respondents invested between N250,000 and N500,000. The determinants of profit efficiency were farming experience, savings, sales, investment, cost of modern machines, and distance, which had positive and negative coefficients and were statistically significant at 1 and 5%, respectively. The R2 was 0.98, meaning that about 98% of the variations in the profit efficiency were explained by the explanatory variables. Fertilizers labour, and pesticides were positive and significant. Based on the findings, it was recommended that farmers should be encouraged to expand their scales of production by providing them with production inputs such as credit facilities, fertilizer, and Agrochemicals to increase yields and maximize profit.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-10-15
DOI
https://doi.org/10.5281/zenodo.13937208
Primary Topic
Spatial Cognition and Navigation
Type
article
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article

ANALYSIS OF PRODUCTION AND INVESTMENT OF FARMERS IN SOYABEAN ENTERPRISE IN TARABA STATE, NIGERIA

Zenodo (CERN European Organization for Nuclear Research)
Spatial Cognition and Navigation
article

ANALYSIS OF PRODUCTION AND INVESTMENT OF FARMERS IN SOYABEAN ENTERPRISE IN TARABA STATE, NIGERIA

article en

Abstract

This study analyzed the production and investments of farmers in soybean (Glycine max) enterprise in Taraba State. The specific objectives of the study were to describe the socioeconomic characteristics of soybean farmers, identify the soybean varieties produced by the farmers, investigate the performance indices of producers, evaluate the determinants of profit efficiency and estimate the technical efficiency of soybean producers and their determinants in the study area. Multistage techniques were adopted for the study. Data were collected with the aid of a structured questionnaire. Data were analyzed using descriptive statistics, Stochastic Frontier Production function, and Tobit Regression. The results showed that females (54%) dominated the soybean enterprise with a mean farm size of 2.78 hectares. It was found that 44.4% of the respondents cultivated the TGX 1448–2E variety. 75.2% of the respondents invested between N250,000 and N500,000. The determinants of profit efficiency were farming experience, savings, sales, investment, cost of modern machines, and distance, which had positive and negative coefficients and were statistically significant at 1 and 5%, respectively. The R2 was 0.98, meaning that about 98% of the variations in the profit efficiency were explained by the explanatory variables. Fertilizers labour, and pesticides were positive and significant. Based on the findings, it was recommended that farmers should be encouraged to expand their scales of production by providing them with production inputs such as credit facilities, fertilizer, and Agrochemicals to increase yields and maximize profit.

Zenodo (CERN European Organization for Nuclear Research)
Taraba State University (NG), University of Abuja (NG)
Decent work and economic growth
Openalex Percentile: Top 63%
Spatial Cognition and Navigation
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