Ge Jiankun, Yu Zihui, Gong Xuewen, Ping Yinglu, Luo Jinyao, Li Yanbin
College of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450045, China.
Ningbo Water Conservancy and Hydropower Planning Design Institute Co., Ltd., Ningbo 315192, China.
Plants (Basel). 2023 Nov 15;12(22):3863. doi: 10.3390/plants12223863.
The improvement of the simulation accuracy of crop models in different greenhouse environments would be better applied to the automation management of greenhouse cultivation. Tomatoes under drip irrigation in a greenhouse were taken as the research object, and the cumulative evaporation capacity () of the 20 cm standard evaporation dish was taken as the basis for irrigation. Three treatments were set up in the experiment: high water treatment without mulch (NM-0.9 ), high water treatment with mulch (M-0.9 ), and low water treatment with mulch (M-0.5 ). AquaCrop and DSSAT models were used to simulate the canopy coverage, soil water content, biomass, and yield of the tomatoes. Data from 2020 were used to correct the model, and simulation results from 2021 were analyzed in this paper. The results showed that: (1) Of the two crop models, the simulation accuracy of the greenhouse tomato canopy coverage was higher, and the root mean square errors were less than 6.8% (AquaCrop model) and 8.5% (DSSAT model); (2) The AquaCrop model could accurately simulate soil water change under high water treatments, while the DSSAT model was more suitable for the conditions without mulch; (3) The relative error RE of simulated and observed values for biomass B, yield Y, and water use efficiency WUE in the AquaCrop model were less than 2.0%, 2.3%, and 9.0%, respectively, while those of the DSSAT model were less than 4.7%, 7.6%, and 10.4%, respectively; (4) Considering the simulation results of each index comprehensively, the AquaCrop model was superior to the DSSAT model; subsequently, the former was used to predict 16 different water and film coating treatments (S1-S16). It was found that the greenhouse tomato yield and WUE were the highest under S7 (0.8 ), at 8.201 t/ha and 2.79 kg/m, respectively.
提高作物模型在不同温室环境下的模拟精度,将更有利于应用于温室栽培的自动化管理。以温室滴灌番茄为研究对象,以20厘米标准蒸发皿的累积蒸发量()作为灌溉依据。试验设置了三个处理:无地膜高水处理(NM - 0.9)、有地膜高水处理(M - 0.9)和有地膜低水处理(M - 0.5)。利用AquaCrop和DSSAT模型模拟番茄的冠层覆盖度、土壤含水量、生物量和产量。用2020年的数据对模型进行校正,本文分析了2021年的模拟结果。结果表明:(1)在两种作物模型中,温室番茄冠层覆盖度的模拟精度较高,均方根误差分别小于6.8%(AquaCrop模型)和8.5%(DSSAT模型);(2)AquaCrop模型能够准确模拟高水处理下的土壤水分变化,而DSSAT模型更适合无地膜条件;(3)AquaCrop模型中生物量B、产量Y和水分利用效率WUE的模拟值与观测值的相对误差RE分别小于2.0%、2.3%和9.0%,而DSSAT模型的相对误差分别小于4.7%、7.6%和10.4%;(4)综合各指标的模拟结果,AquaCrop模型优于DSSAT模型;随后,用前者预测16种不同的水分和覆膜处理(S1 - S16)。结果发现,S7(0.8)处理下温室番茄产量和水分利用效率最高,分别为8.201吨/公顷和2.79千克/平方米。