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 ° 19N, 86 ° 24E) of China showed that this model had a good predictability and practicability.
Processing tomato(Lycopersicon esculentum Mill) Dry matter accumulation Dry matter partitioning Partitioning index Yield formation Simulation model
WANGJichuan YU Jun GAO Shan YUAN Jie MA Fuyu CHEN Yuanliang HE Wei
College of Plant Science, Tarim University, Alar, Xinjiang, P.R.China, 843300, Institute of Industrial Crops, Xinjiang Academy of Agricultural Sciences, Urumqi, Xinjiang, P.R.Chin Key Laboratory ofOasis Ecology Agriculture of Xinjiang Production and Construction Crops, Shihezi Xi Institute of Vegetable Science, Shihezi, Xinjiang, P.R.China, 832003 No.223Farm of the Second Agriculture Division, Xinjiang Production and Construction Crops, Hejing Xi