Enzymatic keratin hydrolysis: Dynamic modelling, parameter estimation and validation

Alistair Rodman, Dimitrios Gerogiorgis

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

Abstract / Description of output

Keratin rich waste material is an abundant by-product from the agroindustry, particularly the meat and poultry industries: skin remains, bristle, animal hair, horns and hooves, feathers, etc. This waste may not be incinerated due to environmental concerns, so producers seek waste valorization by upcycling this non-biodegradable by-product by depolymerization to extract soluble proteins, which can be used as animal feed supplements. This can be performed thermally, however high temperature processing destroys amino acids which are necessary in the product and are costly to later supplement. A novel two-stage enzymatic de-polymerization process for keratin is being investigated. The first stage involves growing the microbial keratinases on a substrate sample, and is optimized for maximal enzyme production. The second stage uses the keratinases in a bioreactor optimized for substrate hydrolysis. The enzymatic hydrolysis mechanism for keratin is not well documented rendering current the current industrial application limited. This paper presents lab scale experimental results from the second (hydrolysis) stage using a keratinolytic enzymatic cocktail with the filamentous bacterium Amycolatopsis keratiniphila D2 (DSM 44409). Dynamic state data for the product (protein) and substrate (keratin) concentrations following varying substrate loading has been used to construct the first reduced order model for the enzymatic hydrolysis of waste keratin. Potential model applications include to dynamically optimize this second process stage by computing optimal dosage strategies (keratin deposit intervals and volume) to minimize processing time and cost to dispose or repurpose the biochemical waste.
Original languageEnglish
Title of host publication28th European Symposium on Computer Aided Process Engineering
EditorsAnton Friedl, Jiri Klemeš, Stefan Radl, Petar Varbanov, Thomas Wallek
Place of PublicationAmsterdam
PublisherElsevier B.V.
Number of pages6
Publication statusPublished - 11 Jun 2018

Publication series

NameComputer-Aided Chemical Engineering


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