Abstract
A battery of assays to characterize the cooking and eating attributes of rice have been in routine use for several decades. The classification system to group rice varieties into different quality types are often based on cooking and eating attributes defined based on amylose content, rather than being considered a set of attributes contributing to an overall quality type based on multi-dimensional approach. In this chapter, the methods developed to measure the cooking quality attributes of rice are described. Instead of considering each attribute on its own, the authors employ multidimensional data generated from the estimation of amylose content, gel consistency, gelatinization temperature, Rapid Visco-Analyzer parameters to classify rice into distinct cooking quality ideotypes. If used universally, such an approach can improve prediction of cooking quality classifications of rice varieties in the breeding programs.
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Acknowledgments
The authors thank Dennis Villegas, Teodoro Atienza, Leah Villanueva, Jennine Rose Lapis, Reah Gonzales, Eric Jhon Cruz, Marnol Santos, Ruben Chavez, and Mitzi Alodia Asih for assistance in processing and collecting data for the samples used in the case study and in the validation and optimization of the methodologies in GQNSL. This work has been supported under the CGIAR thematic area Global Rice Agri-Food System CRP, RICE, Stress-Tolerant Rice for Africa and South Asia (STRASA) Phase III funding.
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Molina, L., Jimenez, R., Sreenivasulu, N., Cuevas, R.P.O. (2019). Multi-Dimensional Cooking Quality Classification Using Routine Quality Evaluation Methods. In: Sreenivasulu, N. (eds) Rice Grain Quality. Methods in Molecular Biology, vol 1892. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8914-0_8
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DOI: https://doi.org/10.1007/978-1-4939-8914-0_8
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