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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Multi-Sensor Approach for Tropical Soil Fertility Analysis: Comparison of Individual and Combined Performance of VNIR, XRF, and LIBS Spectroscopies

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Tavares, Tiago Rodrigues [1] ; Molin, Jose Paulo [1] ; Nunes, Lidiane Cristina [2] ; Wei, Marcelo Chan Fu [1] ; Krug, Francisco Jose [2] ; de Carvalho, Hudson Wallace Pereira [3] ; Mouazen, Abdul Mounem [4]
Total Authors: 7
[1] Univ Sao Paulo, Dept Biosyst Engn, Luiz de Queiroz Coll Agr ESALQ, Lab Precis Agr LAP, BR-13418900 Sao Paulo - Brazil
[2] Univ Sao Paulo, Ctr Nucl Energy Agr CENA, Lab Analyt Chem LQA, BR-13416000 Sao Paulo - Brazil
[3] Univ Sao Paulo, Ctr Nucl Energy Agr CENA, Lab Nucl Instrumentat LIN, BR-13416000 Piracicaba, SP - Brazil
[4] Univ Ghent, Fac Biosci Engn, Dept Environm, Precis Soil & Crop Engn Grp Precis SCoRing, Coupure Links 653, Blok B, 1st Floor, B-9000 Ghent - Belgium
Total Affiliations: 4
Document type: Journal article
Source: AGRONOMY-BASEL; v. 11, n. 6 JUN 2021.
Web of Science Citations: 0

Rapid, cost-effective, and environmentally friendly analysis of key soil fertility attributes requires an ideal combination of sensors. The individual and combined performance of visible and near infrared (VNIR) diffuse reflectance spectroscopy, X-ray fluorescence spectroscopy (XRF), and laser-induced breakdown spectroscopy (LIBS) was assessed for predicting clay, organic matter (OM), cation exchange capacity (CEC), pH, base saturation (V), and extractable (ex-) nutrients in tropical soils. A set of 102 samples, collected from two agricultural fields, with broad ranges of fertility attributes were selected. Two contrasting data fusion approaches have been applied for modeling: (i) merging spectral data of different sensors followed by partial least squares regression (PLS), known as fusion before prediction; and (ii) applying the Granger and Ramanathan (GR) averaging approach, known as fusion after prediction. Results showed VNIR as individual technique to be the best for the prediction of clay and OM content (2.61 <= residual prediction deviation (RPD) <= 3.37), while the chemical attributes CEC, V, ex-P, ex-K, ex-Ca, and ex-Mg were better predicted (1.82 <= RPD <= 4.82) by elemental analysis techniques (i.e., XRF and LIBS). Only pH cannot be predicted regardless the technique. The attributes OM, V, and ex-P were best predicted using single-sensor approaches, while the attributes clay, CEC, pH, ex-K, ex-Ca, and ex-Mg were overall best predicted using multi-sensor approaches. Regarding the performance of the multi-sensor approaches, ex-K, ex-Ca, and ex-Mg, were best predicted (RPD of 4.98, 5.30, and 4.11 for ex-K, ex-Ca and ex-Mg, respectively) using two-sensor fusion approach (VNIR + XRF for ex-K and XRF + LIBS for ex-Ca and ex-Mg), while clay, CEC and pH were best predicted (RPD of 4.02, 2.63, and 1.32 for clay, CEC, and pH, respectively) with the three-sensor fusion approach (VNIR + XRF + LIBS). Therefore, the best combination of sensors for predicting key fertility attributes proved to be attribute-specific, which is a drawback of the data fusion approach. The present work is pioneering in highlighting benefits and limitations of the in tandem application of VNIR, XRF, and LIBS spectroscopies for fertility analysis in tropical soils. (AU)

FAPESP's process: 17/21969-0 - Evaluation of alternative techniques to traditional laboratory analysis for prediction of attributes in agricultural soils: approaches using VisNIR, XRF and LIBS spectroscopy
Grantee:Tiago Rodrigues Tavares
Support Opportunities: Scholarships in Brazil - Doctorate
FAPESP's process: 04/15965-2 - Implementation and development of Laser Induced Breakdown Spectroscopy (LIBS)
Grantee:Francisco José Krug
Support Opportunities: Research Projects - Thematic Grants