Analysis of soil spatial distribution of soil nutrient fastness meter in purple hilly area
Lift Table For Intelligent Assembly Lift table for intelligent assembly Lifting Table For Assembly,Assembly Line Scissor Lift Table,Smart Lift Table Marco Lift (Ningbo) Co., Ltd. , https://www.marcolifttables.com
At the landscape and catchment scales, the climate and parent material are relatively uniform, and topography and land use are the main factors that affect the spatial variability of soil nutrients. In recent years, many researchers at home and abroad have conducted research on the spatial variability of soil nutrients. The spatial variability of soil available P and nitrate was studied, which provided an important basis for the rational application of N and P in farmland. Hu Kelin et al. studied the spatial variability of farmland soil nutrients, and pointed out that the variation of alkaline soil nitrogen and surface organic matter in the soil of the substratum obeyed the normal distribution, and the alkali nitrogen dissolved and available phosphorus in the surface basically obeyed the lognormal distribution, and between alkali nitrogen, organic matter and available phosphorus. There is correlation. Although a great deal of research has been done on the spatial variability of soil nutrients, it is not yet possible to predict the spatial distribution of soil nutrients in the purple soil hilly region. Precise and convenient prediction of the soil nutrients in the purple soil hilly region is of great significance to promote the sustainable development of modern agriculture.
The prediction of spatial distribution of soil nutrients depends on accurate soil nutrient testers. In the past, this information was mainly derived from traditional soil maps. However, traditional soil maps have low precision (simplification with polygonal spot mapping and discontinuous spatial distribution of soil nutrients), slow renewal speed, and high cost, which can no longer satisfy the requirements of detailed soil information from modern precision agriculture and environmental model simulation. In order to make up for the shortcomings of traditional soil mapping methods, many scholars have proposed a series of new soil mapping methods, of which geostatistical methods are the most widely used.
The use of soil nutrient speed meter not only facilitates us to master the soil structure, but also predicts plant growth based on soil organic matter content, and timely adjusts crop types. Farmers can also appropriately fertilize soil nutrients to promote plant growth and increase crop yield and quality.