Cargando…
Improving Prediction of Peroxide Value of Edible Oils Using Regularized Regression Models
We present four unique prediction techniques, combined with multiple data pre-processing methods, utilizing a wide range of both oil types and oil peroxide values (PV) as well as incorporating natural aging for peroxide creation. Samples were PV assayed using a standard starch titration method, AOCS...
Autores principales: | Gilbraith, William E., Carter, J. Chance, Adams, Kristl L., Booksh, Karl S., Ottaway, Joshua M. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8659081/ https://www.ncbi.nlm.nih.gov/pubmed/34885855 http://dx.doi.org/10.3390/molecules26237281 |
Ejemplares similares
-
Visual Colorimetric Detection of Edible Oil Freshness for Peroxides Based on Nanocellulose
por: Jiang, Xiongli, et al.
Publicado: (2023) -
Evolutionary polynomial regression improved by regularization methods
por: Li, Yao, et al.
Publicado: (2023) -
Iodine values, peroxide values and acid values of Bohai algae oil compared with other oils during the cooking
por: Geng, Lijing, et al.
Publicado: (2023) -
Robust priors for regularized regression
por: Bobadilla-Suarez, Sebastian, et al.
Publicado: (2022) -
Towards improvement in prediction of iodine value in edible oil system based on chemometric analysis of portable vibrational spectroscopic data
por: Yan, Hong, et al.
Publicado: (2018)