ArticleScientific reports2021
Chemometric approach to characterization of the selected grape seed oils based on their fatty acids composition and FTIR spectroscopy.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Winery By-Products as Sustainable Functional Resources: An Overview of Composition, Green Extraction Technologies, and Industrial Valorization.Molecules (Basel, Switzerland) · 2026Review
- Comparative Characterization of Ancient Wheat Cultivars Through Fatty Acid and Phytosterol Profiling.Foods (Basel, Switzerland) · 2026Article
- Enhancing Orange Juice Shelf Life Using Soy Lecithin-Stabilized Lemongrass Essential Oil Nanoemulsions: Formulation, Optimization, and Application.Food science & nutrition · 2025Article
- Grape Seed Oil Microemulsion for Improved Skin Delivery of Resveratrol.AAPS PharmSciTech · 2025Article
- Research of 2D-COS with metabolomics modifications through deep learning for traceability of wine.Scientific reports · 2024Article
- Encapsulation of grape seed oil in oil-in-water emulsion using multilayer technology: Investigation of physical stability, physicochemical and oxidative properties of emulsions under the influence of the number of layers.Current research in food science · 2024Article
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Authors and funding
8 authors.
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Abstract
Addressing the issues arising from the production and trade of low-quality foods necessitates developing new quality control methods. Cooking oils, especially those produced from the grape seeds, are an example of food products that often suffer from questionable quality due to various adulterations and low-quality fruits used for their production. Among many methods allowing for fast and efficient food quality control, the combination of experimental and advanced mathematical approaches seems most reliable. In this work a method for grape seed oils compositional characterization based on the infrared (FTIR) spectroscopy and fatty acids profile is reported. Also, the relevant parameters of oils are characterized using a combination of standard techniques such as the Principal Component Analysis, k-Means, and Gaussian Mixture Model (GMM) fitting parameters. Two different approaches to perform unsupervised clustering using GMM were investigated. The first approach relies on the profile of fatty acids, while the second is FT-IR spectroscopy-based. The GMM fitting parameters in both approaches were compared. The results obtained from both approaches are consistent and complementary and provide the tools to address the characterization and clustering issues in grape seed oils.
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