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Mara A, Migliorini M, Ciulu M, Chignola R, Egido C, Núñez O, Sentellas S, Saurina J, Caredda M, Deroma MA, Deidda S, Langasco I, Pilo MI, Spano N, Sanna G. Elemental Fingerprinting Combined with Machine Learning Techniques as a Powerful Tool for Geographical Discrimination of Honeys from Nearby Regions. Foods 2024; 13:243. [PMID: 38254544 PMCID: PMC10814624 DOI: 10.3390/foods13020243] [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: 12/14/2023] [Revised: 01/04/2024] [Accepted: 01/08/2024] [Indexed: 01/24/2024] Open
Abstract
Discrimination of honey based on geographical origin is a common fraudulent practice and is one of the most investigated topics in honey authentication. This research aims to discriminate honeys according to their geographical origin by combining elemental fingerprinting with machine-learning techniques. In particular, the main objective of this study is to distinguish the origin of unifloral and multifloral honeys produced in neighboring regions, such as Sardinia (Italy) and Spain. The elemental compositions of 247 honeys were determined using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The origins of honey were differentiated using Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Random Forest (RF). Compared to LDA, RF demonstrated greater stability and better classification performance. The best classification was based on geographical origin, achieving 90% accuracy using Na, Mg, Mn, Sr, Zn, Ce, Nd, Eu, and Tb as predictors.
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Affiliation(s)
- Andrea Mara
- Department of Chemical, Physical, Mathematical and Natural Sciences, University of Sassari, Via Vienna 2, 07100 Sassari, Italy; (A.M.); (S.D.); (I.L.); (M.I.P.); (N.S.)
| | - Matteo Migliorini
- Department of Biotechnology, University of Verona, Strada le Grazie 15, 37134 Verona, Italy; (M.M.); (M.C.); (R.C.)
| | - Marco Ciulu
- Department of Biotechnology, University of Verona, Strada le Grazie 15, 37134 Verona, Italy; (M.M.); (M.C.); (R.C.)
| | - Roberto Chignola
- Department of Biotechnology, University of Verona, Strada le Grazie 15, 37134 Verona, Italy; (M.M.); (M.C.); (R.C.)
| | - Carla Egido
- Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Martí i Franquès 1-11, 08028 Barcelona, Spain; (C.E.); (O.N.); (S.S.); (J.S.)
| | - Oscar Núñez
- Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Martí i Franquès 1-11, 08028 Barcelona, Spain; (C.E.); (O.N.); (S.S.); (J.S.)
- Research Institute in Food Nutrition and Food Safety, University of Barcelona, Recinte Torribera, Av. Prat de la Riba 171, Edifici de Recerca (Gaudí), Santa Coloma de Gramenet, 08921 Barcelona, Spain
- Serra Húnter Fellow, Departament de Recerca i Universitats, Generalitat de Catalunya, Via Laietana 2, 08003 Barcelona, Spain
| | - Sònia Sentellas
- Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Martí i Franquès 1-11, 08028 Barcelona, Spain; (C.E.); (O.N.); (S.S.); (J.S.)
- Research Institute in Food Nutrition and Food Safety, University of Barcelona, Recinte Torribera, Av. Prat de la Riba 171, Edifici de Recerca (Gaudí), Santa Coloma de Gramenet, 08921 Barcelona, Spain
- Serra Húnter Fellow, Departament de Recerca i Universitats, Generalitat de Catalunya, Via Laietana 2, 08003 Barcelona, Spain
| | - Javier Saurina
- Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Martí i Franquès 1-11, 08028 Barcelona, Spain; (C.E.); (O.N.); (S.S.); (J.S.)
- Research Institute in Food Nutrition and Food Safety, University of Barcelona, Recinte Torribera, Av. Prat de la Riba 171, Edifici de Recerca (Gaudí), Santa Coloma de Gramenet, 08921 Barcelona, Spain
| | - Marco Caredda
- Department of Animal Science, AGRIS Sardegna, Loc. Bonassai, 07100 Sassari, Italy;
| | - Mario A. Deroma
- Department of Agriculture, University of Sassari, Viale Italia, 39A, 07100 Sassari, Italy;
| | - Sara Deidda
- Department of Chemical, Physical, Mathematical and Natural Sciences, University of Sassari, Via Vienna 2, 07100 Sassari, Italy; (A.M.); (S.D.); (I.L.); (M.I.P.); (N.S.)
| | - Ilaria Langasco
- Department of Chemical, Physical, Mathematical and Natural Sciences, University of Sassari, Via Vienna 2, 07100 Sassari, Italy; (A.M.); (S.D.); (I.L.); (M.I.P.); (N.S.)
