Simulation On Growth, Development And Grain Quality In Barley

Based on the relationship between growth and environmental factors in barley, the models were constructed systematically to predict the apical and phenological development stages, the internode and spike growth, the photosynthetic production, the dry matter accumulation and partitioning, the yield components, the nitrogen absorption and translocation and grain quality. The validations were made in the different genotypes, sowing dates, N rates and regions.The characters of Beta function were analyzed. It is widely used to describe the nonlinear effects of temperature on crop phenological development. The Beta function has many advantages. It can reflect the general requirements of the effectiveness functions of temperature on crop phenological development and well describe the expressions of other types of functions such quadratic function, Gause function and sine function. If k<1 , P<1 or k > 1, P<1/k, the Beta function is certainly convex. The study also demonstrated the relationship between P values and the temperature sums and reasoned the range of parameter P. The models of apical and phenological development stages in barley were constructed by the scale of physiological development time, which was based on the ecophysiological development process. In the models, the Beta function was used to describe the response of barley development to temperature. The genetic parameters of the temperature sensitivity, physiological vernalization time, photoperiod sensitivity, intrinsic earliness, filling fraction were introduced. The validation showed that the absolute prediction errors for development stages were generally less than 6 d, and the root mean square errors (RMSEs) were 0.9 2.9 d in Yangzhou in 2004²006 years. The absolute prediction errors for phenological development stages were less than 5 d, and the RMSEs were 1.0².8 d in Lianyungang in 2004²006 years. The models reflected an enhancement in mechanism, explanation and prediction.Based on physiological development time, the spike and internode growth dynamics were simulated by Richards equation in order to construct systematically architectural models in barley. In the models, growth process and order of spike and internode were judged by physiological development time, with special consideration of the effects of nitrogen, temperature and light. The validating results showed that the absolute prediction error ranges of spike length were 0.05¹.66 cm and the RMSEs were 0.28～0.75 cm. The absolute prediction error ranges of internode length were 0.03⁶.08 cm, and the RMSEs were 0.23～4.43 cm. The absolute prediction error ranges of internode thickness were 0.002⁰.122 cm, and the RMSEs were 0.016～0.048 cm.Based on the experimental observation and quantitative analysis, the model of leaf area index (LAI) in barley was constructed by two nonlinear equations, with the maximal value of per plant leaf area as genetic parameter. The model represented the influence of nitrogen and temperature on leaf growth, and solved how two nonlinear equations joined. With reference to the relative models in wheat, the photosynthetic production models in barley were constructed. Taken the physiological development time as the developmental scale, the models of the partitioning indexes of dry matter for the green leaf, stem, spike and grain were constructed. In the model of dry matter partitioning index for grain, the maximal value of partitioning index was uses as the genetic parameter to reflect the grain-filling characteristics of different genotypes of barley. The validating results showed that the absolute prediction error ranges for LAI were 0.007¹.468, and the RMSEs were 0.109～0.718. The absolute prediction error ranges for dry matter weight were 0.002～0.264 kg·m^-2, and the RMSEs were 0.019～0.206 kg·m^-2.The absolute prediction error ranges of leaf weight were 0.001～0.199 kg·m^-2, and the RMSEs were 0.013～0.060 kg·m^-2. The absolute prediction error ranges for stem weight were 0.001～0.689 kg·m^-2, and RMSEs were 0.006～0.227 kg·m^-2. The absolute prediction error ranges for spike weight were 0.001～0.056 kg·m^-2,and RMSEs were 0.004～0.018 kg·m^-2. The absolute prediction error ranges for grain weight were 0.000～0.178 kg·m^-2, and the RMSEs were 0.007～0.090 kg·m^-2。Some assumptions were made during the nitrogen accumulation process in barley as following. ( 1) Before anthesis, the nitrogen absorbed from soil was distributed to various organs according to certain proportions. (2) After anthesis, the absorbed nitrogen from the soils all was used for the grain protein formation. (3) After anthesis, the nitrogen stored in leaf, stem and spike starts to remobilize to the grain. Based on these assumptions, the dynamic models of nitrogen accumulation were constructed by relationship between dry matter accumulation and the nitrogen accumulation. In the model, the complex process of nitrogen remobilization after anthesis was simplified. The soil nitrogen factor was used to reflect the nitrogen supply levels in the soil and the contents of NO3--N and NH4+-N were regarded as the criterion of nitrogen supply conditions. In the computation about nutrient absorption, the computation related to the root system was avoided. Based on the experimental data, the dynamics of nitrogen partitioning indexes with the physiological development time was modeled. The validating results showed that the absolute prediction error ranges for nitrogen accumulation in barley were 0.030～3.300 g·m^-2and the RMSEs were 0.330～1.568 g·m^-2.The absolute prediction error ranges for leaf nitrogen accumulation were 0.015～1.839 g·m^-2 and the RMSEs were 0.190～0.871 g·m^-2. The absolute prediction error ranges for stem nitrogen accumulation were 0.004～1.732 g·m^-2, and the RMSEs were 0.197～0.676 g·m^-2. The absolute prediction error ranges of spike nitrogen accumulation were 0.007～0.782 g·m^-2 and the RMSEs were 0.053～0.191 g·m^-2.This research assumpted that during the barley grain filling, the grain nitrogen accumulation had the maximized tendency and the nitrogen demand of grain was supplied from the vegetative organs and the soil. Nitrogen absorbed from the soil was used completely for the grain. When nitrogen supply was insufficient, the grain would gain more nitrogen from the vegetative organ. Based on these hypothesis, the nitrogen absorption and remobilization model after anthesis were constructed. In the model, the relationship between leaf nitrogen remobilization and the leaf area index were described with exponential functions. The nitrogen translocation from stem and spike showed nonlinear relations with the respective nitrogen contents in these two organs. The nitrogen accumulation in grain was closely related to grain dry matter weight and was expressed with exponential functions. Based on physiological development time,the model to predict 1000- grain weight was constructed and in the model the effects of the nitrogen supply,temperature and light were included. The test results showed that the absolute prediction error ranges of nitrogen accumulation in grain were 0.004～2.539 g·m^-2,and the RMSEs were 0.664～1.343 g·m^-2. The absolute prediction error ranges for grain weight were 0.01～6.00 g, and RMSEs were 0.27～3.80 g. The absolute prediction error ranges for grain protein contents were 0.06%～3.23%, and RMSEs were 0.51%～1.57%. The absolute prediction error ranges for 1000-grain weight were 0.04～6.00 g, and the RMSEs were 3.08～3.80 g.