DSSAT CROPGRO-Cotton模型校正与验证的遗传参数估计

G. Srinivasan, S. Pazhanivelan, S. Krishnasamy, N. S. Sudarmanian, S. Rajeswari, B. Kannan
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引用次数: 0

摘要

一般采用DSSAT CROPGRO-Cotton模型(4.7.5版本)来预测气候变化对生产力的影响。本研究的目的是在印度泰米尔纳德邦校准和验证该模型,以模拟不同种植日期(即7月28日,8月11日,8月18日,8月25日,9月8日和9月15日)下苏拉吉棉花品种的发育,生长和籽棉产量。该模型使用2019年收集的数据(物候、生物量和产量成分)进行校准。种子棉产量(kg ha-1)的CROPGRO-Cotton遗传系数标定在所有不同种植日期密度下,当标准化RMSE (NRMSE)值小于10%时,对开花天数、种植至首荚天数和生理成熟天数、LAI和籽棉产量的模拟均被认为是优秀的。最后,我们发现在合适的时间种植可以减轻天气波动对棉花产量的许多负面影响。结果表明,DSSAT模型可用于气候变化条件下的棉花种植决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimating Genetic Parameters for DSSAT CROPGRO-Cotton Model Calibration and Validation
DSSAT CROPGRO-Cotton Model (version 4.7.5) was generally used to forecast the effect of climate change on productivity. The objective of this study was to calibrate and validate this model in Tamil Nadu, India for simulation of development, growth and seed cotton yield of Suraj cotton cultivars under varied planting dates viz., 28th July, 11th August, 18th August, 25th August, 8th September and 15th September. The model was calibrated with data (phenology, biomass and yield components) collected during 2019. Calibration of CROPGRO-Cotton model with genetic coefficients of cultivar Suraj for seed cotton yield (kg ha-1). Simulation of days to flowering, days from planting to first pod and physiological maturity, LAI and seed cotton yield with normalized RMSE (NRMSE) values of less than 10% across all the various planting dates densities were considered excellent. Finally, we discovered that planting at the right time can mitigate many of the negative effects of fluctuating weather on cotton productivity. As a result conclude that DSSAT model will be used to make decision on cotton planting in changing climates.
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