2026-04-13T03:57:05Zhttps://recercat.cat/oai/requestoai:recercat.cat:2445/2208082025-12-05T14:51:39Zcom_2072_1057col_2072_478917col_2072_478924
RECERCAT
author
Torres Cobos, Berta
author
Tres Oliver, Alba
author
Vichi, S. (Stefania)
author
Guardiola Ibarz, Francesc
author
Rovira, Mercè
author
Romero, Agustí
author
Baeten, V.
author
Fernández-Pierna, J. A.
2025-05-05T11:20:35Z2025-05-05T11:20:35Z20242025-05-05T11:20:35Z
Hazelnut market prices fluctuate significantly based on cultivar and provenance, making them susceptible to counterfeiting. To develop an accurate authentication method, we compared the performances of three spectroscopic methods: near infrared (NIR), handheld near infrared (hNIR), and medium infrared (MIR), on over 300 samples from various origins, cultivars, and harvest years. Spectroscopic fingerprints were used to develop and externally validate PLS-DA classification models. Both cultivar and origin models showed high accuracy in external validation. The hNIR model effectively distinguished cultivars but struggled with geographic distinctions due to lower sensitivity. NIR and MIR models showed over 93% accuracy, with NIR slightly outperforming MIR for geographic origin. NIR proved to be a fast and suitable tool for hazelnut authentication. This study is the first to systematically compare spectroscopic tools for authenticating hazelnut cultivar and origin using the same dataset, offering valuable insights for future food authentication applications.
cc-by-nc-nd (c) Berta Torres-Cobos, et al., 2024 http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess
Avellanes
Química dels aliments
Fruita seca
Hazelnuts
Food composition
Dried fruit
Comparative analysis of spectroscopic methods for rapid authentication of hazelnut cultivar and origin
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion