Justin Miller-Schulze and Smith Purdum explain how machine learning and chemometrics can improve fire debris classification in forensic science applications.
|Articles|April 8, 2015
LCGC TV: Rudolf Krska on Mycotoxin Analysis Using LC–MS–MS
Mycotoxins are an important group of secondary metabolites produced by fungi that can cause disease in humans and animals. Rudolf Krska from BOKU, IFA-Tulln, in Vienna, Austria, describes why he uses LC–MS–MS in his analysis of mycotoxins and offers advice to separation scientists thinking about using the technique in their research.
Advertisement
Advertisement
Related to this article
Ultrahigh-performance liquid chromatography-mass spectrometry (UHPLC-MS) reveals how temperature and life stage shift jellyfish venom.
Gas chromatography-mass spectrometry (GC-MS) chromatography reveals elevated polycyclic aromatic hydrocarbons (PAH) levels in wildfire smoke over Nevada.
This week, the Chromatography Online website observed National Forensic Science Week with expert interviews on how chromatography helps solve cases, plus career stories from women in analytical science and new research on detecting rat poison in cats and tracking mold toxins in gluten-free pasta.
Kinjal Bhatt argues inclusion advocacy shouldn't fall on women alone, while Ina Varfaj credits sharing the load and learning to say no for avoiding burnout.
Steven Ray Wilson defines organ-on-a-chip as organoids on microfluidic devices, tracing their small, complex samples to the case for automated online LC–MS.
Liquid chromatography-mass spectrometry (LC-MS) detects Maillard byproducts in hay after steaming and storage.
Liquid chromatography-high resolution mass spectrometry (LC-HRMS) finds aflatoxin and fumonisins stay stable in gluten-free pasta.
Advertisement
Advertisement
Trending on LCGC International
1
LC-MS/MS Method Detects Propofol via Metabolite
2
Best of the Week: National Forensic Science Week, and Chromatography Is On the Case
3
Women in Chromatography: The Draw of Analytical Science
4
Chemometric-based Machine Learning for the Forensic Classification of Fire Debris
5