Characterization of mechanical texture attributes of cooked milled rice by texture profile analyses and unraveling viscoelasticity properties through rheometry

Rosa Paula O. Cuevas, Pawan S. Takhar, Nese Sreenivasulu

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The mechanical attributes of cooked rice grains reflected by textural characteristics capture consumers preferences. Two of these attributes such as hardness and stickiness are typically indicated in grain quality evaluation programs by the amylose content of rice. However, the association of amylose content with two other textural attributes such as cohesiveness and springiness remains unknown. Hence, texture profile analyses play a role in quantifying these mechanical parameters of texture. Rheometry on the other hand can be utilized to characterize both viscous and elastic properties of rice during cooking in a water-rice proportion closer to what consumers typically use for cooking. In this chapter, methods for texture profiling and rheometry are presented to capture inferences on cooking quality modeling. Data extracted from rice texture and viscoelastic properties that go beyond what amylose content can predict, has been deciphered through mathematical modeling, which can help predict cooking quality of new rice breeding lines to improve textural and cooking quality specifications.

Original languageEnglish (US)
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Pages151-167
Number of pages17
DOIs
StatePublished - 2019

Publication series

NameMethods in Molecular Biology
Volume1892
ISSN (Print)1064-3745

Keywords

  • Rheometry
  • Rice
  • Texture
  • Texture profile analyses
  • Viscoelastic properties

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics

Fingerprint

Dive into the research topics of 'Characterization of mechanical texture attributes of cooked milled rice by texture profile analyses and unraveling viscoelasticity properties through rheometry'. Together they form a unique fingerprint.

Cite this