DEVELOPING NOVEL PROCESSES FOR INCORPORATING THE UNIQUE NUTRITIONAL AMD FUNCTIONAL PROPERTIES OF RICE INTO VALUE-ADDED PRODUCTS
Location: Food Processing and Sensory Quality Research
Title: Relating raw rice color and composition to cooked rice color.
Submitted to: Journal of the Science of Food and Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: June 13, 2011
Publication Date: June 30, 2011
Citation: Bett Garber, K.L., Champagne, E.T., Thomson, J.L., Lea, J.M. 2011. Relating raw rice color and composition to cooked rice color. Journal of the Science of Food and Agriculture. 92:283-291.
Interpretive Summary: Rice consumers, particularly from countries for which rice is the staple, have strong preferences for the sensory properties of rice. Different countries have different requirements for the flavor and texture of rice, and within countries, a range of preferences can be found. However, when it comes to appearance, consumers worldwide desire raw and cooked rice with a high degree of whiteness. Little attention has been given to relating raw rice color to cooked milled rice color and, specifically, to determining the influence of amylose (a form of starch) and protein contents on the cooked color. A useful tool for the rice industry would be one that can predict cooked rice color from raw rice. In this study, the interrelationships of raw color, cooked color, amylose content, and protein content were determined using a set of 28 premium, aromatic and non-aromatic rice cultivars from the U.S. and rice-growing countries around the world. Mathematical models were developed to assess whether or not the color of cooked rice can be predicted from raw rice color in conjunction with amylose and protein contents. Only the color variable that gives an indication of the amount of redness or greenness could be predicted with high enough precision to be useful and this was only for modeling using samples cooked in the same manner. Controlling for conditions that affect color (e.g.cooking method, post-harvest handling) appears to be necessary to improve models.
Traditionally, the color of milled rice is economically important. The whiter the rice the more it is preferred by consumers and the more value it has in the market place. Little attention has been given to relating raw rice color to cooked milled rice color and, specifically, to determining the influence of amylose and protein contents on the cooked color. Thus, the first objective of this study was to determine the interrelationships of raw color, cooked color, amylose content, and protein content in rice using a set of 28 premium, aromatic and non-aromatic cultivars from the U.S. and rice-growing countries around the world. The second objective was to assess whether or not the color of cooked rice can be predicted from raw rice color in conjunction with amylose and protein contents. The international rice cultivars were prepared according to customary cooking procedures within the countries of origin; all U.S. grown rice was prepared in rice cookers. Tristimulus color values (L*, a* and b*) were measured using the Hunter Miniscan XE Plus colorimeter on the rice before and after cooking. Chroma (C*) and hue angle were calculated from a* and b* values. Protein and amylose contents were not significantly correlated with the measured or calculated color measurements for raw rice. Protein and amylose showed moderate, significant associations with L* and a* and a*, b*, and C*, respectively, for cooked rice. Only a* and hue angle of raw rice showed moderate, significant association with a cooked rice color variable and that variable was a*. Modeling showed that amylose and protein in combination were not adequate in predicting cooked rice color or the difference between cooked and raw rice color. Improvement in the predictive abilities of the models was obtained when raw rice color measurements were included with amylose and protein contents in the regression. However, only the color variable a* (red to green) could be predicted using protein, amylose, and raw rice color with high enough precision to be useful, and this was only for modeling using samples cooked in the same manner (rice cooker). Cooking method (rice cooker vs. excess water) affected the color of cooked rice.