|Sohn, Mi Ryeong|
|Barton Ii, Franklin|
|Griffey, Carl - USDA|
|Brooks, Wynse - USDA|
Submitted to: Applied Spectroscopy
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: January 17, 2008
Publication Date: April 1, 2008
Citation: Sohn, M., Himmelsbach, D.S., Barton Ii, F.E., Griffey, C.A., Brooks, W., Hicks, K.B. 2008. Near-infrared analysis of whole kernel barley: comparison of three spectrometers. Applied Spectroscopy. 62(4). p. 427-432 2008. Interpretive Summary: Recently there has been growing interest in using barley as a feedstock for fuel ethanol production. Rapid determination of components in barley is important to estimate ethanol yield or to evaluate co-product quality. In the previous study, we investigated the potential of near-infrared spectroscopy for assessment of barley quality using ground material and most of the components have been measured successfully with an acceptable accuracy for screening or classification of barley. Being able to predict the component composition of barley as whole kernel, avoiding a grinding and any wet chemistry is the most important use for near-infrared spectroscopy as a rapid assessment tool of barley for ethanol production. The current study was conducted to develop calibration models for determining barley quality using whole kernel material. To find the best calibration model, three near-infrared instruments with different resolutions were used and the results were compared. The accuracy of the calibration models on whole kernel barley was comparable to the models on ground barley and were successful. The models should be useful to estimate ethanol yield or to evaluate co-product quality from the whole kernel barley prior to ethanol production. The research result will give an interest to a broad audience who work in the field of bio-fuel production and work in the field of algorithm development using spectroscopic data.
Technical Abstract: This study has been conducted to develop calibration models for determining quality parameters of whole kernel barley using a rapid and non-destructive near-infrared (NIR) spectroscopic method. Two hundred five samples of whole barley grains of three winter-habit types (hulled, malt and hull-less) produced over three growing seasons and from various locations in the United States were used in this study. Among these samples, 137 were used for calibration and 68 for validation. Three NIR instruments with different resolutions, one Fourier-transform instrument (4 cm-1 resolution) and two dispersive instruments (8 nm and 10 nm bandpass) were utilized to develop calibration models for six components (moisture, starch, '-glucan, protein, oil and ash) and the results were compared. Partial least squares regression was used to build models, and various methods for preprocessing of spectral data were used to find the best model. Our results reveal that the coefficient of determination for calibration models (NIR predicted versus reference values) ranged from 0.96 for moisture to 0.79 for '-glucan. The level of precision of the model developed for each component was sufficient for screening or classification of whole kernel barley, except for '-glucan. The higher-resolution Fourier-transform instrument gave better results than the lower-resolution instrument for starch and '-glucan analysis. The starch model was most improved by the increased resolution. There was no advantage of using a higher-resolution instrument over a lower-resolution instrument for other components. Most of the components were best predicted using 1st derivative processing, except for '-glucan, where 2nd derivative processing was more informative and precise.