当前位置: X-MOL 学术Commun. Soil Sci. Plant Anal. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Simulating the Production of Rice Genotypes by Flood Management and End-Season Water Stress Conditions Using AquaCrop Model
Communications in Soil Science and Plant Analysis ( IF 1.3 ) Pub Date : 2020-09-07 , DOI: 10.1080/00103624.2020.1813750
Ali vahdati 1 , Naser Mohebalipour 1 , Ebrahim Amiri 2 , Ali Akbar Ebadi 3 , Ali Faramarzi 1
Affiliation  

ABSTRACT The present study was conducted to assess the ability of AquaCrop model in predicting of grain and biological yield of rice genotypes in water management. A two-year field experiment was conducted at the experimental farm of the Iranian Rice Research Institute in Rasht, Iran from 2016 to 2017. The experiment was established in a split-plot design with two irrigation management (continuous submergence and end season water stress) as the main plot, fourth rice genotypes as the sub-plot and three replications. The goodness-of-fit between observed and simulated grain yield and final biomass was assessed by means of the coefficient of determination (R 2), the absolute and normalized root mean square errors (RMSE). The RMSEn of predicting grain yield at calibration and evaluation stages was in the range of 6–12% and 6–8% for biological yield. The results indicated that AquaCrop model is suitable to predict grain yield and biological yield of rice genotypes in northern Iran. AquaCrop model can be used to determine optimization strategies to improve the water consumption of rice genotypes.

中文翻译:

使用 AquaCrop 模型模拟通过洪水管理和季末水分胁迫条件生产水稻基因型

摘要 本研究旨在评估 AquaCrop 模型在预测水分管理中水稻基因型的谷物和生物产量方面的能力。2016-2017年在伊朗拉什特的伊朗水稻研究所试验农场进行了为期两年的田间试验。该试验采用裂区设计,采用两种灌溉管理(连续淹没和季末缺水)以4个水稻基因型为主区,次区为3个重复。通过确定系数 (R 2)、绝对和归一化均方根误差 (RMSE) 评估观察到的和模拟的谷物产量与最终生物量之间的拟合优度。在校准和评估阶段预测谷物产量的 RMSEn 在生物产量的 6-12% 和 6-8% 的范围内。结果表明,AquaCrop模型适用于预测伊朗北部水稻基因型的粮食产量和生物产量。AquaCrop 模型可用于确定优化策略以提高水稻基因型的耗水量。
更新日期:2020-09-07
down
wechat
bug