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Khan UM, Sameen A, Decker EA, Shabbir MA, Hussain S, Latif A, Abdi G, Aadil RM. Implementation of plant extracts for cheddar-type cheese production in conjunction with FTIR and Raman spectroscopy comparison. Food Chem X 2024; 22:101256. [PMID: 38495457 PMCID: PMC10943033 DOI: 10.1016/j.fochx.2024.101256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 02/13/2024] [Accepted: 02/25/2024] [Indexed: 03/19/2024] Open
Abstract
Plant extracts have demonstrated the ability to act as coagulants for milk coagulation at an adequate concentration, wide temperatures and pH ranges. This research is focused on the use of different vegetative extracts such as Citrus aurnatium flower extract (CAFE), bromelain, fig latex, and melon extract as economical and beneficial coagulants in the development of plant-based cheddar-type cheese. The cheddar-type cheese samples were subjected to physicochemical analysis in comparison to controlled cheese samples made from acetic acid and rennet. The fat, moisture, protein, and salt contents remained the same over the storage period, but a slight decline was observed in pH. The Ferric reducing antioxidant power (FRAP) increased with the passage of the ripening period. The FTIR and Raman spectra showed exponential changes and qualitative estimates in the binding and vibrational structure of lipids and protein in plant-based cheeses. The higher FTIR and Raman spectra bands were observed in acid, rennet, bromelain, and CAFE due to their firm and strong texture of cheese while lower spectra were observed in cheese made from melon extract due to weak curdling and textural properties. These plant extracts are economical and easily available alternative sources for cheese production with higher protein and nutritional contents.
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Affiliation(s)
- Usman Mir Khan
- National Institute of Food Science and Technology, University of Agriculture, Faisalabad 38000, Pakistan
| | - Aysha Sameen
- Department of Food Science and Technology, Government College Women University, Faisalabad 38000, Pakistan
| | - Eric Andrew Decker
- Department of Food Science, University of Massachusetts, Amherst, MA 01003, USA
| | - Muhammad Asim Shabbir
- National Institute of Food Science and Technology, University of Agriculture, Faisalabad 38000, Pakistan
| | - Shahzad Hussain
- Department of Food Science and Nutrition, College of Food and Agriculture, King Saud University, Riyadh 11451, Saudi Arabia
| | - Anam Latif
- Institute of Food Science and Nutrition, University of Sargodha, Sargodha 40100, Pakistan
| | - Gholamreza Abdi
- Department of Biotechnology, Persian Gulf Research Institute, Persian Gulf University, Bushehr 75169, Iran
| | - Rana Muhammad Aadil
- National Institute of Food Science and Technology, University of Agriculture, Faisalabad 38000, Pakistan
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2
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Spina AA, Ceniti C, De Fazio R, Oppedisano F, Palma E, Gugliandolo E, Crupi R, Raza SHA, Britti D, Piras C, Morittu VM. Spectral Profiling (Fourier Transform Infrared Spectroscopy) and Machine Learning for the Recognition of Milk from Different Bovine Breeds. Animals (Basel) 2024; 14:1271. [PMID: 38731274 PMCID: PMC11083570 DOI: 10.3390/ani14091271] [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: 02/29/2024] [Revised: 04/09/2024] [Accepted: 04/12/2024] [Indexed: 05/13/2024] Open
Abstract
The Podolica cattle breed is widespread in southern Italy, and its productivity is characterized by low yields and an extraordinary quality of milk and meats. Most of the milk produced is transformed into "Caciocavallo Podolico" cheese, which is made with 100% Podolica milk. Fourier Transform Infrared Spectroscopy (FTIR) is the technique that, in this research work, was applied together with machine learning to discriminate 100% Podolica milk from contamination of other Calabrian cattle breeds. The analysis on the test set produced a misclassification percentage of 6.7%. Among the 15 non-Podolica samples in the test set, 2 were misclassified and recognized as Podolica milk even though the milk was from other species. The correct classification rate improved to 100% when the same method was applied to the recognition of Podolica and Pezzata Rossa milk produced by the same farm. Furthermore, this technique was tested for the recognition of Podolica milk mixed with milk from other bovine species. The multivariate model and the respective confusion matrices obtained showed that all the 14 Podolica samples (test set) mixed with 40% non-Podolica milk were correctly classified. In addition, Pezzata Rossa milk produced by the same farm was detected as a contaminant in Podolica milk from the same farm down to concentrations as little as 5% with a 100% correct classification rate in the test set. The method described yielded higher accuracy values when applied to the discrimination of milks from different breeds belonging to the same farm. One of the reasons for this phenomenon could be linked to the elimination of the environmental variable. However, the results obtained in this work demonstrate the possibility of using FTIR to discriminate between milks from different breeds.
