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• W1971151819 abstract "ABSTRACT In this study, short wave visible–near infrared reflectance spectroscopy was evaluated for prediction of diverse soil properties related to four different soil series of several regions in Jiangxi, China. A total of 240 soil samples were collected for the calibration (n = 168) and prediction (n = 72) sets. The used wavelength range of short wave visible–near infrared reflectance spectroscopy is 325–1075 nm. Partial least squares regression and back propagation neural network were used to develop models for soil properties such as organic matter and extractable forms of calcium, magnesium, and potassium. Performance of these models was also compared and analyzed. The input of back propagation neural network was the first six principal components resulted from the principal component analysis and the optimal number of latent variables obtained from partial least squares regression. The overall results showed that the performance of partial least squares regression model was inferior to all back propagation neural network models. The best prediction was obtained with latent variables as input of back propagation neural network model for organic matter (determination coefficient = 0.84 and relative predictive determinant = 2.38), which was classified as very good model predictions. The prediction of calcium, magnesium, and potassium was classified as fair (determination coefficient = 0.56–0.68 and relative predictive determinant = 1.51–1.61), where quantitative predictions were considered possible. It is recommended to adopt latent variables as input for back propagation neural network model predicting soil properties with short wave visible–near infrared reflectance spectroscopy. In conclusion, short wave visible–near infrared reflectance spectroscopy was variably successful in estimating soil properties and showed potential for substituting laboratory analyses." @default.
• W1971151819 created "2016-06-24" @default.
• W1971151819 creator A5034751342 @default.
• W1971151819 creator A5063701397 @default.
• W1971151819 date "2014-05-09" @default.
• W1971151819 modified "2023-09-24" @default.
• W1971151819 title "Using Short Wave Visible–Near Infrared Reflectance Spectroscopy to Predict Soil Properties and Content" @default.
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• W1971151819 doi "https://doi.org/10.1080/00387010.2013.840315" @default.
• W1971151819 hasPublicationYear "2014" @default.
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