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

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...

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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
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Abstract	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.
AbstractList	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. 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.
Author	dos Santos, Isabel Cristina Vicente de Lima, Caike Lobo Rodrigues Fernandes, Caroline Lins Dias Diniz, Paulo Henrique Gonçalves Rodrigues, José Filipe Bacalhau da Silva Simões, Simone Fialho, Djair Araújo Fook, Marcus Vinicius Lia Silva, Tiago Santos
Author_xml	– sequence: 1 givenname: Caroline Lins surname: Fernandes fullname: Fernandes, Caroline Lins organization: Chemistry Department, Science and Technology Center, State University of Paraiba, Campina Grande, PB 58429-500, Brazil – sequence: 2 givenname: Tiago Santos surname: Silva fullname: Silva, Tiago Santos organization: Chemistry Department, Science and Technology Center, State University of Paraiba, Campina Grande, PB 58429-500, Brazil – sequence: 3 givenname: Caike Lobo Rodrigues surname: de Lima fullname: de Lima, Caike Lobo Rodrigues organization: Chemistry Department, Science and Technology Center, State University of Paraiba, Campina Grande, PB 58429-500, Brazil – sequence: 4 givenname: Isabel Cristina Vicente surname: dos Santos fullname: dos Santos, Isabel Cristina Vicente organization: Chemistry Department, Science and Technology Center, State University of Paraiba, Campina Grande, PB 58429-500, Brazil – sequence: 5 givenname: Djair Araújo surname: Fialho fullname: Fialho, Djair Araújo organization: Materials Science and Engineering Department, Northeast Laboratory for Evaluation and Development of Biomaterials, Academic Unit of Materials Science and Engineering, Federal University of Campina Grande, Campina Grande, PB 58429-000, Brazil – sequence: 6 givenname: Marcus Vinicius Lia surname: Fook fullname: Fook, Marcus Vinicius Lia organization: Materials Science and Engineering Department, Northeast Laboratory for Evaluation and Development of Biomaterials, Academic Unit of Materials Science and Engineering, Federal University of Campina Grande, Campina Grande, PB 58429-000, Brazil – sequence: 7 givenname: Paulo Henrique Gonçalves surname: Dias Diniz fullname: Dias Diniz, Paulo Henrique Gonçalves organization: Federal University of Western Bahia, Programa de Pós-Graduação em Química Pura e Aplicada, Barreiras, BA CEP 47.810-059Brazil – sequence: 8 givenname: José Filipe Bacalhau surname: Rodrigues fullname: Rodrigues, José Filipe Bacalhau organization: Materials Science and Engineering Department, Northeast Laboratory for Evaluation and Development of Biomaterials, Academic Unit of Materials Science and Engineering, Federal University of Campina Grande, Campina Grande, PB 58429-000, Brazil – sequence: 9 givenname: Simone surname: da Silva Simões fullname: da Silva Simões, Simone email: simonesimoes@servidor.uepb.edu.br organization: Chemistry Department, Science and Technology Center, State University of Paraiba, Campina Grande, PB 58429-500, Brazil
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SubjectTerms	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
Title	Vibrational spectroscopic techniques and variable selection in Linear Discriminant Analysis to geographical origin discrimination of Jatropha mollissima sap
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