Modeling of Enzymatic Hydrolysis of Whey Proteins
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  • 作者:Gabriela Mart铆nez-Araiza (1)
    Eduardo Casta帽o-Tostado (1) ecastano@uaq.mx
    Silvia L. Amaya-Llano (1)
    Carlos Regalado-Gonzlez (1)
    Carlos Mart铆nez-Vera (2)
    Lech Ozimek (3)
  • 关键词:Hydrolysis modeling – ; Whey protein – ; Inverse modeling
  • 刊名:Food and Bioprocess Technology
  • 出版年:2012
  • 出版时间:August 2012
  • 年:2012
  • 卷:5
  • 期:6
  • 页码:2596-2601
  • 全文大小:278.4 KB
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  • 作者单位:1. Programa de Posgrado en Alimentos del Centro de la Rep煤blica (PROPAC), Universidad Aut贸noma de Quer茅taro, Apdo 184, Quer茅taro, Quer茅taro 76010, Mexico2. Departamento de Ingeniera de Procesos e Hidrulica, Universidad Aut贸noma Metropolitana鈥揑ztapalapa, San Rafael Atlixco No. 186 Col. Vicentina, Iztapalapa, M茅xico, Federal District 09340, Mexico3. Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada T6G 2P5
  • ISSN:1935-5149
文摘
The aim of this work was to emphasize the limitations of modeling complex phenomena under unrealistic model assumptions. As a case study, the whey protein hydrolysis mechanism was modeled. A stirred batch reactor was used to study the degree of hydrolysis of sweet whey protein concentrate by using the protease alcalase. A completely random two-factorial experimental design was used, three levels of initial enzyme concentrations (E 0) (1.58, 3.18, 6.36 AU (Anson units)/L) times three levels of initial substrate concentrations (S 0) (18.73, 38.45, 81.16 g/L). All treatments were carried out at optimal alcalase—activity conditions: pH 8 and 50 掳C. Reactions were monitored for 180 min. The degree of hydrolysis (h) curves was finally adjusted for each treatment to the exponential model \frac\textdh\textdt = a ·exp( - b ·h ) \frac{{{\text{d}}h}}{{{\text{d}}t}} = a \cdot \exp \left( { - b \cdot h} \right) using nonlinear regression techniques but not assuming a Michaelis–Menten relationship. From the estimation process, the coefficient b was constant (27.26201;卤201;1.37) and independent of E 0 and S 0, while coefficient a depended directly on the ratio E 0/S 0, ranging from 0.0017 to 0.0497. A noncritical strategy of forward modeling based on unrealistic assumptions was misleading in the face of complex phenomena; instead, a modeling strategy moving from data to the identification and estimation of parameters of practical interest must be considered.

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