中文摘要：

根据试验资料及温室番茄（Lycopersicon esculentum）作物的生长特性，构建了基于分配指数（Partitioning index，PI）和收获指数（Harvest index，HI）与辐热积（Product of thermal effectiveness and PAR，TEP）关系的番茄干物质分配和产量预测的数学模型，并利用不同品种、基质和地点的试验资料对模型进行检验．模型对番茄地上部分干重、根系干重、茎干重、叶片干重和果干重的预测结果与1：1直线之间的决定系数（Coefficient of determination，R^2）分别为0．95、0．57、0．82、0．79和0．93；统计回归标准误差（Root mean squared error，RMSE）分别为647．0、78．1、279．0、496．9和381．8kg·hm^-2；对产量的预测结果与1：1直线之间的R^2和RMSE分别为0．88和5828．5kg·hm^-2；不仅预测精度较高，且参数少、用户易于获取，为温室番茄模型应用于温室番茄生产的优化管理奠定了基础．

英文摘要：

Based on the relationships between dry matter partitioning index, harvest index, and product of thermal effectiveness and PAR, a simulation model for greenhouse tomato dry matter partitioning and yield prediction was built, and validated by independent experimental data of different cultivars, substrates and locations. The coefficient of determination （R^2） between simulated and measured shoot, root, stem, leaf and fruit dry matter weight based on 1：1 line was 0.95, 0.57, 0.82, 0.79 and 0.93, the root mean squared error （RMSE） between them was 647.0, 78.1, 279.0, 496.9 and 381.8 kg·hm^-2, and the R^2 and RMSE between predicted and measured yield based on 1：1 line were 0.88 and 5 828.5 kg·hm^-2, respectively. Compared to ＇source-sink＇ theory, the model developed in this study could give satisfactory prediction of the dry weight of leaf, stem, fruit and yield, with fewer parameters that could be easily obtained in practice.