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Affiliation(s)
- Anna Antonella Spina
- Department of Health Sciences, “Magna Græcia University” of Catanzaro, Campus Universitario “Salvatore Venuta” Viale Europa, 88100 Catanzaro, Italy; (A.A.S.); (C.C.); (R.D.F.); (E.P.); (D.B.)
| | - Carlotta Ceniti
- Department of Health Sciences, “Magna Græcia University” of Catanzaro, Campus Universitario “Salvatore Venuta” Viale Europa, 88100 Catanzaro, Italy; (A.A.S.); (C.C.); (R.D.F.); (E.P.); (D.B.)
| | - Rosario De Fazio
- Department of Health Sciences, “Magna Græcia University” of Catanzaro, Campus Universitario “Salvatore Venuta” Viale Europa, 88100 Catanzaro, Italy; (A.A.S.); (C.C.); (R.D.F.); (E.P.); (D.B.)
| | - Francesca Oppedisano
- Department of Health Sciences, Institute of Research for Food Safety & Health (IRC-FSH), “Magna Græcia University” of Catanzaro, Campus Universitario “Salvatore Venuta” Viale Europa, 88100 Catanzaro, Italy;
| | - Ernesto Palma
- Department of Health Sciences, “Magna Græcia University” of Catanzaro, Campus Universitario “Salvatore Venuta” Viale Europa, 88100 Catanzaro, Italy; (A.A.S.); (C.C.); (R.D.F.); (E.P.); (D.B.)
- Department of Health Sciences, Institute of Research for Food Safety & Health (IRC-FSH), “Magna Græcia University” of Catanzaro, Campus Universitario “Salvatore Venuta” Viale Europa, 88100 Catanzaro, Italy;
- Interdepartmental Center Veterinary Service for Human and Animal Health, “Magna Græcia University” of Catanzaro, CISVetSUA, Campus Universitario “Salvatore Venuta” Viale Europa, 88100 Catanzaro, Italy;
- Nutramed S.c.a.r.l., Complesso Ninì Barbieri, Roccelletta di Borgia, 88021 Catanzaro, Italy
| | - Enrico Gugliandolo
- Department of Veterinary Science, University of Messina, 98166 Messina, Italy; (E.G.); (R.C.)
| | - Rosalia Crupi
- Department of Veterinary Science, University of Messina, 98166 Messina, Italy; (E.G.); (R.C.)
| | - Sayed Haidar Abbas Raza
- Guangdong Provincial Key Laboratory of Food Quality and Safety, Nation-Local Joint Engineering Research Center for Machining and Safety of Livestock and Poultry Products, South China Agricultural University, Guangzhou 510642, China;
| | - Domenico Britti
- Department of Health Sciences, “Magna Græcia University” of Catanzaro, Campus Universitario “Salvatore Venuta” Viale Europa, 88100 Catanzaro, Italy; (A.A.S.); (C.C.); (R.D.F.); (E.P.); (D.B.)
- Interdepartmental Center Veterinary Service for Human and Animal Health, “Magna Græcia University” of Catanzaro, CISVetSUA, Campus Universitario “Salvatore Venuta” Viale Europa, 88100 Catanzaro, Italy;
| | - Cristian Piras
- Department of Health Sciences, “Magna Græcia University” of Catanzaro, Campus Universitario “Salvatore Venuta” Viale Europa, 88100 Catanzaro, Italy; (A.A.S.); (C.C.); (R.D.F.); (E.P.); (D.B.)
