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首页> 外文期刊>Polish Journal of Environmental Studies. >The Assessment of AquaCrop Model in Predicting Rice Genotypes Grain and Biological Yield under Water Management Conditions
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The Assessment of AquaCrop Model in Predicting Rice Genotypes Grain and Biological Yield under Water Management Conditions

机译:水稻基因型预测水稻基因型的评估及水管理条件下的水稻及生物屈服

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摘要

The present study was conducted to assess the ability of AquaCrop model in predicting genotypes of rice genotypes grain and biological yield in water management on Rice Research Institute of Iran, for two consecutive years of 2017 and 2018. The type of experiment was split plot based on randomized complete block design with three replications per treatment. The main plot included of irrigation treatment at four levels, (flood irrigation, 5, 8 and 11 days intervals) and sub plot, included of Ali kazemi, Dorfak and Bahar rice genotypes. Evaluation simulated and measured grain yield and biological yield by adjusted coefficient of correlation and by absolute and normalized root mean square errors (RMSEn). The results indicated, the RMSEn for predicting the amounts of grain yield in validation and calibration phases for Ali kazemi, Dorfak and Bahar was assessed in the range of 6 to 8 and 8 to 9 percent respectively and the RMSEn for predicting amounts of biological yield in validation and calibration for rice genotypes was assessed in the range of 3 to 13 and 7 to 15 % respectively. The results showed that the AquaCrop model had acceptable accuracy in predicting grain yield and biological yield of the crop.
机译:进行本研究以评估Aquacrop模型在2017年和2018年连续两年中预测水稻基因型预测水稻基因型的基因型和生物产量的能力。基于的实验类型分开随机完整的块设计,每次治疗三种复制。在四个层面的灌溉治疗中包含的主要情节,(洪水灌溉,5,8和11天间隔)和子地块,包括Ali Kazemi,Dorfak和Bahar水稻基因型。评价通过调整的相关系数和绝对和归一化的根均方误差(RMSEN)进行模拟和测量籽粒产量和生物产量。所指出的结果,用于预测Ali Kazemi,Dorfak和Bahar的验证和校准阶段的籽粒产量的RMSEN分别在6至8至8至9%的范围内,RMSEN用于预测生物收率的量水稻基因型的验证和校准分别在3至13和7至15%的范围内进行评估。结果表明,Aquacrop模型在预测作物的谷物产量和生物收率方面具有可接受的准确性。

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