TY - JOUR
T1 - Fluorescence spectroscopy coupled with PARAFAC and PLS DA for characterization and classification of honey
AU - Lenhardt, Lea
AU - Bro, Rasmus
AU - Zekovic, Ivana
AU - Dramicanin, Tatjana
AU - Dramicanin, Miroslav D .
PY - 2015/5/15
Y1 - 2015/5/15
N2 - Fluorescence spectroscopy coupled with parallel factor analysis (PARAFAC) and Partial least squares Discriminant Analysis (PLS DA) were used for characterization and classification of honey. Excitation emission spectra were obtained for 95 honey samples of different botanical origin (acacia, sunflower, linden, meadow, and fake honey) by recording emission from 270 to 640 nm with excitation in the range of 240-500 nm. The number of fluorophores present in honey, excitation and emission spectra of each fluorophore, and their relative concentration are determined using a six-component PARAFAC model. Emissions from phenolic compounds and Maillard reaction products exhibited the largest difference among classes of honey of different botanical origin. The PLS DA classification model, constructed from PARAFAC model scores, detected fake honey samples with 100% sensitivity and specificity. Honey samples were also classified using PLS DA with errors of 0.5% for linden, 10% for acacia, and about 20% for both sunflower and meadow mix.
AB - Fluorescence spectroscopy coupled with parallel factor analysis (PARAFAC) and Partial least squares Discriminant Analysis (PLS DA) were used for characterization and classification of honey. Excitation emission spectra were obtained for 95 honey samples of different botanical origin (acacia, sunflower, linden, meadow, and fake honey) by recording emission from 270 to 640 nm with excitation in the range of 240-500 nm. The number of fluorophores present in honey, excitation and emission spectra of each fluorophore, and their relative concentration are determined using a six-component PARAFAC model. Emissions from phenolic compounds and Maillard reaction products exhibited the largest difference among classes of honey of different botanical origin. The PLS DA classification model, constructed from PARAFAC model scores, detected fake honey samples with 100% sensitivity and specificity. Honey samples were also classified using PLS DA with errors of 0.5% for linden, 10% for acacia, and about 20% for both sunflower and meadow mix.
U2 - 10.1016/j.foodchem.2014.11.162
DO - 10.1016/j.foodchem.2014.11.162
M3 - Journal article
C2 - 25577082
SN - 0308-8146
VL - 175
SP - 284
EP - 291
JO - Food Chemistry
JF - Food Chemistry
ER -