Abstract
The production of Brassica juncea, often known as mustard, holds significant importance in the field of world agriculture as it serves as a crucial source of edible oil, sauces, and livestock feed. The significance of enhancing mustard crop output and quality has escalated in recent years, primarily driven by the increasing demand for edible oils and the imperative for sustainable farming techniques. This abstract provides a comprehensive evaluation of mustard crop yields, with a particular focus on the use of scientific methodologies and on-site observations to enhance productivity. The research was conducted during the year of 2021–2022, where the estimated yields were compared based on the average yield of three consecutive years (18–20) from the Directorate of Economics and Statistics (DES). The results obtained indicate a variation of around 20% in yield differences across all the districts selected for the study. In order to assess the efficacy of our model, a series of statistical analyses were conducted. The findings revealed a range of correlations between 0.8 and 0.9, as well as R-squared values ranging from 0.54 to 0.82. The root mean square standard error (RMSE) varies from 4 to 21%, whereas the D-values vary from 0.85 to 0.93. The obtained result demonstrates a significant use of the radiation use efficiency model in predicting mustard crop production, hence providing valuable assistance in yield forecasting. The agricultural sector plays a crucial role in the Indian economy, as well as in guaranteeing food security.
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Shweta, Rai, P.K., Pandey, R.J. (2024). Mustard Yield Forecast Using Radiation Use Efficiency Method. In: Tripathi, G., Shakya, A., Kanga, S., Singh, S.K., Rai, P.K. (eds) Big Data, Artificial Intelligence, and Data Analytics in Climate Change Research. Advances in Geographical and Environmental Sciences. Springer, Singapore. https://doi.org/10.1007/978-981-97-1685-2_12
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DOI: https://doi.org/10.1007/978-981-97-1685-2_12
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