Development of Near Infrared Spectroscopy Models for Quantitative Prediction of the Content of Bioactive Compounds in Olive Leaves
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 proce...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Croatian Society of Chemical Engineers
2019-01-01
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| Series: | Chemical and Biochemical Engineering Quarterly |
| Subjects: | |
| Online Access: | http://silverstripe.fkit.hr/cabeq/assets/Uploads/12-12-4-2018.pdf |
| _version_ | 1818516083019087872 |
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| author | D. Valinger M. Kušen A. Jurinjak Tušek M. Panić T. Jurina M. Benković I. Radojčić Redovniković J. Gajdoš Kljusurić |
| author_facet | D. Valinger M. Kušen A. Jurinjak Tušek M. Panić T. Jurina M. Benković I. Radojčić Redovniković J. Gajdoš Kljusurić |
| author_sort | D. Valinger |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-11T00:37:20Z |
| format | Article |
| id | doaj.art-f2014ab2fd8a44f19dd77046d56174b6 |
| institution | Directory Open Access Journal |
| issn | 0352-9568 1846-5153 |
| language | English |
| last_indexed | 2024-12-11T00:37:20Z |
| publishDate | 2019-01-01 |
| publisher | Croatian Society of Chemical Engineers |
| record_format | Article |
| series | Chemical and Biochemical Engineering Quarterly |
| spelling | doaj.art-f2014ab2fd8a44f19dd77046d56174b62022-12-22T01:27:06ZengCroatian Society of Chemical EngineersChemical and Biochemical Engineering Quarterly0352-95681846-51532019-01-0132453554310.15255/CABEQ.2018.1396Development of Near Infrared Spectroscopy Models for Quantitative Prediction of the Content of Bioactive Compounds in Olive LeavesD. Valinger0M. Kušen1A. Jurinjak Tušek2M. Panić3 T. Jurina4M. Benković5 I. Radojčić Redovniković6J. Gajdoš Kljusurić7University of Zagreb, Faculty of Food Technology and Biotechnology, Department of Process Engineering, Pierottijeva 6, 10000 ZagrebNutrimedica, Cernička 30, 10000 ZagrebUniversity of Zagreb, Faculty of Food Technology and Biotechnology, Department of Process Engineering, Pierottijeva 6, 10000 ZagrebUniversity of Zagreb, Faculty of Food Technology and Biotechnology, Department of Biochemical Engineering, Pierottijeva 6, 10000 ZagrebUniversity of Zagreb, Faculty of Food Technology and Biotechnology, Department of Process Engineering, Pierottijeva 6, 10000 ZagrebUniversity of Zagreb, Faculty of Food Technology and Biotechnology, Department of Process Engineering, Pierottijeva 6, 10000 ZagrebUniversity of Zagreb, Faculty of Food Technology and Biotechnology, Department of Biochemical Engineering, Pierottijeva 6, 10000 ZagrebUniversity of Zagreb, Faculty of Food Technology and Biotechnology, Department of Process Engineering, Pierottijeva 6, 10000 ZagrebThe 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.http://silverstripe.fkit.hr/cabeq/assets/Uploads/12-12-4-2018.pdfNIR spectraartificial neural networksolive leaf extractsconventional extractionmicrowave-assisted extractionmicrowave-ultrasound-assisted extraction |
| spellingShingle | D. Valinger M. Kušen A. Jurinjak Tušek M. Panić T. Jurina M. Benković I. Radojčić Redovniković 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 NIR spectra artificial neural networks olive leaf extracts conventional extraction microwave-assisted extraction microwave-ultrasound-assisted extraction |
| title | Development of Near Infrared Spectroscopy Models for Quantitative Prediction of the Content of Bioactive Compounds in Olive Leaves |
| title_full | Development of Near Infrared Spectroscopy Models for Quantitative Prediction of the Content of Bioactive Compounds in Olive Leaves |
| title_fullStr | Development of Near Infrared Spectroscopy Models for Quantitative Prediction of the Content of Bioactive Compounds in Olive Leaves |
| title_full_unstemmed | Development of Near Infrared Spectroscopy Models for Quantitative Prediction of the Content of Bioactive Compounds in Olive Leaves |
| title_short | Development of Near Infrared Spectroscopy Models for Quantitative Prediction of the Content of Bioactive Compounds in Olive Leaves |
| title_sort | development of near infrared spectroscopy models for quantitative prediction of the content of bioactive compounds in olive leaves |
| topic | NIR spectra artificial neural networks olive leaf extracts conventional extraction microwave-assisted extraction microwave-ultrasound-assisted extraction |
| url | http://silverstripe.fkit.hr/cabeq/assets/Uploads/12-12-4-2018.pdf |
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