- Interdepartmental Center Veterinary Service for Human and Animal Health, “Magna Græcia University” of Catanzaro, CISVetSUA, Campus Universitario “Salvatore Venuta” Viale Europa, 88100 Catanzaro, Italy;
| | - Valeria Maria Morittu
- Interdepartmental Center Veterinary Service for Human and Animal Health, “Magna Græcia University” of Catanzaro, CISVetSUA, Campus Universitario “Salvatore Venuta” Viale Europa, 88100 Catanzaro, Italy;
- Department of Medical and Surgical Sciences, “Magna Græcia University” of Catanzaro, Campus Universitario “Salvatore Venuta” Viale Europa, 88100 Catanzaro, Italy
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Smaoui S, Tarapoulouzi M, Agriopoulou S, D'Amore T, Varzakas T. Current State of Milk, Dairy Products, Meat and Meat Products, Eggs, Fish and Fishery Products Authentication and Chemometrics. Foods 2023; 12:4254. [PMID: 38231684 DOI: 10.3390/foods12234254] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Revised: 11/21/2023] [Accepted: 11/22/2023] [Indexed: 01/19/2024] Open
Abstract
Food fraud is a matter of major concern as many foods and beverages do not follow their labelling. Because of economic interests, as well as consumers' health protection, the related topics, food adulteration, counterfeiting, substitution and inaccurate labelling, have become top issues and priorities in food safety and quality. In addition, globalized and complex food supply chains have increased rapidly and contribute to a growing problem affecting local, regional and global food systems. Animal origin food products such as milk, dairy products, meat and meat products, eggs and fish and fishery products are included in the most commonly adulterated food items. In order to prevent unfair competition and protect the rights of consumers, it is vital to detect any kind of adulteration to them. Geographical origin, production methods and farming systems, species identification, processing treatments and the detection of adulterants are among the important authenticity problems for these foods. The existence of accurate and automated analytical techniques in combination with available chemometric tools provides reliable information about adulteration and fraud. Therefore, the purpose of this review is to present the advances made through recent studies in terms of the analytical techniques and chemometric approaches that have been developed to address the authenticity issues in animal origin food products.
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Affiliation(s)
- Slim Smaoui
- Laboratory of Microbial, Enzymatic Biotechnology, and Biomolecules (LBMEB), Center of Biotechnology of Sfax, University of Sfax-Tunisia, Sfax 3029, Tunisia
| | - Maria Tarapoulouzi
- Department of Chemistry, Faculty of Pure and Applied Science, University of Cyprus, P.O. Box 20537, Nicosia CY-1678, Cyprus
| | - Sofia Agriopoulou
- Department of Food Science and Technology, University of the Peloponnese, Antikalamos, 24100 Kalamata, Greece
| | - Teresa D'Amore
- IRCCS CROB, Centro di Riferimento Oncologico della Basilicata, 85028 Rionero in Vulture, Italy
| | - Theodoros Varzakas
- Department of Food Science and Technology, University of the Peloponnese, Antikalamos, 24100 Kalamata, Greece
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Wang W, Jia R, Hui Y, Zhang F, Zhang L, Liu Y, Song Y, Wang B. Utilization of two plant polysaccharides to improve fresh goat milk cheese: Texture, rheological properties, and microstructure characterization. J Dairy Sci 2023; 106:3900-3917. [PMID: 37080791 DOI: 10.3168/jds.2022-22195] [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: 04/14/2022] [Accepted: 12/22/2022] [Indexed: 04/22/2023]
Abstract
This study aimed to evaluate the effects of added jujube polysaccharide (JP) and Lycium barbarum polysaccharide (LBP) on the texture, rheological properties, and microstructure of goat milk cheese. Seven groups of fresh goat milk cheese were produced with 4 levels (0, 0.2, 0.6, and 1%, wt/wt) of JP and LBP. The goat milk cheese containing 1% JP showed the highest water-holding capacity, hardness, and the strongest rheological properties by creating a denser and more stable casein network structure. In addition, the yield of goat milk cheese was substantially improved as a result of JP incorporation. Cheeses containing LBP expressed lower fat content, higher moisture, and softer texture compared with the control cheese. Fourier-transform infrared spectroscopy and low-field nuclear magnetic resonance analysis demonstrated that the addition of JP improved the stability of the secondary protein structure in cheese and significantly enhanced the binding capacity of the casein matrix to water molecules due to strengthened intermolecular interactions. The current research demonstrated the potential feasibility of modifying the texture of goat milk cheese by JP or LBP, available for developing tunable goat milk cheese to satisfy consumer preferences and production needs.
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Affiliation(s)
- Weizhe Wang
- College of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi'an, Shaanxi 710119, China
| | - Rong Jia
- College of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi'an, Shaanxi 710119, China
| | - Yuanyuan Hui
- College of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi'an, Shaanxi 710119, China
| | - Fuxin Zhang
- College of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi'an, Shaanxi 710119, China
| | - Lei Zhang
- College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Yufang Liu
- College of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi'an, Shaanxi 710119, China
| | - Yuxuan Song
- College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China.
| | - Bini Wang
- College of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi'an, Shaanxi 710119, China.
