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Evaluation of Irrigation Modes for Greenhouse Drip Irrigation Tomatoes Based on AquaCrop and DSSAT Models

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 (Ep...

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Autores principales: Ge, Jiankun, Yu, Zihui, Gong, Xuewen, Ping, Yinglu, Luo, Jinyao, Li, Yanbin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10675354/
https://www.ncbi.nlm.nih.gov/pubmed/38005761
http://dx.doi.org/10.3390/plants12223863
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author Ge, Jiankun
Yu, Zihui
Gong, Xuewen
Ping, Yinglu
Luo, Jinyao
Li, Yanbin
author_facet Ge, Jiankun
Yu, Zihui
Gong, Xuewen
Ping, Yinglu
Luo, Jinyao
Li, Yanbin
author_sort Ge, Jiankun
collection PubMed
description 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 (Ep) 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 Ep), high water treatment with mulch (M-0.9 Ep), and low water treatment with mulch (M-0.5 Ep). 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 k(CC) 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 Ep), at 8.201 t/ha and 2.79 kg/m(3), respectively.
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spelling pubmed-106753542023-11-15 Evaluation of Irrigation Modes for Greenhouse Drip Irrigation Tomatoes Based on AquaCrop and DSSAT Models Ge, Jiankun Yu, Zihui Gong, Xuewen Ping, Yinglu Luo, Jinyao Li, Yanbin Plants (Basel) Article 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 (Ep) 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 Ep), high water treatment with mulch (M-0.9 Ep), and low water treatment with mulch (M-0.5 Ep). 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 k(CC) 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 Ep), at 8.201 t/ha and 2.79 kg/m(3), respectively. MDPI 2023-11-15 /pmc/articles/PMC10675354/ /pubmed/38005761 http://dx.doi.org/10.3390/plants12223863 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ge, Jiankun
Yu, Zihui
Gong, Xuewen
Ping, Yinglu
Luo, Jinyao
Li, Yanbin
Evaluation of Irrigation Modes for Greenhouse Drip Irrigation Tomatoes Based on AquaCrop and DSSAT Models
title Evaluation of Irrigation Modes for Greenhouse Drip Irrigation Tomatoes Based on AquaCrop and DSSAT Models
title_full Evaluation of Irrigation Modes for Greenhouse Drip Irrigation Tomatoes Based on AquaCrop and DSSAT Models
title_fullStr Evaluation of Irrigation Modes for Greenhouse Drip Irrigation Tomatoes Based on AquaCrop and DSSAT Models
title_full_unstemmed Evaluation of Irrigation Modes for Greenhouse Drip Irrigation Tomatoes Based on AquaCrop and DSSAT Models
title_short Evaluation of Irrigation Modes for Greenhouse Drip Irrigation Tomatoes Based on AquaCrop and DSSAT Models
title_sort evaluation of irrigation modes for greenhouse drip irrigation tomatoes based on aquacrop and dssat models
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10675354/
https://www.ncbi.nlm.nih.gov/pubmed/38005761
http://dx.doi.org/10.3390/plants12223863
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