Literature DB >> 32492899

Application of ATR-FT-MIR for Tracing the Geographical Origin of Honey Produced in the Maltese Islands.

Jean Paul Formosa1, Frederick Lia1, David Mifsud2, Claude Farrugia1.   

Abstract

Maltese honey has been produced, marketed, and sold as an exclusive local gourmet food product for countless years. Yet, thus far, no study has evaluated the individuality of this local food product. The evaluation of the parameters and properties which characterise the provenance and floral source of honey have been the subject of various studies worldwide, owing to the price and potential beneficial properties of this food product. Models analysing the potential of attenuated total reflection mid-infrared (ATR-FT-MIR) spectroscopy in discriminating and classifying local honey from that of foreign origin were investigated using 21 Maltese honey samples and 49 honey samples collected from abroad (Sicily, Greece, Sweden, Italy, France, Estonia and other samples of mixed geographical origin). Through a combination of spectroscopic techniques, spectral transformations, variable selection and partial least squares discriminant analysis (PLS-DA), chemometric models which successfully classified the provenance of local and non-local honey were developed. The results of these models were also corroborated with other classification and pattern recognition techniques, such as linear discriminate analysis (LDA), support vector machines (SVM) and feed-forward artificial neural networks (FF-ANN).

Entities:  

Keywords:  ATR-FT-MIR; FF-ANN; LDA; Malta; PLS-DA; SVM; chemometrics; honey

Year:  2020        PMID: 32492899     DOI: 10.3390/foods9060710

Source DB:  PubMed          Journal:  Foods        ISSN: 2304-8158


  2 in total

1.  The Development of Honey Recognition Models Based on the Association between ATR-IR Spectroscopy and Advanced Statistical Tools.

Authors:  Maria David; Ariana Raluca Hategan; Camelia Berghian-Grosan; Dana Alina Magdas
Journal:  Int J Mol Sci       Date:  2022-09-01       Impact factor: 6.208

2.  Authentication and Provenance of Walnut Combining Fourier Transform Mid-Infrared Spectroscopy with Machine Learning Algorithms.

Authors:  Hongyan Zhu; Jun-Li Xu
Journal:  Molecules       Date:  2020-10-28       Impact factor: 4.411

  2 in total

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