Developing FT-NIR and PLS1 Methodology for Predicting Adulteration in Representative Varieties/Blends of Extra Virgin...

Area of Science:

• Analytical Chemistry
• Food Science
• Spectroscopy

Background:

• Fourier transform near infrared (FT-NIR) spectroscopy combined with partial least squares (PLS1) has shown promise for assessing extra virgin olive oil (EVOO) authenticity and detecting adulteration.
• Previous calibration models were specific to a single EVOO variety and required further development for broader application.

Purpose of the Study:

• To develop and validate new PLS1 calibration models for FT-NIR spectroscopy applicable to diverse EVOO varieties.
• To accurately predict the presence, identity, and quantity of adulterants in various EVOOs.
• To assess the quality and purity of EVOO using the FT-NIR Index.

Main Methods:

• Development of four distinct sets of PLS1 calibration models tailored to different EVOO varieties based on their fatty acid profiles.
• Creation of an FT-NIR spectral library using 66 EVOO products from California and Europe.
• Utilizing the FT-NIR Index to measure volatile content as an indicator of EVOO quality and purity.

Main Results:

• EVOO varieties were successfully categorized into four distinct groups, each necessitating specific PLS1 models.
• The developed models accurately predicted low concentrations of vegetable oil adulterants with varying fatty acid compositions (linoleic, oleic, palmitic).
• The FT-NIR Index provided a measure of volatile content, aiding in the assessment of EVOO quality.

Conclusions:

• The enhanced PLS1 calibration models enable rapid and accurate prediction of EVOO authenticity and adulteration across different varieties.
• FT-NIR spectroscopy coupled with PLS1 offers a robust analytical tool for quality control in the olive oil industry.
• This approach significantly improves the ability to detect and quantify adulterants in extra virgin olive oil.