Spatial Variability And Management Zones Of Tobacco Soil Nutrients Based On GIS Combined With Geostatisics

Soils are highly variable spatially due to the combined effects of physical, chemical, and biological processes that operate with different intensities and at different scales. Therefore, understanding of the spatial variability of soil properties is essential in determining local fertilizer needs of tobacco. Based on classical statistics, spatial variability of soil nutrients in a tobacco-planted field was studied and spatial distribution maps of soil nutrients was generated by the combined usage of GIS and geostatistics. to improve tobacco quality ceaselessly, to improve tobacco output and the farmer income .It has strong function of managing spatial data for GIS, while geostatistics has strong function of spatial analyse, so they can learn from each other's strong points to offset each other's weakness if combine them, and then they can exert their advantage adequately to open out the spatial variability character of soil fertility. In this study, Based on GIS and GPS technology, The geostatistics method was applied to study the spatial variability characteristics of soil and draw soil nutrient distribution map in tobacco field at modern tobacco demonstration base of WangLing in county of Luoning in HeNan of province. In this study, conventional statistics,Geostatistics,the spatial analysis technique of geographic information system were used to analyze spatio-temporal variability of soil properties in the study area, based on which, to design the classify precise management zones.Soil chemical properties and texture were analyzed and their spatial variability was assessed by geostatistical techniques.The main conclusions were as follows:(1) In all the study area , Soil OM ,AN and Available Fe,Cu,Zn were a lower level with average content. Soil AK, Available Mn were a optimum range and the other soil nutrients were a low level. Coefficients of variation ranged from approximately 4.43% for pH to almos39.3% for total phosphorus.Coefficients of variation ranged from approximately 3.4% for pH to almost 48% for available Zn. Soil pH and available nitrogen had a weak spatial variability and soil total phosphorus, available phosphorus and available Zn had a strong spatial variability, Thus, differentiated management may be necessary to achieve maximum economic and environmental benefits. Distributions of all the variables were only slightly skewed, and their medians were close to their means. The Kolmogorov-Smirnov test revealed that all variables were normally distributed (P >5%) and did not require transformation. By log-transformation, soil available K showed normal distribution, thereby providing a basis for further structural analysis.(2) In the study area, most of the tobacco soil nutrients were all significantly or very significantly correlated. all the nutrient properties of soil pH are negatively correlated, indicating a certain extent, reduce the soil pH can increase the effectiveness of various nutrient content ,except to AN and available Cu; Soil organic matter and available Cu had significant negative correlated with total K, available potassium and available phosphorus, total nitrogen, available nitrogen, available phosphorus and available iron, manganese, zinc positive correlation, suggesting that increased soil organic matter content to improve the content of other nutrients can promote.(3) From the results of geostatistical analysis , The results show that semivariogram analyses are shown that coefficients of determination (R2) for all variables, the semivariograms for pH, TK, available Cu, fit the Spherical Model, AN showed only pure-nugget effect fitted by linear model and the soil nutrient of tobacco fit the Exponential Model.The ratio of nugget variance to sill variance can be used to classify spatial dependence of soil properties. Nugget/Sill<25% indicated strong spatial dependence, between 25% and75% indicated moderate spatial dependence, and >75% indicated weak spatial dependence. Soil properties with strong and moderate spatial dependence will be more readily managed and an accurate site-specific fertilization scheme for precision farming more easily developed. Geostatistical analysis also revealed that the soil pH was strongly spatial dependent.Their spatial variability was mainly caused by structural factors.The available Fe was weak spatial dependent, Moreover, the other soil nutrients were moderately dependent.Their spatial Variability was caused by structural and random factors.The effective range of these items was 43.5 to 610.7meters.(4) The study area, It was shown from Kriging analysis that the pH value gradually ascended from the northwest to southeast, The available K and organic matter were the higher in the middle and southeast investigation region. The area with 65.53-73.65mg kg-1 available nitrogen content accounted for 73.65 % of the investigated region,mainly distributed in the west and a area of southeast of the east ;that with 5.65- 11.69mg kg-1 available P content accounted for 86.59% of the investigated region,and the area that 145.21-190.74mg·kg-1 soil available K content Was accounted for 70.45%,mainly distributed in the west, middle and a part of east, All these results could serve as a basis for precision fertilization in tobacco farming.Micro-nutrient content of soil spatial distribution of available iron in the study area that generally a serious lack of available manganese content of the study area is rich in both high levels in the medium level of available zinc in large differences in the study area, showing scattered , 70% of the region at low concentration level, available copper content in the entire study area are in the middle level. It is suggested based on spatial distribution of trace nutrients, the whole region of applied iron fertilizer, northwest and southeast of applied zinc to ensure normal growth of tobacco. Through the spatial pattern of soil nutrients, intuitive understanding of the spatial distribution of soil nutrients in tobacco field, the differences in soil management Tobacco basis.(5) PCA and fuzzy cluster algorithm were then performed to delineate MZs. The first four PCs with eigenvalues greater than 1 were considered for clustering analysis, The first four principal components that can provide information on all of the soil indicators reflected 70.19%. which was performed in MZA procedure using fuzzy c-means cluster algorithm. Performance index (FPI) and normalized classification entropy (NCE) were used to determine the optimum cluster number. Results showed that the optimum number of MZs for this study area was three.