Article ID Journal Published Year Pages File Type
4997881 Bioresource Technology 2017 43 Pages PDF
Abstract
This study reports the profiling of volatile compounds generated during microwave-assisted chemical pre-treatment of sorghum leaves. Compounds including acetic acid (0-186.26 ng/g SL), furfural (0-240.80 ng/g SL), 5-hydroxymethylfurfural (HMF) (0-19.20 ng/g SL) and phenol (0-7.76 ng/g SL) were detected. The reducing sugar production was optimized. An intelligent model based on Artificial Neural Networks (ANNs) was developed and validated to predict a profile of 21 volatile compounds under novel pre-treatment conditions. This model gave R2-values of up to 0.93. Knowledge extraction revealed furfural and phenol exhibited high sensitivity to acid- and alkali concentration and S:L ratio, while phenol showed high sensitivity to microwave duration and intensity. Furthermore, furfural production was majorly dependent on acid concentration and fit a dosage-response relationship model with a 2.5% HCl threshold. Significant non-linearities were observed between pre-treatment conditions and the profile of various compounds. This tool reduces analytical costs through virtual analytical instrumentation, improving process economics.
Related Topics
Physical Sciences and Engineering Chemical Engineering Process Chemistry and Technology
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