Evaluation of CERES –Rice Model for Simulating Rice Yield and Phenophases

H. V., G. K. Das, S. Chandniha, H.V. Puranik, J.L. Chaudhary
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Abstract

In this study, the performance of the CERES-Rice model in simulating the growth and yield of the Rajeshwari variety in the Raipur district of Chhattisgarh, India, was evaluated. Utilizing observed data from 2021 and 2022, the model was calibrated and validated using key parameters such as days to anthesis, physiological maturity, and yield. Calibration involved adjusting genetic coefficients to improve simulation accuracy, with validation ensuring the model's reliability beyond the calibration period. The comparison between observed and simulated data for crop performance parameters showed that the model performed reasonably well. For days to Anthesis, the RMSE was 4.32 with a d-stat of 0.59, and an error of 5.4%. For Days to Panicle initiation, the RMSE was 1.83, the d-stat was 0.82, and the error was -4.7%. For days to PM, the RMSE was 6.7, the d-stat was 0.65, and the error was 3.0%. Yield showed an RMSE of 472.4, a d-stat of 0.81, and an error of 7.7%. F The mean simulated values closely matched the observed means, indicating overall good model accuracy. In this study, fine tuning the genetic coefficients of CERES rice model for the variety Rjeshwari was done and can be used for further studies and applications.
评估模拟水稻产量和物候期的 CERES -Rice 模型
本研究评估了 CERES-Rice 模型在模拟印度恰蒂斯加尔邦赖普尔地区 Rajeshwari 品种的生长和产量方面的性能。利用 2021 年和 2022 年的观测数据,使用花期天数、生理成熟度和产量等关键参数对模型进行了校准和验证。校准包括调整遗传因子以提高模拟精度,而验证则确保模型在校准期之后的可靠性。作物表现参数的观测数据与模拟数据的比较表明,该模型的表现相当不错。对于开花天数,均方根误差为 4.32,d-stat 为 0.59,误差为 5.4%。在圆锥花序形成天数方面,均方根误差为 1.83,d-统计量为 0.82,误差为-4.7%。至始花期天数的均方根误差为 6.7,d-统计量为 0.65,误差为 3.0%。产量的均方根误差为 472.4,d-统计量为 0.81,误差为 7.7%。F 模拟的平均值与观测的平均值非常吻合,表明模型的整体准确性很高。本研究对 Rjeshwari 品种的 CERES 水稻模型遗传因子进行了微调,可用于进一步的研究和应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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