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A holistic high-throughput screening framework for biofuel feedstock assessment that characterises variations in soluble sugars and cell wall composition in Sorghum bicolor

dc.contributor.authorMartin, Antony P
dc.contributor.authorPalmer, William M
dc.contributor.authorByrt, Caitlin S.
dc.contributor.authorFurbank, Robert
dc.contributor.authorGrof, Christopher P. L.
dc.date.accessioned2018-11-29T22:55:57Z
dc.date.available2018-11-29T22:55:57Z
dc.date.issued2013
dc.date.updated2018-11-29T08:09:04Z
dc.description.abstractBackground: A major hindrance to the development of high yielding biofuel feedstocks is the ability to rapidly assess large populations for fermentable sugar yields. Whilst recent advances have outlined methods for the rapid assessment of biomass saccharification efficiency, none take into account the total biomass, or the soluble sugar fraction of the plant. Here we present a holistic high-throughput methodology for assessing sweet Sorghum bicolor feedstocks at 10 days post-anthesis for total fermentable sugar yields including stalk biomass, soluble sugar concentrations, and cell wall saccharification efficiency. Results: A mathematical method for assessing whole S. bicolor stalks using the fourth internode from the base of the plant proved to be an effective high-throughput strategy for assessing stalk biomass, soluble sugar concentrations, and cell wall composition and allowed calculation of total stalk fermentable sugars. A high-throughput method for measuring soluble sucrose, glucose, and fructose using partial least squares (PLS) modelling of juice Fourier transform infrared (FTIR) spectra was developed. The PLS prediction was shown to be highly accurate with each sugar attaining a coefficient of determination (R §ssup§ 2 §esup§) of 0.99 with a root mean squared error of prediction (RMSEP) of 11.93, 5.52, and 3.23 mM for sucrose, glucose, and fructose, respectively, which constitutes an error of <4% in each case. The sugar PLS model correlated well with gas chromatography-mass spectrometry (GC-MS) and brix measures. Similarly, a high-throughput method for predicting enzymatic cell wall digestibility using PLS modelling of FTIR spectra obtained from S. bicolor bagasse was developed. The PLS prediction was shown to be accurate with an R §ssup§ 2 §esup§ of 0.94 and RMSEP of 0.64 μg.mgDW§ssup§-1§esup§.h§ssup§- 1§esup§. Conclusions: This methodology has been demonstrated as an efficient and effective way to screen large biofuel feedstock populations for biomass, soluble sugar concentrations, and cell wall digestibility simultaneously allowing a total fermentable yield calculation. It unifies and simplifies previous screening methodologies to produce a holistic assessment of biofuel feedstock potential.
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn1754-6834
dc.identifier.urihttp://hdl.handle.net/1885/153340
dc.publisherBioMed Central Ltd.
dc.sourceBiotechnology for Biofuels
dc.subjectKeywords: Cell walls; Digestibility; FTIR; High-throughput; Pls modelling; Soluble sugars; Sorghum; Biofuels; Biomass; Cytology; Feedstocks; Forecasting; Fourier transform infrared spectroscopy; Fructose; Gas chromatography; Glucose; Least squares approximations; S Biofuel; Cell wall; Digestibility; FTIR; High-throughput; PLS modelling; Soluble sugar; Sorghum
dc.titleA holistic high-throughput screening framework for biofuel feedstock assessment that characterises variations in soluble sugars and cell wall composition in Sorghum bicolor
dc.typeJournal article
dcterms.accessRightsOpen Accessen_AU
local.bibliographicCitation.issue1
local.bibliographicCitation.lastpage186
local.bibliographicCitation.startpage186
local.contributor.affiliationMartin, Antony P, University of Newcastle
local.contributor.affiliationPalmer, William M , University of Newcastle
local.contributor.affiliationByrt, Caitlin S., University of Newcastle
local.contributor.affiliationFurbank, Robert, College of Science, ANU
local.contributor.affiliationGrof, Christopher P. L., University of Newcastle
local.contributor.authoruidFurbank, Robert, u1572217
local.description.notesImported from ARIES
local.identifier.absfor060705 - Plant Physiology
local.identifier.absseo970106 - Expanding Knowledge in the Biological Sciences
local.identifier.ariespublicationU3488905xPUB6177
local.identifier.citationvolume6
local.identifier.doi10.1186/1754-6834-6-186
local.identifier.scopusID2-s2.0-84890739863
local.identifier.thomsonID000329914300001
local.type.statusPublished Version

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