RESUMO
Avocado oil is a nutritious, edible oil produced from avocado fruit. It has high commercial value and is increasing in popularity, thus powerful analytical methods are needed to ensure its quality and authenticity. Recent advancements in low-field (LF) NMR spectroscopy allow for collection of high-quality data despite the use of low magnetic fields produced by non-superconductive magnets. Combined with chemometrics, LF NMR opens new opportunities in food analysis using targeted and untargeted approaches. Here, it was used to determine poly-, mono-, and saturated fatty acids in avocado oil. Although direct signal integration of LF NMR spectra was able to determine certain classes of fatty acids, it had several challenges arising from signal overlapping. Thus, we used partial least square regression and developed models with good prediction performance for fatty acid composition, with residual prediction deviation ranging 3.46-5.53 and root mean squared error of prediction CV ranging 0.46-2.48. In addition, LF NMR, combined with unsupervised and supervised methods, enabled the differentiation of avocado oil from other oils, namely, olive oil, soybean oil, canola oil, high oleic (OL) safflower oil, and high OL sunflower oil. This study showed that LF NMR can be used as an efficient alternative for the compositional analysis and authentication of avocado oil. PRACTICAL APPLICATION: Here, we describe the application of LF-NMR for fatty acid analysis and avocado oil authentication. LF-NMR can be an efficient tool for targeted and untargeted analysis, thus becoming an attractive option for companies, regulatory agencies, and quality control laboratories. This tool is especially important for organizations and entities seeking economic, user-friendly, and sustainable analysis solutions.