Dataset on viscosity and starch polymer properties to predict texture through modeling

Vista sencilla de ítem
dc.creatorBuenafe, Reuben James Q.
dc.creatorKumanduri, Vasudev
dc.creatorSreenivasulu, Nese
dc.date2021-06
dc.date2024-12-19T12:53:39Z
dc.date2024-12-19T12:53:39Z
dc.date.accessioned2026-06-27T04:16:20Z
dc.descriptionAccurate classification tool for screening varieties with superior eating and cooking quality based on its pasting and starch structure properties is in demand to satisfy both consumers’ and farmers’ need. Here we showed the data related to the article entitled “Deploying viscosity and starch polymer properties to predict cooking and eating quality models: a novel breeding tool to predict texture” [1] which provides solution to this problem. The paper compiles all the pasting, starch structure, sensory and routine quality data of the rice sample used in the article into graphical form. It also shows how the data were processed and obtained.
dc.identifierhttps://hdl.handle.net/10568/164260
dc.identifier.urihttp://hdl.handle.net/123456789/27257
dc.languageen
dc.publisherElsevier
dc.rightsOpen Access
dc.sourceBuenafe, Reuben James Q.; Kumanduri, Vasudev and Sreenivasulu, Nese. 2021. Dataset on viscosity and starch polymer properties to predict texture through modeling. Data in Brief, Volume 36 p. 107038
dc.titleDataset on viscosity and starch polymer properties to predict texture through modeling
dc.typeJournal Article

Archivos

Colecciones

Instituto Internacional de Investigación del Arroz (IRRI)