Chemometric modeling of thermogravimetric data for the compositional analysis of forest biomass.

The objective of this study was to investigated the use of chemometric modeling of thermogravimetric (TG) data as an alternative approach to estimate the chemical and proximate (i.e. volatile matter, fixed carbon and ash contents) composition of lignocellulosic biomass. Since these properties affect...

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Main Authors: Gifty E Acquah, Brian K Via, Oladiran O Fasina, Sushil Adhikari, Nedret Billor, Lori G Eckhardt
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2017-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC5333859?pdf=render
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spelling doaj-cc4c216d59074a16891fd63176fd809d2020-11-25T01:30:48ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01123e017299910.1371/journal.pone.0172999Chemometric modeling of thermogravimetric data for the compositional analysis of forest biomass.Gifty E AcquahBrian K ViaOladiran O FasinaSushil AdhikariNedret BillorLori G EckhardtThe objective of this study was to investigated the use of chemometric modeling of thermogravimetric (TG) data as an alternative approach to estimate the chemical and proximate (i.e. volatile matter, fixed carbon and ash contents) composition of lignocellulosic biomass. Since these properties affect the conversion pathway, processing costs, yield and / or quality of products, a capability to rapidly determine these for biomass feedstock entering the process stream will be useful in the success and efficiency of bioconversion technologies. The 38-minute long methodology developed in this study enabled the simultaneous prediction of both the chemical and proximate properties of forest-derived biomass from the same TG data. Conventionally, two separate experiments had to be conducted to obtain such information. In addition, the chemometric models constructed with normalized TG data outperformed models developed via the traditional deconvolution of TG data. PLS and PCR models were especially robust in predicting the volatile matter (R2-0.92; RPD- 3.58) and lignin (R2-0.82; RPD- 2.40) contents of the biomass. The application of chemometrics to TG data also made it possible to predict some monomeric sugars in this study. Elucidation of PC loadings obtained from chemometric models also provided some insights into the thermal decomposition behavior of the chemical constituents of lignocellulosic biomass. For instance, similar loadings were noted for volatile matter and cellulose, and for fixed carbon and lignin. The findings indicate that common latent variables are shared between these chemical and thermal reactivity properties. Results from this study buttresses literature that have reported that the less thermally stable polysaccharides are responsible for the yield of volatiles whereas the more recalcitrant lignin with its higher percentage of elementary carbon contributes to the yield of fixed carbon.http://europepmc.org/articles/PMC5333859?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Gifty E Acquah
Brian K Via
Oladiran O Fasina
Sushil Adhikari
Nedret Billor
Lori G Eckhardt
spellingShingle Gifty E Acquah
Brian K Via
Oladiran O Fasina
Sushil Adhikari
Nedret Billor
Lori G Eckhardt
Chemometric modeling of thermogravimetric data for the compositional analysis of forest biomass.
PLoS ONE
author_facet Gifty E Acquah
Brian K Via
Oladiran O Fasina
Sushil Adhikari
Nedret Billor
Lori G Eckhardt
author_sort Gifty E Acquah
title Chemometric modeling of thermogravimetric data for the compositional analysis of forest biomass.
title_short Chemometric modeling of thermogravimetric data for the compositional analysis of forest biomass.
title_full Chemometric modeling of thermogravimetric data for the compositional analysis of forest biomass.
title_fullStr Chemometric modeling of thermogravimetric data for the compositional analysis of forest biomass.
title_full_unstemmed Chemometric modeling of thermogravimetric data for the compositional analysis of forest biomass.
title_sort chemometric modeling of thermogravimetric data for the compositional analysis of forest biomass.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2017-01-01
description The objective of this study was to investigated the use of chemometric modeling of thermogravimetric (TG) data as an alternative approach to estimate the chemical and proximate (i.e. volatile matter, fixed carbon and ash contents) composition of lignocellulosic biomass. Since these properties affect the conversion pathway, processing costs, yield and / or quality of products, a capability to rapidly determine these for biomass feedstock entering the process stream will be useful in the success and efficiency of bioconversion technologies. The 38-minute long methodology developed in this study enabled the simultaneous prediction of both the chemical and proximate properties of forest-derived biomass from the same TG data. Conventionally, two separate experiments had to be conducted to obtain such information. In addition, the chemometric models constructed with normalized TG data outperformed models developed via the traditional deconvolution of TG data. PLS and PCR models were especially robust in predicting the volatile matter (R2-0.92; RPD- 3.58) and lignin (R2-0.82; RPD- 2.40) contents of the biomass. The application of chemometrics to TG data also made it possible to predict some monomeric sugars in this study. Elucidation of PC loadings obtained from chemometric models also provided some insights into the thermal decomposition behavior of the chemical constituents of lignocellulosic biomass. For instance, similar loadings were noted for volatile matter and cellulose, and for fixed carbon and lignin. The findings indicate that common latent variables are shared between these chemical and thermal reactivity properties. Results from this study buttresses literature that have reported that the less thermally stable polysaccharides are responsible for the yield of volatiles whereas the more recalcitrant lignin with its higher percentage of elementary carbon contributes to the yield of fixed carbon.
url http://europepmc.org/articles/PMC5333859?pdf=render
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