Crop insurance is one of the methods by which farmers can stabilize farm income, investment and guard against disastrous effect of losses due to natural hazards or low market prices. Crop insurance not only stabilizes the farm income but also helps the farmers to initiate production activity after a bad agricultural year. The study was conducted in Karnataka State during 2017-18 by using “Ex-post- facto” research design. Belgavi, Dharwad, Haveri and Vijayapura districts were selected purposely based on more number of insured farmers. Further, two taluks from each district and from each taluk three villages (i.e. total 24 villages) were selected randomly. Sample size for the study was 240. Purposive sampling procedure was used. The data collected from respondents were tabulated and analyzed by using Garrett’s Ranking Technique. The findings of the study revealed that, delay in getting the claim was the prime constraint faced by the insured farmers with a highest Garret Score (GS) of 73.53 and ranked as first (I), followed by inadequate compensation (GS-61.51 and Rank-II) and officials bias in loss assessment (GS-56.42 and Rank-III). With respect to suggestions given by the farmers were, claim should be dispersed before starting of the next season with utmost priority by farmers with a Garret Score of 75.70 and ranked first (I), followed by creation of separate insurance cell at Block / Taluk level (GS-66.40 & Rank-II) and more number of trainings need to be organized on Crop Insurance Scheme (GS-54.91 & Rank-III). The study brought out various constraints faced by the farmers related to Crop Insurance Schemes. Thus, concerned officers should approach the State Government to make sincere efforts to pay the claim before the start of next season and conduct more number of training and awareness programmes. Non-loanee farmers also should be encouraged by simplifying the online registration process and making the ‘Samrakshane Portal’ farmer friendly.
To break the productivity barriers in Bt cotton (Gossypium spp.), adoption of optical sensor based nitrogen (N) management practices is the need of the hour. In light of this, a field experiment was conducted at the main Agricultural Research Station, Dharwad, Karnataka during rainy (kharif) season 2019 and 2020 to optimize the response index (RI) and sufficiency index (SI) for real time nitrogen management in Bt cotton through optical sensors. Experiment was conducted in split plot design with 16 treatment combinations having 2 genotypes (main plot) and 8 N management practices (subplot). Pooled data indicated that non-significant (P=0.3480) difference in seed cotton yield was observed with genotypes (First Class and Ajeet 155 recorded 3313 and 3159 kg/ha, respectively). Seed cotton yields varied significantly (P<.0001) due to different optical sensor-based N management practices. N supplementation at 1.1–1.5 RI and 81–90% SI (4460 and 4412 kg/ha, respectively) produced higher but on par yields with RDF (4386 kg/ha) with saving of 15 kg N through sensors during both the years. Interactions were found non-significant (P>.9999). Similarly, N supplementation at 1.1–1.5 RI and 81–90% SI recorded significantly (P<.0001) higher number of good and bad opened bolls, total number of bolls, sympodials, seed cotton yield per plant, boll weight, lint index and harvest index but was found on par with RDF.
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