温室网纹甜瓜干物质分配、产量形成与采收期模拟研究

 【目的】建立一个可以预测温室网纹甜瓜产量与采收期的模拟模型，为温室网纹甜瓜生产管理和环境调控的优化提供决策支持。【方法】本研究据温室网纹甜瓜器官生长与温度和辐射的关系，建立了基于分配指数的温室网纹甜瓜干物质分配、产量形成与采收期模拟模型，并利用不同基质的试验资料对模型进行了检验。【结果】模型对地上部分干重、根干重、茎干重、叶干重、果实干重的模拟结果与1∶1直线之间的R2分别为0.99、0.65、0.97、0.98和0.98；预测相对误差分别为0.88%、70.21%、7.44%、9.33%和5.28%。模型对网纹甜瓜果实鲜重的模拟结果与1∶1直线之间的R2为0.94，预测相对误差为8.13%，对网纹甜瓜直径的模拟结果与1∶1直线之间的R2为0.95，预测相对误差为9.23%，对网纹甜瓜采收期的预测误差在 1 d内。【结论】与已有的温室作物生长模型相比，本研究建立的模型不仅预测精度较高和功能全面，而且模型参数易获取，具有较强实用性。

Simulation of Dry Matter Partitioning, Yield Formation and Fruit Harvest Date of Greenhouse Muskmelon

【Objective】 The aim of the study was to develop a simulation model to predict the yield and harvest date of greenhouse muskmelon for the optimization of climate control and crop management for greenhouse muskmelon production. 【Method】Based on the relationships between partitioning index and the accumulated product of thermal effectiveness and photosynthetically active radiation (TEP), a dry matter partitioning，yield formation and harvest date simulation model for greenhouse muskmelon was developed. Experiments with different sowing dates and substrates were carried out in Shanghai and Nanjing to collect data to develop and validate the model. 【Result】The results showed that for shoot dry weight, root dry weight, stem dry weight, leaf dry weight and fruit dry weight, the coefficient of determination R2 between the simulated and the measured value based on the 1:1 line was 0.99, 0.65, 0.97, 0.98, 0.98, respectively; and the relative prediction error (RSE) was 0.88%, 70.21%, 7.44%, 9.33%, 5.28%, respectively. The R2 and RSE between the simulated and the measured fresh weight of muskmelon based on the 1:1 line was 0.94 and 8.13%, respectively. The R2 and RSE between the simulated and the measured diameter of muskmelon fruit based on the 1:1 line were 0.95 and 9.23%, respectively. The prediction error for harvest date was in 1 day. 【Conclusion】From the results mentioned above, it can be concluded that the model developed in this study not only can give satisfactory prediction of dry matter partitioning, yield and harvest date of greenhouse muskmelon, but also is user-friendly.