| Based on the achievements in physiological and ecological mechanisms of cotton boll development and seed quality formation, the experiment conducted in Nanjing (the lower reaches of Yangtze River Valley) in 2006 and 2007, and the experiment conducted in the Yellow River Valley (Xuzhou and Anyang) and the lower reaches of Yangtze River Valley (Huaian and Nanjing) in 2005, we quantify the effects of cultivar characteristics, weather (temperature and solar radiation), and crop management variables (precisely N supply) on cotton boll development and seed quality formation using agricultural model principle and systematic analysis method. And then we developed the cotton boll maturation period model base on physiological development time, cottonseed quality ecological model, and the simulation model of cottonseed biomass accumulation, protein and oil formation based on the eco-physiology processes. These models were tested with the field experimental data collected from different sits with different cotton cultivars.1. Cotton boll maturation period modelBy the field experiments with different maturity cotton cultivars, the responses of cotton boll development to cultivar characteristics, weather conditions (temperature and solar radiation), and crop management variable (N nutrients) were quantified. Cotton boll development was simulated using the scale of physiological development time. The model was tested using independent field data in 2005. The simulated values of boll maturation period showed reasonable agreement with the observed values, with root mean square error (RMSE) of 2.25 days for DSC-1, of 2.61 days for KC-1, and of 2.75 days for AC-33B. The results showed that the model was sufficiently robust to simulate boll development and predict boll maturation period under diverse environmental conditions. It is the improvement of boll maturation period model and provides the time variable for simulation model of cottonseed growth and quality formation.2. Simulation model of cottonseed biomass accumulation By the field experiments with different maturity cotton cultivars and sowing dates conducted at different sites, the responses of cottonseed biomass accumulation to cultivar characteristics, weather conditions (temperature and solar radiation), and crop management variable (N nutrients) were quantified. Based on the hypothesis of sink-determined, the cottonseed biomass accumulation model was then developed. The subtending leaf N concentration of cotton boll was simulated with a semi-empirical equation, which was made as the direct indicator of the N nutrition effect on cottonseed growth and development. The model was tested using independent field data obtained in the Yellow River Valley (Xuzhou and Anyang) and the lower reaches of Yangtze River Valley (Huaian) in 2005. The RMSEs of cottonseed dry weight predictions were 9.5 mg·seed-1 for KC-1 and 8.2 mg·seed-1 for AC-33B. The results showed that the model was sufficiently robust to predict cottonseed biomass accumulation under diverse environmental conditions.3. Ecological model of cottonseed protein and oil contentThe prediction of cottonseed (Gossypium hirsutum L.) quality by ecological factors is an area of great uncertainty. Our object is to investigate the relationship between the cottonseed protein and oil content and the multi-ecological conditions and develop an ecological model to predict the cottonseed protein and oil content under different environments. A set of field experiments were conducted in the lower reaches of Yangtze River Valley (Nanjing, Huaian) and the Yellow River Valley (Xuzhou, Anyang) in 2005, where KC-1 and AC-33B were selected, two sowing dates and three N rates were set. According to the data at sowing date of 25 April, the effect of cultivar, weather conditions, and crop management variables on cottonseed protein and oil content was analyzed by step regression analysis and non-liner regression analysis. We determined that cultivar characteristics, temperature, solar radiation, and N fertilizer rate are main impact factors on cottonseed quality. The optimum temperature for cottonseed protein formation is 26.1℃, and which for oil accumulation is 25.7℃. Adequate solar radiation will reduce the protein and oil content. Increasing the N fertilizer rate will raise protein content and reduce the oil content in cottonseed. The present study developed a ecological model to predict cottonseed protein and oil content. The model was tested by the data collected at sowing date of 25 May in Nanjing, Xuzhou, and Anyang. The RMSE of the model was 2.03% in prediction of cottonseed protein content, and 2.54% in prediction cottonseed oil content. The results showed that the model is sufficiently robust to accuracy predict cottonseed protein content and oil content under diverse environmental conditions.4. Simulation model of cottonseed protein formation based on eco-physiology processThe simulation of cottonseed (Gossypium hirsutum L.) growth is an area of great uncertainty, especially in the process of cottonseed quality formation. To simulate the formation of cottonseed protein under different environmental conditions, a simple process-based model was developed driven by the inputs of cultivar parameters, weather, and crop management variable (precisely N supply). A set of field experiments were conducted in the lower reaches of Yangtze River Valley (Nanjing, Huaian) and the Yellow River Valley (Xuzhou, Anyang) in 2005, where KC-1 and AC-33B were selected, two sowing dates and three N rates were set. According to the data collected in Nanjing, the responds functions of cottonseed protein accumulation to weather conditions (temperature, solar radiation), crop management variable (N supply) and boll position were all developed and involved in the model. The model based on the hypothesis that nitrogen accumulation synthesis in cottonseed are mainly sink determined, and was integrated with the cotton boll maturation period model and cottonseed biomass accumulation model. The parameters in the model were calibrated using the field data obtained in Nanjing. The model was tested using the field data obtained in Huaian, Xuzhou and Anyang. The root mean square error (RMSE) of the simulated and measured cottonseed protein content was 2.05% for KC-1 and 2.33% for AC-33B. The results showed that the model is sufficiently robust to accuracy predict cottonseed protein content under diverse environmental conditions. This model is a necessary component of cotton growth model, and provides a good platform for further study in modeling cottonseed protein yield.5. Simulation model of cottonseed oil formation based on eco-physiology processThe simulation of cottonseed (Gossypium hirsutum L.) growth is an area of great uncertainty, especially in the process of cottonseed quality formation. To simulate the formation of cottonseed oil under different environmental conditions, a simple process-based model was developed driven by the inputs of cultivar parameters, weather, and crop management variable (precisely N supply). A set of field experiments were conducted in the lower reaches of Yangtze River Valley (Nanjing, Huaian) and the Yellow River Valley (Xuzhou, Anyang) in 2005, where KC-1 and AC-33B were selected, two sowing dates and three N rates were set. According to the data collected in Nanjing, the responds functions of cottonseed oil accumulation to weather conditions (temperature, solar radiation), crop management variable (N supply) and boll position were all developed and involved in the model. The model based on the hypothesis that fat synthesis in cottonseed are mainly sink determined, and was integrated with the cotton boll maturation period model and cottonseed biomass accumulation model. The parameters in the model were calibrated using the field data obtained in Nanjing. The model was tested using the field data obtained in Huaian, Xuzhou and Anyang. The root mean square error (RMSE) of the simulated and measured cottonseed oil content was 2.45% for KC-1 and 2.95% for AC-33B. The results showed that the model is sufficiently robust to accuracy predict cottonseed oil content under diverse environmental conditions. This model is a necessary component of cotton growth model, and provides a good platform for further study in modeling cottonseed oil yield.This research provided a systematic process-based simulation model modeling subtending leaf N concentration of cotton boll, cottonseed development, biomass accumulation, N uptake, protein formation, and oil synthesis. This research is an effective supplement for cotton growth model, which fills the vacuity in the research areas, provides a well platform for further study in modeling the formation of cottonseed yield, protein yield and oil yield, and provides also technical supports for regulation and control in cotton production. |
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