Study On Surface Soil Quality Management Of Agricultural Land In Wudi

By analyzing the characteristics of soil spatial variability to study precision soil management zone and variable-rate fertilization management has become a research hotspot in international precision agriculture in recent years.Management zoning technology can implement precise fertilization,scientific management,reduce human and material costs,improve soil fertility and crop yield,improve economic efficiency and management accuracy according to soil nutrient status,crop types and utilization methods,thereby reducing agricultural pollution and protecting the agricultural ecological environment the goal of.The division of soil management zones is mainly based on soil sampling data,lack of discussion on structural factors,the scale range is small and mostly based on the same ecology,and the cost of human and material resources is high.In recent years,3S technology has developed vigorously,and remote sensing data is easier to obtain,which provides the possibility of rapid and effective large-scale soil management zoning.Therefore,in this study,agricultural land in Wudi County,Binzhou City was use d as the research area.Based on soil data and remote sensing index,the soil quality and chemical indicators(pH,water-soluble salts,organic matter,alkali-decomposed nitrogen,effective Phosphorus,available potassium,available iron,available manganese,available copper,available zinc)spatial differentiation characteristics,screening spatially correlated soil chemical indicators and indexes reflecting soil moisture composition of the soil quality factor for principal component analysis,the soil quality factor Carry out multiple regression with the vegetation index to establish a vegetation index soil quality simulation model,use fuzzy C-means clustering to evaluate the accuracy of the vegetation index soil quality simulation model to divide the soil management zone,analyze the feasibility of remote sensing data to dividethe soil management zone,The corresponding management measures were implemented for the basic characteristics of soil,and the following conclusions were obtained:(1)Descriptive statistical analysis of soil chemical indicators,the soil has different degrees of salinization,high pH,low organic matter and alkali-decomposed nitrogen content,moderate available phosphorus and available potassium content,effective iron,effective manganese,effective Trace elements such as copper and effective zinc are abundant.Except for the pH coefficient of variation of 0.042,all reached moderate intensity of variation,with a maximum coefficient of variation of1.365.There are significant correlations between NDVI and the seven indicators of soil quality factors,so NDVI is selected as the basis for dividing vegetation management zones by vegetation index.(2)Spatial interpolation analysis of soil chemical indicators is used to analyze the spatial variability.The factors with strong spatial autocorrelation are mainly soil organic matter,alkali-decomposed nitrogen,available phosphorus,available manganese and available copper.These five indicators are selected as soil management zones quality factor.Water-soluble salts,available potassium,available iron and available zinc have a moderate spatial correlation.Salinization is the main factor restricting agricultural land production activities,and soil moisture is a factor that affects crop production.Therefore,soil water-soluble salts,organic matter,alkali-decomposed nitrogen,available phosphorus,available manganese,available copper,and temperature vegetation drought index are used in this study Soil quality factor.(3)The main control factors of the first main component are available phosphorus,alkali-decomposed nitrogen,organic matter and water-soluble salts,the main control factors of the second main component are available manganese,available copper and TVDI,and the main control factors of the third main component It is TVDI,alkali-decomposed nitrogen and available manganese.The main controlling factors of the fourth main component are TVDI,available copper and organic matter.(4)Results of NDVI simulation model soil management zoning Each soil quality index reached a significant level of difference between different management zonings(P <0.05).After the division,the coefficient of variation of each soil quality index decreased to varying degrees,water-soluble salts decreased by 0.05-0.014,organic matter decreased by 0.09-0.17,alkali-hydrolyzed nitrogen decreased by 0.03-0.12,available phosphorus decreased by 0.07-0.13,and the average value of each soil quality factor between the divisions There are certain differences.Zone 2 has the highest soil quality,Zone 3 follows,and Zone 1 has the lowest soil quality.(5)The water,fertilizer and salt control of the partition results.The partition 2has a relatively low salinization degree,light water stress,additional nitrogen and organic fertilizers to increase yield,straw mulch to improve the soil water retention capacity,and to suppress the surface soil salinity.Division 3 has moderate salinity and water stress,and combines straw mulch with optimized irrigation to improve the salinity inhibition effect on the crop surface and root layers,and appropriately increase the amount of organic matter and nitrogen fertilizer.Division 1 has severe salinization,severe water stress,reducing nitrogen and phosphorus to promote crop growth to resist drought,increasing irrigation,and combining soil amendments,trenching,drainage and salt drainage,and deep ploughing to control saline and alkaline damage.In summary,this paper takes agricultural land in Wudi County as the research area,uses soil chemical index data as the basis and uses remote sensing index to divide the soil management zoning,and proposes a zoning management plan.The results show that the division of soil nutrient management zones based on the remote sensing index is effective and has high precision.A scientific fertilization system can be established to provide support for the development of precision agriculture and smart agriculture in the future.