Vibrational spectroscopic techniques and variable selection in Linear Discriminant Analysis to geographical origin discrimination of Jatropha mollissima sap

• Published in: Phytochemistry letters Vol. 64; pp. 37 - 46
• Main Authors: Fernandes, Caroline Lins, Silva, Tiago Santos, de Lima, Caike Lobo Rodrigues, dos Santos, Isabel Cristina Vicente, Fialho, Djair Araújo, Fook, Marcus Vinicius Lia, Dias Diniz, Paulo Henrique Gonçalves, Rodrigues, José Filipe Bacalhau, da Silva Simões, Simone
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.12.2024
• Subjects: algorithms; Chemometrics; cost effectiveness; discriminant analysis; flavonoids; freeze drying; Geographical origin; green chemistry; Jatropha; near-infrared spectroscopy; Pattern recognition; polyphenols; principal component analysis; provenance; sap; Secondary metabolites; shelf life; spectral analysis; system optimization; Vibrational spectroscopy; Geographical origin; Secondary metabolites; Pattern recognition; Chemometrics; Jatropha; Vibrational spectroscopy
• ISSN: 1874-3900
• DOI: 10.1016/j.phytol.2024.09.007

This study aimed at the geographical origin discrimination of Jatropha mollissima saps using mid- and near-infrared spectroscopies (MIR and NIR, respectively) and Linear Discriminant Analysis (LDA). For this purpose, a total of 108 sap samples were collected in 3 different geographical regions over 12 months, and their content of total polyphenols, flavonoids, and tannins were quantified. Overall, samples from region C had consistently lower levels of these secondary metabolites throughout most of the months studied. In contrast, samples from regions A and B displayed relatively stable metabolite concentrations over the collection period. Since raw sap samples are subject to deterioration during storage, lyophilization was employed to remove moisture and consequently increase their shelf-life. Thus, MIR spectroscopy was applied to both raw and lyophilized sap samples, while NIR spectroscopy was only applied to lyophilized samples. Then, Principal Component Analysis from the secondary metabolites and spectral data indicated a trend of separation between the region C (located in Sertão) and the regions A and B (located in Agreste). Next, the Successive Projection Algorithm (SPA), Genetic Algorithm (GA), and Ant Colony Optimization (ACO) were used for variable selection in LDA. As a result, all constructed models achieved a sensitivity, specificity, and accuracy of 100 %, or very close to it, in both the training and test sets. However, the SPA-LDA models were more parsimonious, selecting fewer variables and presenting reproductive results as it is a deterministic technique. Hence, the proposed analytical methodologies align with the principles of Green Chemistry by requiring a simple sample preparation, avoiding the use of reagents and solvents, and reducing waste generation. Moreover, special attention can be given to NIR spectroscopy, as it offers a cost-effective analytical tool that can be explored in situ using a portable miniaturized device in the future. [Display omitted] •Performance of NIR and MIR was evaluated to distinguish Jatropha mollisima saps from three different geographical origins.•Discriminant power of LDA with selected variables from the AOC, GA, and SPA algorithms were evaluated and showed high sensitivity and specificity.•Evaluated techniques achieved classification errors of less than 5 %.•Methods developed are fast, quick, and efficient in solving the proposed problem.