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Research Project:
NEW SUSTAINABLE PROCESSING TECHNOLOGIES TO PRODUCE HEALTHY, VALUE-ADDED FOODS FROM SPECIALTY CROPS AND THEIR CO-PRODUCTS
Location: Processed Foods Research
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
Authors
 | Ronoubigowa, Ambouroue - |  |
Pan, Zhongli
|  | Wada, Yoshiharu - |  | Tomohiko, Yoshida - |
Submitted to: Journal of Plant Production Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: August 19, 2010
Publication Date: May 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.
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Last Modified: 06/20/2013
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