Cargando…
Mathematical modeling to predict rice's phenolic and mineral content through multispectral imaging
Over half the world population relies on rice for energy, but being a carbohydrate-based crop, it offers limited nutritional benefits. To achieve nutritional security targets in Asia, we must understand the genetic variation in multi-nutritional properties with therapeutic properties and deploy this...
Autores principales: | Buenafe, Reuben James, Tiozon, Rhowell, Boyd, Lesley A., Sartagoda, Kristel June, Sreenivasulu, Nese |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9767410/ https://www.ncbi.nlm.nih.gov/pubmed/36570628 http://dx.doi.org/10.1016/j.focha.2022.100141 |
Ejemplares similares
-
Metabolomics based inferences to unravel phenolic compound diversity in cereals and its implications for human gut health
por: Tiozon, Rhowell Jr. N., et al.
Publicado: (2022) -
Metabolomics and machine learning technique revealed that germination enhances the multi-nutritional properties of pigmented rice
por: Tiozon, Rhowell Jr. N., et al.
Publicado: (2023) -
Food Processing Technologies to Develop Functional Foods With Enriched Bioactive Phenolic Compounds in Cereals
por: Kasote, Deepak, et al.
Publicado: (2021) -
Post-genomics revolution in the design of premium quality rice in a high-yielding background to meet consumer demands in the 21st century
por: Sreenivasulu, Nese, et al.
Publicado: (2021) -
Impact of ultrasonic treatment on rice starch and grain functional properties: A review
por: Bonto, Aldrin P., et al.
Publicado: (2020)