TY - GEN
T1 - Can Minerals Be Used as a Tool to Classify Cinnamon Samples?
AU - Silva, Anna Flavia S.
AU - Martins, Luís Cláudio
AU - Moraes, Liz M.B.
AU - Gonçalves, Isabela C.
AU - de Godoy, Bianca B.R.
AU - Erasmus, Sara W.
AU - van Ruth, Saskia
AU - Rocha, Fábio R.P.
PY - 2021
Y1 - 2021
N2 - Cinnamon (Cinnamomum zeylanicum) is a spice largely consumed worldwide, but there is still restricted information about its fingerprint. This work aimed to investigate the mineral composition as a possible marker for the classification of cinnamon samples. To this aim, the mineral composition (P, S, Mg, Ca, K, Cu, Zn, B, Fe, Al, Mn, and Si contents) of 56 ground cinnamon samples from different regions of the State of São Paulo, Brazil was determined by inductively coupled plasma optical emission spectroscopy (ICP OES). Principal component analysis was exploited for sample classification, and the microelements presented the best correlation: PC1, PC2, and PC3 explained 93% of the observed variance at 95% confidence level. Si, Al, Fe, and Cu presented the most significant contributions to cluster analysis. Samples were classified into six groups, in which those presenting C. zeylanicum were well clustered, and the samples acquired in bulk as well as those whose labels declared traces of grains and/or spices presented the highest variability. Thus, it was pioneeringly demonstrated the possibility of identifying C. zeylanicum in commercial cinnamon powders, using microelements as authenticity markers.
AB - Cinnamon (Cinnamomum zeylanicum) is a spice largely consumed worldwide, but there is still restricted information about its fingerprint. This work aimed to investigate the mineral composition as a possible marker for the classification of cinnamon samples. To this aim, the mineral composition (P, S, Mg, Ca, K, Cu, Zn, B, Fe, Al, Mn, and Si contents) of 56 ground cinnamon samples from different regions of the State of São Paulo, Brazil was determined by inductively coupled plasma optical emission spectroscopy (ICP OES). Principal component analysis was exploited for sample classification, and the microelements presented the best correlation: PC1, PC2, and PC3 explained 93% of the observed variance at 95% confidence level. Si, Al, Fe, and Cu presented the most significant contributions to cluster analysis. Samples were classified into six groups, in which those presenting C. zeylanicum were well clustered, and the samples acquired in bulk as well as those whose labels declared traces of grains and/or spices presented the highest variability. Thus, it was pioneeringly demonstrated the possibility of identifying C. zeylanicum in commercial cinnamon powders, using microelements as authenticity markers.
U2 - 10.3390/foods_2020-07652
DO - 10.3390/foods_2020-07652
M3 - Conference paper
T3 - Proceedings
BT - Proceedings, 2021, Foods 2020
A2 - Smith, C.J.
PB - MDPI
T2 - The 1st International Electronic Conference on Food Science and Functional Foods
Y2 - 10 November 2020 through 25 November 2020
ER -