Zastosowanie metod chemometrycznych do woltamperometrycznego profilowania żywności

• Autorzy: Wójcik Szymon , Ciepiela Filip , Baś Bogusław , Jakubowska Małgorzata

Identyfikatory

DOI

10.53584/wiadchem.2025.1.3

Warianty tytułu

Application of chemometric methods foe voltammetric profiling of food

• Języki publikacji: PL

Abstrakty

EN

The development of society and the rise in consumer awareness generate the need for rapid and precise analysis of food products to ensure their high quality. Consumers are increasingly paying attention to the origin, composition, and production processes of food. Heightened competition among producers and rising production costs lead to serious challenges, such as food product adulteration to lower prices and maximize profits. This study presents results of analysis of a wide range of food products, including wines, whiskies, apple juices, honey, isotonic drinks, and plant-based milks. The research focused on profiling these samples and identifying potential issues, such as the presence of undesirable additives. The registration of voltammetric profiles was made possible through the use of modern working electrodes. As a result of the conducted research, several innovative methods were developed, combining chemical analysis and machine learning strategies that effectively address the identified research problems. Research plans were created to detect adulteration in apple juices and honeys, and predictive models regarding the aging of young wines were defined. Procedures for profiling products such as wines, whiskies, honeys, isotonic drinks, and plant-based milks were also designed. For each of these procedures, a multi-stage optimization of voltammetric profile registration parameters was carried out, and the obtained data underwent advanced signal processing to ensure the highest possible quality of results.

Słowa kluczowe

PL

profilowanie żywności; uczenie maszynowe; głębokie uczenie maszynowe; chemometria; woltamperometryczny elektroniczny język

EN

food profiling; voltammetric profiling; machine learning; deep machine learning; chemometrics; voltammetric electronic tongue

• Wydawca: Polskie Towarzystwo Chemiczne
• Czasopismo: Wiadomości Chemiczne
• Rocznik: 2025
• Tom: [Z] 79, 1-2
• Strony: 39--58
• Opis fizyczny: Bibliogr. 40 poz., fot., rys., wykr.

Twórcy

autor

Wójcik Szymon

• Katedra Chemii Krzemianów i Związków Wielkocząsteczkowych, Wydział Inżynierii Materiałowej i Ceramiki, Akademia Górniczo – Hutnicza im. Stanisława Staszica w Krakowie, ul. Mickiewicza 30, 30-059 Kraków

• https://orcid.org/0000-0003-3124-3067

autor

Ciepiela Filip

• Katedra Chemii Analitycznej i Biochemii, Wydział Inżynierii Materiałowej i Ceramiki, Akademia Górniczo – Hutnicza im. Stanisława Staszica w Krakowie, ul. Mickiewicza 30, 30-059 Kraków

• https://orcid.org/0000-0001-7640-9169

autor

Baś Bogusław

• Katedra Chemii Analitycznej i Biochemii, Wydział Inżynierii Materiałowej i Ceramiki, Akademia Górniczo – Hutnicza im. Stanisława Staszica w Krakowie, ul. Mickiewicza 30, 30-059 Kraków

• https://orcid.org/0000-0002-5129-2942

autor

Jakubowska Małgorzata

• Katedra Chemii Analitycznej i Biochemii, Wydział Inżynierii Materiałowej i Ceramiki, Akademia Górniczo – Hutnicza im. Stanisława Staszica w Krakowie, ul. Mickiewicza 30, 30-059 Kraków

• https://orcid.org/0000-0002-0192-4083

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).