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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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[1] 郭世荣, 孙锦, 束胜, 等.我国设施园艺概况及发展趋势.中国蔬菜, 2012(18):1-14.Guo S R, Sun J, Shu S, et al. Analysis of general situation, characteristics, existing problems and development trend of protected horticulture in China. China Veg, 2012(18): 1-14. [2] 韩静, 史欣, 秦建平, 等. 设施番茄栽培技术及常见病害防治. 农业工程技术, 2023, 43(3): 73-74.Han J, Shi X, Qin J P, et al. Cultivation techniques of protected tomato and control of common diseases. Agric Eng Technol, 2023, 43(3): 73-74. [3] 郑艳姣, 杨再强, 王琳, 等. 中国南方设施番茄高温热害风险区划. 应用气象学报, 2021, 32(4): 432-442. doi: 10.11898/1001-7313.20210405Zheng Y J, Yang Z Q, Wang L, et al. Refined risk zoning of high temperature and heat damage to greenhouse tomato in Southern China. J Appl Meteor Sci, 2021, 32(4): 432-442. doi: 10.11898/1001-7313.20210405 [4] 朱雨晴, 薛晓萍. 遮阴及复光对花果期番茄叶片光合特性的影响. 中国农业气象, 2019, 40(2): 126-134. doi: 10.3969/j.issn.1000-6362.2019.02.007Zhu Y Q, Xue X P. Effects of shading and light restoration on photosynthetic characteristics of tomato leaves during flowering and fruit period. Chinese J Agrometeor, 2019, 40(2): 126-134. doi: 10.3969/j.issn.1000-6362.2019.02.007 [5] 张淑杰, 杨再强, 陈艳秋, 等. 低温、弱光、高湿胁迫对日光温室番茄花期生理生化指标的影响. 生态学杂志, 2014, 33(11): 2995-3001.Zhang S J, Yang Z Q, Chen Y Q, et al. Effects of low temperature, weak light and high humidity stresses on the physiological and biochemical indicators of greenhouse tomato during flowering period. Chinese J Ecol, 2014, 33(11): 2995-3001. [6] 杨世琼, 杨再强, 王琳, 等. 高温高湿交互对设施番茄叶片光合特性的影响. 生态学杂志, 2018, 37(1): 57-63.Yang S Q, Yang Z Q, Wang L, et al. Effect of high humidity and high temperature interaction on photosynthetic characteristics of greenhouse tomato crops. Chinese J Ecol, 2018, 37(1): 57-63. [7] 朱丽云. 花期低温寡照对设施番茄产量及果实品质的影响. 南京: 南京信息工程大学, 2018.Zhu L Y. Effects of Low Temperature and Low Light at Flowering Stage on Yield and Fruit Quality of Greenhouse Tomato. Nanjing: Nanjing University of Information Science & Technology, 2018. [8] Sinnathamby S, Douglas-Mankin K R, Craige C. Field-scale calibration of crop-yield parameters in the Soil and Water Assessment Tool (SWAT). Agric Water Manag, 2017, 180: 61-69. doi: 10.1016/j.agwat.2016.10.024 [9] Paredes P, Torres M O. Parameterization of AquaCrop model for vining pea biomass and yield predictions and assessing impacts of irrigation strategies considering various sowing dates. Irrig Sci, 2017, 35(1): 27-41. doi: 10.1007/s00271-016-0520-x [10] 马玉平, 王培娟, 王达, 等. 作物发育模式重构及基于甘蔗的模拟检验. 