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Hategan AR, David M, Pirnau A, Cozar B, Cinta-Pinzaru S, Guyon F, Magdas DA. Fusing 1H NMR and Raman experimental data for the improvement of wine recognition models. Food Chem 2024; 458:140245. [PMID: 38954957 DOI: 10.1016/j.foodchem.2024.140245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2024] [Revised: 06/12/2024] [Accepted: 06/25/2024] [Indexed: 07/04/2024]
Abstract
The present study proposes the development of new wine recognition models based on Artificial Intelligence (AI) applied to the mid-level data fusion of 1H NMR and Raman data. In this regard, a supervised machine learning method, namely Support Vector Machines (SVMs), was applied for classifying wine samples with respect to the cultivar, vintage, and geographical origin. Because the association between the two data sources generated an input space with a high dimensionality, a feature selection algorithm was employed to identify the most relevant discriminant markers for each wine classification criterion, before SVM modeling. The proposed data processing strategy allowed the classification of the wine sample set with accuracies up to 100% in both cross-validation and on an independent test set and highlighted the efficiency of 1H NMR and Raman data fusion as opposed to the use of a single-source data for differentiating wine concerning the cultivar and vintage.
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Affiliation(s)
- Ariana Raluca Hategan
- National 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.
| | - Maria David
- National 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.
| | - Adrian Pirnau
- National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donat Street, 400293 Cluj-Napoca, Romania.
| | - Bogdan Cozar
- National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donat Street, 400293 Cluj-Napoca, Romania.
| | - Simona Cinta-Pinzaru
- Faculty of Physics, Babeș-Bolyai University, Kogălniceanu 1, 400084 Cluj-Napoca, Romania.
| | - Francois Guyon
- Service Commun des Laboratoires, 146 Traverse Charles Susini, 13388 Marseille, France.
| | - Dana Alina Magdas
- National 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.
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Hategan AR, Dehelean A, Puscas R, Cristea G, Belc N, Mustatea G, Magdas DA. The development of honey recognition models with broad applicability based on the association of isotope and elemental content with ANNs. Food Chem 2024; 458:140209. [PMID: 38943967 DOI: 10.1016/j.foodchem.2024.140209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Revised: 06/12/2024] [Accepted: 06/22/2024] [Indexed: 07/01/2024]
Abstract
Honey adulteration represents a worldwide problem, driven by the illicit economic gain that producers, traders, or merchants pursue. Among the falsification methods that can unfairly influence the price is the incorrect declaration of the botanical origin and harvesting year. Therefore, the present study aimed to test the potential given by the application of Artificial Neural Networks (ANNs) for developing prediction models able to assess honey botanical origin and harvesting year based on isotope and elemental fingerprints. For each classification criterion, significant focus was dedicated to the data preprocessing phase to enhance the models' prediction capability. The obtained classification performances (accuracy scores >86% during the test phase) have highlighted the efficiency of ANNs for honey authentication as well as the feasibility of applying the developed classifiers for a large-scale application, supported by their ability to recognize the correct origin despite considerable variability in botanical source, geographical origin, and harvesting period.
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Affiliation(s)
- Ariana Raluca Hategan
- National 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.
| | - Adriana Dehelean
- National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donat Street, 400293 Cluj-Napoca, Romania.
| | - Romulus Puscas
- National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donat Street, 400293 Cluj-Napoca, Romania.
| | - Gabriela Cristea
- National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donat Street, 400293 Cluj-Napoca, Romania.
| | - Nastasia Belc
- National Institute of Research and Development for Food Bioresources - IBA Bucharest, 6 Dinu Vintila Street, 021102 Bucharest, Romania.
| | - Gabriel Mustatea
- National Institute of Research and Development for Food Bioresources - IBA Bucharest, 6 Dinu Vintila Street, 021102 Bucharest, Romania.
| | - Dana Alina Magdas
- National 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.
