Arrowroot and Cassava Mixed Starch Products Identification by Raman Analysis with Chemometrics

Food frauds present a major problem in the foodstuff industry. Arrowroot and cassava may be targeted in adulteration and falsification processes. Raman analysis combined with chemometric techniques was proposed to identify the mixing and adulteration of these foodstuffs in commercial products. 67 ca...

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Bibliographic Details
Authors: Macedo, Isaac Yves Lopes de, Cereda, Marney Pascoli [UNESP], Bet, Camila Delinski, Junior, Jose Francisco Santos Silveira, Carvalho, Murilo Ferreira de, Gil, Eric de Souza
Format: article
Status:Published version
Publication Date:2021
Country:Brasil
Institution:Universidade Estadual Paulista (UNESP)
Repository:Repositório Institucional da UNESP
Language:English
OAI Identifier:oai:repositorio.unesp.br:11449/304861
Online Access:http://dx.doi.org/10.3390/polysaccharides2030043
https://hdl.handle.net/11449/304861
Access Level:Open access
Keyword:adulteration
food
fraud
Description
Summary:Food frauds present a major problem in the foodstuff industry. Arrowroot and cassava may be targeted in adulteration and falsification processes. Raman analysis combined with chemometric techniques was proposed to identify the mixing and adulteration of these foodstuffs in commercial products. 67 cassava and 5 arrowroot samples were prepared in laboratory. 21 cassava and 5 arrowroot commercial samples were purchased in local stores. Raman assays were performed in the range of 400 to 2300 cm−1. Principal component analysis with K-means clustering was used to identify the adulteration of these products. It was possible to observe the separation of three different groups in the data, these groups labelled group 1, 2 and 3 were correspondent to cassava-like samples, mixed samples, and arrowroot-like samples, respectively. Despite the visual analysis related to sensory characteristics and the visual analysis of each Raman spectrum of cassava and arrowroot not being able to differentiate these foodstuffs, the chemometric approaches with the Raman specters data were able to identify which samples were pure arrowroot, pure cassava and which were mixed products. The proposed approach showed to be an effective tool in the investigation of fraud for arrowroot and cassava.