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AMDIS-Metab R data manipulation for the geographical and floral differentiation of selected honeys from Zambia and Botswana based on volatile chemical compositions using SPME–GC–MS

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Abstract

A metabolomic classification of commercial and unprocessed organic honeys from Zambia and Botswana based on geographic and floral origins was done forthwith. Classification using gas chromatography–mass spectrometry/solid phase microextraction (GC–MS/SPME) was accomplished on three commercial and three unprocessed organic honeys. The Automated Mass spectral Deconvolution and Identification System (AMDIS), Metab R, an R platform application and MINITAB version 14 partial least squares (PLS) were used for data processing. Sixteen volatile metabolites in three commercial and 40 in three unprocessed organic honeys were identified, confirmed and formed the basis for differentiation. Database search showed that the honeys were polyfloral with major ingredients coming from common flowering plants, conifers and other gymnosperms such as Carica papaya L. (papaya), Monstera deliciosa (ceriman) and fruits, i.e., guava, melon and pineapple, endemic in the areas from which the honeys originated from.

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Acknowledgements

The authors thank the University of Botswana for material support and the Ministry of Agriculture in Botswana; for providing information on beekeepers and granting the research permit to do the project.

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Authors and Affiliations

  1. Department of Chemistry, Faculty of Science, University of Botswana, PB UB 00704, Gaborone, Botswana

    Kwenga Sichilongo & Tumelo Padiso

  2. Ministry of Agriculture, PB 003, Gaborone, Botswana

    Queen Turner

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  1. Kwenga Sichilongo
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  2. Tumelo Padiso
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  3. Queen Turner
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Correspondence to Kwenga Sichilongo.

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Sichilongo, K., Padiso, T. & Turner, Q. AMDIS-Metab R data manipulation for the geographical and floral differentiation of selected honeys from Zambia and Botswana based on volatile chemical compositions using SPME–GC–MS. Eur Food Res Technol 246, 1679–1690 (2020). https://doi.org/10.1007/s00217-020-03523-x

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  • DOI: https://doi.org/10.1007/s00217-020-03523-x

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