首页> 外文期刊>Analytical and Bioanalytical Chemistry >Online monitoring of coffee roasting by proton transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS): towards a real-time process control for a consistent roast profile
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Online monitoring of coffee roasting by proton transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS): towards a real-time process control for a consistent roast profile

机译:通过质子转移反应飞行时间质谱(PTR-ToF-MS)在线监控咖啡烘焙:实现实时过程控制以实现一致的烘焙曲线

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摘要

A real-time automated process control tool for coffee roasting is presented to consistently and accurately achieve a targeted roast degree. It is based on the online monitoring of volatile organic compounds (VOC) in the off-gas of a drum roaster by proton transfer reaction time-of-flight mass spectrometry at a high time (1 Hz) and mass resolution (5,500 m/Δm at full width at half-maximum) and high sensitivity (better than parts per billion by volume). Forty-two roasting experiments were performed with the drum roaster being operated either on a low, medium or high hot-air inlet temperature (= energy input) and the coffee (Arabica from Antigua, Guatemala) being roasted to low, medium or dark roast degrees. A principal component analysis (PCA) discriminated, for each one of the three hot-air inlet temperatures, the roast degree with a resolution of better than ±1 Colorette. The 3D space of the three first principal components was defined based on 23 mass spectral profiles of VOCs and their roast degree at the end point of roasting. This provided a very detailed picture of the evolution of the roasting process and allowed establishment of a predictive model that projects the online-monitored VOC profile of the roaster off-gas in real time onto the PCA space defined by the calibration process and, ultimately, to control the coffee roasting process so as to achieve a target roast degree and a consistent roasting.
机译:提出了一种用于咖啡烘焙的实时自动化过程控制工具,以一致且准确地达到目标烘焙程度。它基于质子传递反应飞行时间质谱在高时间(1 Hz)和质量分辨率(5,500 m /Δm)下在线监测鼓式焙烧炉尾气中的挥发性有机化合物(VOC)全宽(一半为最大值)和高灵敏度(优于十亿分之几的体积)。进行了42次烘焙实验,其中鼓式烘焙机在低,中或高热风入口温度(=能量输入)下运行,咖啡(危地马拉安提瓜的阿拉比卡咖啡)被烘焙到低,中或深色烘焙度。主成分分析(PCA)对三种热风入口温度中的每一种进行鉴别,其烘烤度的分辨率优于±1 Colorette。根据23种VOC的质谱图及其在焙烧终点的焙烧度定义了三个第一主成分的3D空间。这提供了烘烤过程演变的非常详细的图片,并允许建立一个预测模型,该模型将在线监测的烘烤废气的VOC轮廓实时投影到由校准过程定义的PCA空间中,最终,控制咖啡烘焙过程,以达到目标烘焙程度和一致的烘焙效果。

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