Multivariate model to characterise relations between maize mutant starches and hydrolysis kinetics
Kamal Kansou1, Alain Buléon1, Catherine Gérard2
1INRA - Biopolymères Interactions Assemblages (UR1268), F-44300 Nantes, France.
Carbohydrate Polymers
|September 8, 2015
Summary
Multivariate analysis of maize starch (Zea mays) amylolysis reveals amylose content significantly impacts hydrolysis rate retardation. Understanding starch structure is key to predicting enzyme kinetics.
Area of Science:
- Biochemistry
- Food Science
- Enzymology
Background:
- Starch physico-chemical properties influence amylolysis, but complex granular structure hinders result interpretation.
- Multivariate statistical analysis offers a way to analyze interrelated factors in starch amylolysis.
Purpose of the Study:
- To apply multivariate statistical analysis to understand the relationship between maize starch properties and amylolysis kinetics.
- To identify key starch structural factors influencing porcine pancreatic alpha-amylase (PPA) activity.
Main Methods:
- Amylolysis progress curves of 13 maize starch samples (wild type and mutants) were fitted using a Weibull function.
- Kinetic parameters (k, h, X∞) were extracted and related to macromolecular composition and crystalline polymorphic types via multivariate models.
Main Results:
- Hydrolysis rate retardation (h) and final hydrolysis extent (X∞) were strongly correlated with measured starch properties.
- Amylose content showed a significant correlation with hydrolysis rate retardation (h).
- Multivariate models predicted h and X∞ well, but a portion of the variability in the initial reaction rate (k) remained unexplained.
Conclusions:
- Amylose content plays a significant role in modulating the rate of starch hydrolysis by PPA.
- Further detailed characterization of starch granule structure is needed to explain remaining variability in amylolysis kinetics, particularly for the initial reaction rate (k).
