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Chemical and Biochemical Engineering Quarterly, Vol. 32 No. 4, 2018.

Izvorni znanstveni članak
https://doi.org/10.15255/CABEQ.2018.1396

Development of Near Infrared Spectroscopy Models for Quantitative Prediction of the Content of Bioactive Compounds in Olive Leaves

D. Valinger ; University of Zagreb, Faculty of Food Technology and Biotechnology, Department of Process Engineering, Pierottijeva 6, 10000 Zagreb
M. Kušen ; Nutrimedica, Cernička 30, 10000 Zagreb
A. Jurinjak Tušek   ORCID icon orcid.org/0000-0002-3032-903X ; University of Zagreb, Faculty of Food Technology and Biotechnology, Department of Process Engineering, Pierottijeva 6, 10000 Zagreb
M. Panić ; University of Zagreb, Faculty of Food Technology and Biotechnology, Department of Biochemical Engineering, Pierottijeva 6, 10000 Zagreb
T. Jurina ; University of Zagreb, Faculty of Food Technology and Biotechnology, Department of Process Engineering, Pierottijeva 6, 10000 Zagreb
M. Benković ; University of Zagreb, Faculty of Food Technology and Biotechnology, Department of Process Engineering, Pierottijeva 6, 10000 Zagreb
I. Radojčić Redovniković ; University of Zagreb, Faculty of Food Technology and Biotechnology, Department of Biochemical Engineering, Pierottijeva 6, 10000 Zagreb
J. Gajdoš Kljusurić ; University of Zagreb, Faculty of Food Technology and Biotechnology, Department of Process Engineering, Pierottijeva 6, 10000 Zagreb

Puni tekst: engleski, pdf (841 KB) str. 535-543 preuzimanja: 3* citiraj
APA 6th Edition
Valinger, D., Kušen, M., Jurinjak Tušek, A., Panić, M., Jurina, T., Benković, M., ... Gajdoš Kljusurić, J. (2018). Development of Near Infrared Spectroscopy Models for Quantitative Prediction of the Content of Bioactive Compounds in Olive Leaves. Chemical and Biochemical Engineering Quarterly, 32 (4), 535-543. https://doi.org/10.15255/CABEQ.2018.1396
MLA 8th Edition
Valinger, D., et al. "Development of Near Infrared Spectroscopy Models for Quantitative Prediction of the Content of Bioactive Compounds in Olive Leaves." Chemical and Biochemical Engineering Quarterly, vol. 32, br. 4, 2018, str. 535-543. https://doi.org/10.15255/CABEQ.2018.1396. Citirano 20.03.2019.
Chicago 17th Edition
Valinger, D., M. Kušen, A. Jurinjak Tušek, M. Panić, T. Jurina, M. Benković, I. Radojčić Redovniković i J. Gajdoš Kljusurić. "Development of Near Infrared Spectroscopy Models for Quantitative Prediction of the Content of Bioactive Compounds in Olive Leaves." Chemical and Biochemical Engineering Quarterly 32, br. 4 (2018): 535-543. https://doi.org/10.15255/CABEQ.2018.1396
Harvard
Valinger, D., et al. (2018). 'Development of Near Infrared Spectroscopy Models for Quantitative Prediction of the Content of Bioactive Compounds in Olive Leaves', Chemical and Biochemical Engineering Quarterly, 32(4), str. 535-543. doi: https://doi.org/10.15255/CABEQ.2018.1396
Vancouver
Valinger D, Kušen M, Jurinjak Tušek A, Panić M, Jurina T, Benković M i sur. Development of Near Infrared Spectroscopy Models for Quantitative Prediction of the Content of Bioactive Compounds in Olive Leaves. Chemical and Biochemical Engineering Quarterly [Internet]. 2018 [pristupljeno 20.03.2019.];32(4):535-543. doi: https://doi.org/10.15255/CABEQ.2018.1396
IEEE
D. Valinger, et al., "Development of Near Infrared Spectroscopy Models for Quantitative Prediction of the Content of Bioactive Compounds in Olive Leaves", Chemical and Biochemical Engineering Quarterly, vol.32, br. 4, str. 535-543, 2018. [Online]. doi: https://doi.org/10.15255/CABEQ.2018.1396

Sažetak
The objective of this work was to evaluate the ability of artificial neural networks (ANN) in near infrared (NIR) spectra calibration models to predict the total polyphenolic content, antioxidant activity, and extraction yield of the olive leaves aqueous extracts prepared with three extraction procedures (conventional extraction, microwave-assisted extraction, and microwave-ultrasound-assisted extraction). Partial least squares (PLS) models were developed from principal component analyses (PCA) scores of NIR spectra of olive leaf aqueous extracts in terms of total polyphenols concentration, antioxidant activity, and extraction yield for each extraction procedure. PLS models were used to view which PCA scores are the best suited as input for ANN based on three output variables.
ANN showed very good correlation of NIRs and all tested variables, especially in the case of total polyphenolic content (TPC). Therefore, ANN can be used for the prediction of total polyphenol concentrations, antioxidant activity, and extraction yield of plant extracts based on the NIR spectra.






Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Ključne riječi
NIR spectra; artificial neural networks; olive leaf extracts; conventional extraction; microwave-assisted extraction; microwave-ultrasound-assisted extraction

Hrčak ID: 215721

URI
https://hrcak.srce.hr/215721

Posjeta: 12 *