Asset Details
Do you wish to reserve the book?
Characterization and authentication of olive, camellia and other vegetable oils by combination of chromatographic and chemometric techniques: role of fatty acids, tocopherols, sterols and squalene
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Characterization and authentication of olive, camellia and other vegetable oils by combination of chromatographic and chemometric techniques: role of fatty acids, tocopherols, sterols and squalene
Do you wish to request the book?
Characterization and authentication of olive, camellia and other vegetable oils by combination of chromatographic and chemometric techniques: role of fatty acids, tocopherols, sterols and squalene
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Characterization and authentication of olive, camellia and other vegetable oils by combination of chromatographic and chemometric techniques: role of fatty acids, tocopherols, sterols and squalene
2021
Overview
Fatty acids, tocopherols, sterols and squalene were analyzed by chromatographic-based techniques and were selected as variables to build a variety of classification models for the accurate characterization and authentication of olive, camellia oil and six other vegetable oils (soybean, corn, rapeseed, peanut, palm and sunflower). Different unsupervised and supervised chemometrics techniques, such as principal component analysis (PCA), linear discriminant analysis (LDA) and partial least squares discriminant analysis (PLS-DA), have been applied. In addition, the Kennard–Stone algorithm was used to select the training samples for the construction of supervised models. The discriminating power of different components was compared, and the results suggested that fatty acids are the most powerful in distinguishing vegetable oils, followed by tocopherols and sterols, and squalene contributed to the discrimination between olive and camellia oils despite their apparent similarities. This proposed method was straightforward and can be easily implemented to identify unknown oil samples.
Publisher
Springer Nature B.V
Subject
