Events1st International Electronic Conference on Food Science and Functional Foods
Published
with-doi10.3390/foods_2020-07652 (registering DOI)
This submission belongs to the session 5. Food Safety and Sustainable Development of the event 1st International Electronic Conference on Food Science and Functional Foods
Published date
09 Nov, 2020
Citation
Anna Flavia de Souza Silva, Luís Cláudio Martins, Liz Mary B. Moraes, Isabela Camargo Gonçalves, Bianca Bacellar Rodrigues de Godoy, Sara W. Erasmus, Saskia van Ruth, Fábio R. Piovezani Rocha, Can minerals be used as a tool to classify cinnamon samples?, in Proceedings of 1st International Electronic Conference on Food Science and Functional Foods, 10 November–25 November 2020, MDPI: Basel, Switzerland, doi: 10.3390/foods_2020-07652
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Can minerals be used as a tool to classify cinnamon samples?

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Liz Mary B. Moraes 3
Bianca Bacellar Rodrigues de Godoy 3,4
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1. Center for Nuclear Energy in Agriculture, University of Sao Paulo (CENA/USP), Brazil
2. Food Quality and Design, Wageningen University and Research
3. Center for Nuclear Energy in Agriculture, University of Sao Paulo (CENA/USP)
4. Luiz de Queiroz College of Agriculture (ESALQ/USP)
Abstract

Cinnamon (Cinnamomum zeylanicum) is a spice largely consumed worldwide. In spite of its high popularity, there is still restricted information about its fingerprint. This work aims to investigate the mineral composition as a possible marker for the classification of cinnamon samples. A set of 56 ground cinnamon samples were bought in different markets and regions of the State of São Paulo, Brazil. Mineral composition (P, S, Mg, Ca, K, Cu, Zn, B, Fe, Al, Mn, and Si contents) was determined by inductively coupled plasma optical emission spectroscopy (ICP OES) after cryogenic grinding) and microwave-assisted acid digestion (6.0 mL of 2.0 mol L-1 HNO3 + 2.0 mL of 30% v/v H2O2). The principal component analysis was exploited for sample classification, and the content of 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 contribution to cluster samples, while B presented the lowest one. Samples were classified into 6 groups, in which those presenting C. zeylanicum were well clustered. Two samples, whose labeled information include traces of celery, mustard, and other spices were identified as outliers. Samples acquired in bulk as well as those whose labels declared traces of grains and/or spices presented the highest variability. Thus, it was pioneering to indicate the possibility to identify C. zeylanicum in commercial cinnamon powders, using microelements as authenticity markers.

Keywords
Food Authenticity
Microelements
Chemical targets
Spice
Manuscript
Oral Presentation
Poster
presentation Foods.pdf
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