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PRINT ISSN : 2319-7692
Online ISSN : 2319-7706 Issues : 12 per year Publisher : Excellent Publishers Email : editorijcmas@gmail.com / submit@ijcmas.com Editor-in-chief: Dr.M.Prakash Index Copernicus ICV 2018: 95.39 NAAS RATING 2020: 5.38 |
Climate change is predicted by scientists to have the main impact on agriculture, economy and livelihood of the populations of developing countries. Human expectations regarding weather and climate sometimes lead to perceptions of climate change which are not supported by observational evidences. A better understanding of how farmers’ perceive climate change is needed to craft policies and programmes aimed at promoting successful adaptation of the agricultural sector. The present study was carried out in Chhattisgarh state during the years 2016. In this study, the relationship between dependent variables and selected independent variables were ascertained by calculating correlation coefficient (‘r’ value) and multiple regression analysis. In case of impact of climate change twenty variables like Age (X1), Educational status (X2), Farming experience (X4), Social participation (X5), Land holding (X7), Irrigation (X8), Annual income (X10), Annual expenditure (X11), Distance to market (X12), Socio-economic status (X13), Crop insurance (X14), Sources of information (X15), Exposure to mass media (X16), Contact with extension personnel (X17), Access to weather forecasts (X18), Cosmopoliteness (X19), Awareness (X20), Innovativeness (X22), Scientific orientation (X23), Risk orientation (X24) were highly and positively significantly correlated with perception of farmers about impact of climate change on agriculture and allied activities (Y2) at 0.05 level of probability. Out of twenty three variables considered in the model, seven variables like age (X1), land holding (X7), irrigation (X8), annual income (X10), exposure to mass media (X16), awareness (X20) and innovativeness (X22) showed significant contribution on predicting perception of farmers’ about climate change (Y1) at 0.05 level of probability. It was found that the model developed by considering variables (X1, X7, X8, X10, X16, X20 and X22) showing significant relationship with dependent variable (Y1) explained highest variation (49.40%) in predicting perception of farmers’ about climate change with significant ‘F’ value (32.344) at 5 per cent level of probability. It was found that the model developed by considering variables (X1, X3, X8, X12, X15, X20 and X22) showing significant relationship with dependent variable (Y2) and explained highest variation (60.80%) in predicting perception of farmers’ about climate change with significant ‘F’ value (51.384) at 5 per cent level of probability.