2026-04-13T01:00:06Zhttps://recercat.cat/oai/request

oai:recercat.cat:2445/2160662026-01-14T19:11:37Zcom_2072_1057col_2072_478813col_2072_478913col_2072_478917

00925njm 22002777a 4500 dc Caredda, Marco author Ciulu, Marco author Tilocca, F. author Langasco, Ilaria author Núñez Burcio, Oscar author Sentellas, Sonia author Saurina, Javier author Pilo, Maria I. author Spano, Nadia author Sanna, Gavino author Mara, Alessandro author 2024-10-25T16:57:17Z 2024-10-25T16:57:17Z 2024-09-26 2024-10-25T16:57:17Z Fraudulent practices concerning honey are growing fast and involve misrepresentation of origin and adulteration. Simple and feasible methods for honey authentication are needed to ascertain honey compliance and quality. Working on a robust dataset and simultaneously investigating honey traceability and adulterant detection, this study proposed a portable FTNIR fingerprinting approach combined with chemometrics. Multifloral and unifloral honey samples (n = 244) from Spain and Sardinia (Italy) were discriminated by botanical and geographical origin. Qualitative and quantitative methods were developed using linear discriminant analysis (LDA) and partial least squares (PLS) regression to detect adulterated honey with two syrups, consisting of glucose, fructose, and maltose. Botanical and geographical origins were predicted with 90% and 95% accuracy, respectively. LDA models discriminated pure and adulterated honey samples with an accuracy of over 92%, whereas PLS allows for the accurate quantification of over 10% of adulterants in unifloral and 20% in multifloral honey. Espectroscòpia Mel d'abelles Cuina (Xarops) Spectrum analysis Honey Cooking (Syrups) Portable NIR spectroscopy to simultaneously trace honey botanical and geographicl origins and detect syrup adulteration.