Routine Classification for Food Authenticity...Routine Classification for Food Authenticity Karen E....
Transcript of Routine Classification for Food Authenticity...Routine Classification for Food Authenticity Karen E....
Routine Classification for Food Authenticity
Karen E. Yannell, PhD
Agilent Technologies
Santa Clara, CA
Using the 6546 LC/Q-TOF, Profinder 10.0, Mass Profiler Professional 15.0, and Classifier 1.0
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Two different roles: • Method Developer (Scientist)
• Analyst (Technician) [New]
Routine Analysis
• MH Acq and Classifier software ONLY
Method Developer Improvements• Faster Profinder with less RAM
• Method automation in MPP [New]
LC/Q-TOF (.d), GC/SQ and GC/Q-TOF (.cef)
Classifier comes with a MPP 15.0 license
Not unique to food
• Terms are generic in the software
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Classifier 1.0 Allows for Routine Classification Analysis
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Overview of Acquisition and Analysis for Mango Data
Application: Using 6546 and Classifier to Determine Mango Puree Purity
• RP chromatography
• Tune: m/z 750
• MS only acquisition in
positive mode (m/z 50-1000)
• QuEChERS extraction
• Liquid extraction is a
good place to start for
discovery
• Simple workflow for
technician without Profinder
or MPP
• 100% accuracy for QC
samples
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Critical for good results
Sample Design
Authentic samples are needed• Mangos are proof of concept
Six individual samples
Positive QCs • Mimics pure samples
• Pooled from knowns
Negative QCs• Mimics adulterated samples• Ratios of different Positive QCs
Worklist: Randomized and Blocked• Model samples go first
• Unknowns after• All bracketed with QCs
Internal Standards
Optional but a good idea to
check data quality• At least in method validation
step
Anything exogenous to the
sample• Drugs and deuterated
pesticides were used here
Ideal: added at multiple points:
Use MH Quant to for quick DA• RT, area, accuracy
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Important for quality control and troubleshooting
Internal Standard Results
• Five days of data collection without daily calibration or maintenance.
• Internal standard was stable in the method development & validation.
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Profinder is faster and MPP has method automation to streamline analysis
Feature Finding in Profinder and Statistics and Model Building in MPP
New Analysis and Models
MPP 15.0 VIP Scores & New Models
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• VIP scores added
• Customer requested class
prediction algorithms
(SIMCA)
• All ‘Workflow’ tasks can be created in an automated method.
• Parameters are customizable.
• Statistical workflows can be saved, shared, and re-run for fast reanalysis.
• Results in fewer clicks and less error for analysis.
MPP 15.0: Method Automation
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eFam is Great for Familiarizing New Users with the Software and Statistics
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Software for Routine Classification Analysis
MassHunter Classifier 1.0
Classifier Inputs
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Given by a method
development scientist
MassHunter Classifier 1.0 Results
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Sample Table lists
processed and queued
samples, list predicted
group, and confidence
value
2D and 3D PCA plots
show selected sample
orientation to the
model groups
Compound Table
lists the features in
the model
Accurate Results Based on Confidence Scores
• Set a confidence score threshold to call a sample pure or adulterated
• This should be based on a method validation and sensitivity and specificity needs (false positive
and false negative) of the assay
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Classifier 1.0 Allows for Routine Classification Analysis
Two different roles:
• Method Developer (Scientist)
• Analyst (Technician) [New]
Routine Analysis
• MH Acq and Classifier software ONLY
Method Developer Improvements
• Faster Profinder with less RAM
• Method automation in MPP [New]
Clear results describing adulteration from confidence scores
Thank you!
Questions?
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