Abstract
Applying Near Infrared Reflectance Spectroscopy (NIRS) on farmlands can effectively estimate the available phosphorus and potassium contents of soil online. Spectral preprocessing, including Savitzky Golay (SG), Standard Normal Variate (SNV), Multiplicative Scatter Correction (MSC) and SG 1st derivative, aimed to eliminate system noise and external interference. A correction model was created using respectively Radial Basis Function (RBF) and Least Squares Support Vector Machine (LS-SVM) methods with input from the characteristic wavelengths obtained using Successive Projections Algorithm (SPA). The results of predicting available phosphorus and potassium contents in soil using these two modeling methods were evaluated and the better model was selected. The results showed that the LS-SVM method with input from the characteristic wavelengths obtained using SPA had an advantage over the RBF modeling method. In SPA-LS-SVM models, the correlation coefficient and mean square error of prediction for available phosphorus were 0.8625 and 8.67 and those for available potassium were 0.7843 and 13.42, respectively. This indicates that SPA-based visible-near-infrared spectroscopy using LS-SVM for modeling can be used as a method to accurately measure available phosphorus and potassium contents in soil.
Highlights
Soil nutrient is one of the major limiting factors that affect crop growth
This study examined the feasibility of applying Successive Projections Algorithm (SPA) in conjunction with the Least Squares Support Vector Machine (LS-SVM) modeling method to select and optimize modeling variables for soil near-infrared spectrum
Algorithm (SPA) selects a small number of wavelengths from the original data by projecting and Effect of sampling height on spectrum: Reflectance spectrum in soil measurement is affected by factors such as measured component structure, stability and probe mounting height, so it is necessary to examine the effect of probe mounting height on measuring accuracy in order to increase the accuracy of online measurement
Summary
Crops need water and various nutrients from agricultural soils to grow and a large amount of soil phosphorus and potassium is needed by plants These elements are one of the major factors that decide plant growth and soil productivity, as well as an important basis to guide scientific and balanced fertilization. The result showed that it is feasible to use NIRS technology to estimate alkalihydrolyzable nitrogen content in soil, but the feasibility of estimating available phosphorus and potassium contents still requires further study. Max.: Maximum; Min.: Minimum; S.D.: Standard deviation used in modeling to an extent less than that using algorithm such as Monte Carlo UVE, genetic algorithm and wavelet algorithm. This study examined the feasibility of applying SPA in conjunction with the LS-SVM modeling method to select and optimize modeling variables for soil near-infrared spectrum. The optimized samples were used to create a model for predicting available phosphorus and potassium contents in soil
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