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Dr. Rajendra Prasad Central Agricultural University, Pusa

In the imperial Gazetteer of India 1878, Pusa was recorded as a government estate of about 1350 acres in Darbhanba. It was acquired by East India Company for running a stud farm to supply better breed of horses mainly for the army. Frequent incidence of glanders disease (swelling of glands), mostly affecting the valuable imported bloodstock made the civil veterinary department to shift the entire stock out of Pusa. A British tobacco concern Beg Sutherland & co. got the estate on lease but it also left in 1897 abandoning the government estate of Pusa. Lord Mayo, The Viceroy and Governor General, had been repeatedly trying to get through his proposal for setting up a directorate general of Agriculture that would take care of the soil and its productivity, formulate newer techniques of cultivation, improve the quality of seeds and livestock and also arrange for imparting agricultural education. The government of India had invited a British expert. Dr. J. A. Voelcker who had submitted as report on the development of Indian agriculture. As a follow-up action, three experts in different fields were appointed for the first time during 1885 to 1895 namely, agricultural chemist (Dr. J. W. Leafer), cryptogamic botanist (Dr. R. A. Butler) and entomologist (Dr. H. Maxwell Lefroy) with headquarters at Dehradun (U.P.) in the forest Research Institute complex. Surprisingly, until now Pusa, which was destined to become the centre of agricultural revolution in the country, was lying as before an abandoned government estate. In 1898. Lord Curzon took over as the viceroy. A widely traveled person and an administrator, he salvaged out the earlier proposal and got London’s approval for the appointment of the inspector General of Agriculture to which the first incumbent Mr. J. Mollison (Dy. Director of Agriculture, Bombay) joined in 1901 with headquarters at Nagpur The then government of Bengal had mooted in 1902 a proposal to the centre for setting up a model cattle farm for improving the dilapidated condition of the livestock at Pusa estate where plenty of land, water and feed would be available, and with Mr. Mollison’s support this was accepted in principle. Around Pusa, there were many British planters and also an indigo research centre Dalsing Sarai (near Pusa). Mr. Mollison’s visits to this mini British kingdom and his strong recommendations. In favour of Pusa as the most ideal place for the Bengal government project obviously caught the attention for the viceroy.

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Author: KRISHNA, GAJJARAPU JAYA × Start date: 2020 × Type: Thesis ×
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    ThesisItemOpen Access
    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
    (RPCAU, Pusa, 2023) KRISHNA, GAJJARAPU JAYA; KUMAR, MAHESH
    This 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.