Dataset on viscosity and starch polymer properties to predict texture through modeling
Accurate 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 polyme...
| Autores principales: | , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Elsevier
2021
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| Acceso en línea: | https://hdl.handle.net/10568/164260 |
| _version_ | 1855543555041263616 |
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| author | Buenafe, Reuben James Q. Kumanduri, Vasudev Sreenivasulu, Nese |
| author_browse | Buenafe, Reuben James Q. Kumanduri, Vasudev Sreenivasulu, Nese |
| author_facet | Buenafe, Reuben James Q. Kumanduri, Vasudev Sreenivasulu, Nese |
| author_sort | Buenafe, Reuben James Q. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Accurate 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. |
| format | Journal Article |
| id | CGSpace164260 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | CGSpace1642602024-12-19T14:13:51Z Dataset on viscosity and starch polymer properties to predict texture through modeling Buenafe, Reuben James Q. Kumanduri, Vasudev Sreenivasulu, Nese Accurate 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. 2021-06 2024-12-19T12:53:39Z 2024-12-19T12:53:39Z Journal Article https://hdl.handle.net/10568/164260 en Open Access Elsevier Buenafe, 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 |
| spellingShingle | Buenafe, Reuben James Q. Kumanduri, Vasudev Sreenivasulu, Nese Dataset on viscosity and starch polymer properties to predict texture through modeling |
| title | Dataset on viscosity and starch polymer properties to predict texture through modeling |
| title_full | Dataset on viscosity and starch polymer properties to predict texture through modeling |
| title_fullStr | Dataset on viscosity and starch polymer properties to predict texture through modeling |
| title_full_unstemmed | Dataset on viscosity and starch polymer properties to predict texture through modeling |
| title_short | Dataset on viscosity and starch polymer properties to predict texture through modeling |
| title_sort | dataset on viscosity and starch polymer properties to predict texture through modeling |
| url | https://hdl.handle.net/10568/164260 |
| work_keys_str_mv | AT buenafereubenjamesq datasetonviscosityandstarchpolymerpropertiestopredicttexturethroughmodeling AT kumandurivasudev datasetonviscosityandstarchpolymerpropertiestopredicttexturethroughmodeling AT sreenivasulunese datasetonviscosityandstarchpolymerpropertiestopredicttexturethroughmodeling |