Honey adulteration detection based on composition and differential scanning calorimetry (DSC) parameters

One of the most important issues regarding the quality of honey is its adulteration through the addition of non-allowed substances. For this reason, this study aimed at assessing the usefulness of DSC combined with sugar composition analysis for the detection of sunflower honey adulteration with fiv...

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Veröffentlicht in:Food science & technology 2022-10, Vol.168, p.113910, Article 113910
Hauptverfasser: Dranca, Florina, Ropciuc, Sorina, Pauliuc, Daniela, Oroian, Mircea
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Sprache:eng
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Zusammenfassung:One of the most important issues regarding the quality of honey is its adulteration through the addition of non-allowed substances. For this reason, this study aimed at assessing the usefulness of DSC combined with sugar composition analysis for the detection of sunflower honey adulteration with five types of syrups (agave, maple, rice, corn, and inverted sugar syrup) in percentages of 5, 10 and 20%. Sunflower honey and the syrup samples showed differences in the fructose and glucose content. For these two sugars, an overall reduction of the concentration was observed following adulteration; a greater difference was observed when the adulteration was made with corn syrup, maple syrup or rice syrup. Authentic honey showed one or two thermal transitions (glass transition and a second transition), and notable different DSC parameters by comparison to syrup samples. The addition of syrup and the increase of the proportion of syrup added determined a slight decrease of the glass transition temperature of honey. The sugar composition and the DSC parameters coupled with PLSR were successful in predicting the percentage of adulteration agent added into honey. •Sunflower honey samples were adulterated with five different syrups.•The usefulness of DSC and sugar analysis for honey adulteration detection was studied.•Adulteration determined changes in sugar composition and thermal behavior.•The data was subjected to DA and PLS-DA to improve discrimination between samples.•A PLSR model was found successful in predicting the adulteration agent percentage.
ISSN:0023-6438
1096-1127
DOI:10.1016/j.lwt.2022.113910