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The aim of the study is to ascertain the perception of farmers towards Pradhan Mantri Fasal Bima Yojana (PMFBY).The research design adopted for this study is an ex-post facto. The present investigation was carried out in Konganapuram and Kadayampatti  block of Salem district of Tamil Nadu. The duration of the study is from 2020-2021. As per the list provided by Joint Director of Agriculture and other officials  farmers were selected from each village, who have registered under P.M.F.B.Y. Respondents were selected from each village through proportionate sampling method and the sample size was 117. Based on judges’ opinion and review of literature, the well-structured interview schedule was prepared and used to collect data from the respondents. The collected data were coded, quantified, classified, tabulated and analyzed with the help of frequency and percentage to get the inference. The statement like all farmers can pay the amount of premium under crop insurance ranked as I (MS - 2.52) followed by the damage caused by fire and electricity must be included in Insurance (MS - 2.44), It is mandatory for all farmers to get crop insurance (MS - 2.42) were ranked as 2 and 3 respectively. As crop insurance protects the farmers from the uncertainty of risk in farming like natural calamities (floods, droughts, cyclones, and earth quakes, etc.). That crop insurance is mandatory for every type of farmer; Government should take the initiative to give subsidies for small scale farmers and large-scale farmers as a basis of proportion to their income levels.

We aimed to estimate Soil Nutrients and relate the spectral signatures to that of the Laboratory reference Measurements utilizing CART analysis. Sustainable agriculture aims at controlled and/or precise soil fertility interventions based on spatial soil information. The profound advancements in remote sensing and geospatial techniques provide means for determining the spatial coverage and variability of the soil properties through the survey and image data incorporated in the mapping procedures (i.e.) Digital Soil Mapping. The soil moisture content at varying levels influences crop growth and decides the yield, as the crop requires water at critical crop growth stages.  Machine learning techniques provide the means of optimized model calibration when compared to conventional geostatistical or statistical approaches.