应用气象学报, 2021, 32(5): 603-617. doi: 10.11898/1001-7313.20210508Ma Y P, Wang P J, Wang D, et al. Reconstruction of crop development model with its simulation test based on sugarcane. J Appl Meteor Sci, 2021, 32(5): 603-617. doi: 10.11898/1001-7313.20210508 [11] 陈杨. 有效积温与夏玉米生长发育和氮磷钾积累定量化研究. 北京: 中国农业科学院, 2021.Chen Y. Quantitative Study on Effective Accumulated Temperature and Growth and Development of Summer Maize and Accumulation of Nitrogen, Phosphorus and Potassium. Beijing: Chinese Academy of Agricultural Sciences, 2021. [12] Pearl R. The growth of populations. Quart Rev Biol, 1927, 2(4): 532-548. doi: 10.1086/394288 [13] Tsoularis A, Wallace J. Analysis of logistic growth models. Math Biosci, 2002, 179(1): 21-55. doi: 10.1016/S0025-5564(02)00096-2 [14] Reed H S, Holland R H. The growth rate of an annual plant helianthus. PNAS, 1919, 5(4): 135-144. doi: 10.1073/pnas.5.4.135 [15] West G B, Brown J H, Enquist B J. A general model for ontogenetic growth. Nature, 2001, 413(6856): 628-631. doi: 10.1038/35098076 [16] Mahbod M, Sepaskhah A R, Zand-Parsa S. Estimation of yield and dry matter of winter wheat using logistic model under different irrigation water regimes and nitrogen application rates. Arch Agron Soil Sci, 2014, 60(12): 1661-1676. doi: 10.1080/03650340.2014.917169 [17] Shi P J, Men X Y, Sandhu H S, et al. The "general" ontogenetic growth model is inapplicable to crop growth. Ecol Model, 2013, 266: 1-9. doi: 10.1016/j.ecolmodel.2013.06.025 [18] Yu Q, Liu J D, Zhang Y Q, et al. Simulation of rice biomass accumulation by an extended logistic model including influence of meteorological factors. Int J Biometeor, 2002, 46(4): 185-191. doi: 10.1007/s00484-002-0141-3 [19] Mirschel W, Schultz A, Wenkel K O, et al. Crop growth modelling on different spatial scales—A wide spectrum of approaches. Arch Agron Soil Sci, 2004, 50(3): 329-343. doi: 10.1080/03650340310001634353 [20] Fang S L, Kuo Y H, Kang L, et al. Using sigmoid growth models to simulate greenhouse tomato growth and development. Horticulturae, 2022, 8(11). DOI: 10.3390/horticulturae8111021. [21] He C, Zhang Z. Modeling the relationship between tomato fruit growth and the effective accumulated temperature in solar greenhouse. Acta Hortic, 2006(718): 581-588. [22] 李美萱, 霍治国, 孔瑞, 等. 黄淮海冬小麦春季低温灾害等级指标构建. 应用气象学报, 2024, 35(1): 45-56. doi: 10.11898/1001-7313.20240104Li M X, Huo Z G, Kong R, et al. Indicator construction of spring low-temperature disaster affecting winter wheat of Huang-Huai-Hai based on meta-analysis. J Appl Meteor Sci, 2024, 35(1): 45-56. doi: 10.11898/1001-7313.20240104 [23] 苏李君, 刘云鹤, 王全九. 基于有效积温的中国水稻生长模型的构建. 农业工程学报, 2020, 36(1): 162-174.Su L J, Liu Y H, Wang Q J. Rice growth model in China based on growing degree days. Trans Chinese Soc Agric Eng, 2020, 36(1): 162-174. [24] 石楠, 高志强, 陈崇怡, 等. 基于Logistic模型水稻地上部干物质与叶面积指数模拟与分析. 