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Untargeted metabolomic analysis of honey mixtures: discrimination opportunities based on ATR-FTIR data and machine learning algorithms. Microchem J 2023. [DOI: 10.1016/j.microc.2023.108458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
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Kastanos E, Papaneophytou C, Georgiou T, Demoliou C. A simple and fast triplex-PCR for the identification of milk's animal origin in Halloumi cheese and yoghurt. J DAIRY RES 2022; 89:1-4. [PMID: 35983806 DOI: 10.1017/s0022029922000577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
In this research communication we describe a straightforward triplex-PCR protocol able to differentiate the origin of milk from three closely related species (goat, sheep and cow) in Halloumi, a cheese with Protected Designation of Origin (PDO), and yogurts. Halloumi must contain at least 51% sheep or goat milk, therefore, the fraudulent adulteration of this cheese with excess of cow milk must be routinely tested. The assay employs one universal forward primer and three species-specific reverse primers giving rise to 287 bp (cow), 313 bp (goat), and 336 bp (sheep) amplicons, under the same amplification conditions. This protocol, when used to test a small number of Cyprus commercial products, correctly detected mislabeling in Halloumi (2 out of 6 samples were adulterated) and yogurt brands (1 out of 4 was adulterated). The suggested protocol is a reliable tool for identifying the origin of milk in Halloumi cheeses and yogurts and can be used in any laboratory equipped with a thermocycler and an agarose gel electrophoresis apparatus.
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Affiliation(s)
- Evdokia Kastanos
- Department of Biology, Montgomery College, 51 Mannakee St, Rockville, MD 20850, USA
| | - Christos Papaneophytou
- Department of Life and Health Sciences, University of Nicosia, School of Sciences and Engineering, 2417, Nicosia, Cyprus
| | - Thanasis Georgiou
- Department of Life and Health Sciences, University of Nicosia, School of Sciences and Engineering, 2417, Nicosia, Cyprus
| | - Catherine Demoliou
- Department of Life and Health Sciences, University of Nicosia, School of Sciences and Engineering, 2417, Nicosia, Cyprus
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Mafra I, Honrado M, Amaral JS. Animal Species Authentication in Dairy Products. Foods 2022; 11:foods11081124. [PMID: 35454711 PMCID: PMC9027536 DOI: 10.3390/foods11081124] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 04/06/2022] [Accepted: 04/11/2022] [Indexed: 02/01/2023] Open
Abstract
Milk is one of the most important nutritious foods, widely consumed worldwide, either in its natural form or via dairy products. Currently, several economic, health and ethical issues emphasize the need for a more frequent and rigorous quality control of dairy products and the importance of detecting adulterations in these products. For this reason, several conventional and advanced techniques have been proposed, aiming at detecting and quantifying eventual adulterations, preferentially in a rapid, cost-effective, easy to implement, sensitive and specific way. They have relied mostly on electrophoretic, chromatographic and immunoenzymatic techniques. More recently, mass spectrometry, spectroscopic methods (near infrared (NIR), mid infrared (MIR), nuclear magnetic resonance (NMR) and front face fluorescence coupled to chemometrics), DNA analysis (real-time PCR, high-resolution melting analysis, next generation sequencing and droplet digital PCR) and biosensors have been advanced as innovative tools for dairy product authentication. Milk substitution from high-valued species with lower-cost bovine milk is one of the most frequent adulteration practices. Therefore, this review intends to describe the most relevant developments regarding the current and advanced analytical methodologies applied to species authentication of milk and dairy products.
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Affiliation(s)
- Isabel Mafra
- REQUIMTE-LAQV, Faculdade de Farmácia, Universidade do Porto, 4050-313 Porto, Portugal
- Correspondence: (I.M.); (J.S.A.)
| | - Mónica Honrado
- CIMO, Instituto Politécnico de Bragança, 5300-253 Bragança, Portugal;
| | - Joana S. Amaral
- CIMO, Instituto Politécnico de Bragança, 5300-253 Bragança, Portugal;
- Correspondence: (I.M.); (J.S.A.)
