Publication: Prediction Models for Textural Properties of Puffed Rice Starch Product by Relative Crystallinity
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Issued Date
2016
Resource Type
File Type
application/pdf
ISSN
1469428
Other identifier(s)
2-s2.0-84989838518
Rights Holder(s)
Scopus
Bibliographic Citation
Journal of Food Quality. Vol 39, No.5 (2016), p.445-455
Suggested Citation
Jiamjariyatam R., Kongpensook V., Pradipasena P. Prediction Models for Textural Properties of Puffed Rice Starch Product by Relative Crystallinity. Journal of Food Quality. Vol 39, No.5 (2016), p.445-455. doi:10.1111/jfq.12218 Retrieved from: https://hdl.handle.net/20.500.14740/5138
Author(s)
Abstract
This research aimed to determine the textural attributes of fried puffed rice starch products by the relative crystallinity (RC) of pellets (RCp). Three factors, amylose content (AC), aging time and cooling rate were varied to obtain various levels of RCp. The different textural characteristics of the puffed rice products were evaluated by instrumental and descriptive sensory analysis. The higher AC and longer aging time resulted in higher RCp. Pellets with higher RCp had smaller and denser air cell structures and lower expansion, resulting in higher crispness, hardness and fracturability. High correlation between the RCp and the instrumental and the sensory texture characteristics were determined and regression models (with R2 > 0.80) were established. These models can be used to predict some properties of puffed products, such as crispness, hardness, and brittleness. Panelists rated samples with an AC of 9% (in a range of 2.8–3.7% RCp) highest in appearance and texture scores. Practical Applications: The RCp and textural properties of puffed products can be affected by many factors including ingredients and process parameters. This study provides a better understanding of both the textural characteristics of puffed rice starch products using sensory and instrumental approaches, but also their correlations. The relationship between the RCp and sensory evaluation data can be applied for the prediction of puffing quality. © 2016 Wiley Periodicals, Inc.