东北农业大学学报, 2022, 53(3): 10-18.Shi N, Gao Z Q, Chen C Y, et al. Simulation and analysis of above-ground dry matter and leaf area index of rice based on Logistic model. J Northeast Agric Univ, 2022, 53(3): 10-18. [25] 倪纪恒, 罗卫红, 李永秀, 等. 温室番茄发育模拟模型研究. 中国农业科学, 2005, 38(6): 1219-1225. doi: 10.3321/j.issn:0578-1752.2005.06.022Ni J H, Luo W H, Li Y X, et al. Simulation of the development of tomato in greenhouse. Sci Agric Sinica, 2005, 38(6): 1219-1225. doi: 10.3321/j.issn:0578-1752.2005.06.022 [26] 倪纪恒, 罗卫红, 李永秀, 等. 温室番茄干物质分配与产量的模拟分析. 应用生态学报, 2006, 17(5): 811-816. doi: 10.3321/j.issn:1001-9332.2006.05.011Ni J H, Luo W H, Li Y X, et al. Simulation of greenhouse tomato dry matter partitioning and yield prediction. Chinese J Appl Ecol, 2006, 17(5): 811-816. doi: 10.3321/j.issn:1001-9332.2006.05.011 [27] 明村豪, 蒋芳玲, 王广龙, 等. 黄瓜壮苗指标与辐热积关系的模拟模型. 农业工程学报, 2012, 28(9): 109-113.Ming C H, Jiang F L, Wang G L, et al. Simulation model of cucumber healthy indexes based on radiation and thermal effectiveness. Trans Chinese Soc Agric Eng, 2012, 28(9): 109-113. [28] 石小虎, 蔡焕杰, 赵丽丽, 等. 不同水分处理下基于辐热积的温室番茄干物质生产及分配模型. 农业工程学报, 2016, 32(3): 69-77.Shi X H, Cai H J, Zhao L L, et al. Greenhouse tomato dry matter production and distribution model under condition of irrigation based on product of thermal effectiveness and photosynthesis active radiation. Trans Chinese Soc Agric Eng, 2016, 32(3): 69-77. [29] 李永秀, 罗卫红, 倪纪恒, 等. 基于辐射和温度热效应的温室水果黄瓜叶面积模型. 植物生态学报, 2006, 30(5): 861-867.Li Y X, Luo W H, Ni J H, et al. Simulation of greenhouse cucumber leaf area based on radiation and thermal effectiveness. J Plant Ecol, 2006, 30(5): 861-867. [30] Marcelis LFM, Gijzen H. A model for prediction of yield and quality of cucumber fruits. Acta Horticulturae, 1998, 476: 237-242. [31] Holzkämper A, Calanca P, Fuhrer J. Identifying climatic limitations to grain maize yield potentials using a suitability evaluation approach. Agric For Meteor, 2013, 168: 149-159. [32] 邱美娟, 宋迎波, 王建林, 等. 山东省冬小麦产量动态集成预报方法. 应用气象学报, 2016, 27(2): 191-200. doi: 10.11898/1001-7313.20160207Qiu M J, Song Y B, Wang J L, et al. Integrated technology of yield dynamic prediction of winter wheat in Shandong Province. J Appl Meteor Sci, 2016, 27(2): 191-200. doi: 10.11898/1001-7313.20160207 [33] 宋艳玲, 周广胜, 郭建平, 等. 不同播期对玉米先玉335产量和品质的影响. 应用气象学报, 2024, 35(5): 619-628. doi: 10.11898/1001-7313.20240509Song Y L, Zhou G S, Guo J P, et al. Influence of different sowing dates on yield and quality of corn Xianyu 335. J Applied Meteor Sci, 2024, 35(5): 619-628. doi: 10.11898/1001-7313.20240509 [34] 汪天颖, 李民华, 吴重池, 等. 丘陵山区黄桃气候品质等级评价模型. 