Use este identificador para citar ou linkar para este item: https://locus.ufv.br//handle/123456789/22535
Tipo: Artigo
Título: Smartphone application for methanol determination in sugar cane spirits employing digital image-based method
Autor(es): Franco, Mathews de Oliveira Krambeck
Suarez, Willian Toito
Maia, Matheus Valentin
Santos, Vagner Bezerra dos
Abstract: A simple, accurate, and low-cost analytical procedure for methanol determination in sugarcane spirits (cachaça) employing analysis of digital images is presented. A portable system with cheap materials and lighting system to obtain images from a smartphone was built and an RGB system was used for analytical purposes. The reaction for determination of methanol in beverages consists in methanol oxidation to methanal, and consequent formation of a violet chromophore in the presence of chromotropic acid on heating in an oven at 80 °C for 15 min. From the system optimization, analytical curves that showed good linearity for the green channel (from RGB) was built, with regression coefficient (R^ 2) of 0.998. Relevant matrix effect in the samples was not verified, since the recovery percentage ranged from 83 to 110%. The results of methanol concentration in six cachaça samples obtained by the developed method were compared with using the spectrophotometric method with a confidence level of 95% (n = 3). The developed method has some economic and environmental benefits, since it has low reagent consumption with 800 μL per measured spot, as well as, it presents cheap and handle-easy devices, which encourages the quality control of this toxic and undesirable contaminant for smallholders and industries on production of sugar cane spirits.
Palavras-chave: Spot test
Digital image analysis
Methanol
Sugar cane spirits
Cachaça
Food analysis
Food contamination
Editor: Food Analytical Methods
Tipo de Acesso: Springer Science+Business Media New York 2016
URI: http://dx.doi.org/10.1007/s12161-016-0777-y
http://www.locus.ufv.br/handle/123456789/22535
Data do documento: 29-Dez-2016
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