Feasibility study of tomato fruit characterization by fast XRF analysis for quality assessment and food traceability.

Elemental composition Food authentication Food traceability Principal Component Analysis (PCA) Protected Geographical Indication (PGI) Tomato fruits X-ray fluorescence (XRF)

Journal

Food chemistry
ISSN: 1873-7072
Titre abrégé: Food Chem
Pays: England
ID NLM: 7702639

Informations de publication

Date de publication:
30 Jul 2022
Historique:
received: 03 08 2021
revised: 02 02 2022
accepted: 04 02 2022
pubmed: 23 2 2022
medline: 13 4 2022
entrez: 22 2 2022
Statut: ppublish

Résumé

Food product nutritional and sensory characteristics are often deeply linked to its territory of origin; therefore, its authentication by means of elemental composition becomes crucial for traceability and fighting food fraud. This study aims to establish a fast and reproducible procedure for origin and quality assessment of Sicilian tomato fruits, including PGI "Pomodoro di Pachino", by using the X-ray fluorescence (XRF) technique. Measurements were performed on different parts of PGI Pachino tomatoes belonging to the same production lot. Principal Component and Cluster Analyses show that the samples cluster accordingly with the production lot, disentangling the different parts of the fruit. This procedure, which uses XRF yield elemental pattern and statistical analysis, establishes a solid basis for characterizing elemental profiles by a fast XRF in-situ campaign, supporting the traceability system. The reliability of XRF results was confirmed by comparing elemental concentrations with ICP-MS measurements, performed for comparison, and tomato literature values.

Identifiants

pubmed: 35193091
pii: S0308-8146(22)00326-0
doi: 10.1016/j.foodchem.2022.132364
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

132364

Informations de copyright

Copyright © 2022 Elsevier Ltd. All rights reserved.

Auteurs

S Panebianco (S)

Dipartimento di Fisica e Astronomia, Università di Catania, Catania, Italy.

P Mazzoleni (P)

Dipartimento di Scienze Biologiche, Geologiche e Ambientali, Università di Catania, Italy. Electronic address: paolo.mazzoleni@unict.it.

G Barone (G)

Dipartimento di Scienze Biologiche, Geologiche e Ambientali, Università di Catania, Italy.

A Musumarra (A)

Dipartimento di Fisica e Astronomia, Università di Catania, Catania, Italy; Istituto Nazionale di Fisica Nucleare, Sezione di Catania, Catania, Italy.

M G Pellegriti (MG)

Istituto Nazionale di Fisica Nucleare, Sezione di Catania, Catania, Italy.

A Pulvirenti (A)

Dipartimento di Medicina Clinica e Sperimentale, Unità Bioinformatica, Università di Catania, Catania, Italy.

A Scordino (A)

Dipartimento di Fisica e Astronomia, Università di Catania, Catania, Italy; Istituto Nazionale di Fisica Nucleare - Laboratori Nazionali del Sud, Catania, Italy.

G Cirvilleri (G)

Dipartimento di Agricoltura, Alimentazione e Ambiente, Università di Catania, Italy.

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Classifications MeSH