LiveID Software

Real-time Sample Recognition with LiveID Software

LiveID™ Software enables the real-time classification of samples using direct-analysis mass spectrometry (MS). Information is provided to the user immediately at the time of analysis enabling informed, real-time, decision making and removing doubt from sample identity.

This video includes the process of model building with data acquired from a DART QDa System with LiveID, and how to utilize the model for identification.

Overview

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No requirements for up-front sample preparation

The process is fast, simple and robust with no requirements for up-front sample preparation. Direct analysis MS measures a range of compounds in an unbiased fashion providing a holistic molecular profile of the chemical components within a sample. LiveID has a visually modern, attractive, web-based interface that offers a workflow-driven process which is easy to learn and use. Initially, authentic verified samples are used to create and validate a statistical model. Validated models can then be used with test samples to generate live classifications. The output is a simple to interpret yes/no answer.

LiveID can be used with nominal mass data generated from a Waters ACQUITY QDa Mass Detector fitted with DART® technology, or high resolution time-of-flight data generated from Waters Xevo G2-XS/SYNAPT G2-Si MS instruments fitted with a REIMS source.

Application areas are extensive and include:

Confirmation of sample authenticity for foods and bulk chemicals
Food fraud
Plant phenotyping in herbicide research
Microbe classification
Bioengineering research

LiveID is intended for research and commercial use only and not for diagnostic use.

Direct Analysis MS Data

Direct analysis MS data is imported into LiveID. Shown is a total ion chromatogram from ten collections and an example MS spectrum combined from the area highlighted in orange.

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PCA and LDA

After MS data is imported, Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) are used to build a statistical model of the samples under examination. Shown is a PCA plot of data from two classes of samples (chop in red, liver in blue; n=20 per class) and a clear inter-class separation, especially in the PC1 axis.

Classified Data

Once a statistical model is built with authentic samples and validated, it can be used for live recognition. Shown is data from nine measurements that have been classified as chop or liver.

For more information about the identity of chemical components observed from samples, MS data can be further analysed off-line in Progenesis QI. Please refer to Progenesis QI for more information.

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