کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
7079086 1459989 2014 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Statistical prediction of biomethane potentials based on the composition of lignocellulosic biomass
ترجمه فارسی عنوان
پیش بینی آماری پتانسیل های بیومتون بر اساس ترکیب زیست توده لیگنوسلولوزیک
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی تکنولوژی و شیمی فرآیندی
چکیده انگلیسی
Mixture models are introduced as a new and stronger methodology for statistical prediction of biomethane potentials (BPM) from lignocellulosic biomass compared to the linear regression models previously used. A large dataset from literature combined with our own data were analysed using canonical linear and quadratic mixture models. The full model to predict BMP (R2 > 0.96), including the four biomass components cellulose (xC), hemicellulose (xH), lignin (xL) and residuals (xR = 1 − xC − xH − xL) had highly significant regression coefficients. It was possible to reduce the model without substantially affecting the quality of the prediction, as the regression coefficients for xC, xH and xR were not significantly different based on the dataset. The model was extended with an effect of different methods of analysing the biomass constituents content (DA) which had a significant impact. In conclusion, the best prediction of BMP is pBMP = 347xC+H+R − 438xL + 63DA.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Bioresource Technology - Volume 154, February 2014, Pages 80-86
نویسندگان
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