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温室不同灌溉水平下DSSAT-CROPGRO-番茄模型的参数估计与验证

[Parameter estimation and verification of DSSAT-CROPGRO-Tomato model under different irrigation levels in greenhouse.].

作者信息

Zhao Zi Long, Li Bo, Feng Xue, Yao Ming Ze, Xie Ying, Xing Jing Wei, Li Chang Xin

机构信息

College of Water Conservancy, Shenyang Agricultural University, Shenyang 110866, China.

College of Science, Shenyang Agricultural University, Shenyang 110866, China.

出版信息

Ying Yong Sheng Tai Xue Bao. 2018 Jun;29(6):2017-2027. doi: 10.13287/j.1001-9332.201806.012.

Abstract

Based on the greenhouse experiment in Shenyang, the growth, development, and yield formation of tomato under different irrigation levels were simulated by growth model DSSAT-CROPGRO-Tomato. The optimal scheme of parameter estimation and model validation was determined. There were four treatments in this experiment. Irrigation upper limit of whole growth season was set as field capacity, while the lower limit was 50% (W), 60% (W), 70% (W), and 80% of field capacity (CK), respectively. The relevant genetic coefficients were estimated by DSSAT-GLUE, a program package for parameter estimation in DSSAT. The differences between simulated and observed values of phenological phase, canopy height, shoot dry matter, tomato fresh mass, leaf area index (LAI), and soil moisture were analyzed to determine the accuracy of simulation. The results showed that the estimated value of genetic parameter of tomato (thermal time for final pod load appeared greater variability under optimal genetic coefficient of tomato, PODUR) had large variability, with the coefficient of variation being 11.5%. When the CROPGRO-Tomato model was applied to the greenhouse in different regions, the PODUR should be estimated adequately. Otherwise, the accuracy of simulation would be affected. In the process of model application, the observation data of sufficient irrigation treatment should be selected for estimating genetic parameters, which could improve the simulation precision. The absolute relative error and standard root mean square error were 8.7% and 10.5%, respectively. The simulation results of LAI and soil moisture showed that the higher the irrigation level was, the higher accuracy of simulation was. By leave-one-out cross validation, the overall error validation ranged from 10.5% to 12.5%. Our results indicated that the growth, development, and yield formation of tomato could be accurately simulated by DSSAT CROPGRO-Tomato model under different irrigation conditions in Shenyang greenhouse.

摘要

基于沈阳的温室试验,利用生长模型DSSAT-CROPGRO-Tomato模拟了不同灌溉水平下番茄的生长、发育及产量形成过程。确定了参数估计和模型验证的最优方案。本试验设置了4个处理,将全生育期灌溉上限设定为田间持水量,下限分别为田间持水量的50%(W)、60%(W)、70%(W)和80%(CK)。利用DSSAT中的参数估计程序包DSSAT-GLUE估计相关遗传系数。分析了物候期、株高、地上部干物质、番茄鲜质量、叶面积指数(LAI)和土壤水分的模拟值与观测值之间的差异,以确定模拟的准确性。结果表明,番茄遗传参数(最终豆荚负载热时间,在番茄最优遗传系数PODUR下变异较大)的估计值变异较大,变异系数为11.5%。当CROPGRO-Tomato模型应用于不同地区的温室时,应充分估计PODUR,否则会影响模拟精度。在模型应用过程中,应选择充分灌溉处理的观测数据来估计遗传参数,以提高模拟精度。绝对相对误差和标准均方根误差分别为8.7%和10.5%。LAI和土壤水分的模拟结果表明,灌溉水平越高,模拟精度越高。通过留一法交叉验证,总体误差验证范围为10.5%至12.5%。我们的结果表明,在沈阳温室不同灌溉条件下,DSSAT CROPGRO-Tomato模型能够准确模拟番茄的生长、发育及产量形成过程。

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