Tomato sauce is a world famous food product. Despite standards regulating the production of tomato derivatives, the market suffers frpm fraud such as product adulteration, origin mislabelling and counterfeiting. Methods suitable to discriminate the geographical origin of food samples and identify counterfeits are required. Chemometric approaches offer valuable information: data on tomato sauce is usually obtained through chromatography (HPLC and GC) coupled to mass spectrometry, which requires chemical pretreatment and the use of organic solvents. In this paper, a faster, cheaper, and greener analytical procedure has been developed for the analysis of volatile organic compounds (VOCs) and the colloidal fraction via multivariate statistical analysis. Tomato sauce VOCs were analysed by GC coupled to flame ionisation (GC-FID) and to ion mobility spectrometry (GC-IMS). Instead of using HPLC, the colloidal fraction was analysed by asymmetric flow field-fractionation (AF4), which was applied to this kind of sample for the first time. The GC and AF4 data showed promising perspectives in food-quality control: the AF4 method yielded comparable or better results than GC-IMS and offered complementary information. The ability to work in saline conditions with easy pretreatment and no chemical waste is a significant advantage compared to environmentally heavy techniques. The method presented here should therefore be taken into consideration when designing chemometric approaches which encompass a large number of samples.

A Green Analytical Method Combined with Chemometrics for Traceability of Tomato Sauce Based on Colloidal and Volatile Fingerprinting / Zappi, Alessandro; Marassi, Valentina; Kassouf, Nicholas; Giordani, Stefano; Pasqualucci, Gaia; Garbini, Davide; Roda, Barbara; Zattoni, Andrea; Reschiglian, Pierluigi; Melucci, Dora. - In: MOLECULES. - ISSN 1420-3049. - ELETTRONICO. - 27:17(2022), pp. 5507.1-5507.19. [10.3390/molecules27175507]

A Green Analytical Method Combined with Chemometrics for Traceability of Tomato Sauce Based on Colloidal and Volatile Fingerprinting

Zappi, Alessandro
Primo
;
Marassi, Valentina
;
Kassouf, Nicholas;Giordani, Stefano;Pasqualucci, Gaia;Roda, Barbara;Zattoni, Andrea;Reschiglian, Pierluigi;Melucci, Dora
Ultimo
2022

Abstract

Tomato sauce is a world famous food product. Despite standards regulating the production of tomato derivatives, the market suffers frpm fraud such as product adulteration, origin mislabelling and counterfeiting. Methods suitable to discriminate the geographical origin of food samples and identify counterfeits are required. Chemometric approaches offer valuable information: data on tomato sauce is usually obtained through chromatography (HPLC and GC) coupled to mass spectrometry, which requires chemical pretreatment and the use of organic solvents. In this paper, a faster, cheaper, and greener analytical procedure has been developed for the analysis of volatile organic compounds (VOCs) and the colloidal fraction via multivariate statistical analysis. Tomato sauce VOCs were analysed by GC coupled to flame ionisation (GC-FID) and to ion mobility spectrometry (GC-IMS). Instead of using HPLC, the colloidal fraction was analysed by asymmetric flow field-fractionation (AF4), which was applied to this kind of sample for the first time. The GC and AF4 data showed promising perspectives in food-quality control: the AF4 method yielded comparable or better results than GC-IMS and offered complementary information. The ability to work in saline conditions with easy pretreatment and no chemical waste is a significant advantage compared to environmentally heavy techniques. The method presented here should therefore be taken into consideration when designing chemometric approaches which encompass a large number of samples.
2022
A Green Analytical Method Combined with Chemometrics for Traceability of Tomato Sauce Based on Colloidal and Volatile Fingerprinting / Zappi, Alessandro; Marassi, Valentina; Kassouf, Nicholas; Giordani, Stefano; Pasqualucci, Gaia; Garbini, Davide; Roda, Barbara; Zattoni, Andrea; Reschiglian, Pierluigi; Melucci, Dora. - In: MOLECULES. - ISSN 1420-3049. - ELETTRONICO. - 27:17(2022), pp. 5507.1-5507.19. [10.3390/molecules27175507]
Zappi, Alessandro; Marassi, Valentina; Kassouf, Nicholas; Giordani, Stefano; Pasqualucci, Gaia; Garbini, Davide; Roda, Barbara; Zattoni, Andrea; Reschiglian, Pierluigi; Melucci, Dora
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/894761
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