• ISSN 1008-505X
  • CN 11-3996/S
GAO Hong-yan, SUO Quan-yi, ZHENG Hai-chun, GAO Fan-shen. Construction of regional fertilization system based on GIS and nutrient abundance index[J]. Journal of Plant Nutrition and Fertilizers, 2021, 27(9): 1648-1655. DOI: 10.11674/zwyf.2021219
Citation: GAO Hong-yan, SUO Quan-yi, ZHENG Hai-chun, GAO Fan-shen. Construction of regional fertilization system based on GIS and nutrient abundance index[J]. Journal of Plant Nutrition and Fertilizers, 2021, 27(9): 1648-1655. DOI: 10.11674/zwyf.2021219

Construction of regional fertilization system based on GIS and nutrient abundance index

  • Objectives We assessed available soil nutrients using a nutrient abundance index and graded the spatial distribution of the former based on GIS and soil nutrient grading in Xiliao River Plain. Further, we proposed fertilizer recommendations across the spatial layout.
    Methods Xiliao River Plain in Inner Mongolia covers Horqin District, Kailu County, Naiman Banner, Horqin Left Back Banner, and Horqin Left Middle Banner. Based on 15421 soil test data and 143 “3414” maize trail data, we calculate the spatial interpolation results of alkaline N, available P, and readily available K in the cultivated soil using GIS. Combining GIS with the method of soil abundance index, the nutrient management zones of soil alkaline N (AN), available P (AP), and readily available K (AK) were divided in Xiliao River Plain. The fertilizer uptake of different soil NPK nutrient combinations was determined. The map of N, P, and K zonal fertilization of maize was developed.
    Results The spatial distribution of soil nutrients in the cultivated soil was uneven. The content of soil AN was low, and the contents of soil AP and AK were medium in Xiliao River Plain. The most important combinations of soil AN–AP–AK were low (N)–medium (P)–medium (K), medium (N)–medium (P)–medium (K), and medium (N)–medium (P)–high (K). The area ratio of each combination was 42.4%, 14.1%, and 13.5%. There were better logarithmic relationships between the soil AN, AP, and AK content (x) and the economic optimal fertilizer rate (y). Nitrogen optimal fertilization model was y = –102.5ln (x) + 617.22, phosphorus optimal fertilization model was y = –36.11ln (x) + 174.1, and potassium optimal fertilization model was y = –25.89ln (x) + 180.96. Under the different soil nutrient combinations, the optimal dosage combinations of N, P2O5, and K2O for maize were 202–110–58 (kg/hm2), 168–107–57 (kg/hm2), and 164–102–47 (kg/hm2).
    Conclusions The relative yield of maize has a good logarithmic relationship with soil AN, AP, and AK content. The simulation effects of the function between the relative yield of maize and soil nutrients differ under different methods.When dividing the abundance index of soil alkaline nitrogen, available phosphorus, and readily available potassium in the Xiliao River Plain, grading intervals of the relative yield of 75% and 85% are suitable. Under the big data support of soil nutrients, the regional fertilization management system can be established accurately and rapidly by combining the GIS and abundance index methods.
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