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便携式近红外光谱仪,可快速识别巧克力中的脂肪花。

Portable NIR spectrometer for quick identification of fat bloom in chocolates.

机构信息

Department of Food Technology - School of Food Engineering, University of Campinas, Monteiro Lobato Street, 80, CEP 13083-862 Campinas, São Paulo, Brazil.

Department of Analytical Chemistry - Institute of Chemistry, Josué de Castro Street, CEP 13083-970 Campinas, São Paulo, Brazil.

出版信息

Food Chem. 2021 Apr 16;342:128267. doi: 10.1016/j.foodchem.2020.128267. Epub 2020 Oct 8.

Abstract

Cocoa butter provides desirable sensory properties to chocolates; however, the exposure of chocolate to temperature variations during transportation and/or storage can lead to changes in the polymorphic form of butter, with the appearance of a dull-white film on the chocolate surface, known as fat bloom. This study investigated the use of a portable NIR spectrometer combined with chemometric tools to discriminate milk chocolate, white chocolate, 40% cocoa chocolate, and 70% cocoa chocolate samples, which were subjected to temperature abuse for 6 hours. The PCA allowed separating the samples into three classes: control at 20 °C, chocolate subjected to 35 °C, and chocolate subjected to 40 °C, for each type of chocolate studied. The PLS-DA models provided sensibility, specificity, and accuracy values in the range of 80 to 100%, and allowed identifying the wavelengths associated with the different chocolates that most impacted the construction of the models.

摘要

可可脂赋予巧克力理想的感官特性;然而,巧克力在运输和/或储存过程中暴露于温度变化会导致黄油的多晶型形式发生变化,巧克力表面出现暗白色薄膜,称为脂肪花。本研究调查了使用便携式近红外光谱仪结合化学计量工具来区分牛奶巧克力、白巧克力、40%可可巧克力和 70%可可巧克力样品,这些样品在 6 小时内受到温度滥用。PCA 将样品分为三类:20°C 时的对照品、35°C 时的巧克力和 40°C 时的巧克力,适用于研究的每种巧克力。PLS-DA 模型提供了 80%至 100%范围内的灵敏度、特异性和准确性值,并允许识别与不同巧克力相关的波长,这些波长对模型的构建影响最大。

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