Literature DB >> 23923993

Particle size distribution of brown and white rice during gastric digestion measured by image analysis.

Gail M Bornhorst1, Kevin Kostlan, R Paul Singh.   

Abstract

The particle size distribution of foods during gastric digestion indicates the amount of physical breakdown that occurred due to the peristaltic movement of the stomach walls in addition to the breakdown that initially occurred during oral processing. The objective of this study was to present an image analysis technique that was rapid, simple, and could distinguish between food components (that is, rice kernel and bran layer in brown rice). The technique was used to quantify particle breakdown of brown and white rice during gastric digestion in growing pigs (used as a model for an adult human) over 480 min of digestion. The particle area distributions were fit to a Rosin-Rammler distribution function. Brown and white rice exhibited considerable breakdown as the number of particles per image decreased over time. The median particle area (x(50)) increased during digestion, suggesting a gastric sieving phenomenon, where small particles were emptied and larger particles were retained for additional breakdown. Brown rice breakdown was further quantified by an examination of the bran layer fragments and rice grain pieces. The percentage of total particle area composed of bran layer fragments was greater in the distal stomach than the proximal stomach in the first 120 min of digestion. The results of this study showed that image analysis may be used to quantify particle breakdown of a soft food product during gastric digestion, discriminate between different food components, and help to clarify the role of food structure and processing in food breakdown during gastric digestion.
© 2013 Institute of Food Technologists®

Entities:  

Keywords:  breakdown; gastric digestion; gastric sieving; image analysis; rice

Mesh:

Year:  2013        PMID: 23923993     DOI: 10.1111/1750-3841.12228

Source DB:  PubMed          Journal:  J Food Sci        ISSN: 0022-1147            Impact factor:   3.167


  2 in total

1.  Head rice rate measurement based on concave point matching.

Authors:  Yuan Yao; Wei Wu; Tianle Yang; Tao Liu; Wen Chen; Chen Chen; Rui Li; Tong Zhou; Chengming Sun; Yue Zhou; Xinlu Li
Journal:  Sci Rep       Date:  2017-01-27       Impact factor: 4.379

Review 2.  Rice as an alternative feed ingredient in swine diets.

Authors:  Sheena Kim; Jin Ho Cho; Hyeun Bum Kim; Minho Song
Journal:  J Anim Sci Technol       Date:  2021-05-31
  2 in total

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