CHEMICAL PROFILING OF PALM OIL AND OTHER SELECTED PLANT OILS BY PROTON NUCLEAR MAGNETIC RESONANCE COMBINED WITH CHEMOMETRICS

被引:2
|
作者
Tahir, Noor Idayu [1 ]
Ishak, Asiah Nabihan [2 ]
Sin, Teh Soek [1 ]
Othman, Abrizah [1 ]
Ramli, Umi Salamah [1 ]
机构
[1] Malaysian Palm Oil Board, 6 Persiaran Inst, Kajang 43000, Selangor, Malaysia
[2] Int Islamic Univ Malaysia IIUM, Dept Plant Sci, Kulliyyah Sci, Bandar Indera Mahkota, Kuantan 25200, Pahang, Malaysia
来源
JOURNAL OF OIL PALM RESEARCH | 2023年 / 35卷 / 04期
关键词
chemical signatures; NMR spectroscopy; oil purity and stability; proton signals; vegetable oil; SPECTROSCOPY; ADULTERATION; ORIGIN;
D O I
10.21894/jopr.2023.0021
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
Nuclear magnetic resonance (NMR) spectroscopy is an important and universal tool for chemical profiling. Combined with chemometrics for statistical interpretation and visualisation, the technique has gained recognition as an efficient method for assessing the quality and safety of vegetable oils. Nevertheless, its application in palm oil traceability is scarce. In this investigation, different origins, types and preparations of palm oils, olive oils, virgin coconut oils (VCO) and seed oils from sesame, black caraway, argan, corn, peanut and sunflower were examined for their chemical attributes using proton (H-1) NMR. The analysis used milligrams quantity of samples and was proven to be rapid with minimal sample preparation and analysis time. The statistical components of the multivariate model generated from the dataset were significant and highlighted the characterisation of the specimens into groups of palm, olive, virgin coconut and seed oils based on the presence and abundance of various types of proton signals. Different packaging and blends of commercial palm cooking oils exhibited similar proton profiles while the lab-prepared palm oil is closely linked to VCO. The work contributes to the development of authentication and traceability analytical methods for palm oil and will be expanded into a predictive platform with a larger dataset.
引用
收藏
页码:738 / 746
页数:9
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