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优化第二代生物乙醇用——近红外光谱(NIRS)可行性研究,对小麦秸秆成分的电厂摄入量进行量化。

Power plant intake quantification of wheat straw composition for 2nd generation bioethanol optimization--a Near Infrared Spectroscopy (NIRS) feasibility study.

机构信息

Applied Chemometrics, Analytical Chemistry, Acoustic Chemometrics, Applied Biotechnology, Bioenergy and Sampling Research Group, Aalborg University, Niels Bohrs Vej 8, DK-6700 Esbjerg, Denmark.

出版信息

Bioresour Technol. 2010 Feb;101(4):1199-205. doi: 10.1016/j.biortech.2009.09.027. Epub 2009 Oct 17.

Abstract

Optimization of 2nd generation bioethanol production from wheat straw requires comprehensive knowledge of plant intake feedstock composition. Near Infrared Spectroscopy is evaluated as a potential method for instantaneous quantification of the salient fermentation wheat straw components: cellulose (glucan), hemicelluloses (xylan, arabinan), and lignin. Aiming at chemometric multivariate calibration, 44 pre-selected samples were subjected to spectroscopy and reference analysis. For glucan and xylan prediction accuracies (slope: 0.89, 0.94) and precisions (r(2): 0.87) were obtained, corresponding to error of prediction levels at 8-9%. Models for arabinan and lignin were marginally less good, and especially for lignin a further expansion of the feasibility dataset was deemed necessary. The results are related to significant influences from sub-sampling/mass reduction errors in the laboratory regimen. A relative high proportion of outliers excluded from the present models (10-20%) may indicate that comminution sample preparation is most likely always needed. Different solutions to these issues are suggested.

摘要

优化第二代生物乙醇从小麦秸秆生产需要全面了解植物摄入饲料的组成。近红外光谱被评估为一种潜在的方法,用于即时定量的突出发酵小麦秸秆成分:纤维素(葡聚糖),半纤维素(木聚糖,阿拉伯聚糖)和木质素。针对化学计量多元校准,44 个预选定的样品进行了光谱和参考分析。对于葡聚糖和木聚糖预测精度(斜率:0.89,0.94)和精度(r(2):0.87),对应于预测水平的误差在 8-9%。阿拉伯聚糖和木质素模型略差,特别是木质素,需要进一步扩展可行性数据集。结果与实验室方案中的分样/质量减少误差的显著影响有关。从目前的模型中排除的异常值的相对较高比例(10-20%)可能表明,粉碎样品制备可能总是需要的。对这些问题提出了不同的解决方案。

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