Syngenta Seeds S.A., Barcelona 08006, Spain.
Bioresour Technol. 2011 Oct;102(20):9542-9. doi: 10.1016/j.biortech.2011.07.045. Epub 2011 Aug 4.
Sugar beets are a raw material for the production of sugar and ethanol. The decision on which end product to pursue could be facilitated by fast and reliable means of predicting the potential ethanol yield from the beets. A Near Infrared (NIR) Spectroscopy-based approach was tested for the direct prediction of the potential bioethanol production from sugar beets. A modified partial least squares (MPLS) regression model was applied to 125 samples, ranging from 21.9 to 31.0 gL(-1) of bioethanol in sugar beet brei. The samples were analyzed in reflectance mode in a Direct Contact Food Analyser (DCFA) FOSS-NIRSystems 6500 monochromator, with standard error of cross validation (SECV), standard error of prediction (SEP), coefficient of determination (r(2)) and coefficient of variation (CV) of 0.51, 0.49, 0.91 and 1.9 gL(-1), respectively. The NIR technique allowed direct prediction of the ethanol yield from sugar beet brei (i.e. the product obtained after sawing beets with a proper machine) in less than 3 min.
甜菜是生产糖和乙醇的原料。通过快速可靠的方法预测甜菜的潜在乙醇产量，可以促进对最终产品的选择。本研究采用基于近红外（NIR）光谱的方法直接预测从甜菜中提取潜在生物乙醇的产量。将改良的偏最小二乘法（MPLS）回归模型应用于 125 个样本，这些样本的生物乙醇浓度在 21.9 到 31.0 g/L 之间，是从甜菜浆中提取的。使用 DCFA FOSS-NIRSystems 6500 单色仪以反射模式进行分析，交叉验证标准误差（SECV）、预测标准误差（SEP）、决定系数（r(2)）和变异系数（CV）分别为 0.51、0.49、0.91 和 1.9 g/L。NIR 技术允许在不到 3 分钟的时间内直接预测从甜菜浆中提取乙醇的产量（即用适当的机器切割甜菜后得到的产物）。
