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Chemometric Analysis for the Prediction of Biochemical Compounds in Leaves Using UV-VIS-NIR-SWIR Hyperspectroscopy.

Authors :
Falcioni R
Gonçalves JVF
de Oliveira KM
de Oliveira CA
Reis AS
Crusiol LGT
Furlanetto RH
Antunes WC
Cezar E
de Oliveira RB
Chicati ML
Demattê JAM
Nanni MR
Source :
Plants (Basel, Switzerland) [Plants (Basel)] 2023 Sep 28; Vol. 12 (19). Date of Electronic Publication: 2023 Sep 28.
Publication Year :
2023

Abstract

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, i PLS-VIP, GA, RF, and CARS-the most responsive wavelengths were discerned. PLSR models consistently achieved R <superscript>2</superscript> 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.

Details

Language :
English
ISSN :
2223-7747
Volume :
12
Issue :
19
Database :
MEDLINE
Journal :
Plants (Basel, Switzerland)
Publication Type :
Academic Journal
Accession number :
37836163
Full Text :
https://doi.org/10.3390/plants12193424