Application Note: Detecting Contamination in Shochu Using the Agilent GC/MSD, Mass Profiler Professional and Sample Class Prediction Models
21 November 2012

Sample Class Prediction (SCP) models are powerful tools that can use mass spectrometry data from highly complex samples to identify differences in sample classes, such as contamination. In this application note from Agilent Technologies, a method was developed that used SCP to accurately detect and classify contamination in shochu samples, for use in quality assurance and quality control during the manufacturing process.