Simulation of Processing Tomato Dry Matter Accumulation,Partitioning and Yield Prediction

摘要

Simulation of dry matter accumulation and distribution of crop growth models is an important means of predicting yield formation. This study set up test of different processing tomato cultivars, sowing date and density test. By analyzing the quantitative relationships between processing tomato(Lycopersicon esculentum Mill) growth and physiological development time (PDTv), based on knowledge model, dry matter partitioning index and harvest index(HI), the simulation models were developed to estimate the total dry matter accumulation, shoot dry matter partitioning and yield formation of processing tomato. The sowing date factor(SDF) was introduced to regulate the partitioning intensity, and the genetic feature of cultivar was considered. The validation with trial data gained by setting cultivars and sowing experiments in Xinjiang Shihezi (44°26' N, 86°01' E) and Hejing (42 ° 19"N, 86 ° 24'E) of China showed that this model had a good predictability and practicability.