Toward Smart Online Coffee Roasting Process Control: Feasibility of Real-Time Prediction of Coffee Roast Degree and Brew Antioxidant Capacity by Single-Photon Ionization Mass Spectrometric Monitoring of Roast Gases.,Journal of Agricultural and Food Chemistry

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Toward Smart Online Coffee Roasting Process Control: Feasibility of Real-Time Prediction of Coffee Roast Degree and Brew Antioxidant Capacity by Single-Photon Ionization Mass Spectrometric Monitoring of Roast Gases.
Journal of Agricultural and Food Chemistry ( IF 5.7 ) Pub Date : 2020-01-22 , DOI: 10.1021/acs.jafc.9b06502
Jan Heide ₁ , Hendryk Czech _{1,

2} , Sven Ehlert _{3,

4} , Thomas Koziorowski ₅ , Ralf Zimmermann _{1,

2,

4}

Affiliation

Precise controlling and monitoring the status of the coffee roasting process is essential for consistent product quality and optimization toward targeted coffee properties. In small-scale roasting experiments, the chemical composition of the roasting off-gas was analyzed by online single-photon ionization time-of-flight mass spectrometry (SPI-TOFMS) at 118 nm with 5 s time resolution. Subsequently, mass spectra at the drop of the coffee beans were combined with off-line measurements of roast degree, described by color value "Colorette", and the antioxidant capacity, obtained from the Folin-Ciocalteu (FC) assay, in an explanatory projection on latent structure regression model. While the roast degree gives an indication of the coffee flavor, antioxidants in brewed coffee are regarded as beneficial for human health. Colorette and FC values could be derived from the SPI mass spectra with root-mean-square errors from Monte Carlo cross-validation of 6.0 and 139 mg of gallic acid equiv L-1, respectively, and explained covariance (R2CV) better than 89%. Finally, the regression models were applied to the SPI mass spectra over the entire roast to demonstrate the predictive ability for online process control in real time.

中文翻译：

迈向智能在线咖啡烘焙过程控制：通过烘焙气体的单光子电离质谱监测实时预测咖啡烘焙程度和咖啡抗氧化能力的可行性。

精确控制和监视咖啡烘焙过程的状态对于稳定的产品质量和针对目标咖啡属性的优化至关重要。在小规模焙烧实验中，通过在线单光子电离飞行时间质谱（SPI-TOFMS）在5 s的时间分辨率下，通过在线单光子电离飞行时间质谱（SPI-TOFMS）分析了焙烧废气的化学成分。随后，将咖啡豆滴处的质谱与通过颜色值“色度”描述的离线烘烤程度测量值以及通过Folin-Ciocalteu（FC）测定法获得的抗氧化能力相结合，进行了解释说明在潜在结构回归模型上。烘焙程度可以说明咖啡的味道，而冲泡咖啡中的抗氧化剂被认为对人体健康有益。色度和FC值可以从SPI质谱图得出，均方根误差分别来自6.0和139 mg没食子酸当量L-1的蒙特卡罗交叉验证，并且解释的协方差（R2CV）优于89％。最后，将回归模型应用于整个烘烤过程中的SPI质谱，以证明实时在线过程控制的预测能力。

更新日期：2020-01-22

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