title: Power plant intake quantification of wheat straw composition for 2nd generation bioethanol optimization--a Near Infrared Spectroscopy (NIRS) feasibility study.
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.
authors.affiliation: Applied Chemometrics, Analytical Chemistry, Acoustic Chemometrics, Applied Biotechnology, Bioenergy and Sampling Research Group, Aalborg University, Niels Bohrs Vej 8, DK-6700 Esbjerg, Denmark. cjlomborg@yahoo.dk
authors.forename: Carina J
authors.initials: CJ
authors.lastname: Lomborg
authors.forename: Mette H
authors.initials: MH
authors.lastname: Thomsen
authors.forename: Erik Steen
authors.initials: ES
authors.lastname: Jensen
authors.forename: Kim H
authors.initials: KH
authors.lastname: Esbensen
mesh_terms: D056804:Biofuels / Q000032:analysis*; D002138:Calibration; D000431:Ethanol / Q000138:chemical synthesis*; D005240:Feasibility Studies; D016018:Least-Squares Analysis; D008031:Lignin / Q000032:analysis; D008956:Models, Chemical; D015999:Multivariate Analysis; D009862:Online Systems; D052638:Particulate Matter / Q000032:analysis; D011134:Polysaccharides / Q000032:analysis; D011210:Power Plants / Q000295:instrumentation*; D015203:Reproducibility of Results; D019265:Spectroscopy, Near-Infrared / Q000295:instrumentation* / Q000379:methods*; D014908:Triticum / Q000737:chemistry*; D014990:Xylans / Q000032:analysis
chemical_list: D056804:Biofuels; D052638:Particulate Matter; D011134:Polysaccharides; D014990:Xylans; C030080:araban; D000431:Ethanol; D008031:Lignin