Anticounterfeiting and Fraud Mitigation Solutions for High-value Food Products

Maritano, V.; Barge, P.; Biglia, A.; Comba, L.; Ricauda Aimonino, D.; Tortia, C.; Gay, P.

doi:10.1016/j.jfp.2024.100251

Cited by 2 publications

(1 citation statement)

References 86 publications

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“…At the same time, fish is one of the categories of food most vulnerable to fraud. This fraud is mainly connected with species substitution, where a more expensive variety is replaced with low-value species, the mislabeling of fish regarding its geographical origin, selling thawed fish as fresh, and the undeclared use of food additives [ 2 , 3 , 4 ].…”

Section: Introductionmentioning

confidence: 99%

Near-Infrared Spectroscopy for Rapid Differentiation of Fresh and Frozen–Thawed Common Carp (Cyprinus carpio)

Atanassova,

Yorgov,

Stratev

et al. 2024

Sensors

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This study aimed to investigate near-infrared spectroscopy (NIRS) in combination with classification methods for the discrimination of fresh and once- or twice-freeze–thawed fish. An experiment was carried out with common carp (Cyprinus carpio). From each fish, test pieces were cut from the dorsal and ventral regions and measured from the skin side as fresh, after single freezing at minus 18 °C for 15 ÷ 28 days and 15 ÷ 21 days for the second freezing after the freeze–thawing cycle. NIRS measurements were performed via a NIRQuest 512 spectrometer at the region of 900–1700 nm in Reflection mode. The Pirouette 4.5 software was used for data processing. SIMCA and PLS-DA models were developed for classification, and their performance was estimated using the F1 score and total accuracy. The predictive power of each model was evaluated for fish samples in the fresh, single-freezing, and second-freezing classes. Additionally, aquagrams were calculated. Differences in the spectra between fresh and frozen samples were observed. They might be assigned mainly to the O–H and N–H bands. The aquagrams confirmed changes in water organization in the fish samples due to freezing–thawing. The total accuracy of the SIMCA models for the dorsal samples was 98.23% for the calibration set and 90.55% for the validation set. For the ventral samples, respective values were 99.28 and 79.70%. Similar accuracy was found for the PLS-PA models. The NIR spectroscopy and tested classification methods have a potential for nondestructively discriminating fresh from frozen–thawed fish in as methods to protect against fish meat food fraud.

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Section: Introductionmentioning

confidence: 99%