DisplayTitle

Sensory and Instrumental Relationships of Texture of Cooked Rice from Selected Cultivars and Postharvest Handling Practices

¹USDA/ARS, Richard B. Russell Agricultural Research Center, P.O. Box 5677, Athens, GA 30604-5677. ²Corresponding author. Phone (706) 546-3167. Fax (706) 546-3607. E-mail: bglyon@ars.usda.gov ³USDA/ARS, Southern Regional Research Center, 1100 Robert E. Lee Blvd., New Orleans, LA 70124. ⁴USDA/ARS, Biometrical Consulting Service, Bldg. 001 BARC-West, 10300 Baltimore Blvd., Beltsville, MD 20705-2325.

Measurement of cooked rice texture attributes by sensory and instrumental methods is important because of the increased popularity of rice and rice products by globally diverse cultures. Many factors influence cooked rice texture, including cultivar, physicochemical properties, postharvest handling practices (milling degree, drying conditions, and final moisture), and cooking method. Information on the relationships between sensory, physical, and chemical characteristics will lead to better methods to quickly evaluate and predict end-use qualities, which will help to match rices with specific characteristics to populations that demand those attributes. This article reports the relationships between two modes of measuring texture attributes of rices: sensory and instrumental texture analyzers. Six medium- and short-grain rice samples differing by cultivar or growing location were dried to achieve final moisture levels of 12 or 15% and then regular- or deep-milled (n = 120). Correlations between individual sensory descriptive attributes and instrumental texture profile parameters were weak. Of only 12 significant correlations, the highest value was r = 0.624. Combined sensory and instrumental data were factor-analyzed. This analysis revealed that sensory attributes still accounted for the most variation (35.32% out of 76.55%). Sensory descriptive analysis was more sensitive to subtle changes in initial texture perception including parameters relating to stickiness and adhesiveness. The two-cycle compression test for texture profile parameters (i.e., hardness, cohesiveness, adhesiveness, gumminess, springiness, and chewiness) accounted for less variation in the data on texture differences.