A Step Forward in Hybrid Soil Laboratory Analysis: Merging Chemometric Corrections, Protocols and Data-Driven Methods
The need to maintain soil health and produce more food worldwide has increased, and soil analysis is essential for its management. Although spectroscopy has emerged as an important tool, it is important to focus primarily on predictive modeling procedures rather than specific protocols. This article aims to contribute to a routine work sequence in a hybrid laboratory that seeks to provide the best data for its users. In this study, 18,730 soil samples from the state of Paraná, Brazil, were analyzed using three different laboratories, sensors and geometries for data acquisition. Thirty soil properties were analyzed, some using different chemical methodologies for comparison purposes. After a spectral reading, two literary protocols were applied, and the final prediction results were observed. We applied cubist models, which were the best for our population. The combination of different spectral analysis systems, with a standardized protocol using LB for the ISS detection of discrepant samples, was shown to significantly improve the accuracy of predictions for 21 of the 30 soil properties analyzed, highlighting the importance of choosing the extraction methodology and improving data quality, which have a significant impact on laboratory analyses, reaffirming spectroscopy as an essential tool for the efficient and sustainable management of soil resources.
Authors
- Raúl Roberto Poppiel (ORCID: https://orcid.org/0000-0002-1628-4154)
- João Vitor Ferreira Gonçalves (ORCID: https://orcid.org/0000-0001-7377-7070)
- João Augusto Coblinski (ORCID: https://orcid.org/0000-0002-8184-5632)
- Renato Herrig Furlanetto (ORCID: https://orcid.org/0000-0001-9586-5995)
- Marcos Rafael Nanni (ORCID: https://orcid.org/0000-0003-4854-2661)
- Jorge Tadeu Fim Rosas (ORCID: https://orcid.org/0000-0002-3244-4816)
- José Alexandre Melo Demattê (ORCID: https://orcid.org/0000-0001-5328-0323)
- Nícolas Augusto Rosin (ORCID: https://orcid.org/0000-0002-3439-4701)
- Caio Almeida de Oliveira
- Renan Falcioni (ORCID: https://orcid.org/0000-0002-2343-5045)
- Uemeson José dos Santos (ORCID: https://orcid.org/0000-0002-0884-254X)
- Eyal Ben Dor (ORCID: https://orcid.org/0000-0001-6757-3530)
- Marcelo Henrique Procópio Pelegrino (ORCID: https://orcid.org/0000-0002-0963-1189)
- Nicole Ghinzelli Vedana (ORCID: https://orcid.org/0009-0000-4252-6543)
- Paulo Rogério Gallo
- Bruno dos Anjos Bartsch
- Estefan Ortiz
- Viviane Cristina Vivian Kochinki
Institutions
- Universidade Estadual de Maringá (BR)
- Tel Aviv University (IL)
- Universidade de São Paulo (BR)
- University of Florida (US)
- Institute of Soil Science and Plant Cultivation (PL)
- Instituto Federal de Educação, Ciência e Tecnologia do Pará (BR)
- Forest Science and Research Institute (BR)
- Fundação do ABC (BR)
- University of West Florida (US)
Publication Details
- Journal
- Remote Sensing
- Published
- 2024-12-04
- DOI
- https://doi.org/10.3390/rs16234543
- Citations
- 3
- Primary Topic
- Soil Geostatistics and Mapping
- Type
- article
- Field-Weighted Citation Impact
- 0.62
Funders
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
- Fundação Araucária