欢迎访问《生态学杂志》官方网站,今天是 分享到:

生态学杂志 ›› 2021, Vol. 40 ›› Issue (3): 908-918.doi: 10.13292/j.1000-4890.202103.009

• 技术与方法 • 上一篇    下一篇

温室秸秆不同还田量条件下DSSAT-CROPGRO-Tomato模型的调参与验证

李波,孙翔龙,姚名泽*,鲍慧,王俊皓   

  1. (沈阳农业大学水利学院, 沈阳 110866)
  • 出版日期:2021-03-10 发布日期:2021-03-17

Parameter estimation and verification of the DSSAT-CROPGRO-Tomato model under the condition of different amounts of straw returned to the field in the greenhouse.

LI Bo, SUN Xiang-long, YAO Ming-ze*, BAO Hui, WANG Jun-hao   

  1. (College of Water Conservancy, Shenyang Agricultural University, Shenyang 110866, China).
  • Online:2021-03-10 Published:2021-03-17

摘要: 为了探讨番茄生长模拟模型DSSAT-CROPGRO-Tomato能否准确模拟秸秆还田条件下北方日光温室番茄的生长发育和产量形成过程,基于2016年和2018年温室番茄小区试验数据对模型进行验证。试验设置4个秸秆还田量处理,分别为0(S0)、1.5×104(S1)、3×104(S2)和4.5×104 kg·hm-2(S3)。利用GLUE参数估计模块获得不同方案相应的作物遗传参数,通过分析和对比番茄物候期、鲜果产量、最大叶面积指数、土壤水分、土壤无机态氮和地上干物质量的实测值与模拟值,验证模型模拟精度并确定最优方案。结果表明,参数PODUR(最优条件下最终果实负载所需光热时长)和SLAVR(比叶面积)的变异系数较大,分别为28.53%和14.13%。模型在2016年所有处理为参数估计方案时模拟精度最高,其ARE和nRMSE分别为10.33%和7.12%。模型对温室土壤水分、番茄生长和产量的模拟精度较高。留一交叉验证法体现模型对温室番茄产量总体误差在18.68%~21.95%。说明CROPGRO-Tomato模型可以较准确模拟秸秆不同还田量条件下沈阳日光温室番茄生长和产量形成过程。

关键词: 日光温室, 番茄, DSSAT-CROPGRO-Tomato, 秸秆还田, 留一交叉验证

Abstract: We examined whether the tomato growth simulation model DSSAT-CROPGRO-Tomato can accurately simulate the growth, development, and yield formation of tomatoes in northern China solar greenhouse under the condition of returning straw to the field. The model was verified based on the greenhouse tomato plot test data in both 2016 and 2018. There were four treatments of straw returning, including 0 (S0), 1.5×104 (S1), 3×104 (S2) and 4.5×104 kg·hm-2 (S3). The corresponding crop genetic parameters of different schemes were obtained using GLUE parameter estimation module. Moreover, the simulation accuracy of the model was verified by comparing the measured and simulated values of tomato phenology, fresh fruit yield, maximum leaf area index, soil moisture, soil inorganic nitrogen, and aboveground dry matter quality. The results showed that the coefficients of variation of the parameters PODUR (the duration of light 〖JP2〗and heat required for the final fruit load under optimal conditions) and SLAVR (specific leaf area)were 28.53% and 14.13%, respectively. The model had the highest simulation accuracy in 2016 when all treatments were under parameter estimation schemes, and its ARE (absolute relative error) and nRMSE were 10.33% and 7.12%, respectively. The model had high accuracy in simulating soil moisture, tomato growth, and yield. The results of leave-one-out cross-validation method showed that the overall error of the model to the yield of greenhouse tomato was 18.68%-21.95%. Our results indicated that the CROPGRO-Tomato model can accurately simulate tomato growth and yield formation in the solar greenhouse in Shenyang with straw returning to the field.

Key words: solar greenhouse, tomato, DSSAT-CROPGRO-Tomato, straw return, leave-one-out cross-validation.