Abstract: 【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.

Key words: Greenhouse muskmelon, Dry matter partitioning, Yield, Harvest date, Fruit diameter