Awareness of Farmers on Weather Based Agro Advisory Services in Telangana State, India
A. Harshini, K. Madhu Babu, Ch. Venu Gopala Reddy, K. Suhasini
International Journal of Environment and Climate Change · pp. 355–365 · Published 16 Aug 2023
10.9734/ijecc/2023/v13i102648Abstract
Agriculture production is significantly influenced by the weather. From seeding to crop harvest, it has a significant impact on all aspects of farming. Crop germination, establishment, growth, development and yield are all affected. Extreme weather conditions including drought, floods, heavy rains, heat waves, frost, hailstorms, cyclones, etc. may cause the farming community to suffer significant crop yield losses. Since the farming community will be aware of the upcoming weather conditions in advance, required adjustments may be made to farm level agricultural operations and decisions to lessen the consequences of unfavorable weather conditions. Therefore, Integrated Agro met Advisory Services will make it possible for the farmer to be informed of current and expected weather as well as advice to the farmer the best course of action to reduce losses caused by unfavorable weather conditions and increase the output of agricultural systems. A study was conducted in Telangana state to ascertain the degree of farmer’s awareness on weather-based agro advisory services. Random sampling technique employed to collect data from 120 farmers. Ex-post facto research design was used for the investigation. The data with regards to level of awareness possessed by farmers about weather based agro advisory services, it is revealed that 38.33 % of them had the medium level of awareness followed by low level 35.01 % and high level 26.66% of awareness, respectively. All profile characteristics of respondents showed a significant correlation with the degree to which farmers were aware of weather-based agro advisory services, with the exception of education, annual income, farming experience, mass media exposure, and cropping pattern. Multiple linear regression value 77.61 per cent contributed to the extent of variation towards independent variables.
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