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Artificial neuronal networks (ANN) to model the hydrolysis of goat milk protein by subtilisin and trypsin

Published online by Cambridge University Press:  29 August 2018

Francisco Javier Espejo-Carpio ,
Raúl Pérez-Gálvez ,
Antonio Guadix  and
Emilia María Guadix
Francisco Javier Espejo-Carpio
Affiliation:
Department of Chemical Engineering, University of Granada, 18071 Granada, Spain
Raúl Pérez-Gálvez*
Affiliation:
Department of Chemical Engineering, University of Granada, 18071 Granada, Spain
Antonio Guadix
Affiliation:
Department of Chemical Engineering, University of Granada, 18071 Granada, Spain
Emilia María Guadix
Affiliation:
Department of Chemical Engineering, University of Granada, 18071 Granada, Spain
*
*For correspondence; e-mail: [email protected]
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Abstract

The enzymatic hydrolysis of milk proteins yield final products with improved properties and reduced allergenicity. The degree of hydrolysis (DH) influences both technological (e.g., solubility, water binding capacity) and biological (e.g., angiotensin-converting enzyme (ACE) inhibition, antioxidation) properties of the resulting hydrolysate. Phenomenological models are unable to reproduce the complexity of enzymatic reactions in dairy systems. However, empirical approaches offer high predictability and can be easily transposed to different substrates and enzymes. In this work, the DH of goat milk protein by subtilisin and trypsin was modelled by feedforward artificial neural networks (ANN). To this end, we produced a set of protein hydrolysates, employing various reaction temperatures and enzyme/substrate ratios, based on an experimental design. The time evolution of the DH was monitored and processed to generate the ANN models. Extensive hydrolysis is desirable because a high DH enhances some bioactivities in the final hydrolysate, such as antioxidant or antihypertensive. The optimization of both ANN models led to a maximal DH of 23·47% at 56·4 °C and enzyme–substrate ratio of 5% for subtilisin, while hydrolysis with trypsin reached a maximum of 21·3% at 35 °C and an enzyme–substrate ratio of 4%.

Keywords

Enzymatic hydrolysisgoat milk hydrolysatesartificial neural networksproteases; optimization
Type
Research Article
Information
Journal of Dairy Research , Volume 85 , Issue 3 , August 2018 , pp. 339 - 346
Copyright
Copyright © Hannah Dairy Research Foundation 2018 

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