Studies On The Dynamic Simulation Models For Growth Of Super Hybrid Rice Seedings

Agricultural information technology has become a new scientific field with the development of agricultural science and information technology. Crop system simulation model is one of hot topic in the fields of agricultural information technology. Crop simulation model has developed greatly in recent 20 years. It has gone trough from the qualitative conceptual model to quantitative simulation model and has been applied to production practice successfully.This thesis, based on the growth full stage of Super hybrid rice and applied with the mathematical model, referenced to a large number of domestic and overseas achievements about crops growth stage simulation model, has established preliminarily development stage simulation model of Super hybrid rice. Xiangliangyou 68, Zhuliangyou 02 and Zhuliangyou 819,these three of the representative Super hybrid rice varieties in hunan province were selected to do the fields experiment in Ningxiang area. The experimental data is used for determining the model parameters and model validation. The model mainly includes:(1) developing stage model; (2). leaf age model.The result as following,1.Rice development stage forecasting is the foundation of rice development stage simulation model. This thesis described quantificationally of the process of Super hybrid rice development stage on the basis of Super hybrid rice development stage characteristics and the features of developmental stage model. The auther fully considered its' basic nutrition characteristics, photonasty and sensitivity for temperature which determined the parameters for the model, using the method of unconstrained conditions of nonlinear programming step-length accelerated. Tested with data from field experiments, the model showed that the absolute deviation between observed and simulated development stage was less than 3 days. This is a very good result.2. The auther considered the influence on leaves growth with rice varieties and the temperature and stablished the Super hybrid rice leaves age model. The model had better practicability because it involved in less varieties parameters and meteorological data. Tested with data from field experiments, the model showed that the deviation between observed and simulated leaf ages was less than 1 leaf age.