R-SPECT - Novel Raman chemometrics-based approach in food quality assessment: Carotenoids as model nutrients for application to functional products

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R-SPECT - Novel Raman chemometrics-based approach in food quality assessment: Carotenoids as model nutrients for application to functional products (en)
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Raman spectroscopy coupled with chemometric modeling approaches for authentication of different paprika varieties at physiological maturity

Kolašinac, Stefan; Pećinar, Ilinka; Danojević, Dario; Dajić Stevanović, Zora

(Elsevier, 2022)

TY  - JOUR
AU  - Kolašinac, Stefan
AU  - Pećinar, Ilinka
AU  - Danojević, Dario
AU  - Dajić Stevanović, Zora
PY  - 2022
UR  - http://fiver.ifvcns.rs/handle/123456789/2651
AB  - Five Balkan paprika varieties at physiological maturity were investigated by means of Raman spectroscopy in order to discriminate the differences which stemmed from their genetic variability since the plants were grown under the same experimental conditions. The spectra were obtained using the 532 nm wavelength. In an effort to find the best classification power, several pre-processing methods were applied: 1) baseline correction, unit vector normalization; 2) baseline correction, unit vector normalization and first Savitzky-Golay derivative; 3) baseline correction, unit vector normalization and second Savitzky-Golay derivative; 4) baseline correction, unit 
vector normalization and third Savitzky-Golay derivative. All of the pre-processing methods were followed by 
making PCA-LDA (Principal Component Analysis-Linear Discriminant Analysis), QDA (Quadratic Discriminant 
Analysis), and PLS-DA (Partial Least Square - Discriminant Analysis) classification models. QDA showed the best discrimination power (83.87–100% and 89.47–100% for the training and the test data, respectively), then PCA-LDA (0.00–100 and 0.00–100% for the training and the test data, respectively) and PLS-DA (19.35–100% and 0.00–100.00% for the training and the test data, respectively). The results pointed out the applicability of 
chemometric modeling associated with Raman spectroscopy in the assessment of nutritionally similar samples, 
such as the studied red paprika varieties.
PB  - Elsevier
T2  - LWT Food Science and Technology
T1  - Raman spectroscopy coupled with chemometric modeling approaches for authentication of different paprika varieties at physiological maturity
SP  - 113402
VL  - 162
DO  - 10.1016/j.lwt.2022.113402
ER  - 
@article{
author = "Kolašinac, Stefan and Pećinar, Ilinka and Danojević, Dario and Dajić Stevanović, Zora",
year = "2022",
abstract = "Five Balkan paprika varieties at physiological maturity were investigated by means of Raman spectroscopy in order to discriminate the differences which stemmed from their genetic variability since the plants were grown under the same experimental conditions. The spectra were obtained using the 532 nm wavelength. In an effort to find the best classification power, several pre-processing methods were applied: 1) baseline correction, unit vector normalization; 2) baseline correction, unit vector normalization and first Savitzky-Golay derivative; 3) baseline correction, unit vector normalization and second Savitzky-Golay derivative; 4) baseline correction, unit 
vector normalization and third Savitzky-Golay derivative. All of the pre-processing methods were followed by 
making PCA-LDA (Principal Component Analysis-Linear Discriminant Analysis), QDA (Quadratic Discriminant 
Analysis), and PLS-DA (Partial Least Square - Discriminant Analysis) classification models. QDA showed the best discrimination power (83.87–100% and 89.47–100% for the training and the test data, respectively), then PCA-LDA (0.00–100 and 0.00–100% for the training and the test data, respectively) and PLS-DA (19.35–100% and 0.00–100.00% for the training and the test data, respectively). The results pointed out the applicability of 
chemometric modeling associated with Raman spectroscopy in the assessment of nutritionally similar samples, 
such as the studied red paprika varieties.",
publisher = "Elsevier",
journal = "LWT Food Science and Technology",
title = "Raman spectroscopy coupled with chemometric modeling approaches for authentication of different paprika varieties at physiological maturity",
pages = "113402",
volume = "162",
doi = "10.1016/j.lwt.2022.113402"
}
Kolašinac, S., Pećinar, I., Danojević, D.,& Dajić Stevanović, Z.. (2022). Raman spectroscopy coupled with chemometric modeling approaches for authentication of different paprika varieties at physiological maturity. in LWT Food Science and Technology
Elsevier., 162, 113402.
https://doi.org/10.1016/j.lwt.2022.113402
Kolašinac S, Pećinar I, Danojević D, Dajić Stevanović Z. Raman spectroscopy coupled with chemometric modeling approaches for authentication of different paprika varieties at physiological maturity. in LWT Food Science and Technology. 2022;162:113402.
doi:10.1016/j.lwt.2022.113402 .
Kolašinac, Stefan, Pećinar, Ilinka, Danojević, Dario, Dajić Stevanović, Zora, "Raman spectroscopy coupled with chemometric modeling approaches for authentication of different paprika varieties at physiological maturity" in LWT Food Science and Technology, 162 (2022):113402,
https://doi.org/10.1016/j.lwt.2022.113402 . .
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