| As one of the most important indicators for evaluating soil quality, soil nutrient is not only the fundamental substance of productivity of land, but also the necessary condition of crop growing. Ningxiang county is a traditional agricultural area in the middle part of Hunan province. With the increase of applying chemical fertilizer and pesticide content, and the changes of no-tillage and seedling-throwing in farming practices, its soil nutrient has changed greatly. At present, the current studies on soil nutrient in Ningxiang county are only limited to the massiveness of farmland scale. There are adequate analysis and full understanding on the present situation of farmland involving county-wide scale. It has a certain reference value and guiding significance to county scale soil management in decision-making practices via expounding spatial variation law and integrated soil nutrient status of basic farmland paddy soil nutrients in Ningxiang county.Taking Ningxiang county of Hunan province as the studied region, in this present study, investigator corrected composite soil samples from 0~10cm deep paddy soil layers in 41 representatives sampling sites after the late rice harvest in 2013. All the soil samples were taken to the laboratory for measurements of soil p H, organic matter, total nitrogen, total phosphorus, total potassium, available nitrogen, available phosphorus, available potassium. Traditional statistics methods, geostatistics methods and variable fuzzy sets theories were used for studying the spatial distribution and comprehensive evaluation of the soil nutrient indexes. It would provide a theoretical basis for regional soil fertilizer precise management and ensuring food safety production. The main results are listed as follows:(1) The variation coefficients of the eight nutrient indexes were varied from 15.54% to 74.89%, both belonging to middle variation, among which available phosphorus was the highest. Correlation analysis showed that soil p H can be used as the physical indicator of soil nutrients, but there was no significant correlation between p H and other soil nutrients, and significant correlations were detected between organic matter and available nitrogen.(2) Geostatistics analysis showed that the C0/(C0+C1) of soil p H, organic matter, total nitrogen, total phosphorus, total potassium, available nitrogen, available phosphorus and available potassium were 0.14, 0.49, 0.44, 0.56, 0.61, 0.35, 0.52 and 0.71, respectively. Besides, p H implied a strong spatial dependence, and other nutrient indexes were moderate dependence.(3) The distribution maps of soil nutrient indexes produced by Kriging methods showed that four indicators showed strip trends except p H, organic matter, available nitrogen, available phosphorus. Areas of low soil p H were located in the south-east and west of the region; organic matter and available nitrogen exerted higher values in the central and eastern; total nitrogen was higher in the east and west and lower in the north and south; total phosphorus and available phosphorus presented higher values in the central; total potassium and available potassium were characterized by low content in the central region.(4) By using fuzzy variable model with combined weights to evaluate the soil nutrient of studied region, the results showed that the evaluation values were ranged between 0.00 and 3.75. The low nutrient content of soil nutrition were shown up in the east-central area and that of high were emerged in the west and northeast region, assuming cyclic annular. It is shown that, meanwhile, variable fuzzy assessment method has increased the relative and dynamic variability and improved the stability and reliability of the evaluation results by using fuzzy mathematics method for validation. |
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