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Article

Prediction of Physicochemical Properties in Honeys with Portable Near-Infrared (microNIR) Spectroscopy Combined with Multivariate Data Processing

Department of Vegetal Biology and Soil Sciences, Faculty of Sciences, University of Vigo, 32004 Ourense, Spain
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Author to whom correspondence should be addressed.
Academic Editor: Christopher John Smith
Foods 2021, 10(2), 317; https://doi.org/10.3390/foods10020317
Received: 5 January 2021 / Revised: 28 January 2021 / Accepted: 30 January 2021 / Published: 3 February 2021
There is an increase in the consumption of natural foods with healthy benefits such as honey. The physicochemical composition contributes to the particularities of honey that differ depending on the botanical origin. Botanical and geographical declaration protects consumers from possible fraud and ensures the quality of the product. The objective of this study was to develop prediction models using a portable near-Infrared (MicroNIR) Spectroscopy to contribute to authenticate honeys from Northwest Spain. Based on reference physicochemical analyses of honey, prediction equations using principal components analysis and partial least square regression were developed. Statistical descriptors were good for moisture, hydroxymethylfurfural (HMF), color (Pfund, L and b* coordinates of CIELab) and flavonoids (RSQ > 0.75; RPD > 2.0), and acceptable for electrical conductivity (EC), pH and phenols (RSQ > 0.61; RDP > 1.5). Linear discriminant analysis correctly classified the 88.1% of honeys based on physicochemical parameters and botanical origin (heather, chestnut, eucalyptus, blackberry, honeydew, multifloral). Estimation of quality and physicochemical properties of honey with NIR-spectra data and chemometrics proves to be a powerful tool to fulfil quality goals of this bee product. Results supported that the portable spectroscopy devices provided an effective tool for the apicultural sector to rapid in-situ classification and authentication of honey. View Full-Text
Keywords: honey; quality control; authentication; botanical origin; NIR; modified partial least squares; linear discriminant analysis honey; quality control; authentication; botanical origin; NIR; modified partial least squares; linear discriminant analysis
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MDPI and ACS Style

Escuredo, O.; Rodríguez-Flores, M.S.; Meno, L.; Seijo, M.C. Prediction of Physicochemical Properties in Honeys with Portable Near-Infrared (microNIR) Spectroscopy Combined with Multivariate Data Processing. Foods 2021, 10, 317. https://doi.org/10.3390/foods10020317

AMA Style

Escuredo O, Rodríguez-Flores MS, Meno L, Seijo MC. Prediction of Physicochemical Properties in Honeys with Portable Near-Infrared (microNIR) Spectroscopy Combined with Multivariate Data Processing. Foods. 2021; 10(2):317. https://doi.org/10.3390/foods10020317

Chicago/Turabian Style

Escuredo, Olga, María S. Rodríguez-Flores, Laura Meno, and María C. Seijo. 2021. "Prediction of Physicochemical Properties in Honeys with Portable Near-Infrared (microNIR) Spectroscopy Combined with Multivariate Data Processing" Foods 10, no. 2: 317. https://doi.org/10.3390/foods10020317

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