Abstract
The objective of this work was to modify extrusion parameters to yield greater resistant starch (RS) in a kibble and create a model to predict its concentration. A dog food was extruded through a small-scale twin-screw extruder as a central composite design with 6 central points (replicates) and 14 single replicates. There were three factors tested at three levels: corn particle size, extruder shaft speed, and in-barrel moisture (IBM). The remaining processing inputs were kept constant. Chemical and physical starch analyses were performed. A model to predict RS was created using the REG procedure from SAS. Pearson correlations between extrusion parameters and starch analyses were conducted. A model to predict RS was created (R2adj= 0.834; P < .0001). Both SME and extrudate temperature had a high negative correlation with RS and RVA raw starch. Results suggest that low mechanical energy and high IBM increase kibble RS.
Competing Interest Statement
The authors have declared no competing interest.
Abbreviations
- PC
- extruder preconditioner
- RS
- resistant starch
- RVA
- rapid visco analyzer
- SCFA
- short-chain fatty acids
- PS
- particle size
- OE
- off the extruder
- OD
- off the drier
- IBM
- in-barrel moisture
- SME
- specific mechanical energy
- SEI
- sectional expansion index
- VEI
- volumetric expansion index
- LEI
- longitudinal expansion index
- SS
- extruder shaft speed.