Spectral Method for Liming Recommendation in Oxisol Based on the Prediction of Chemical Characteristics Using Interval Partial Least Squares Regression

文献类型： 外文期刊

第一作者： dos Santos, Glaucio Leboso Alemparte Abrantes

作者： dos Santos, Glaucio Leboso Alemparte Abrantes;Besen, Marcos Renan;Furlanetto, Renato Herrig;Crusiol, Luis Guilherme Teixeira;Rodrigues, Marlon;Reis, Amanda Silveira;de Oliveira, Karym Mayara;Coneglian, Carolina Fedrigo;Batista, Marcelo Augusto;Nanni, Marcos Rafael;Crusiol, Luis Guilherme Teixeira;de Oliveira, Roney Berti

作者机构：

关键词： hyperspectral data; chemometrics; proximal sensing of soil; latossolo; ferralsol; limestone; no-till

期刊名称：REMOTE SENSING （ 影响因子：5.349； 五年影响因子：5.786 ）

ISSN：

年卷期： 2022 年 14 卷 9 期

页码：

收录情况： SCI

摘要： Thousands of chemical analyses are carried out annually with the aim of recommending soil correction; however, these analyses are expensive, destructive, time-consuming, and can be harmful to the environment. As an alternative to conventional analysis methods, diffuse reflectance spectroscopy has been proposed as an option for evaluating the chemical characteristics of soil. The selection of variables has also emerged as an alternative to improve the performance of PLSR (partial least squares regression), as it decreases the root mean square error (RMSE) and increases the accuracy of the models. However, few studies have used a previous selection of variables for the construction of PLSR models to estimate the chemical characteristics of soil. In this context, the hypothesis in this study was that it is possible to calculate the liming recommendation in Oxisol based on the chemical characteristics estimated by PLSR, with a previous selection of variables using iPLS (Interval PLS). The objective was to calculate the need for liming based on chemical characteristics estimated via iPLS selection and PLSR modeling of specific wavelengths of soil reflectance. The experimental area was treated with different application rates of limestone, with and without incorporation, and phosphogypsum was applied in additional treatments. Soil assessments were carried out 5, 12, 24, and 36 months after the application of the treatments, using six layers: 0.00-0.05, 0.05-0.10, 0.10-0.20, 0.20-0.30, 0.30-0.40 and 0.40-0.60 m. Samples were subjected to conventional laboratory analyses, and spectral readings (400-2500 nm) were obtained with a spectroradiometer. The spectral curves were subjected to the iPLS variable selection method to generate PLSR models of the chemical characteristics used to calculate the liming recommendation. The chemical characteristics of the soil, such as Ca2+, sum of bases (SB), effective cation exchange capacity (CTCe), cation exchange capacity (CTC), and base saturation (BS), could be estimated, with values of R-2 ranging from 0.83 to 0.92 in the calibration and validation steps, and from 0.84 to 0.90 for the prediction step (in the fourth assessment). The liming recommendation calculated based on the chemical characteristics predicted from the PLSR models showed a strong correlation (r > 0.86) with the liming recommendation calculated by conventional laboratory techniques. The fourth soil assessment yielded the best correlation coefficient (r = 0.95).

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