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Categorizing Rice Cultivars Based on Cluster Analysis of Amylose Content, Protein Content and Sensory Attributes

¹USDA-ARS Southern Regional Research Center, P.O. Box 19687, New Orleans, LA 70179. ²Corresponding author. E-mail: kbett@srrc.ars.usda.gov Phone: 504-286-4459. Fax: 504-286-4419. ³USDA-ARS, Rice Research Unit, Beaumont, TX. ⁴University of Arkansas Rice Research and Extension Center, Stuttgart, AR. ⁵Louisiana State University Rice Research Station, Crowley, LA. ⁶California Cooperative Rice Research Foundation, Biggs, CA.

Presently, rice cultivars are categorized according to grain dimensions, amylose content, and alkali spreading value (gelatinization temperature type). Categorization of rice cultivars based on total sensory impact is needed. This work endeavors to divide world rices into groups based on amylose, protein, flavor, and texture properties. Ninety-one rice samples representing 79 different cultivars and seven growing locations were separated into seven groups with Ward's Cluster Analysis. Cluster 1 included a third of the rice samples and had cultivars with a large diversity of grain shapes and amylose contents. Mean attribute scores for this cluster were near the grand mean for the collective rice samples for nearly every sensory attribute. Cluster 2 included conventional U.S. short- and medium-grain cultivars. Cluster 3 included conventional U.S. medium cultivars that were produced in Louisiana. Mean sensory scores for this cluster characterized these cultivars as having relatively undesirable flavor and texture attributes. Cluster 4 included Japanese premium quality cultivars and U.S. medium-grain cultivars developed for the Japanese market. Cluster 5 included high-amylose, indica types that had relatively firm textural properties. Cluster 6 included relatively soft cooking, aromatic cultivars. Cluster 7 included waxy cultivars and other soft cooking grains. In several cases, the production environment (location, weather effects, etc.) influenced flavor and texture characteristics and resulted in the cultivar falling into an unexpected cluster. This categorization serves as a catalyst for indexing rice cultivars for cooking and processing qualities.