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

mproving soil organic carbon mapping with a field-specific calibration approach through diffuse reflectance spectroscopy and machine learning algorithm

Full text
Author(s):
Camargo, Livia Arantes [1] ; do Amaral, Lucas Rios [2] ; dos Reis, Aliny Aparecida [1] ; Brasco, Thiago Luis [2] ; Graziano Magalhaes, Paulo Sergio [1, 2]
Total Authors: 5
Affiliation:
[1] Univ Estadual Campinas, Interdisciplinary Ctr Energy Planning NIPE, UNICAMP, BR-13083896 Campinas, SP - Brazil
[2] Univ Estadual Campinas, Sch Agr Engn FEAGRI, UNICAMP, Campinas - Brazil
Total Affiliations: 2
Document type: Journal article
Source: SOIL USE AND MANAGEMENT; v. 38, n. 1 NOV 2021.
Web of Science Citations: 0
Abstract

Detailed mapping of soil attributes is often not viable due to the high cost of wet-chemical laboratory analysis, which requires a large number of samples. Thus, we evaluated whether the prediction of SOC contents through field-specific diffuse reflectance spectroscopy (DRS) can increase the amount of samples available to SOC mapping through data interpolation. For such, we tested the performance of the partial least squares regression (PLSR), random forest (RF) and gradient boosting tree (GBT) algorithms to model and predict SOC. The field-specific calibration approach proposed here proved to be suitable for predicting SOC content on soil samples, reducing the dependence on wet-chemical soil laboratory analyses for mapping. With such SOC content prediction, the higher amount of samples to be used for spatial interpolation can be increased, leading to more accurate SOC maps that can be applied for site-specific management. (AU)

FAPESP's process: 18/24985-0 - Methodology for mapping and monitoring different pasture-based Livestock management and Mixed Crop-Livestock systems with remote sensing
Grantee:Aliny Aparecida dos Reis
Support Opportunities: Scholarships in Brazil - Post-Doctoral
FAPESP's process: 17/50205-9 - Monitoring integrated crop-livestock systems through remote sensing and precision agriculture for more sustainable production - towards low carbon agriculture
Grantee:Paulo Sergio Graziano Magalhães
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 18/24493-0 - Precision agriculture in integrated crop-livestock systems
Grantee:Livia Arantes Camargo
Support Opportunities: Scholarships in Brazil - Post-Doctoral