Food Colour and Quality Laboratory, Área de Nutrición y Bromatología, Facultad de Farmacia, Universidad de Sevilla, 41012 Sevilla, Spain.
Food Colour and Quality Laboratory, Área de Nutrición y Bromatología, Facultad de Farmacia, Universidad de Sevilla, 41012 Sevilla, Spain.
Food Chem. 2018 Apr 1;244:206-212. doi: 10.1016/j.foodchem.2017.10.027. Epub 2017 Oct 10.
Extractable total phenolic content of American non-toasted oak (Quercus alba L.) shavings has been determined using near infrared hyperspectral imaging. A like-wine model solution was used for the simulated maceration procedure. Calibrations were performed by partial least squares regression (MPLS) using a number of spectral pre-treatments. The coefficient of determination of wood for extractable total phenolic content was 0.89, and the standard error of prediction was 6.3 mg g. Thus, near infrared hyperspectral imaging arises as an attractive strategy for predicting extractable total phenolic content in the range of 0-65 mg g, of great relevance from the point of view of quality assurance regarding wood used in the wine sector. Near infrared hyperspectral imaging arises as an attractive strategy for the feasibility of enhancing the value of cooperage byproduct through the fast determination of extractable bioactive molecules, such as polyphenols.
采用近红外高光谱成像技术测定了美国未烤橡木（Quercus alba L.）刨花的总酚提取含量。模拟浸渍过程中使用了类似葡萄酒的模型溶液。采用偏最小二乘回归（MPLS）对多种光谱预处理方法进行了校准。木材的提取总酚含量的决定系数为 0.89，预测标准误差为 6.3mg/g。因此，近红外高光谱成像作为一种有吸引力的策略，可用于预测 0-65mg/g 范围内的提取总酚含量，这从葡萄酒行业中使用木材的质量保证角度来看具有重要意义。近红外高光谱成像作为一种有吸引力的策略，可以通过快速测定提取的生物活性分子（如多酚）来提高桶材副产物的价值。
