Forage quality and composition measurements as predictors of ethanol yield from maize (Zea mays L.) stover

Aaron J. Lorenz, Rob P. Anex, Asli Isci, James G. Coors, Natalia de Leon, Paul J. Weimer

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60 Scopus citations


Background: Improvement of biofeedstock quality for cellulosic ethanol production will be facilitated by inexpensive and rapid methods of evaluation, such as those already employed in the field of ruminant nutrition. Our objective was to evaluate whether forage quality and compositional measurements could be used to estimate ethanol yield of maize stover as measured by a simplified pretreatment and simultaneous saccharification and fermentation assay. Twelve maize varieties selected to be diverse for stover digestibility and composition were evaluated. Results: Variation in ethanol yield was driven by glucan convertibility rather than by glucan content. Convertibility was highly correlated with ruminal digestibility and lignin content. There was no relationship between structural carbohydrate content (glucan and neutral detergent fiber) and ethanol yield. However, when these variables were included in multiple regression equations including convertibility or neutral detergent fiber digestibility, their partial regression coefficients were significant and positive. A regression model including both neutral detergent fiber and its ruminal digestibility explained 95% of the variation in ethanol yield. Conclusion: Forage quality and composition measurements may be used to predict cellulosic ethanol yield to guide biofeedstock improvement through agronomic research and plant breeding.

Original languageEnglish (US)
Article number5
JournalBiotechnology for Biofuels
StatePublished - Mar 9 2009

Bibliographical note

Funding Information:
We thank Dr. Edward Wolfrum, Dr. Bonnie Hames, and Amie Sluiter (National Bioenergy Center at NREL) for providing NIRS predictions for glucan and lignin concentration. This work was supported by the USDA and DOE grant Integrated Feedstock Supply Systems for Corn Stover Biomass (grant no. 144-144NR81).


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