水分对温室网纹甜瓜植株形态与干物质分配影响的模拟

Simulation of Effects of Water on Plant Morphology and Dry Matter Partitioning of Greenhouse Muskmelon

为定量研究水分对温室网纹甜瓜植株长势(株高、茎粗)以及各器官干物质分配的影响,以温室网纹甜瓜品种"网路"为材料,于2010年3月～2010年11月在玻璃温室内进行不同定植期和不同水分处理的栽培试验,以生理辐热积为预测指标,定量分析了基质水势对网纹甜瓜株高、茎粗以及各器官干物质分配的动态影响,建立了基质水势对网纹甜瓜株高、茎粗和各器官干物质分配指数的模拟模型,并用与建立模型相对独立的数据进行检验。结果表明:随基质水势的升高,网纹甜瓜的株高和茎粗增加,各器官间的干物质分配量减少。模型对网纹甜瓜植株株高、茎粗的预测值与实测值基于1:1线间的决定系数(R2)分别为0.977和0.936,预测相对误差分别为6.1%和5.4%;对网纹甜瓜叶、茎、果实、地上部、地下部的干重的预测值与实测值基于1:1线间的R2分别为0.971、0.976、0.982、0.982、0.980;相对预测误差分别为10.1%、3.2%、11.8%、9.2%、12.7%。模拟预测精度较高,可较好地模拟不同基质水势条件下的网纹甜瓜植株形态和各器官干物质动态的变化过程。

To quantitatively investigate the effects of water on plant morphology （plant height, stem diameter） and dry matter partitioning of greenhouse muskmelon, cultivation experiments of greenhouse muskmelon （＇ Wanglu＇） with different planting dates and different levels of water treatment were performed in a glass solar greenhouse from March to November, 2010. The physiological product of thermal effectiveness and PAR （PTEP） was used to describe the seasonal change of the indices. Effects of substrate water potential on the dynamics of plant height, stem diameter and dry matter partitioning were quantified based on the experimental data. The simulating dynamics model of plant height, stem diameter and dry matter partitioning was established and validated by independent experimental data. The results showed that with increase of substrate water potential, plant height and stem diameter increased, but dry matter distribution of organs decreased. For plant height and stem diameter, the coefficient of determination R2 between the simulated and the measured value based on the 1.1 line was 0. 977 and 0. 936, respectively; and the relative prediction error was 6.1% and 5.4%, respectively. For leaf dry weight, stem dry weight, fruit dry weight, shoot dry weight and root dry weight, the coefficient of determination R2 between the simulated and the measured value based on the 1.1 line was 0. 971, 0. 976, 0. 982, 0. 982, 0. 980, respectively; the relative prediction error was 10. 1%, 3. 2%, 11. 8%,9. 2%, 12. 7%, respectively. The model developed in this study has high simulating and predicting precision, which can simulate plant morphology of muskmelon and dynamic changes of organic dry matter under different substrate water potential well.