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Chaudhary Charan Singh Haryana Agricultural University, Hisar

Chaudhary Charan Singh Haryana Agricultural University popularly known as HAU, is one of Asia's biggest agricultural universities, located at Hisar in the Indian state of Haryana. It is named after India's seventh Prime Minister, Chaudhary Charan Singh. It is a leader in agricultural research in India and contributed significantly to Green Revolution and White Revolution in India in the 1960s and 70s. It has a very large campus and has several research centres throughout the state. It won the Indian Council of Agricultural Research's Award for the Best Institute in 1997. HAU was initially a campus of Punjab Agricultural University, Ludhiana. After the formation of Haryana in 1966, it became an autonomous institution on February 2, 1970 through a Presidential Ordinance, later ratified as Haryana and Punjab Agricultural Universities Act, 1970, passed by the Lok Sabha on March 29, 1970. A. L. Fletcher, the first Vice-Chancellor of the university, was instrumental in its initial growth.

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Subject: Statistics × Author: Sanjeev × End date: 2022 × Start date: 2022 × Thesis Type: Ph.D ×
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    ThesisItemOpen Access
    A comparative study of forecast models for sugarcane yield prediction of Haryana
    (CCSHAU, Hisar, 2022-11) Sanjeev; Bhardwaj, Nitin
    Crop yield prediction is one of the most difficult issues in precision agriculture, and numerous models have been proposed. Because agricultural production is affected by a variety of factors such as climate, weather, soil, fertilizer, and seed variety. The most commonly used features in these models are temperature, rainfall, and soil type. Crop yield forecasting plays an important role for decision-makers at the national and regional levels. An accurate crop yield forecast model can help farmers decide what to plant and when to plant. Furthermore, as agricultural trade expanded and transportation infrastructure improved, farmers adopted a more business-like mindset and stopped viewing themselves as subsistence units. The study developed and compared the accuracy of sugarcane yield prediction models such as ARIMA, ARIMAX, ANN, NARX and Hybrid (ARIMA-ANN, ARIMAX-ANN) for the Karnal, Ambala, Kurukshetra, Yamunanagar, Panipat districts and Haryana as whole. The development of various models made use of time series data on sugarcane yields as well as fortnightly weather data on average maximum temperature, average minimum temperature, and accumulated rainfall over the crop period for Karnal, Ambala and Haryana from 1966–1967 to 2014–15, Kurukshetra, Yamunanagar, and Panipat from 1972–1973 to 2014–15. The yield data period from2015-16 to 2019-20 has been used to check the validity of the fitted models for sugarcane yield. The statistical modeling approaches viz., stepwise multiple linear regression, ARIMA, ARIMAX, ANN, NARX and Hybrid (ARIMA-ANN, ARIMAX-ANN) were applied for the study. ARIMAX and NARX models were developed to predict sugarcane yield for selected districts and Haryana using weather variable selected from stepwise multiple linear regression. Finally, forecast performance(s) of the fitted models were observed in terms of percent relative deviation, root mean square error and mean absolute percentage error of sugarcane yield forecasts from observed yield(s). Hybrid (ARIMA-ANN, ARIMAX-ANN) models performed well with lower error metrics as compared to the other fitted models. Five-steps ahead forecast figures i.e. 2015-16 to 2019-20 favored the use of Hybrid models to obtain sugarcane yield forecasts in all selected districts and Haryana under study. Empirical evidence from this study confirms that the Hybrid models can produce reliable forecasts. Therefore, developed forecast models are capable of providing reliable estimates of sugarcane yield well in advance while yield estimates given by state department were obtained quite later.