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ARS Home » Pacific West Area » Albany, California » Western Regional Research Center » Healthy Processed Foods Research » Research » Publications at this Location » Publication #263430
Title: Two alternative methods to predict amylose content in rice grain by using tristimulus CIELAB values and developing a specific color board of starch-iodine complex solution

Author
item RONOUBIGOWA, AMBOUROUE - Tokyo University Of Agriculture & Technology
item Pan, Zhongli
item WADA, YOSHIHARU - Utsunomiya University
item TOMOHIKO, YOSHIDA - Utsunomiya University

Submitted to: Journal of Plant Production Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/19/2010
Publication Date: 5/1/2011
Citation: Ronoubigowa, A., Pan, Z., Wada, Y., Tomohiko, Y. 2011. Two alternative methods to predict amylose content in rice grain by using tristimulus CIELAB values and developing a specific color board of starch-iodine complex solution. Journal of Plant Production Science. 14(2):164-168.

Interpretive Summary: The research showed that L*a*b* (chroma meter) values can be used to determine amylose content in rice as substitute to absorbance (spectrophotometer). A specific color board was created to characterize amylose-iodine solution, for estimating and classifying the amylose content in rice.

Technical Abstract: Amylose content was predicted by measuring tridimensional L*a*b* values in starch-iodine solutions and building a regression model. The developed regression model showed a highly significant relationship (R2= 0.99) between the L*a*b values and the amylose content. Apparent amylose content was strongly and negatively correlated with L*a*b* values. This method could be used to predict amylose content in rice. The conversion of L*a*b* values to RGB values and to color hexadecimal codes allowed reproducing the colors of starch-iodine solution and making an explicit color board. From this specific color board, entries could be assorted in their respective classes and their apparent amylose content could be easily estimated.