NMR-Based Chemometric Approaches for Vegetable Oil Quality Evaluation

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Nuclear magnetic resonance (NMR) spectroscopy is routinely used to evaluate vegetable oil quality. The technique, which is often combined with chemometric modeling has only advanced and improved the analysis of various oils (1).

A recent review article published in the journal Trends in Food Science & Technology highlighted how NMR and chemometric modeling are being applied to analyze vegetable oil. The study explores how both methods, when combined, are delivering new advancements in food science and technology (1).

Vegetable oils are known for potential health benefits and nutritional value (2). The benefits include antioxidant activity, the prevention of cardiovascular disease, and kidney and liver protection (2). According to the review article, the 11 most common vegetable oils can be grouped into four categories based on dominant fatty acid composition: palmitic acid oil (palm oil); high oleic acid oils (camellia oil, olive oil, and high oleic sunflower oil); linoleic acid oils (sunflower, corn, sesame, peanut, and rice bran oil); and linolenic acid oils (soybean and rapeseed oil) (1). Although each oil type has unique health and culinary advantages, challenges remain in ensuring consistent nutritional quality, monitoring oxidative stability, and verifying authenticity to combat adulteration and mislabeling.

The researchers explained that NMR can address these issues. By exploiting different nuclei such as ^1H, ^13C, and ^31P, NMR provides detailed, quantitative insights into fatty acids, triglycerides, sterols, squalene, and oxidation products (1). When paired with chemometric tools, these data can be transformed into robust predictive models that enable both qualitative and quantitative assessments (1).

Compared with traditional mass spectrometry (MS) and chromatography, NMR-based methods offer a faster, less labor-intensive alternative for oil characterization. The review article documents how NMR and chemometrics has already been successfully applied to predict nutritional profiles, evaluate oxidation, and detect adulteration across multiple vegetable oil types (1). Importantly, the method supports not only laboratory-based analysis but also paves the way for future field applications (1).

Meanwhile, the researchers see this field advancing by integrating NMR-chemometric approaches with machine learning (ML) and portable technologies. Such advances could bring rapid, on-site testing of vegetable oil quality closer to reality, offering significant benefits for food producers, regulators, and consumers alike (1).

As the researchers conclude in their study, the growing precision of computational models will help ensure vegetable oils meet nutritional and safety standards while preserving authenticity in an increasingly globalized food supply (1).

References

1. Shi, T.; Dai, T.; Zhang, T.; et al. NMR spectroscopy combined with chemometrics for quality assessment of common vegetable oils: A review. Trends Food Sci. Technol. 2025, 157, 104889. DOI: 10.1016/j.tifs.2025.104889.
2. Tian, M.; Bai, Y.; Tian, H.; et al. The Chemical Composition and Health-Promoting Benefits of Vegetable Oils—A Review. Molecules 2023, 28 (17), 6393. DOI: 10.3390/molecules28176393