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Chemometric Analysis for the Prediction of Biochemical Compounds in Leaves Using UV-VIS-NIR-SWIR Hyperspectroscopy
Reflectance hyperspectroscopy is recognised for its potential to elucidate biochemical changes, thereby enhancing the understanding of plant biochemistry. This study used the UV-VIS-NIR-SWIR spectral range to identify the different biochemical constituents in Hibiscus and Geranium plants. Hyperspect...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10574701/ https://www.ncbi.nlm.nih.gov/pubmed/37836163 http://dx.doi.org/10.3390/plants12193424 |
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author | Falcioni, Renan Gonçalves, João Vitor Ferreira de Oliveira, Karym Mayara de Oliveira, Caio Almeida Reis, Amanda Silveira Crusiol, Luis Guilherme Teixeira Furlanetto, Renato Herrig Antunes, Werner Camargos Cezar, Everson de Oliveira, Roney Berti Chicati, Marcelo Luiz Demattê, José Alexandre M. Nanni, Marcos Rafael |
author_facet | Falcioni, Renan Gonçalves, João Vitor Ferreira de Oliveira, Karym Mayara de Oliveira, Caio Almeida Reis, Amanda Silveira Crusiol, Luis Guilherme Teixeira Furlanetto, Renato Herrig Antunes, Werner Camargos Cezar, Everson de Oliveira, Roney Berti Chicati, Marcelo Luiz Demattê, José Alexandre M. Nanni, Marcos Rafael |
author_sort | Falcioni, Renan |
collection | PubMed |
description | Reflectance hyperspectroscopy is recognised for its potential to elucidate biochemical changes, thereby enhancing the understanding of plant biochemistry. This study used the UV-VIS-NIR-SWIR spectral range to identify the different biochemical constituents in Hibiscus and Geranium plants. Hyperspectral vegetation indices (HVIs), principal component analysis (PCA), and correlation matrices provided in-depth insights into spectral differences. Through the application of advanced algorithms—such as PLS, VIP, iPLS-VIP, GA, RF, and CARS—the most responsive wavelengths were discerned. PLSR models consistently achieved R(2) values above 0.75, presenting noteworthy predictions of 0.86 for DPPH and 0.89 for lignin. The red-edge and SWIR bands displayed strong associations with pivotal plant pigments and structural molecules, thus expanding the perspectives on leaf spectral dynamics. These findings highlight the efficacy of spectroscopy coupled with multivariate analysis in evaluating the management of biochemical compounds. A technique was introduced to measure the photosynthetic pigments and structural compounds via hyperspectroscopy across UV-VIS-NIR-SWIR, underpinned by rapid multivariate PLSR. Collectively, our results underscore the burgeoning potential of hyperspectroscopy in precision agriculture. This indicates a promising paradigm shift in plant phenotyping and biochemical evaluation. |
format | Online Article Text |
id | pubmed-10574701 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-105747012023-10-14 Chemometric Analysis for the Prediction of Biochemical Compounds in Leaves Using UV-VIS-NIR-SWIR Hyperspectroscopy Falcioni, Renan Gonçalves, João Vitor Ferreira de Oliveira, Karym Mayara de Oliveira, Caio Almeida Reis, Amanda Silveira Crusiol, Luis Guilherme Teixeira Furlanetto, Renato Herrig Antunes, Werner Camargos Cezar, Everson de Oliveira, Roney Berti Chicati, Marcelo Luiz Demattê, José Alexandre M. Nanni, Marcos Rafael Plants (Basel) Article Reflectance hyperspectroscopy is recognised for its potential to elucidate biochemical changes, thereby enhancing the understanding of plant biochemistry. This study used the UV-VIS-NIR-SWIR spectral range to identify the different biochemical constituents in Hibiscus and Geranium plants. Hyperspectral vegetation indices (HVIs), principal component analysis (PCA), and correlation matrices provided in-depth insights into spectral differences. Through the application of advanced algorithms—such as PLS, VIP, iPLS-VIP, GA, RF, and CARS—the most responsive wavelengths were discerned. PLSR models consistently achieved R(2) values above 0.75, presenting noteworthy predictions of 0.86 for DPPH and 0.89 for lignin. The red-edge and SWIR bands displayed strong associations with pivotal plant pigments and structural molecules, thus expanding the perspectives on leaf spectral dynamics. These findings highlight the efficacy of spectroscopy coupled with multivariate analysis in evaluating the management of biochemical compounds. A technique was introduced to measure the photosynthetic pigments and structural compounds via hyperspectroscopy across UV-VIS-NIR-SWIR, underpinned by rapid multivariate PLSR. Collectively, our results underscore the burgeoning potential of hyperspectroscopy in precision agriculture. This indicates a promising paradigm shift in plant phenotyping and biochemical evaluation. MDPI 2023-09-28 /pmc/articles/PMC10574701/ /pubmed/37836163 http://dx.doi.org/10.3390/plants12193424 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Falcioni, Renan Gonçalves, João Vitor Ferreira de Oliveira, Karym Mayara de Oliveira, Caio Almeida Reis, Amanda Silveira Crusiol, Luis Guilherme Teixeira Furlanetto, Renato Herrig Antunes, Werner Camargos Cezar, Everson de Oliveira, Roney Berti Chicati, Marcelo Luiz Demattê, José Alexandre M. Nanni, Marcos Rafael Chemometric Analysis for the Prediction of Biochemical Compounds in Leaves Using UV-VIS-NIR-SWIR Hyperspectroscopy |
title | Chemometric Analysis for the Prediction of Biochemical Compounds in Leaves Using UV-VIS-NIR-SWIR Hyperspectroscopy |
title_full | Chemometric Analysis for the Prediction of Biochemical Compounds in Leaves Using UV-VIS-NIR-SWIR Hyperspectroscopy |
title_fullStr | Chemometric Analysis for the Prediction of Biochemical Compounds in Leaves Using UV-VIS-NIR-SWIR Hyperspectroscopy |
title_full_unstemmed | Chemometric Analysis for the Prediction of Biochemical Compounds in Leaves Using UV-VIS-NIR-SWIR Hyperspectroscopy |
title_short | Chemometric Analysis for the Prediction of Biochemical Compounds in Leaves Using UV-VIS-NIR-SWIR Hyperspectroscopy |
title_sort | chemometric analysis for the prediction of biochemical compounds in leaves using uv-vis-nir-swir hyperspectroscopy |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10574701/ https://www.ncbi.nlm.nih.gov/pubmed/37836163 http://dx.doi.org/10.3390/plants12193424 |
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