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Comparison and Evaluation of Tomato Growth Models Based on Different Drivers
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摘要: 利用2018—2023年在山东省临沂、济南和济宁开展的日光温室试验测定数据, 基于环境因素与番茄的不同生长指标, 分别以辐热积、有效积温和适宜度指数为自变量, 以番茄不同生长指标为因变量构建Logistic生长模型, 并利用独立数据对模型进行验证, 比较3种模型对番茄不同生长指标模拟的准确性和优缺点, 得到番茄不同发育期的最优模型。结果表明:温室番茄开花期对光照不敏感, 此时选择积温法建立Logistic模型, 对开花数的模拟程度最优;影响番茄坐果数的主要气象因子为光照、温度和湿度, 适宜度法建立的Logistic模型精确度最高;番茄果茎生长主要与光合有效辐射和温度有关, 辐热积法建立的Logistic模型精确度最高。
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关键词:
- 辐热积;
- 积温;
- 适宜度;
- Logistic模型
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.-
Key words:
- photothermal product;
- accumulated temperature;
- suitability;
- Logistic model
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图 1 番茄发育期内光合有效辐射(a)、日平均温度(b)和日平均相对湿度(c)变化
Fig. 1 Light, average temperature and average relative humidity during 3 experiments
图 2 番茄生长指标与辐热积的Logistics模型曲线
Fig. 2 Logistics model curve of tomato growth index and photo-thermal product
图 3 番茄生长指标与有效积温的Logistics模型曲线
Fig. 3 Logistics model curve of tomato growth index and accumulated temperature
图 4 番茄生长指标与适宜度的Logistics模型曲线
Fig. 4 Logistics model curve of tomato growth index and suitability
图 5 不同模型模拟值与实测值对比
Fig. 5 Comparison of measurement and simulated value of different models
表 1 番茄各发育期三基点温度[25]
Table 1 Temperature of three basis points in each growth period of tomato (from Reference [25])
发育期 To/℃ Tb/℃ Tm/℃ 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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表 2 番茄生长指标与辐热积、有效积温与适宜度的Logistic模型
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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表 3 用不同自变量模拟番茄生长指标的验证结果统计
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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