Statistical analysis of factors affecting crop production in Navrongo, Tono irrigation dam a case study

D. Jakperik* and S. Oduro

University for Development Studies, Tamale, Department of Statistics, Navrongo Campus, Ghana.

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AbstractThis study identified the essential factors of production in the Tono irrigation dam of the Upper East Region. The accessibility and patronage of these factors by farmers in this area was studied and how they influence crop production in the Region. A total of two hundred questionnaires designed by the Ministry of Food and Agriculture for farmers in Navrongo were administered. A snowball sampling design was employed to identify farmers on these facilities in the study area. Pearson correlation coefficient, principal component analysis, and subset regression analysis were used to unveil the relevant information in the study. The results revealed a high correlation between the factors of production being studied with each pair having a probability level less than 0.0001. The full general linear model was highly significant (F=662.50, p<0.0001) with only two factors (Farm size and Fertilizer) accounting for 98.86% of the total variation in yield. This is a clear indication of multicollinearity and a subset regression analysis was used to identify the best subset that improves yield in the irrigation dam. The best subset comprised of Age, Farm size, seed, and Fertilizer accounting for 97.75% of the total variation in crop production in Navrongo. To enhance yield in Navrongo therefore, high yielding seeds, timely granting of fertilizer credit to farmers who mature enough and responsible with reasonable farm sizes should be encouraged.

Keywords: Subset Regression, Yield, Multicollinearity 

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