Physiological and ecological analysis of greenhouse tomato and construction of temperature prediction model

doi:10.3969/j.issn.1004-1524.20250244

Acta Agriculturae Zhejiangensis ›› 2026, Vol. 38 ›› Issue (5): 898-908.DOI: 10.3969/j.issn.1004-1524.20250244

• Horticultural Science • Previous Articles Next Articles

Physiological and ecological analysis of greenhouse tomato and construction of temperature prediction model

ZHANG Haoyu¹^,²(), MIAO Chen², ZHU Cuifang², ZHU Kaili¹^,², DING Xiaotao²^,^*(), JIANG Yuping¹^,^*()

¹ Department of Urban Construction and Ecological Technology, Shanghai Institute of Technology, Shanghai 201418, China
² Shanghai Key Laboratory of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China

Received:2025-03-25 Online:2026-05-25 Published:2026-06-02

Abstract

Abstract:

To investigate the relationship between environmental ecological factors and plant physiological ecology in modern greenhouse tomato production, temperature, solar radiation intensity, substrate parameters, and stemflow rate were monitored during winter, spring, and summer. Typical weather conditions were selected for analysis. The results showed that leaf temperature was similar to air temperature in winter, with a difference of only 0.5 ℃. At noon in spring and summer, leaf temperature was approximately 1.5 ℃ lower than air temperature. The diurnal variation of substrate temperature lagged behind that of air temperature, with a lag of 3 h in winter and spring and 1 h in summer. Moreover, the maximum substrate temperature in summer was about 2 ℃ higher than air temperature. Substrate moisture content varied consistently with temperature, whereas substrate electrical conductivity varied inversely with moisture content in spring and summer. Stemflow rate was lower in winter and spring and higher in summer, with its diurnal variation primarily dependent on air temperature changes. Compared with sunny days, the diurnal variation amplitude of all parameters decreased significantly on rainy days but still maintained consistent trends with air temperature and solar radiation intensity. Leaf temperature, substrate temperature, substrate moisture content, and stemflow rate were all significantly correlated with air temperature and solar radiation intensity at the statistical level of p<0.01, with correlation coefficients with air temperature exceeding 0.787. The segmented prediction models for leaf temperature and substrate temperature, based on environmental factors and weather conditions, had root mean square errors (RMSE) below 1 ℃ and coefficient of determination (R²) above 0.93. The accuracy of the prediction models was higher on rainy days. This study improves the understanding of greenhouse environmental factors and establishes prediction models for leaf and substrate temperatures, providing a theoretical basis for greenhouse environmental control.

Key words: greenhouse environment, leaf temperature, substrate temperature, stemflow, temperature model

CLC Number:

ZHANG Haoyu, MIAO Chen, ZHU Cuifang, ZHU Kaili, DING Xiaotao, JIANG Yuping. Physiological and ecological analysis of greenhouse tomato and construction of temperature prediction model[J]. Acta Agriculturae Zhejiangensis, 2026, 38(5): 898-908.

Figures/Tables 10

Fig.1 Instrumentation layout

Fig.2 Diurnal variations of leaf temperature, greenhouse air temperature, and solar radiation intensity on sunny days in different seasons A, Winter (January 12-14); B, Spring (April 9-11); C, Summer (July 3-5).

Fig.3 Diurnal variations of leaf temperature, greenhouse air temperature, and solar radiation intensity on cloudy and rainy days in different seasons A, Winter (January 18-20); B, Spring (March 2-4); C, Summer (July 10-12).

Fig.4 Diurnal variations of substrate temperature, water content, and electrical conductivity on sunny days in different seasons A, Winter (January 12-14); B, Spring (April 9-11); C, Summer (July 3-5).

Fig.5 Diurnal variations of substrate temperature, water content, and electrical conductivity on cloudy and rainy days in different seasons A, Winter (January 18-20); B, Spring (March 2-4); C, Summer (July 10-12).

Fig.6 Diurnal variations of stemflow rate on sunny days in different seasons A, Winter (January 12-14); B, Spring (April 9-11); C, Summer (July 3-5).

Fig.7 Diurnal variation of stemflow rate on cloudy and rainy days in different seasons A, Winter (January 18-20); B, Spring (March 2-4); C, Summer (July 10-12).

Table 1 Correlation of ecological factors

生态因子 Ecological factor	空气温度 Air temperature	太阳辐射强度 Solar radiation intensity	叶片温度 Leaf temperature	基质温度 Substrate temperature	基质含水量 Substrate water content	基质电导率 Substrate electrical conductivity
辐射强度 Solar radiation intensity	0.520^**
叶片温度Leaf temperature	0.988^**	0.535^**
基质温度 Substrate temperature	0.949^**	0.386^**	0.226^**
基质含水量 Substrate water content	0.862^**	0.300^**	0.030	0.494^**
基质电导率 Substrate electrical conductivity	-0.128	-0.158	-0.209^*	-0.009	0.216^**
茎流速率Stemflow rate	0.787^**	0.653^**	0.137	-0.180*	0.519^**	-0.728^**

Fig.8 Comparison of predicted and measured leaf temperatures RMSE,Root mean square error; R2, Coefficient of determination. The same as below. A, Sunny day; B, Cloudy and rainy day; C, Night; ■, Predicted value; ―, 1∶1 line.

Fig.9 Comparison of predicted and measured substrate temperatures A, Warm sunny day; B, Warm cloudy and rainy day; C, Cool sunny day; D, Cool cloudy and rainy day; ■, Predicted value; ―, 1∶1 line.

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Physiological and ecological analysis of greenhouse tomato and construction of temperature prediction model

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