Departament of Chemistry, Universidade Federal de Viçosa, 36570-900 Viçosa, Minas Gerais, Brazil.
Departament of Plant Science, Universidade Federal de Viçosa, 36570-900 Viçosa, Minas Gerais, Brazil.
Carbohydr Polym. 2017 Feb 20;158:20-28. doi: 10.1016/j.carbpol.2016.12.005. Epub 2016 Dec 5.
A method for estimation of sugarcane (Saccharum spp.) biomass crystallinity using near infrared spectroscopy (NIR) and partial least squares regression (PLS) as an alternative to the standard method using X-ray diffractometry (XRD) is proposed. Crystallinity was obtained using XRD from sugarcane bagasse. NIR spectra were obtained of the same material. PLS models were built using the NIR and crystallinity values. Cellulose crystallinity ranged from 50 to 81%. Two variable selection algorithms were applied to improve the predictive ability of models, i.e. (a) Ordered Predictors Selection (OPS) and (b) Genetic Algorithm. The best model, obtained with the OPS algorithm, presented values of correlation coefficient of prediction, root mean squared error of prediction and ratio of performance deviation equals to 0.92, 3.01 and 1.71, respectively. A scatter matrix among lignin, α-cellulose, hemicellulose, ash and crystallinity was built that showed that there was no correlation among these properties for the samples studied.
提出了一种使用近红外光谱（NIR）和偏最小二乘法回归（PLS）估算甘蔗（Saccharum spp.）生物质结晶度的方法，以替代使用 X 射线衍射法（XRD）的标准方法。结晶度是从甘蔗渣的 XRD 获得的。对相同的材料进行了 NIR 光谱测量。使用 NIR 和结晶度值建立了 PLS 模型。纤维素结晶度范围为 50-81%。应用了两种变量选择算法来提高模型的预测能力，即（a）有序预测器选择（OPS）和（b）遗传算法。使用 OPS 算法获得的最佳模型，预测值的相关系数、预测均方根误差和性能偏差比分别为 0.92、3.01 和 1.71。建立了木质素、α-纤维素、半纤维素、灰分和结晶度之间的散射矩阵，表明研究样本中这些性质之间没有相关性。
