Chemical Fingerprint of Non-aged Artisanal Sugarcane Spirits Using Kohonen Artificial Neural Network

نویسندگان

چکیده

Abstract This study focuses on the determination of chemical profile 24 non-aged Brazilian artisanal sugarcane spirits ( cachaça ) samples through chromatographic quantification and chemometric treatment via principal component analysis (PCA) Kohonen’s neural network. In total, forty-seven (47) compounds were identified in , addition to determining alcohol content, volatile acidity, copper. For PCA compounds’ profile, it could be observed that grouped into seven groups. On other hand, variables’ bearings together, making difficult separate components relation sample groups reducing chances obtaining all necessary information. However, by using a network, eight tool proved more accurate groups’ formation. Among classes observed, esters stood out, followed alcohols, acids, aldehydes, ketones, phenol, The abundance these may suggest would part regional standard for cachaças produced region Salinas, Minas Gerais.

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ژورنال

عنوان ژورنال: Food Analytical Methods

سال: 2021

ISSN: ['1936-9751', '1936-976X']

DOI: https://doi.org/10.1007/s12161-021-02160-8