Dry-cured tuna products exhibit unique aroma characteristics appreciated by local consumers, particularly in the southern Iberian Peninsula. In the present study, headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME-GC/MS) was used to identify and quantify volatile organic compounds (VOCs), establishing a volatile fingerprint of dry-cured tuna throughout the manufacturing process. Unsupervised (PCA) and supervised (PLS-DA and sPLS-DA) multivariate statistical methods were applied to visualise, group, and classify the samples. A total of fifty-four VOCs were identified across the four steps involved in processing the final product. The ML-PLS-DA model demonstrated excellent discrimination (R2 = 0.912, Q2 = 0.878, and Accuracy = 1) for the samples. Additionally, ML-sPLS-DA was conducted to screen various VOC metabolites in the samples after both the salting and salt-washing steps; the levels of eighteen VOCs changed significantly (VIP > 1; p < 0.05). These results provide a theoretical basis for determining flavour formation and quality control in the traditional dry-curing process of tuna.
Effect of Industrial Processing on the Volatile Organic Compound Fingerprint of Dry-Cured Tuna / M. Sanchez-Parra, A. Lopez, V.M. Moretti, J.L. Ordonez-Diaz, J.M. Moreno-Rojas. - In: FOODS. - ISSN 2304-8158. - 14:4(2025 Feb 11), pp. 592.1-592.23. [10.3390/foods14040592]
Effect of Industrial Processing on the Volatile Organic Compound Fingerprint of Dry-Cured Tuna
A. LopezSecondo
;V.M. Moretti;
2025
Abstract
Dry-cured tuna products exhibit unique aroma characteristics appreciated by local consumers, particularly in the southern Iberian Peninsula. In the present study, headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME-GC/MS) was used to identify and quantify volatile organic compounds (VOCs), establishing a volatile fingerprint of dry-cured tuna throughout the manufacturing process. Unsupervised (PCA) and supervised (PLS-DA and sPLS-DA) multivariate statistical methods were applied to visualise, group, and classify the samples. A total of fifty-four VOCs were identified across the four steps involved in processing the final product. The ML-PLS-DA model demonstrated excellent discrimination (R2 = 0.912, Q2 = 0.878, and Accuracy = 1) for the samples. Additionally, ML-sPLS-DA was conducted to screen various VOC metabolites in the samples after both the salting and salt-washing steps; the levels of eighteen VOCs changed significantly (VIP > 1; p < 0.05). These results provide a theoretical basis for determining flavour formation and quality control in the traditional dry-curing process of tuna.File | Dimensione | Formato | |
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2025_Sanchez Parra et al_Foods_VOCs mojama effect of industrial processing.pdf
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