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United States Department of Agriculture

Agricultural Research Service

Research Project: 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: Relationship of cooked rice nutritionally-important starch fractions with other physicochemical properties.

Authors
item Patindol, James
item Guraya, Harmeet
item Champagne, Elaine
item Chen, Ming-Hsuan
item McClung, Anna
item McClung, Anna

Submitted to: Starch/Starke
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: December 28, 2009
Publication Date: April 7, 2010
Citation: Patindol, J.A., Guraya, H.S., Champagne, E.T., Chen, M., Mcclung, A.M. 2010. Relationship of cooked rice nutritionally-important starch fractions with other physicochemical properties. Starch/Starke. 62:246-256.

Interpretive Summary: Chemometrics is the science of extracting information from multivariate chemical data using statistical and mathematical methods. Chemometric tools were used to establish the association of cooked rice nutritionally-important starch fractions (NISF) with genetic markers and other physicochemical properties. NISF, which includes rapidly digestible (RDS), slowly digestible (SDS), and resistant starch (RS), have significant implications on human health, particularly glucose (carbohydrate) metabolism. Available methods for measuring NISF are tedious and time-consuming, therefore, developing simple, fast, and accurate estimators will be a valuable innovation. Sixteen rice cultivars grown in Arkansas and Texas that represented five cytosine-thymine repeat (CTn) genetic marker groups (CT11, CT14, CT17, CT18, and CT20) were used as test samples. CT11 was generally associated with high percentages of RS and SDS, and low RDS. CT14 was associated with low SDS, whereas, CT17 and CT18 were associated with low RS. The CT20 cultivars were similar to CT11 in SDS and RS, and to CT14, CT17, and CT18 in terms of RDS. RS was successfully predicted by regression models derived from some physicochemical measurements, whereas, estimates for SDS and RDS picked up little success. Basic grain quality indices (amylose, protein, gel consistency, and alkali spreading value) explained NISF variations better than pasting and thermal properties. These findings are valuable in meeting consumers’ growing interest on healthy eating and food processors’ endeavors to develop health-promoting rice-based food products.

Technical Abstract: Sixteen rice cultivars representing 5 cytosine-thymine repeat (CTn) microsatellite genetic marker groups were analyzed for their cooked rice nutritionally-important starch fractions (rapidly digestible, slowly digestible, and resistant starch), basic grain quality indices (apparent amylose, crude protein, alkali spreading value, and gel consistency), pasting characteristics, and thermal properties. Chemometric tools (bivariate correlation, principal component analysis, multiple linear regression, and partial least squares regression) were used to establish the association of nutritionally-important starch fractions (NISF) with other milled rice physicochemical properties. CT11 was generally associated with high percentages of resistant starch (RS) and slowly digestible starch (SDS), and a low percentage of rapidly digestible starch (RDS). CT14 was associated with low SDS, whereas, CT17 and CT18 were associated with low RS. The CT20 samples were similar to CT11 in SDS and RS; and to CT14, CT17 and CT18 in RDS content. RDS, SDS, and RS were loaded on three different quadrants of the principal component similarity map. RDS was not significantly correlated with any of the physicochemical properties, whereas, SDS was positively correlated with gel consistency. RS was positively correlated with apparent amylose, setback viscosity, total setback viscosity, and peak gelatinization temperature, and negatively correlated with breakdown viscosity. Multivariate techniques indicated lack of robustness in predicting RDS and SDS, as the models only explained <50% of the variance. More robust regression models were obtained for RS, explaining >60% of its variation. Basic grain quality indices explained NISF variations better than pasting and thermal properties.

Last Modified: 7/28/2014
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