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The discrimination of honey origin using melissopalynology and Raman spectroscopy techniques coupled with multivariate analysis.

Abstract：

:Honey traceability to food quality is required by consumers and food control institutions. Melissopalynologists traditionally use percentages of nectariferous pollens to discriminate the botanical origin and the entire pollen spectrum (presence/absence, type and quantities and association of some pollen types) to determinate the geographical origin of honeys. To improve melissopalynological routine analysis, principal components analysis (PCA) was used. A remarkable and innovative result was that the most significant pollens for the traditional discrimination of the botanical and geographical origin of honeys were the same as those individuated with the chemometric model. The reliability of assignments of samples to honey classes was estimated through explained variance (85%). This confirms that the chemometric model properly describes the melissopalynological data. With the aim to improve honey discrimination, FT-microRaman spectrography and multivariate analysis were also applied. Well performing PCA models and good agreement with known classes were achieved. Encouraging results were obtained for botanical discrimination.

journal_name

Food Chem

journal_title

Food chemistry

authors

Corvucci F,Nobili L,Melucci D,Grillenzoni FV

doi

10.1016/j.foodchem.2014.07.122

subject

Has Abstract

pub_date

2015-02-15 00:00:00

pages

297-304

eissn

0308-8146

issn

1873-7072

pii

S0308-8146(14)01170-4

journal_volume

169

pub_type

杂志文章

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