With the application of methods such as GPS, GIS, and geostatistics in soils, the spatial variability of soil characteristics has received increasing attention. Chinese soil researchers began to study soil spatial variability in the early 1980s. Many years of research have shown that because topographic factors are closely related to the transport of water in the soil and the transport of matter, thus affecting the distribution of nutrients in the soil, understanding the spatial variability of soil nutrients for rational fertilization and increasing the efficiency of nutrient use in farmland Crop yield and quality are of great significance. Therefore, the study of soil nutrient variability through soil nutrient fastness measurement has become one of the hot spots in soil science research.
Because the average value and the coefficient of variation reflect the overall situation of the whole land, covering the change information of each specific location, it is necessary to use the soil nutrient fastness instrument method to analyze more accurately. The skewness, kurtosis and KS test (P>0.05) showed that all soil nutrients conform to the requirement of normal distribution, and the instrumental method was used to predict the spatial distribution of soil nutrients. It was found that the soil nutrient speed meter could be used. The statistical data of the statistics were spatially analyzed.
The coefficient of variation (CV) reflects the degree of spatial variability of the texture of the soil between sampling sites. It is a weak variability at CV<10%, and a strong variability at >100%, and is intermediate between the two. Variability. From the coefficient of variation of soil nutrients in the measurement data related to the soil nutrient fastness meter, except for pH and cation exchange capacity, the coefficient of variation of other soil nutrients belongs to moderate intensity variation.
Soil samples were taken at a sampling interval of 20m. The soil nutrient velocity analyzer was used to analyze the spatial variability and spatial distribution of nutrients. Due to time constraints, this experiment only analyzed the spatial variability of these elements from one-year data and failed to reflect temporal variability. The next study can use multi-year data to analyze the spatial distribution characteristics of soil nutrients. At the same time, factors such as soil nutrient trend effects and spatial autocorrelation should be taken into consideration to comprehensively analyze the spatial variability of soil trace elements.
Because the average value and the coefficient of variation reflect the overall situation of the whole land, covering the change information of each specific location, it is necessary to use the soil nutrient fastness instrument method to analyze more accurately. The skewness, kurtosis and KS test (P>0.05) showed that all soil nutrients conform to the requirement of normal distribution, and the instrumental method was used to predict the spatial distribution of soil nutrients. It was found that the soil nutrient speed meter could be used. The statistical data of the statistics were spatially analyzed.
The coefficient of variation (CV) reflects the degree of spatial variability of the texture of the soil between sampling sites. It is a weak variability at CV<10%, and a strong variability at >100%, and is intermediate between the two. Variability. From the coefficient of variation of soil nutrients in the measurement data related to the soil nutrient fastness meter, except for pH and cation exchange capacity, the coefficient of variation of other soil nutrients belongs to moderate intensity variation.
Soil samples were taken at a sampling interval of 20m. The soil nutrient velocity analyzer was used to analyze the spatial variability and spatial distribution of nutrients. Due to time constraints, this experiment only analyzed the spatial variability of these elements from one-year data and failed to reflect temporal variability. The next study can use multi-year data to analyze the spatial distribution characteristics of soil nutrients. At the same time, factors such as soil nutrient trend effects and spatial autocorrelation should be taken into consideration to comprehensively analyze the spatial variability of soil trace elements.
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