FORECASTING OF RICE YIELD BASED ON BIOMETRICAL CHARACTERS AND ANALYSE THE PERFORMANCE OF PRADHAN MANTRI FASAL BIMA YOJANA IN WEST GODAVARI DISTRICT OF ANDHRA PRADESH

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dc.contributor.advisorKUMAR, MAHESH
dc.contributor.authorKRISHNA, GAJJARAPU JAYA
dc.date.accessioned2024-06-29T13:04:13Z
dc.date.available2024-06-29T13:04:13Z
dc.date.issued2023
dc.description.abstractThis study, conducted in West Godavari district, Andhra Pradesh, a prominent rice-producing region, employs biometrical characteristics to forecast rice yield and assesses the performance of the Pradhan Mantri Fasal Bima Yojana (PMFBY) program. Time series analysis reveals stable rice-growing area but increasing production and yield. The study identifies ten biometrical characteristics affecting rice yield, including plant population(X1), plant height(X2), tiller count(X3), panicle length(X4), nitrogen(X5), phosphorus(X6), potassium levels(X7), irrigation frequency(X8), disease infestation(X9), and plant condition(X10). Multiple regression analyses were conducted using these variables, resulting in a model selection process which includes R-square, adjusted R-square, Root Mean Square Error (RMSE), Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and Coefficient of Variation (CV) based on these 5 models are selected from overall possible models. Residual analysis of these 5 models favoured a third model of the selected five models for forecasting rice yield. The chosen model (Ŷ = 46.08838 + 0.80226X₁ + 0.14708X₂ - 0.36854X₃ - 0.02404X₅ + 0.02418X₇ + 1.28461X₈) having yield affecting characters such as plant population, plant height, tiller count, nitrogen application, potassium application and irrigation frequency adeptly forecasts rice yield (94.01 quintals/ha) and accounts for 52.6% of yield variation. These models were rigorously assessed for validity. The final selection was based on residual analysis, with a preference for models demonstrating the least Mean Absolute Percentage Error (MAPE), ensuring robust predictive performance. Furthermore, the study highlights the robust growth of PMFBY insurance scheme metrics, emphasizing higher Compound Annual Growth Rates (CAGRs) during Rabi seasons. In the 2022 Kharif season, 604,529 farmers were insured, covering 180.5 thousand hectares, with a gross premium of 105.07 crores and a sum insured of 1,756 crores. In conclusion, this research contributes significantly to precise rice yield prediction and showcases the effectiveness of PMFBY in West Godavari district, crucial for enhancing food security and economic stability.
dc.identifier.otherM/STAT/588/2021-22
dc.identifier.urihttps://krishikosh.egranth.ac.in/handle/1/5810211190
dc.keywordsForecasting
dc.keywordsRice yield
dc.keywordsBiometrical characters
dc.keywordsPradhan Mantri Fasal Bima Yojana
dc.keywordsWest Godavari district
dc.keywordsAndhra Pradesh
dc.language.isoEnglish
dc.pages105+ IV
dc.publisherRPCAU, Pusa
dc.subStatistics
dc.themeForecasting of Rice yield based on biometrical characters and analyse the performance of Pradhan Mantri Fasal Bima Yojana in West Godavari district of Andhra Pradesh
dc.these.typeM.Sc
dc.titleFORECASTING OF RICE YIELD BASED ON BIOMETRICAL CHARACTERS AND ANALYSE THE PERFORMANCE OF PRADHAN MANTRI FASAL BIMA YOJANA IN WEST GODAVARI DISTRICT OF ANDHRA PRADESH
dc.typeThesis
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