Microwave-assisted chemical pre-treatment of waste sorghum leaves: Process optimization and development of an intelligent model for determination of volatile compound fractions.
This study reports the profiling of volatile compounds generated during microwave-assisted chemical pre-treatment of sorghum leaves. Compounds including acetic acid (0-186.26ng/g SL), furfural (0-240.80ng/g SL), 5-hydroxymethylfurfural (HMF) (0-19.20ng/g SL) and phenol (0-7.76ng/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.
School of Life Sciences, University of KwaZulu-Natal, Pietermaritzburg, South Africa.
Daneal C S
DCS
Rorke
School of Life Sciences, University of KwaZulu-Natal, Pietermaritzburg, South Africa.
Terence N
TN
Suinyuy
School of Life Sciences, University of KwaZulu-Natal, Pietermaritzburg, South Africa. Electronic address: kanag@ukzn.ac.za.
E B
EB
Gueguim Kana
D019342:Acetic Acid / Q000032:analysis; D005662:Furaldehyde / Q000031:analogs & derivatives / Q000032:analysis; D006851:Hydrochloric Acid / Q000737:chemistry; D008872:Microwaves; D008962:Models, Theoretical; D009005:Monosaccharides / Q000378:metabolism; D016571:Neural Networks, Computer; D010636:Phenols / Q000737:chemistry; D018515:Plant Leaves / Q000737:chemistry* / Q000378:metabolism; D045868:Sorghum / Q000737:chemistry* / Q000378:metabolism; D055549:Volatile Organic Compounds / Q000032:analysis* / Q000737:chemistry; D018505:Waste Management / Q000379:methods; D014866:Waste Products / Q000032:analysis*
D009005:Monosaccharides; D010636:Phenols; D055549:Volatile Organic Compounds; D014866:Waste Products; C008046:5-hydroxymethylfurfural; D005662:Furaldehyde; D019342:Acetic Acid; D006851:Hydrochloric Acid
Artificial Neural Networks; Fermentation Inhibitors; Lignocellulosic pre-treatment; Sorghum leaves