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Artificial smell to control food quality

The methodology has been validated in samples of Iberian ham. Image: AGR-287 Group (UCO)

The methodology has been validated in samples of Iberian ham. Image: AGR-287 Group (UCO)

11/11/2021

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A team led by Santiago Marco, professor at the Department of Electronic Engineering of the UB and member of IBEC, has optimised the use of a technique that analyses, at a molecular level, the present substances in the aroma of food. Therefore, it differentiates, among Iberian ham samples, those pigs that had been fed with acorn and those fed with feed.

The aroma of food is one of the main indicators of its quality, and it can bring additional information on the stages of its production. The analysis of the aromas via modern techniques offers alternatives to the human evaluation, and it is a strong and reliable tool for detecting frauds, which tend to happen in the market of the Iberian ham, olive oil, honey and wine.

One of the most powerful and promising techniques in the field of aroma characterization in food is the gas chromatography – ion mobility spectrometry (GC-IMS), which is fast, effective, economic and easy to transport. Despite its multiple benefits, the analysis of the raw data created with this methodology is highly complex, which makes it difficult and limits its use.

Now, a study has enabled the development of new proceedings for the analysis of GC-IMS data of aromas in food, opening the door to the opportunity of creating customized analysers to verify the quality and authenticity of high value food products.


In this study, recently published in the journal Sensors, researchers present a methodology that goes from raw data processing to the final characterization of the sample. For its validation, they have been able to predict the pig feeding regime (acorn or feed) in samples of Iberian ham.

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