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Tarapoulouzi M, Theocharis CR. Discrimination of Cheddar, Kefalotyri, and Halloumi cheese samples by the chemometric analysis of Fourier transform infrared spectroscopy and proton nuclear magnetic resonance spectra. J FOOD PROCESS ENG 2021. [DOI: 10.1111/jfpe.13933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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9
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Masci M, Zoani C, Nevigato T, Turrini A, Jasionowska R, Caproni R, Ratini P. Authenticity assessment of dairy products by capillary electrophoresis. Electrophoresis 2021; 43:340-354. [PMID: 34407231 DOI: 10.1002/elps.202100154] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 08/12/2021] [Accepted: 08/13/2021] [Indexed: 12/13/2022]
Abstract
Milk and derivatives are a very important part in the diet of the world population. Products from goat, buffalo, and sheep species have a greater economic value than the cow ones, therefore, authenticity frauds by improperly adding cow's milk occur frequently: dairy products are among the seven more attractive foods for adulteration. Milk from each of the above-cited animal species has its own definite profile of whey proteins (variants of α-lactalbumin and β-lactoglobulin) and its definite profile of caseins (variants of αS1 -, αS2 -, β-, and κ-casein). Such proteins can be usefully exploited as markers of authenticity by using capillary electrophoresis which is the technique of choice for the analysis of proteins. Due to the multiple adjustable parameters that are unknown to other analytical techniques, capillary electrophoresis is able to detect frauds in milk mixtures and cheese with little use of solvents, fast analysis time, and ease of operation. This makes it attractive and competitive for routine checks that are very important to fight the adulteration market. Advantages and limitations are discussed.
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Affiliation(s)
- Maurizio Masci
- Research Centre for Food and Nutrition, Council for Agricultural Research and Economics (CREA), Rome, Italy
| | - Claudia Zoani
- Department for Sustainability-Biotechnology and Agroindustry Division (ENEA-SSPT-BIOAG), Italian National Agency for New Technologies, Energy and Sustainable Economic Development, Rome, Italy
| | - Teresina Nevigato
- Research Centre for Food and Nutrition, Council for Agricultural Research and Economics (CREA), Rome, Italy
| | - Aida Turrini
- Research Centre for Food and Nutrition, Council for Agricultural Research and Economics (CREA), Rome, Italy
| | | | - Roberto Caproni
- Research Centre for Food and Nutrition, Council for Agricultural Research and Economics (CREA), Rome, Italy
| | - Patrizia Ratini
- Department of Chemistry, Sapienza University of Rome, Rome, Italy
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Authentication and Chemometric Discrimination of Six Greek PDO Table Olive Varieties through Morphological Characteristics of Their Stones. Foods 2021; 10:foods10081829. [PMID: 34441607 PMCID: PMC8394922 DOI: 10.3390/foods10081829] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Revised: 07/22/2021] [Accepted: 08/04/2021] [Indexed: 12/30/2022] Open
Abstract
Table olives, the number one consumed fermented food in Europe, are widely consumed as they contain many valuable ingredients for health. It is also a food which may be the subject of adulteration, as many different olive varieties with different geographical origin, exist all over the word. In the present study, the image analysis of stones of six main Greek protected designation of origin (PDO) table olive varieties was performed for the control of their authentication and discrimination, with cv. Prasines Chalkidikis, cv. Kalamata Olive, cv. Konservolia Stylidas, cv. Konservolia Amfissis, cv. Throuba Thassos and cv. Throuba Chios being the studied olive varieties. Orthogonal partial least square discriminant analysis (OPLS-DA) was used for discrimination and classification of the six Greek table olive varieties. With a 98.33% of varietal discrimination, the OPLS-DA model proved to be an efficient tool to authentify table olive varieties from their morphological characteristics.
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11
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Chemometric Discrimination of the Geographical Origin of Three Greek Cultivars of Olive Oils by Stable Isotope Ratio Analysis. Foods 2021; 10:foods10020336. [PMID: 33557322 PMCID: PMC7914497 DOI: 10.3390/foods10020336] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2020] [Revised: 01/29/2021] [Accepted: 01/29/2021] [Indexed: 01/11/2023] Open
Abstract
Α stable isotope ratio mass spectrometer was used for stable isotope ratio (i.e., δ13C, δ18O, and δ2H) measurements, achieving geographical discrimination using orthogonal projections to latent structures discriminant analysis. A total of 100 Greek monovarietal olive oil samples from three different olive cultivars (cv. Koroneiki, cv. Lianolia Kerkyras, and cv. Maurolia), derived from Central Greece and Peloponnese, were collected during the 2019-2020 harvest year aiming to investigate the effect of botanical and geographical origin on their discrimination through isotopic data. The selection of these samples was made from traditionally olive-growing areas in which no significant research has been done so far. Samples were discriminated mainly by olive cultivar and, partially, by geographical origin, which is congruent with other authors. Based on this model, correct recognition of 93.75% in the training samples and correct prediction of 100% in the test set were achieved. The overall correct classification of the model was 91%. The predictability based on the externally validated method of discrimination was good (Q2 (cum) = 0.681) and illustrated that δ18O and δ2H were the most important isotope markers for the discrimination of olive oil samples. The authenticity of olive oil based on the examined olive varieties can be determined using this technique.
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