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Labsvards KD, Rudovica V, Borisova A, Kokina K, Bertins M, Naumenko J, Viksna A. Multi-Element Profile Characterization of Monofloral and Polyfloral Honey from Latvia. Foods 2023; 12:4091. [PMID: 38002149 PMCID: PMC10670016 DOI: 10.3390/foods12224091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 11/01/2023] [Accepted: 11/09/2023] [Indexed: 11/26/2023] Open
Abstract
Honey is of scientific interest mainly due to its health-promoting and antibacterial properties, which are also associated with its floral origins. However, the methods for confirming honey floral origins are quite limited and require improvements. One method suggested in the search for a multi-method approach to evaluating the floral origins of Latvian honey is inductively coupled plasma mass spectrometry (ICP-MS). This study investigated the multi-element profile of 83 honey samples of well-specified floral origins. The main findings included using Ba, Ca, Cs, Fe, and Rb as indicator elements for heather honey. The chemometric evaluation supported the use of ICP-MS for distinguishing heather honey from other types of honey. The Latvian polyfloral honey multi-element profile was defined and compared to honey samples with other geographical origins. Additionally, the multi-element profiles of buckwheat, clover, and polyfloral honey proteins were investigated to clarify whether the majority of elements were bound with proteins or not. Preliminary results indicated that Ca, K, Mg, Mn, Na, and Sr were mainly found in non-protein-bound forms, while the majority of Al, Cu, Ni, and Zn were in the form of large chemical structures (>10 kDa).
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Affiliation(s)
- Kriss Davids Labsvards
- Department of Chemistry, University of Latvia, Jelgavas Street 1, LV-1004 Riga, Latvia; (V.R.); (M.B.); (J.N.); (A.V.)
- Institute of Food Safety, Animal Health and Environment “BIOR”, Lejupes Street 3, LV-1076 Riga, Latvia; (A.B.); (K.K.)
| | - Vita Rudovica
- Department of Chemistry, University of Latvia, Jelgavas Street 1, LV-1004 Riga, Latvia; (V.R.); (M.B.); (J.N.); (A.V.)
| | - Anastasija Borisova
- Institute of Food Safety, Animal Health and Environment “BIOR”, Lejupes Street 3, LV-1076 Riga, Latvia; (A.B.); (K.K.)
| | - Kristina Kokina
- Institute of Food Safety, Animal Health and Environment “BIOR”, Lejupes Street 3, LV-1076 Riga, Latvia; (A.B.); (K.K.)
| | - Maris Bertins
- Department of Chemistry, University of Latvia, Jelgavas Street 1, LV-1004 Riga, Latvia; (V.R.); (M.B.); (J.N.); (A.V.)
| | - Jevgenija Naumenko
- Department of Chemistry, University of Latvia, Jelgavas Street 1, LV-1004 Riga, Latvia; (V.R.); (M.B.); (J.N.); (A.V.)
| | - Arturs Viksna
- Department of Chemistry, University of Latvia, Jelgavas Street 1, LV-1004 Riga, Latvia; (V.R.); (M.B.); (J.N.); (A.V.)
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Tarapoulouzi M, Mironescu M, Drouza C, Mironescu ID, Agriopoulou S. Insight into the Recent Application of Chemometrics in Quality Analysis and Characterization of Bee Honey during Processing and Storage. Foods 2023; 12:473. [PMID: 36766000 PMCID: PMC9914568 DOI: 10.3390/foods12030473] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 12/30/2022] [Accepted: 01/16/2023] [Indexed: 01/20/2023] Open
Abstract
The application of chemometrics, a widely used science in food studies (and not only food studies) has begun to increase in importance with chemometrics being a very powerful tool in analyzing large numbers of results. In the case of honey, chemometrics is usually used for assessing honey authenticity and quality control, combined with well-established analytical methods. Research related to investigation of the quality changes in honey due to modifications after processing and storage is rare, with a visibly increasing tendency in the last decade (and concentrated on investigating novel methods to preserve the honey quality, such as ultrasound or high-pressure treatment). This review presents the evolution in the last few years in using chemometrics in analyzing honey quality during processing and storage. The advantages of using chemometrics in assessing honey quality during storage and processing are presented, together with the main characteristics of some well-known chemometric methods. Chemometrics prove to be a successful tool to differentiate honey samples based on changes of characteristics during storage and processing.
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Affiliation(s)
- Maria Tarapoulouzi
- Department of Chemistry, Faculty of Pure and Applied Science, University of Cyprus, P.O. Box 20537, Nicosia 1678, Cyprus
| | - Monica Mironescu
- Faculty of Agricultural Sciences Food Industry and Environmental Protection, Lucian Blaga University of Sibiu, Bv. Victoriei 10, 550024 Sibiu, Romania
| | - Chryssoula Drouza
- Department of Agricultural Production, Biotechnology and Food Science, Cyprus University of Technology, P.O. Box 50329, Limassol 3036, Cyprus
| | - Ion Dan Mironescu
- Faculty of Agricultural Sciences Food Industry and Environmental Protection, Lucian Blaga University of Sibiu, Bv. Victoriei 10, 550024 Sibiu, Romania
| | - Sofia Agriopoulou
- Department of Food Science and Technology, University of the Peloponnese, Antikalamos, 24100 Kalamata, Greece
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