应用气象学报, 2024, 35(4): 456-466. doi: 10.11898/1001-7313.20240406Wang T Y, Li M H, Wu Z C, et al. Evaluation model of yellow peach climatic quality rating in hilly mountainous areas. J Appl Meteor Sci, 2024, 35(4): 456-466. doi: 10.11898/1001-7313.20240406 [35] 孙光辉, 段居琦, 李俊儒, 等. 气候-土地综合影响的我国油茶农业气候区划. 应用气象学报, 2024, 35(4): 444-455. doi: 10.11898/1001-7313.20240405Sun G H, Duan J Q, Li J R, et al. Agro-climatic zoning of oiltea camellia in China based on climate-land integrated impacts. J Appl Meteor Sci, 2024, 35(4): 444-455. doi: 10.11898/1001-7313.20240405 [36] 魏瑞江, 王鑫, 朱慧钦. 日光温室黄瓜小气候适宜度定量评价模型. 气象, 2015, 41(5): 630-638.Wei R J, Wang X, Zhu H Q. Quantitative evaluation model for cucumber microclimate suitability-degree of solar greenhouse. Meteor Mon, 2015, 41(5): 630-638. [37] 刘聪, 李凯伟, 张继权, 等. 基于气候适宜度的南方柑橘种植精细化气候区划. 应用气象学报, 2021, 32(4): 421-431. doi: 10.11898/1001-7313.20210404Liu C, Li K W, Zhang J Q, et al. Refined climatic zoning for citrus cultivation in Southern China based on climate suitability. J Appl Meteor Sci, 2021, 32(4): 421-431. doi: 10.11898/1001-7313.20210404 [38] 李楠, 薛晓萍. 日光温室小气候适宜度定量评价模型改进及应用. 干旱气象, 2020, 38(6): 1009-1015.Li N, Xue X P. Improvement and application of micro-climate suitability quantitative evaluation model in heliogreenhouse. J Arid Meteor, 2020, 38(6): 1009-1015. [39] 朱雨晴, 薛晓萍. 不同遮阴日数对花果期番茄开花坐果特性的影响. 干旱气象, 2020, 38(5): 820-827.Zhu Y Q, Xue X P. Effect of shading days on flowering and fruit setting characteristics of tomatoes at flowering and fruiting stages. J Arid Meteor, 2020, 38(5): 820-827. [40] 祖林禄. 数据驱动的日光温室番茄果实生长预测模型研究. 泰安: 山东农业大学, 2023.Zu L L. Study on Data-driven Tomato Fruit Growth Prediction Model in Solar Greenhouse. Taian: Shandong Agricultural University, 2023. [41] 朱雨晴, 薛晓萍. 花果期遮阴对番茄果实生长及品质的影响. 干旱气象, 2020, 38(6): 994-1000.Zhu Y Q, Xue X P. Effects of shading on growth and quality of tomato during flower and fruit period. J Arid Meteor, 2020, 38(6): 994-1000. [42] 薛晓萍. 棉花临界氮浓度稀释模型确定及其应用研究. 南京: 南京农业大学, 2007.Xue X P. Determination of Critical Nitrogen Concentration Dilution Model of Cotton and its Application. Nanjing: Nanjing Agricultural University, 2007. [43] 侯英雨, 张艳红, 王良宇, 等. 东北地区春玉米气候适宜度模型. 应用生态学报, 2013, 24(11): 3207-3212.Hou Y Y, Zhang Y H, Wang L Y, et al. Climatic suitability model for spring maize in Northeast China. Chinese J Appl Ecol, 2013, 24(11): 3207-3212. [44] 赵峰, 千怀遂, 焦士兴. 农作物气候适宜度模型研究——以河南省冬小麦为例. 资源科学, 2003, 25(6): 77-82.Zhao F, Qian H S, Jiao S X. The climatic suitability model of crop: A case study of winter wheat in Henan Province. Resour Sci, 2003, 25(6): 77-82. [45] 郭申伯, 刘福昊, 王笛, 等. 基于微气候适宜度指数构建番茄生长速率模拟模型. 中国农业气象, 2023, 44(7): 611-623.Guo S B, Liu F H, Wang D, et al. Construction of a tomato growth rate simulation model based on climate suitability index. Chinese J Agrometeor, 2023, 44(7): 611-623. [46] 王琳, 杨再强, 王明田, 等. 