1Scientist (Agricultural Statistics)
2Scientist (Farm Machinery and Power)
3Scientist, (Agricultural Statistics)
4Principal Scientist, (Agricultural Economics)
5Ex principal scientist, (Farm Machinery and Power), Agricultural mechanisation division, ICAR-CIAE, Bhopal
Online published on 27 April, 2020.
The income of farmer is affected by so many factors including farm mechanization. At present, shortage of agricultural labour is an important bottleneck in agricultural production system. It is estimated that percentage of agricultural worker of total work force would drop to 25.7 per cent by 2050 from 54.6 per cent in 2011. Present study has an attempt to identify the important factors, which influencing farmer's income. A study was carried out in Bhopal region of Madhya Pradesh to quantify the agricultural mechanization. For this purpose, the primary data was collected from the farmers including the data on farmer's income. The main cropping pattern of the study area was soybean-wheat. The relationship of farmer's income with other factors like net cultivated area, area under soybean, area under wheat, irrigation intensity, human, animal and machine energy utilized have been analyzed. The ridge regression model was used that gave best fit to quantify the extent of relationship and influencing factors those were highly correlated. The average net cultivated area and annual income (not profit) of a farmer was found to be 4.67 hectare and 1.96 lacs respectively. The most influencing factors of farmer's income were identified using standardized regression coefficients. The ridge parameter at θ*= 0.021 was found suitable that stabilized the regression coefficients. The R2 and adjusted R2 for the fitted ridge regression were found to be 0.964 and 0.963 respectively. It was also found that the farmer's income was highly sensitive to area under wheat followed by net cultivated area, area under soybean and machine energy utilized.
Farmer's income, ridge regression, soybean-wheat cropping pattern