Study On Growth Model And GIS-Based Wheat Prpductivity Prediction Technology

Prediction of crop productivity and analysis on climate change impact are of great importance for evaluating future food security situation in agricultural industry. Crop growth model can be a powerful tool for predicting yield production, assisting management decision, and assessing the impacts of environment changes on agriculture. This study, taking wheat as research crop, firstly, built a simulation model on grain protein composition based on growing degree days (GDD). Secondly, a regional wheat productivity model was developed to scale up growth model from site to region levels, by integrating with Geographic Information System (GIS). Then, it was used to evaluate the influences of production levels and climate change scenarios on regional wheat production. Finally, a decision support system was constructed by combing the WheatGrow model with GIS and using component-based technology. The established system provides a digital tool for simulation of regional grain productivity, evaluation of potential productivity, assessment of climate change impacts and formulation of agricultural policy in wheat production.Based on time-course observations on grain protein components under varied nitrogen rates and water regimes with different cultivars, the change patterns in the contents of different grain protein components with growth progress and environmental factors were characterized, and a dynamic model was developed to simulate formation processes of grain protein components in wheat grains. The dynamic content of albumin with GDD after anthesis could be described with a power model, and the contents of gliadlin and glutenin could be described with a logarithmic model. The effects of nitrogen and water conditions on grain protein components were quantified with nitrogen and water factors. The model was validated with independent experiment data. The results indicated that the present model had a good performance in predicting dynamic contents of major protein components in wheat grains.Considering the approaches to scaling-up the crop model from plot to region level, a regional wheat model was developed by integrating the site-specific wheat model WheatGrow with GIS. To address the spatial variability, grid-based data as model input were generated in advance by interpolation and overlaying with the aid of GIS. When all the necessary input data were available, the target region was partitioned into smaller and relatively homogeneous spatial grids, and crop yields were simulated with WheatGrow for each grid cell. And then all grid results were aggregated to a regional value. Finally, with different experiment and statistical data, the model was operated at site and regional scales, respectively. The results indicated that the present model was accurate and applicable at both scales and the regional wheat model can be used to evaluate grain productivity, water productivity, nitrogen productivity, potential productivity, and climate impacts in wheat production at regional level.By linking the established regional model and the method of scenario analysis, the wheat productivity levels in Huanghuaihai region were simulated under different production scenarios, respectively, and the effects of climate change and the adaptable strategies on wheat production were also assessed under 2080 scenario. The results shown that the simulated yields for three production scenarios were 9386 kg·ha-1-13907 kg·ha-1 for photosynthetic level (PS1),7735 kg·ha-1-12020 kg-ha-1 for photo-thermal level (PS2), and 3770 kg·ha-1-614kg·ha-1 for land level (PS3)?, respectively. The yield increasing potential defined as the gap between PSl and PS3 production situations ranged from 5534 kg·ha-1 to 9065 kg·ha-1. The wheat productivity can be enhanced by reasonable increase in agriculture inputs. As the results of climate warming, the wheat development would be accelerated and the growth duration would be shorted significantly. If the direct effect of CO2 elevation was not concerned, the rain-fed and irrigated wheat yields under 2080 scenario would decrease mostly, although irrigation might partially relieve the impacts of climate changes on wheat yield. Involving the direct CO2 effect, the trend would turn opposite. Several strategies could be proposed to offset the negative influences of climate change on wheat productivity, including changing planting date, using new variety, and enhancing agricultural input.On the platform of Visual Studio 2005, the growth model and GIS-based wheat productivity prediction system was constructed by adopting C# language and component-based software and using Access database. With integration of growth model with GIS, the system can manage and analyze spatial data and generate fine resolution data as input for growth model, and thus could be used to forecast grain productivity levels under different production situations and at different spatial scales. By further combining with scenario simulation and strategy analysis, the present system can help to evaluate the potential impacts of climate change patterns on grain productivity and suitable management strategies in future wheat production.