Research Of Precise Fertilization Decision Support System In Xinjiang Processing Tomato Industry

Precision agriculture is one of the main technical characteristics of modern agriculture. Processing tomato planting in Xinjiang has entered the industrialization scale. Because of traditional large-scale management, mechanical work, widely used, fertilizer efficiency is becoming an important problem to test the economies of scale, so it is imperative for precision agriculture. As a key technology of precision agriculture, precision fertilization can effectively improve the efficiency of the processing tomato industry, reduce the blindness of fertilizer, reduce waste, as much as possible to maintain the original soil physical and chemical properties, and effectively reduce the fertilizer on soil crumb structure. In this paper, in order to realize the goal of precise fertilization, related mathematical models are established through applying mathematics, intelligent control algorithm, computer technology after analyzing and comprehensively evaluating a large number of sample data about the soil, fertilizer, characteristics of crop growth, and a decision support system is formed based on decision theory and method.The discretion of the fertility of soil is the precondition of precise fertilization. For soil fertility problems, soil fertility evaluation model is established based on weighted fuzzy clustering analysis algorithm and fertilizer recommendations are put forward in the paper. In terms of effectiveness, Taking an example of potash, the effect of potash fertilizer on tomato yield and quality traits of correlation order are concluded by using grey correlation analysis. For specific fertilization model, "3414" fertilization model and based on BP neural network of fertilization model was established after the soil fertility and fertilizer effect are determined and the results show that the latter is superior to the former. The processing tomato industry in Xinjiang precise fertilization decision support system is preliminary formed by analyze the decision support system architecture and function of each module.