| | - Maria I. Pilo
- Department of Chemical, Physical, Mathematical and Natural Sciences, University of Sassari, Via Vienna 2, 07100 Sassari, Italy; (A.M.); (S.D.); (I.L.); (M.I.P.); (N.S.)
| | - Nadia Spano
- Department of Chemical, Physical, Mathematical and Natural Sciences, University of Sassari, Via Vienna 2, 07100 Sassari, Italy; (A.M.); (S.D.); (I.L.); (M.I.P.); (N.S.)
| | - Gavino Sanna
- Department of Chemical, Physical, Mathematical and Natural Sciences, University of Sassari, Via Vienna 2, 07100 Sassari, Italy; (A.M.); (S.D.); (I.L.); (M.I.P.); (N.S.)
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Yulia M, Analianasari A, Widodo S, Kusumiyati K, Naito H, Suhandy D. The Authentication of Gayo Arabica Green Coffee Beans with Different Cherry Processing Methods Using Portable LED-Based Fluorescence Spectroscopy and Chemometrics Analysis. Foods 2023; 12:4302. [PMID: 38231760 DOI: 10.3390/foods12234302] [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: 10/30/2023] [Revised: 11/24/2023] [Accepted: 11/24/2023] [Indexed: 01/19/2024] Open
Abstract
Aceh is an important region for the production of high-quality Gayo arabica coffee in Indonesia. In this area, several coffee cherry processing methods are well implemented including the honey process (HP), wine process (WP), and natural process (NP). The most significant difference between the three coffee cherry processing methods is the fermentation process: HP is a process of pulped coffee bean fermentation, WP is coffee cherry fermentation, and NP is no fermentation. It is well known that the WP green coffee beans are better in quality and are sold at higher prices compared with the HP and NP green coffee beans. In this present study, we evaluated the utilization of fluorescence information to discriminate Gayo arabica green coffee beans from different cherry processing methods using portable fluorescence spectroscopy and chemometrics analysis. A total of 300 samples were used (n = 100 for HP, WP, and NP, respectively). Each sample consisted of three selected non-defective green coffee beans. Fluorescence spectral data from 348.5 nm to 866.5 nm were obtained by exciting the intact green coffee beans using a portable spectrometer equipped with four 365 nm LED lamps. The result showed that the fermented green coffee beans (HP and WP) were closely mapped and mostly clustered on the left side of PC1, with negative scores. The non-fermented (NP) green coffee beans were clustered mostly on the right of PC1 with positive scores. The results of the classification using partial least squares-discriminant analysis (PLS-DA), linear discriminant analysis (LDA), and principal component analysis-linear discriminant analysis (PCA-LDA) are acceptable, with an accuracy of more than 80% reported. The highest accuracy of prediction of 96.67% was obtained by using the PCA-LDA model. Our recent results show the potential application of portable fluorescence spectroscopy using LED lamps to classify and authenticate the Gayo arabica green coffee beans according to their different cherry processing methods. This innovative method is more affordable and could be easy to implement (in terms of both affordability and practicability) in the coffee industry in Indonesia.
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Affiliation(s)
- Meinilwita Yulia
- Department of Agricultural Technology, Lampung State Polytechnic, Jl. Soekarno Hatta No. 10, Rajabasa, Bandar Lampung 35141, Indonesia
- Spectroscopy Research Group (SRG), Laboratory of Bioprocess and Postharvest Engineering, Department of Agricultural Engineering, The University of Lampung, Bandar Lampung 35145, Indonesia
| | - Analianasari Analianasari
- Department of Agricultural Technology, Lampung State Polytechnic, Jl. Soekarno Hatta No. 10, Rajabasa, Bandar Lampung 35141, Indonesia
| | - Slamet Widodo
- Department of Mechanical and Biosystem Engineering, Faculty of Agricultural Engineering and Technology, IPB University, Dramaga, Bogor 16680, Indonesia
| | - Kusumiyati Kusumiyati
- Department of Agronomy, Faculty of Agriculture, Universitas Padjadjaran, Sumedang 45363, Indonesia
| | - Hirotaka Naito
- Department of Environmental Science and Technology, Graduate School of Bioresources, Mie University, 1577 Kurima-machiya-cho, Tsu-city 514-8507, Mie, Japan
| | - Diding Suhandy
- Spectroscopy Research Group (SRG), Laboratory of Bioprocess and Postharvest Engineering, Department of Agricultural Engineering, The University of Lampung, Bandar Lampung 35145, Indonesia
- Department of Agricultural Engineering, Faculty of Agriculture, The University of Lampung, Jl. Soemantri Brojonegoro No. 1, Bandar Lampung 35145, Indonesia
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