Visible and near infrared spectroscopy for predicting soil nitrogen mineralization rate: Effect of incubation period and ancillary soil properties

Ruma, Farida Yasmin; Munnaf, Muhammad Abdul; De Neve, Stefaan; Mouazen, Abdul Mounem

doi:10.1016/j.catena.2023.107649

CATENA

2024

DOI: 10.1016/j.catena.2023.107649

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Visible and near infrared spectroscopy for predicting soil nitrogen mineralization rate: Effect of incubation period and ancillary soil properties

Farida Yasmin Ruma,

Muhammad Abdul Munnaf,

Stefaan De Neve

et al.

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2024

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Cited by 2 publications

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Visible-to-near-infrared spectroscopy for prediction of soil nitrogen mineralization after sample stratification by textural homogeneity criteria

Ruma,

Munnaf,

De Neve

et al. 2024

Soil and Tillage Research

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Visible-to-near-infrared spectroscopy for prediction of soil nitrogen mineralization after sample stratification by textural homogeneity criteria

Ruma,

Munnaf,

De Neve

et al. 2024

Soil and Tillage Research

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The Use of Vis-NIR-SWIR Spectroscopy and X-ray Fluorescence in the Development of Predictive Models: A Step forward in the Quantification of Nitrogen, Total Organic Carbon and Humic Fractions in Ferralsols

Lima,

Demattê,

Santos

et al. 2024

Remote Sensing

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The objective was to verify the performance of spectral techniques as well as validation models in the prediction of nitrogen, total organic carbon, and humic fractions under different cultivation conditions. Chemical analyses for the determination of nitrate, total nitrogen, total organic carbon, and the chemical fractionation of soil organic matter were performed, as well as spectral analyses by Vis-NIR-SWIR and X-ray fluorescence. The results of the spectroscopy were processed using RStudio v. 4.1.3, and PLSR and support vector machine learning algorithms were applied to validate the models. The Vis-NIR-SWIR and XRF spectroscopic techniques showed high performance and are indicated for the prediction of nitrogen, total organic carbon, and humic fractions in Ferralsols of medium sandy texture. However, it is important to highlight that each technique has its own characteristic mechanism of action: Vis-NIR-SWIR detects the element based on harmonic tones, while XRF is based on the atomic number of the element or elemental association. The PLSR and SVM models showed excellent validation results, allowing them to fit the experimental data, emphasizing that they are different statistical methods.

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Visible and near infrared spectroscopy for predicting soil nitrogen mineralization rate: Effect of incubation period and ancillary soil properties

Cited by 2 publications

References 67 publications

Visible-to-near-infrared spectroscopy for prediction of soil nitrogen mineralization after sample stratification by textural homogeneity criteria

Visible-to-near-infrared spectroscopy for prediction of soil nitrogen mineralization after sample stratification by textural homogeneity criteria

The Use of Vis-NIR-SWIR Spectroscopy and X-ray Fluorescence in the Development of Predictive Models: A Step forward in the Quantification of Nitrogen, Total Organic Carbon and Humic Fractions in Ferralsols

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