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作 者:朱雨晴 薛晓萍 ZHU Yuqing;XUE Xiaoping(Jining Meteorological Bureau of Shandong Province,Jining 272113,Shandong,China;Shandong Provincial Climate Center,Jinan 250000,China)
机构地区:[1]山东省济宁市气象局,山东济宁272113 [2]山东省气候中心,山东济南250000
出 处:《干旱气象》2024年第5期784-793,共10页Journal of Arid Meteorology
基 金:山东省气象局气象科学技术研究项目(2020sdqxm15);济宁市气象局气象科学技术研究项目自立课题(2022JNZL05);十三五山东重大气象工程项目[鲁发改农经(2017)97号]共同资助。
摘 要:光照和温度对设施番茄生长具有重要影响。为明确光温与番茄生长发育间的量化关系,以设施番茄为试材,构建番茄开花坐果数、果茎生长量、干物质分配与累计辐热积(Photo-thermal Product,PTP)的Logistic生长模型,并用不同茬口、不同地点和品种的番茄对模型进行验证。结果表明,番茄开花、坐果和果实长成所需的累计辐热积分别为146.59、146.90、252.00 mol·m^(-2);模型在模拟番茄开花坐果数、果茎生长量和干物质分配方面精度较高,模拟值与实测值的回归标准误差为0.208~14.229,标准均方根误差为0.027~0.246,决定系数为0.905~0.999;番茄品种影响模型精度,坐果期后不同茬口间果茎生长量差异增大,但模型整体适用性强。该辐热积生长模型能准确预测番茄的开花坐果时间及果实生长进程,为设施番茄产量预报和上市时间预测提供科学依据。Light and temperature are important factors affecting greenhouse tomato growth.In order to find the relationship between light and temperature with growth and development of tomato,a Logistic growth model was constructed for the number of flowers and fruit set,fruit stalk growth,dry matter partition and cumulative Photo-thermal Product(PTP).The model was validated using different crops,locations,and tomato varieties.The results show that the cumulative PTP required for the number of flowers set,fruit set and fruit growth were 146.59,146.90 and 252.00 mol·m^(-2),respectively.The model demonstrated high accuracy in simulating the number of flowers and fruit set,fruit stalk growth and dry matter of tomato,with root mean square errors ranging from 0.208 to 14.229,normalized root mean square errors from 0.027 to 0.246,and correlation coefficients from 0.905 to 0.999,respectively.Varieties differences af⁃fected the accuracy of tomato growth model,and variations in fruit stalk growth among different crops increased after the fruit setting pe⁃riod,but the overall applicability of the model remained strong.This PTP growth model can accurately predict the timing of flowering and fruit set as well as the growth process of the fruit,providing a scientific basis for forecasting the yield and market timing of green⁃house tomatoes.
分 类 号:S16[农业科学—农业气象学]
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