Geographical and varietal origin differentiation of alcoholic beverages through the association between FT-Raman spectroscopy and advanced data processing strategies
The present work aimed to test the efficiency of FT-Raman spectroscopy for fruit spirits discrimination by developing differentiation models based on two approaches, namely a supervised statistical method (Partial Least Squares Discriminant Analysis), and a Machine Learning technique (Support Vector...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-12-01
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| Series: | Food Chemistry: X |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590157523003450 |
| _version_ | 1797383715438985216 |
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| author | Ariana Raluca Hategan Maria David Camelia Berghian-Grosan Dana Alina Magdas |
| author_facet | Ariana Raluca Hategan Maria David Camelia Berghian-Grosan Dana Alina Magdas |
| author_sort | Ariana Raluca Hategan |
| collection | DOAJ |
| description | The present work aimed to test the efficiency of FT-Raman spectroscopy for fruit spirits discrimination by developing differentiation models based on two approaches, namely a supervised statistical method (Partial Least Squares Discriminant Analysis), and a Machine Learning technique (Support Vector Machines). For this purpose, a data set comprising 86 Romanian distillate samples was used, which aimed to be differentiated in terms of the raw material used for production (plum, apple, pear and grape) and county of origin (Cluj, Satu Mare and Salaj). Eight distinct preprocessing methods (autoscale, mean center, variance scaling, smoothing, 1st derivative, 2nd derivative, standard normal variate and Pareto) followed by a feature selection step were applied to identify the meaningful input data based on which the most efficient classification models can be constructed. Both types of models led to accuracy scores greater than 90% in differentiating the distillate samples in terms of geographical and botanical origin. |
| first_indexed | 2024-03-08T21:25:16Z |
| format | Article |
| id | doaj.art-7c3ab9e75d764d1d86b8e8c6f93539d4 |
| institution | Directory Open Access Journal |
| issn | 2590-1575 |
| language | English |
| last_indexed | 2024-03-08T21:25:16Z |
| publishDate | 2023-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Food Chemistry: X |
| spelling | doaj.art-7c3ab9e75d764d1d86b8e8c6f93539d42023-12-21T07:36:30ZengElsevierFood Chemistry: X2590-15752023-12-0120100902Geographical and varietal origin differentiation of alcoholic beverages through the association between FT-Raman spectroscopy and advanced data processing strategiesAriana Raluca Hategan0Maria David1Camelia Berghian-Grosan2Dana Alina Magdas3National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donat Street, 400293 Cluj-Napoca, Romania; Faculty of Physics, Babeș-Bolyai University, Kogălniceanu 1, 400084 Cluj-Napoca, RomaniaNational Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donat Street, 400293 Cluj-Napoca, Romania; Faculty of Physics, Babeș-Bolyai University, Kogălniceanu 1, 400084 Cluj-Napoca, RomaniaNational Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donat Street, 400293 Cluj-Napoca, RomaniaNational Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donat Street, 400293 Cluj-Napoca, Romania; Faculty of Physics, Babeș-Bolyai University, Kogălniceanu 1, 400084 Cluj-Napoca, Romania; Corresponding author at: National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donat Street, 400293 Cluj-Napoca, Romania.The present work aimed to test the efficiency of FT-Raman spectroscopy for fruit spirits discrimination by developing differentiation models based on two approaches, namely a supervised statistical method (Partial Least Squares Discriminant Analysis), and a Machine Learning technique (Support Vector Machines). For this purpose, a data set comprising 86 Romanian distillate samples was used, which aimed to be differentiated in terms of the raw material used for production (plum, apple, pear and grape) and county of origin (Cluj, Satu Mare and Salaj). Eight distinct preprocessing methods (autoscale, mean center, variance scaling, smoothing, 1st derivative, 2nd derivative, standard normal variate and Pareto) followed by a feature selection step were applied to identify the meaningful input data based on which the most efficient classification models can be constructed. Both types of models led to accuracy scores greater than 90% in differentiating the distillate samples in terms of geographical and botanical origin.http://www.sciencedirect.com/science/article/pii/S2590157523003450Fruit spiritsSVMPLS-DARaman spectroscopyRecognition models |
| spellingShingle | Ariana Raluca Hategan Maria David Camelia Berghian-Grosan Dana Alina Magdas Geographical and varietal origin differentiation of alcoholic beverages through the association between FT-Raman spectroscopy and advanced data processing strategies Food Chemistry: X Fruit spirits SVM PLS-DA Raman spectroscopy Recognition models |
| title | Geographical and varietal origin differentiation of alcoholic beverages through the association between FT-Raman spectroscopy and advanced data processing strategies |
| title_full | Geographical and varietal origin differentiation of alcoholic beverages through the association between FT-Raman spectroscopy and advanced data processing strategies |
| title_fullStr | Geographical and varietal origin differentiation of alcoholic beverages through the association between FT-Raman spectroscopy and advanced data processing strategies |
| title_full_unstemmed | Geographical and varietal origin differentiation of alcoholic beverages through the association between FT-Raman spectroscopy and advanced data processing strategies |
| title_short | Geographical and varietal origin differentiation of alcoholic beverages through the association between FT-Raman spectroscopy and advanced data processing strategies |
| title_sort | geographical and varietal origin differentiation of alcoholic beverages through the association between ft raman spectroscopy and advanced data processing strategies |
| topic | Fruit spirits SVM PLS-DA Raman spectroscopy Recognition models |
| url | http://www.sciencedirect.com/science/article/pii/S2590157523003450 |
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