Simultaneous Determination of Ergot Alkaloids in Swine and Dairy Feeds Using Ultra High-Performance Liquid Chromatography-Tandem Mass Spectrometry.
Saranya PoapolathepNarumol KlangkaewZhaowei ZhangMario GiorgiAntonio Francesco LogriecoAmnart PoapolathepPublished in: Toxins (2021)
Ergot alkaloids (EAs) are mycotoxins mainly produced by the fungus Claviceps purpurea. EAs are known to affect the nervous system and to be vasoconstrictors in humans and animals. This work presents recent advances in swine and dairy feeds regarding 11 major EAs, namely ergometrine, ergosine, ergotamine, ergocornine, ergocryptine, ergocristine, ergosinine, ergotaminine, ergocorninine, ergocryptinine, and ergocristinine. A reliable, sensitive, and accurate multiple mycotoxin method, based on extraction with a Mycosep 150 multifunctional column prior to analysis using UHPLC-MS/MS, was validated using samples of swine feed (100) and dairy feed (100) for the 11 targeted EAs. Based on the obtained validation results, this method showed good performance recovery and inter-day and intra-day precision that are in accordance with standard criteria to ensure reliable occurrence data on EA contaminants. More than 49% of the swine feed samples were contaminated with EAs, especially ergocryptine(-ine) (40%) and ergosine (-ine) and ergotamine (-ine) (37%). However, many of the 11 EAs were not detectable in any swine feed samples. In addition, there were contaminated (positive) dairy feed samples, especially for ergocryptine (-ine) (50%), ergosine (-ine) (48%), ergotamine (-ine), and ergocristine (-ine) (49%). The mycotoxin levels in the feed samples in this study almost complied with the European Union regulations.
Keyphrases
- liquid chromatography tandem mass spectrometry
- simultaneous determination
- ms ms
- solid phase extraction
- high performance liquid chromatography
- liquid chromatography
- heavy metals
- tandem mass spectrometry
- ultra high performance liquid chromatography
- drinking water
- risk assessment
- mass spectrometry
- big data
- machine learning
- high resolution mass spectrometry
- deep learning