Variation and simulation of tomato transpiration in a greenhouse under different ventilation modes

被引:0
|
作者
Ge, Jiankun [1 ,2 ]
Wang, Sen [1 ,2 ]
Gong, Xuewen [1 ,2 ]
Zhu, Yuhao [1 ,2 ]
Yu, Zihui [1 ,2 ]
Li, Yanbin [1 ,2 ]
机构
[1] North China Univ Water Resources & Elect Power, Sch Water Conservancy, Zhengzhou 450045, Peoples R China
[2] Henan Key Lab Water Saving Agr, Zhengzhou 450045, Peoples R China
基金
中国国家自然科学基金;
关键词
Ventilation regulation; Transpiration; Resistance parameter; Penman-Monteith model; PENMAN-MONTEITH MODEL; CROP COEFFICIENTS; EVAPOTRANSPIRATION; EVAPORATION; FLUX;
D O I
10.1016/j.agwat.2024.109281
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Greenhouse ventilation is a critical factor in regulating internal microclimates, ensuring optimal crop growth, and improving water use efficiency in facility agriculture. However, the semi-enclosed nature of greenhouses poses challenges for accurately modeling crop water consumption, primarily due to uncertainties in parameter estimation for widely used models such as the Penman-Monteith (P-M) model. To address these challenges, this study refines the P-M model by incorporating resistance parameters specifically tailored to greenhouse convection regimes. Field experiments were conducted at the Xinxiang Integrated Experimental Base of the Chinese Academy of Agricultural Sciences in northern China from March to July in 2020 and 2021. Drip-irrigated tomatoes were grown under natural sunlight with two ventilation treatments: T1 (top window open) and T2 (top and south windows open). Meteorological conditions inside the greenhouse and water consumption indicators were analyzed to improve the Penman-Monteith (P-M) model's resistance parameters (canopy resistance, r c and aerodynamic resistance, r a ). Results showed that ventilation significantly influenced water consumption across growth stages, with the highest water consumption intensity observed during the fruit enlargement stage (3.39 mm d- 1 ). r c and ra were significantly lower under T2, with forced convection dominating in both cases. The improved P-M model demonstrated high predictive accuracy, underestimating transpiration by 2.15% for T1 and overestimating by 6.26% for T2. These findings provide a robust framework for optimizing greenhouse ventilation strategies, enabling precise modeling of crop water consumption and enhancing resource utilization in facility agriculture.
引用
收藏
页数:19
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