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傅里叶变换红外光谱法和近红外光谱法定量分析烘焙咖啡中的缺陷。

Fourier transform infrared spectroscopy and near infrared spectroscopy for the quantification of defects in roasted coffees.

机构信息

PPGCA, Universidade Federal de Minas Gerais, Av. Antônio Carlos, 6627, 31270-901 Belo Horizonte, MG, Brazil; Department of Agricultural and Biological Engineering, Purdue University, 225 S. University Street, West Lafayette, IN 47907, USA.

DEMEC, Universidade Federal de Minas Gerais, Av. Antônio Carlos, 6627, 31270-901 Belo Horizonte, MG, Brazil.

出版信息

Talanta. 2015 Mar;134:379-386. doi: 10.1016/j.talanta.2014.11.038. Epub 2014 Nov 27.

Abstract

The coffee strip-picking harvesting method, preferred in Brazil, results in high percentages of immature and overripe beans, as the fruits in a single tree branch do not reach ripeness at the same time. This practice, together with inappropriate processing and storage conditions, contribute to the production of high amounts of defective coffee beans in Brazil, which upon roasting will impart negative sensory aspects to the beverage. Therefore, the development of analytical methodologies that will enable the discrimination and quantification of defective and non-defective coffees after roasting is rather desirable. Given that infrared spectroscopy has been successfully applied to coffee analysis, the objective of this work was to evaluate and to compare the performances of Fourier transform infrared (FTIR) and near infrared (NIR) spectroscopies for the quantification of defective beans in roasted coffees. Defective and non-defective Arabica coffee beans were manually selected, roasted, ground and sieved. Mixtures of defective and non-defective roasted and ground coffees were produced and analyzed, with % defects ranging from 0% to 30%. FTIR and NIR spectra were recorded, respectively, within a range of 3100-800 cm(-1) and 1200-2400 nm and submitted to mathematical processing. Quantitative models were developed by partial least squares regression (PLSR). Excellent predictive results were obtained indicating that defective coffees could be satisfactorily quantified. The correlation coefficients and the root mean squared errors of validation for the FTIR and NIR models developed to quantify the amount of defective roasted coffees mixed with non-defective ones were, respectively, as high as 0.891 and as low as 0.032, and as high as 0.953 and as low as 0.026. A comparison between the two techniques indicated that NIR provided more robust models.

摘要

巴西采用的咖啡带采摘收获方法会导致大量未成熟和过熟的咖啡豆,因为同一树枝上的果实不会同时成熟。这种做法加上不当的加工和储存条件,导致巴西生产出大量有缺陷的咖啡豆,在烘焙后会给饮料带来负面的感官影响。因此,开发能够在烘焙后区分和定量有缺陷和无缺陷咖啡的分析方法是非常必要的。鉴于红外光谱已成功应用于咖啡分析,本工作的目的是评估和比较傅里叶变换红外(FTIR)和近红外(NIR)光谱法在烘焙咖啡中定量有缺陷咖啡豆的性能。手动选择有缺陷和无缺陷的阿拉比卡咖啡豆进行烘焙、研磨和筛分。制备并分析了有缺陷和无缺陷烘焙和研磨咖啡的混合物,缺陷率范围为 0%至 30%。分别记录 FTIR 和 NIR 光谱,范围分别为 3100-800 cm(-1)和 1200-2400 nm,并进行数学处理。通过偏最小二乘回归(PLSR)建立定量模型。得到了极好的预测结果,表明可以满意地定量有缺陷的咖啡。为定量混合有缺陷和无缺陷烘焙咖啡而开发的 FTIR 和 NIR 模型的相关系数和验证均方根误差分别高达 0.891 和 0.032,以及 0.953 和 0.026。两种技术的比较表明,NIR 提供了更稳健的模型。

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