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Tytuł pozycji:

Biochemical methane potential prediction for mixed feedstocks of straw and manure in anaerobic co-digestion.

Tytuł :
Biochemical methane potential prediction for mixed feedstocks of straw and manure in anaerobic co-digestion.
Autorzy :
Yang G; Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences (CAS Key Laboratory of Renewable Energy), Guangzhou 510640, PR China.
Li Y; Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences (CAS Key Laboratory of Renewable Energy), Guangzhou 510640, PR China.
Zhen F; Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences (CAS Key Laboratory of Renewable Energy), Guangzhou 510640, PR China.
Xu Y; College of Electric and Information, Northeast Agricultural University, Harbin 150030, PR China.
Liu J; Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences (CAS Key Laboratory of Renewable Energy), Guangzhou 510640, PR China; College of Information and Electrical Engineering, Heilongjiang Bayi Agricultural University, Daqing, Heilongjiang 163319, PR China. Electronic address: .
Li N; Experimental Practice and Demonstration Centre, Northeast Agricultural University, Harbin 150030, PR China.
Sun Y; College of Engineering, Northeast Agricultural University, Harbin 150030, PR China.
Luo L; College of Engineering, Northeast Agricultural University, Harbin 150030, PR China.
Wang M; College of Engineering, Northeast Agricultural University, Harbin 150030, PR China.
Zhang L; College of Arts and Sciences, Northeast Agricultural University, Harbin 150030, PR China.
Pokaż więcej
Źródło :
Bioresource technology [Bioresour Technol] 2021 Apr; Vol. 326, pp. 124745. Date of Electronic Publication: 2021 Jan 20.
Typ publikacji :
Journal Article
Język :
English
Imprint Name(s) :
Original Publication: Barking, Essex, England : New York, N.Y. : Elsevier Applied Science ; Elsevier Science Pub. Co., 1991-
MeSH Terms :
Manure*
Methane*
Anaerobiosis ; Animals ; Biofuels ; Digestion
Contributed Indexing :
Keywords: Anaerobic co-digestion; Biochemical methane potential; Multivariate linear regression; Near-infrared spectroscopy; Partial least squares
Substance Nomenclature :
0 (Biofuels)
0 (Manure)
OP0UW79H66 (Methane)
Entry Date(s) :
Date Created: 20210128 Date Completed: 20210219 Latest Revision: 20210219
Update Code :
20210623
DOI :
10.1016/j.biortech.2021.124745
PMID :
33508641
Czasopismo naukowe
To rapidly estimate the biochemical methane potential (BMP) of feedstocks, different multivariate regression models were established between BMP and the physicochemical indexes or near-infrared spectroscopy (NIRS). Mixed fermentation feedstocks of corn stover and livestock manure were rapidly detected BMP in anaerobic co-digestion (co-AD). The results showed that the predicted accuracy of NIRS model based on characteristic wavelengths selected by multiple competitive adaptive reweighted sampling outperformed all regression models based on the physicochemical indexes. For the NIRS regression model, coefficient of determination, root mean squares error, relative root mean squares error, mean relative error and residual predictive deviation of the validation set were 0.982, 6.599, 2.713%, 2.333% and 7.605. The results reveal that the predicted accuracy of NIRS model is very high, and meet the requirements of rapid prediction of BMP for co-AD feedstocks in practical biogas engineering.
(Copyright © 2021 Elsevier Ltd. All rights reserved.)

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