The Best Approach for Early Detection of Fungi in Tomato Sauce
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The detection of fungal contaminations, specifically moulds, in tomato sauce stored in the refrigerator is of great importance and very attractive in smart emerging applications. Using an electronic nose (e-nose) and a Fourier transform infrared (FTIR) spectrometer, we examined two sampling methods to early detect fungal contamination: the first method looks at the accumulated headspace while the second one at the actual headspace. Interestingly, we found that we can use only one sensor to detect the moulds even before their visual development.
KeywordsMould early detection E-nose Machine learning
This work was partially supported by Safe & Smart, Nuove tecnologie abilitanti per la food safety e l’integrità della filiera agro-alimentare in uno scenario globale, project N. CTN01_00230_248064, funded by the Italian Ministry of Education, Universities and Research (MIUR).
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