Comparison and Evaluation of Tomato Growth Models Based on Different Drivers

Zhu Yuqing; Xue Xiaoping

doi:10.11898/1001-7313.20240610

Vol.35, NO.6, 2024

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Article Navigation > Journal of Applied Meteorological Science > 2024 > 35(6): 747-758

Zhu Yuqing, Xue Xiaoping. Comparison and evaluation of tomato growth models based on different drivers. J Appl Meteor Sci, 2024, 35(6): 747-758. DOI: 10.11898/1001-7313.20240610.

Citation:

Zhu Yuqing, Xue Xiaoping. Comparison and evaluation of tomato growth models based on different drivers. J Appl Meteor Sci, 2024, 35(6): 747-758. DOI: 10.11898/1001-7313.20240610.

Zhu Yuqing, Xue Xiaoping. Comparison and evaluation of tomato growth models based on different drivers. J Appl Meteor Sci, 2024, 35(6): 747-758. DOI: 10.11898/1001-7313.20240610.

Citation:

Zhu Yuqing, Xue Xiaoping. Comparison and evaluation of tomato growth models based on different drivers. J Appl Meteor Sci, 2024, 35(6): 747-758. DOI: 10.11898/1001-7313.20240610.

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Comparison and Evaluation of Tomato Growth Models Based on Different Drivers

DOI: 10.11898/1001-7313.20240610

Zhu Yuqing¹,
Xue Xiaoping^{2
,
,}

1.
Jining Meteorological Bureau of Shandong Province, Jining 272113
2.
Shandong Provincial Climate Center, Jinan 250031

Received Date: 2024-08-04
Rev Recd Date: 2024-09-29
Publish Date: 2024-11-30

Abstract

Abstract

Simulating growth processes of greenhouse crops under different environmental factors is one of the important means for planning cultivation and predicting yield in greenhouse production. Tomatoes are main greenhouse plants in northern China, characterized by high nutritional value and strong adaptability to cultivation. Clarifying the quantitative relationship between the growth indicators of greenhouse tomatoes and microclimate environmental factors is of great significance for improving the economic benefits. Utilizing environmental factors and various growth indicators of tomatoes, Logistic growth models are constructed by taking accumulated radiation, effective accumulated temperature, and suitability index as independent variables, and different growth indicators of tomatoes as dependent variables. Subsequently, models are validated using independent data. By comparing the precision of three models in simulating different tomato growth indicators, advantages and disadvantages of each model are analyzed to select the optimal model for different stages of tomato development. It provides a more precise theoretical basis for meteorological services and tomato yield prediction. Results show that greenhouse tomatoes are not sensitive to light during the flowering period. Therefore, choosing the accumulated temperature method to establish a logistic model yields the best simulation of the number of flowers. In the second inflorescence of tomatoes, the limit value of the number of flowers is 5.4; The accumulated radiation required to reach this limit is 146.6 mol·m^-2, the effective accumulated temperature is 73.3 ℃, and the suitability index is 15.1. Main meteorological factors affecting the number of fruit sets in tomatoes are light, temperature, and humidity. Therefore, using the suitability method to establish a logistic model achieves the highest accuracy in simulating this. The maximum number of fruit sets in the second inflorescence of tomatoes is 5.0; the accumulated radiation required to reach this limit is 146.9 mol·m^-2, the effective accumulated temperature is 47.1 ℃ and the suitability index is 14.6. Tomato fruit growth is mainly related to photosynthetically active radiation and temperature; therefore, choosing the accumulated radiation method provides the highest precision in simulating tomato fruit growth. The maximum transverse diameter of the tomato fruit is 51.6 mm, requiring accumulated radiation, effective accumulated temperature, and suitability index of 230.0 mol·m^-2, 69.6 ℃, and 18.8. The maximum longitudinal diameter of the tomato fruit is 74.9 mm, requiring accumulated radiation, effective accumulated temperature, and suitability index of 252.0 mol·m^-2, 69.6 ℃, and 18.8, respectively. Overall, the effective accumulated temperature model has fewer parameters and is simple and convenient to calculate, showing significant effectiveness in simulating the non-light-sensitive developmental stages of crops. The accumulated radiation method has higher accuracy, but involves a complex calculation process and greater difficulty in data acquisition. On the contrary, selecting the suitability method, which involves relatively simple data acquisition and incorporates more environmental factors, for simulation can also achieve relatively accurate results, making it more cost-effective in practical applications.
- photothermal product;
- accumulated temperature;
- suitability;
- Logistic model

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References(56)

Figures and Tables

Fig. 1 Light, average temperature and average relative humidity during 3 experiments

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Fig. 2 Logistics model curve of tomato growth index and photo-thermal product

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Fig. 3 Logistics model curve of tomato growth index and accumulated temperature

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Fig. 4 Logistics model curve of tomato growth index and suitability

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Fig. 5 Comparison of measurement and simulated value of different models

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Table 1 Temperature of three basis points in each growth period of tomato (from Reference [25])

发育期	T_o/℃	T_b/℃	T_m/℃
苗期	25	10	30
花期	25	15	30
结果期	25	15	35
采收期	25	15	35

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Table 2 Logistic model of tomato growth index and radial heat accumulation,accumulated temperature and suitability

生长指标	模拟方法	Logistics模型	决定系数
辐热积	开花数	y=5.238/(1+3.979e^-0.058x)	0.994
	坐果数	y=5.028/(1+2.995e^-0.054x)	0.994
	横茎长度	y=87.782/(1+1.888e^-0.016x)	0.996
	纵茎长度	y=60.573/(1+1.477e^-0.016x)	0.995
有效积温	开花数	y=5.783/(1+4.211e^-0.091x)	0.993
	坐果数	y=5.016/(1+3.679e^-0.209x)	0.969
	横茎长度	y=104.339/(1+1.777e^-0.037x)	0.976
	纵茎长度	y=53.678/(1+1.299e^-0.054x)	0.987
适宜度	开花数	y=5.390/(1+3.583e^-0.477x)	0.996
	坐果数	y=5.013/(1+3.663e^-0.697x)	0.984
	横茎长度	y=101.012/(1+1.887e^-0.149x)	0.988
	纵茎长度	y=55.098/(1+1.447e^-0.197x)	0.996

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Table 3 Statistics of validation results for tomato growth indicators using different arguments

生长指标	模型	均方根误差	相对均方根误差	测定系数
开花数	辐热积	0.780	0.235	1.829
	有效积温	0.175	0.053	1.027
	适宜度	0.749	0.225	1.743
坐果数	辐热积	0.208	0.061	1.229
	有效积温	0.474	0.138	1.482
	适宜度	0.192	0.056	1.117
横茎长度	辐热积	2.743 mm	0.056	0.850
	有效积温	17.525 mm	0.357	1.520
	适宜度	9.460 mm	0.193	1.262
纵茎长度	辐热积	0.991 mm	0.027	0.898
	有效积温	8.428 mm	0.230	1.713
	适宜度	4.310 mm	0.118	1.213

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