Fingerprinting strategies are widely used in food authentication1. Authentication implies to confirm the stated specifications, including quali-quantitative identification of characteristic components, adulterants, contaminants or to verify quality requirements as botanical origin or processing procedures. However, food authentication is based on the evaluation of similarities of an instrumental fingerprint versus a reference representative of sample variability, such as the human fingerprint in forensic science. This step is known as food ‘Identitation’, i.e. the establishment of an instrumental fingerprint characteristic of the authenticity2. The reliability of food authentication depends on a correct ‘Identitation’. The fingerprint approaches require an adequate number of samples stated as authentic food to establish a representative data base of the genuine food population1-3. The use of chemometric as exploration, classification and prediction tools is fundamental to extract significant and not-evident information to develop pattern recognition models. In this study, HS-SPME-GC–MS was applied to the aroma chemical fingerprinting of a set of coffee samples of different origin to discriminate simultaneously their origin and post-harvest treatments. An untargeted analysis of the preprocessed coffee data, including principal component analysis (PCA) and partial least square- discriminant analysis (PLS-DA) was performed. The results showed that, PLS-DA provided significant results for coffee classification, in particular in agreement with their geographical origin and processing, with error rates of 0.03 and 0.06 for fitting and prediction samples, respectively. Coffee aroma fingerprint can therefore be used for food ‘identition’ in view of origin&processing coffee authentication. 1. G.P Danezis, A.S. Tsagkaris, V. Brusic & C.A. Georgiou. Current Opinion in Food Science 2016, 10:22–31. 2. L. Cuadros-Rodríguez, C.Ruiz-Samblas, L. Valverde-Som,E. Perez-Castano, A.Gonzalez-Casado. Anal. Chim. Acta 909 (2016) 9-23. 3. S.D. Johanningsmeier, G.K.Harris, and C.M. Klevorn. Annu. Rev. Food Sci. Technol. 2016. 7:413–38.

Coffee ‘Identitation’ through chromatographic fingerprint: simultaneous classification of geographical origin & post-harvest treatments

BRESSANELLO, DAVIDE;LIBERTO, Erica;BICCHI, Carlo
2017-01-01

Abstract

Fingerprinting strategies are widely used in food authentication1. Authentication implies to confirm the stated specifications, including quali-quantitative identification of characteristic components, adulterants, contaminants or to verify quality requirements as botanical origin or processing procedures. However, food authentication is based on the evaluation of similarities of an instrumental fingerprint versus a reference representative of sample variability, such as the human fingerprint in forensic science. This step is known as food ‘Identitation’, i.e. the establishment of an instrumental fingerprint characteristic of the authenticity2. The reliability of food authentication depends on a correct ‘Identitation’. The fingerprint approaches require an adequate number of samples stated as authentic food to establish a representative data base of the genuine food population1-3. The use of chemometric as exploration, classification and prediction tools is fundamental to extract significant and not-evident information to develop pattern recognition models. In this study, HS-SPME-GC–MS was applied to the aroma chemical fingerprinting of a set of coffee samples of different origin to discriminate simultaneously their origin and post-harvest treatments. An untargeted analysis of the preprocessed coffee data, including principal component analysis (PCA) and partial least square- discriminant analysis (PLS-DA) was performed. The results showed that, PLS-DA provided significant results for coffee classification, in particular in agreement with their geographical origin and processing, with error rates of 0.03 and 0.06 for fitting and prediction samples, respectively. Coffee aroma fingerprint can therefore be used for food ‘identition’ in view of origin&processing coffee authentication. 1. G.P Danezis, A.S. Tsagkaris, V. Brusic & C.A. Georgiou. Current Opinion in Food Science 2016, 10:22–31. 2. L. Cuadros-Rodríguez, C.Ruiz-Samblas, L. Valverde-Som,E. Perez-Castano, A.Gonzalez-Casado. Anal. Chim. Acta 909 (2016) 9-23. 3. S.D. Johanningsmeier, G.K.Harris, and C.M. Klevorn. Annu. Rev. Food Sci. Technol. 2016. 7:413–38.
2017
Fourth International Congress on Cocoa Coffee and Tea
Torino
25-28 June 2017
Book of Abstract CoCoTea 2017
91
91
Bressanello, Davide; Tarighat, Maryam Abbasi; Liberto, Erica; Pellegrino, Gloria; Ruosi, Manuela R.; Bicchi, Carlo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1644955
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