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bioRxiv · 10.1101/2021.10.22.465457

A model that predicts resistant starch in a dog kibble using a small-scale twin-screw extruder

Corsato Alvarenga, I.·Keller, L. C.·Waldy, C.·Aldrich, C. G.
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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.

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Corsato Alvarenga, I., Keller, L. C., Waldy, C., Aldrich, C. G.. 2021-10-22. A model that predicts resistant starch in a dog kibble using a small-scale twin-screw extruder. https://doi.org/10.1101/2021.10.22.465457

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