通过定量描述水稻群体基本苗以及主茎与分蘖数、叶面积指数和干物质积累动态与品种类型、生态环境因子和栽培措施之间的动态关系，以基于生理发育时间的积温来计算的发育进程为主线，建立了广适性的水稻适宜群体生长指标的知识模型，可为不同条件下水稻栽培过程中的生长调控与苗情诊断提供定量化的动态指标体系，包括群体主茎与分蘖动态、叶面积指数动态和干物质积累动态等。利用不同生态点的常年逐日气象资料以及不同品种类型对所建知识模型进行了实例分析。结果表明，本模型设计的大田基本苗与实际生产值RMSE平均为5.0，模型设计的群体生长动态指标与已有的高产栽培模式中实测结果平均相关系数达r=0.85**以上，故知识模型对不同条件下的水稻生长指标适宜动态具有较好的预测性。

Based on the analysis of the quantitative relationships of rice growth dynamics to varietal traits, eco-environments and planting measures, a universal knowledge model for rice was developed, which was driven by physiological development time-based cumulative temperature. The model can be used to predict the time-course dynamics of growth indices including population stem and tiller number, leaf area index and dry matter accumulation for growth guideline and diagnosis with different varieties, eco-environments and planting measures. Case studies with the data sets of normal climatic year and different variety types at different eco-sites indicated a good performance of the model system for prediction with the RMSE=5.0 for the simulated and observed population density, r=0.85** for the simulated and observed growth indices.