Direct analysis of fatty acid profile from milk by thermochemolysis–gas chromatography–mass spectrometry

2011 ◽  
Vol 1218 (2) ◽  
pp. 316-323 ◽  
Author(s):  
Mariza Gomes Reis ◽  
Marlon Martins dos Reis ◽  
Shane Leath ◽  
Kerst Stelwagen
2016 ◽  
Vol 78 (2) ◽  
Author(s):  
Nurrulhidayah Ahmad Fadzlillah ◽  
Abdul Rohman ◽  
Arieff Salleh Rosman ◽  
Farahwahida Mohd Yusof ◽  
Amin Ismail ◽  
...  

Butter is high priced product; as a consequence, butter can be subjected for adulteration with low price components such as lard. The presence of lard in any products is not allowed for Muslim and Jewish, therefore, its presence must be identified. Gas chromatography-mass spectrometry was successfully used to detect and discriminate butter from adulterated with lard. Results were presented in the form of chromatogram. Principal component analysis (PCA) was used to interpret the data and provided a good grouping of samples with 55.8% of the variation accounted for by PC 1 and 21.5% were accounted for by PC 2. All the lard containing samples formed a separate group from the samples that were free of lard. This method can be developed into a rapid method for detecting the presence of lard in food samples for Halal authentication.


2019 ◽  
Author(s):  
Alina Chernova ◽  
Pavel Mazin ◽  
Svetlana Goryunova ◽  
Denis Goryunov ◽  
Yakov Demurin ◽  
...  

Oilseed crops are one of the most important sources of vegetable oils for food and industry. Nutritional and technical properties of vegetable oil are primarily determined by its fatty acid (FA) composition. The content and composition of FAs in plants are commonly determined using gas chromatography-mass spectrometry (GS-MS) or gas chromatography-flame ionization detection (GC-FID) techniques. In the present work, we applied ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) technique to FA profiling of sunflower and rapeseed seeds and compared this method with the GC-FID technique. GC-FID detected 11 FAs in sunflower and 13 FAs in rapeseed, UPLC-MS appeared to be more sensitive, detecting about 2.5 times higher number of FAs in both plants. In addition to even-chain FAs, UPLC-MS was able to detect odd-chain Fas. The longest FA detected using GC-FID was a FA with 24 carbon atoms, whereas UPLC-MS could reveal the presence of longer FAs with the tails of up to 28 carbon atoms. Based on our results, we may conclude that UPLC-MS has a great potential to be used for the assessment of the FA profile of oil crops.


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