Establishment Of Fertilization Index System Of Wheat In China Based On GIS

As one of the main grain crops in China, wheat is the most important commodity grain and strategic variety for grain reserve, which yield and planting area accounted for 1/5 and 1/4 of the total yield and planting area in total food crops. It is of great significance to establish N, P and K fertilizer recommendation system of wheat in China based on different climatic characteristics, soil types and soil nutrients status in guiding crop fertilization and improving farmland ecological environment. This paper studied the effect of climate factors such as temperature, precipitation and soil factors such as soil type, texture on wheat yield, soil fertility capacity and fertilizer use efficiency according to the field trials of wheat in multiple years and sites. Based on nutrient balance and soil tests, a wheat fertilizer recommendation system was established, and wheat fertilization decision-supporting system was also developed using secondary development of ArcGIS. Main conclusions were obtained as follows:(1) Determination of basic parameters in nutrient balance fertilization modelTarget yield was used as an independent variable in the fertilization model and the upper limit of yield was limited by climatic potential productivity. Statistical analysis showed that a significant linear correlation was reached between nutrient uptake of wheat biological yield and its corresponding grain yield. The nutrient uptake per unit yield was trended to a stable range. Therefore, we can set the nutrient uptake per unit yield as a constant in this study. For per 100 kg yield of winter wheat, 3 kg N, 1.2 kg P₂O₅ and 2.8 kg K2O nutrient were respectively needed. And for per 100 kg yield of spring wheat, 3 kg N, 1.1 kg P₂O₅ and 2.6 kg K2O were respectively needed. The calibration coefficient of soil available nutrients and the fertilizer utilization efficiency were respectively calculated based on the experiment data. It was studied the variability of the two parameters on 27 soil types in China. The average value of the two parameters for each soil type was different and the variability which indicated by the standard deviation in the same soil type was also significant. Extremely high discrete degree also showed the high variability in most soil types. The calibration coefficient of soil available nutrients and the fertilizer utilization efficiency were influenced by average temperature and precipitation during wheat growth, soil clay content, pH value, irrigation, and so on.(2) Establishment of two sub-models for calibration coefficient of soil available nutrient and fertilizer utilization efficiencyIt was established the sub-model for calibration coefficient of soil available nutrient by using the factors including soil available nutrient (alkaline hydrolytic nitrogen, available phosphorus and available potassium), soil clay content and average temperature during wheat growth period. The goodness-of-fit was higher which the coefficients of determination (R2) were from 0.55 to 0.85. The fitting accuracy of sub-model for calibration coefficient of soil available nutrient was available phosphorus higher than available potassium, and than alkaline hydrolytic nitrogen. It showed a significant negative correlation with logarithm function between soil nutrient contents and fertilizer utilization efficiency. The sub-model for fertilizer utilization efficiency was established by using soil nutrient content as the independent variable at different yield level. The goodness-of-fit was also higher which the related coefficients (r) were from 0.45 to 0.75 and showed a significant difference. The two sub-models were revised by using soil pH and irrigation factors, respectively.(3) Establishment and validation of nutrient balance fertilization modelIn the nutrient balance fertilization model, the target yield parameter was set as input item, the nutrient uptake of per unit yield was set as a constant. Combining with the two sub-models of calibration coefficient for soil available nutrient and fertilizer utilization efficiency, a comprehensive nutrient balanced fertilization model was established. Target yield and soil available nutrient testing value were set as independent variables, NPK fertilizer application rates as dependent variable. A nationwide fertilizer recommendation system of wheat was established based on 15 soil groups incorporated from 27 soil types. The recommended fertilization from nutrient balance fertilization model was validated by the wheat field trial results arranging the main trial area. The recommended fertilizer rate based on the nutrient balance fertilization model was between the rate for the maximum yield and the optimized economical benefit yield recommended by fertilizer response function model. It indicated the model was feasible for fertilizer recommendation for wheat with simple, fast and accurate characteristics.(4) Building basic spatial database of the ecological and environmental factors for wheatOn the GIS platform, the basic spatial database including each ecological and environmental factor which impacted the wheat fertilization model parameters was built based on meteorological data and soil data such as soil types and soil texture etc. Different kinds of layers were constructed by interpolation, conversion between vector and grid layer, and layer superposition treatment etc. The layers included the grid layers of average temperature, average precipitation during wheat growth, soil clay content and pH value, wheat water requirement and the climatic potential productivity yield etc, and vector layer of the minimum fertilization unit by superposing county boundary map with soil type map in China.(5)Development of wheat fertilization decision-making system based on GISCombining GIS database and wheat fertilization model, the wheat fertilization decision-making system was developed by using ArcGIS Engine and C# language under GIS environment. The layer management of the spatial data and attribute data was realized through the fertilization decision-making system. The fertilizer recommendations were performed based on the database as information source and the fertilization model as decision-making support. The system could support wheat fertilization decision-making for farmers and agriculture departments at the micro-sale and macro-scale level respectively. The development of this system could provide a framework and way to develop the decision-making system for other crops, and technical support for precision agriculture and digital griculture.