Comparison between classical and innovative class-modelling techniques for the characterisation of a PDO olive oil

Area of Science:

• Analytical Chemistry
• Food Science
• Chemometrics

Background:

• Italian Protected Designation of Origin (PDO) olive oils require robust authentication methods.
• Distinguishing authentic Chianti Classico olive oil from similar regional oils is crucial for quality control and consumer trust.

Purpose of the Study:

• To evaluate the effectiveness of multiple analytical techniques combined with chemometric methods for authenticating Italian Chianti Classico PDO olive oil.
• To compare the performance of classical and novel chemometric class-modelling techniques in classifying olive oil samples.

Main Methods:

• Utilized near-infrared (NIR) and UV-Visible spectroscopy, an artificial nose, and an artificial tongue for sample analysis.
• Employed four fingerprinting analytical techniques to generate non-specific signals.
• Applied classical methods (Soft Independent Modelling of Class Analogy, Quadratic Discriminant Analysis) and novel chemometric methods (multivariate range modelling, CAIMAN analogues modelling).

Main Results:

• The four analytical techniques, after pre-processing, provided effective non-specific signals for building class models.
• Chemometric approaches successfully differentiated Chianti Classico olive oils from those of a nearby production area (Maremma).
• The study compared the efficacy of established and emerging chemometric techniques for olive oil authentication.

Conclusions:

• The integrated approach using spectroscopy, electronic sensors, and chemometrics is effective for authenticating Chianti Classico PDO olive oil.
• Novel chemometric methods show promise for enhancing the accuracy and reliability of olive oil authentication systems.
• This study contributes to safeguarding the integrity of high-value food products through advanced analytical strategies.