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Development of Analytical Methods01:21

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Related Experiment Video

Updated: Feb 26, 2026

PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis
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Class-modelling in food analytical chemistry: Development, sampling, optimisation and validation issues - A tutorial.

Paolo Oliveri1

  • 1University of Genova, Department of Pharmacy, Viale Cembrano, 4, I-16148 Genova, Italy.

Analytica Chimica Acta
|July 24, 2017
PubMed
Summary
This summary is machine-generated.

Class-modelling methods are crucial for food analysis but underutilized. This study discusses developing and validating these one-class classifiers for accurate food product characterization, addressing limitations of discriminant methods.

Keywords:
Class-modellingDiscriminant analysisFood authenticityOne-class classificationOptimisationValidation

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Area of Science:

  • Pattern recognition
  • Analytical chemistry
  • Food science

Background:

  • Qualitative data modelling encompasses discriminant and class-modelling methods.
  • Class-modelling, or one-class classification, is ideal for single-class problems.
  • Discriminant methods are often misapplied to one-class food analysis problems, causing bias.

Purpose of the Study:

  • To critically analyze the development, optimization, and validation of class models for food product characterization.
  • To highlight the underutilization of class-modelling techniques in the food analytical field.
  • To discuss the limitations and biases introduced by using discriminant methods for one-class food analysis.

Main Methods:

  • Review and critical analysis of class-modelling techniques.
  • Discussion of model development and optimization strategies.
  • Examination of validation approaches for food product characterization.

Main Results:

  • Class-modelling methods are underused in food analysis despite their suitability.
  • Misapplication of discriminant methods leads to biased outcomes in one-class food problems.
  • Effective class models are essential for accurate food product characterization.

Conclusions:

  • There is a need to increase the adoption and correct application of class-modelling methods in food analysis.
  • Proper development and validation of class models can overcome limitations of current approaches.
  • This work provides insights into robust class modelling for food characterization.