空气相对湿度对高温下番茄幼苗营养物质含量及干物质分配的影响. 中国农业气象, 2018, 39(5): 304-313.Wang L, Yang Z Q, Wang M T, et al. Effect of air humidity on nutrient content and dry matter distribution of tomato seedlings under high temperature. Chinese J Agrometeor, 2018, 39(5): 304-313. [47] 韦婷婷, 杨再强, 王明田, 等. 高温与空气湿度交互对花期番茄植株水分生理的影响. 中国农业气象, 2019, 40(5): 317-326.Wei T T, Yang Z Q, Wang M T, et al. Effects of high temperature and different air humidity on water physiology of flowering tomato seedlings. Chinese J Agrometeor, 2019, 40(5): 317-326. [48] 摆虹霞. 基于不同水分条件下的日光温室黄瓜生长模型研究. 银川: 宁夏大学, 2021.Bai H X. Study on Cucumber Growth Model in Solar Greenhouse Based on Different Moisture Conditions. Yinchuan: Ningxia University, 2021. [49] 张智超, 周放, 张浩鑫, 等. BCC_CSM1.1m对冬季典型环流系统的预测评估. 应用气象学报, 2023, 34(1): 27-38. doi: 10.11898/1001-7313.20230103Zhang Z C, Zhou F, Zhang H X, et al. Predication of typical winter circulation systems based on BCC_CSM1.1m model. J Appl Meteor Sci, 2023, 34(1): 27-38. doi: 10.11898/1001-7313.20230103 [50] Verstraeten W W, Veroustraete F, Feyen J. On temperature and water limitation of net ecosystem productivity: Implementation in the C-fix model. Ecol Model, 2006, 199(1): 4-22. [51] 米娜, 陈鹏狮, 张玉书, 等. 几种蒸散模型在玉米农田蒸散量计算中的应用比较. 资源科学, 2009, 31(9): 1599-1606.Mi N, Chen P S, Zhang Y S, et al. A comparative study on estimation models for field evapotranspiration. Resour Sci, 2009, 31(9): 1599-1606. [52] Song J, Zhang S B, Wang X T, et al. Variations in both FTL1 and SP5G, two tomato FT paralogs, control day-neutral flowering. Mol Plant, 2020, 13(7): 939-942. [53] 倪纪恒, 陈学好, 陈春宏, 等. 用辐热积法模拟温室黄瓜果实生长. 农业工程学报, 2009, 25(5): 192-196.Ni J H, Chen X H, Chen C H, et al. Simulation of cucumber fruit growth in greenhouse based on production of thermal effectiveness and photosynthesis active radiation. Trans Chinese Soc Agric Eng, 2009, 25(5): 192-196. [54] 朱丽云, 杨再强, 李军, 等. 花期低温寡照对番茄开花坐果特性及果实品质的影响. 中国农业气象, 2017, 38(7): 456-465.Zhu L Y, Yang Z Q, Li J, et al. Effect of low temperature and weak light at flowering stage on flower-fruit characteristics of tomato. Chinese J Agrometeor, 2017, 38(7): 456-465. [55] 赵和丽. 高温高湿对设施番茄果实生长及糖、氮代谢的影响. 南京: 南京信息工程大学, 2020.Zhao H L. Effects of High Temperature and Humidity on Fruit Growth and Sugar and Nitrogen Metabolism of Greenhouse Tomato. Nanjing: Nanjing University of Information Science & Technology, 2020. [56] 江晓东, 张建取, 雷虎. 梅雨季节高温高湿环境下调亏灌溉对设施番茄生产的影响. 中国农业气象, 2023, 44(8): 685-694.Jiang X D, Zhang J Q, Lei H. Effect of regulated deficit irrigation on greenhouse tomato production under high temperature and high humidity environment in Meiyu season. Chinese J Agrometeor, 2023, 44(8): 685-694. -
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