Literature DB >> 18028696

Near-infrared analysis of ground barley for use as a feedstock for fuel ethanol production.

Miryeong Sohn1, David S Himmelsbach, Franklin E Barton, Carl A Griffey, Wynse Brooks, Kevin B Hicks.   

Abstract

The objective of this study was to explore the potential of near-infrared spectroscopy for determining the compositional quality properties of barley as a feedstock for fuel ethanol production and to compare the prediction accuracy between calibration models obtained using a Fourier transform near-infrared system (FT-NIR) and a dispersive near-infrared system. The total sample set contained 206 samples of three types of barley, hull-less, malt, and hulled varieties, which were grown at various locations in the eastern U.S. from 2002 to 2005 years. A new hull-less barley variety, Doyce, which was specially bred for potential use in ethanol production, was included in the sample set. One hundred and thirty-eight barley samples were used for calibration and sixty-eight were used for validation. Ground barley samples were scanned on both a FTNIR spectrometer (10 000 to 4000 cm(-1) at 4 cm(-1) resolution) and a dispersive NIR spectrometer (400 to 2498 nm at 10 nm resolution), respectively. Six grain components, moisture, starch, beta-glucan, protein, oil, and ash content, were analyzed as parameters of barley quality. Principal component analysis showed that barley samples could be classified by their types: hull-less, malt, and hulled. Partial least squares regression indicated that both FT-NIR and dispersive NIR spectroscopy have the potential to determine quality properties of barley with an acceptable accuracy, except for beta-glucan content. There was no predictive advantage in using a high-resolution FT-NIR instrument over a dispersive system for most components of barley.

Entities:  

Year:  2007        PMID: 18028696     DOI: 10.1366/000370207782597148

Source DB:  PubMed          Journal:  Appl Spectrosc        ISSN: 0003-7028            Impact factor:   2.388


  2 in total

1.  FT-NIR: a tool for rapid intracellular lipid quantification in oleaginous yeasts.

Authors:  Mikołaj Chmielarz; Sabine Sampels; Johanna Blomqvist; Jule Brandenburg; Frida Wende; Mats Sandgren; Volkmar Passoth
Journal:  Biotechnol Biofuels       Date:  2019-06-29       Impact factor: 6.040

2.  Indirect Measurement of β-Glucan Content in Barley Grain with Near-Infrared Reflectance Spectroscopy.

Authors:  Roberta Ghizzoni; Caterina Morcia; Valeria Terzi; Alberto Gianinetti; Marina Baronchelli
Journal:  Foods       Date:  2022-06-23
  2 in total

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