Affiliation:
1. DIT University, India
2. Veer Chandra Singh Garhwali Uttarakhand University of Horticulture and Forestry, India
Abstract
This chapter observed the latent and construct variables in the farming sector of Gujarat, India through confirmatory factor analysis (CFA). Thereupon, per hectare farm income (FI/Ha) (farm productivity) was used as dependent variable (DV), and climatic factors, appropriate technology, technological development, agricultural development institutions (ADIs), human resource, cropped area, irrigated area, fertilizer, and adaptation strategies were used as independent variables (IVs) in the regression model. The qualitative and quantitative statistics of 240 farmers were used for CFA and regression analysis. The results based on CFA and regression analysis provided confirmation that FI/Ha was negatively affected due to variability in climatic factors (i.e., maximum temperature, actual rainfall, and average precipitation). Annual income, farming of cash crops, income from non-agricultural sources, economic viability of technology, technical and institutional support, technological advancement, and adaptation strategies were appeared useful to increase FI/Ha.
Cited by
7 articles.
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