A review on tomato authenticity: quality control methods in conjunction with multivariate analysis (chemometrics)

Area of Science:

• Food Science
• Analytical Chemistry
• Agricultural Science

Background:

• Food authenticity and traceability are critical concerns in the food supply chain, directly impacting food quality and safety.
• Vegetables are particularly vulnerable to adulteration regarding geographic origin and production methods (e.g., organic, conventional, GMOs).

Purpose of the Study:

• To review current instrumental and sensory analysis methods for vegetable quality control.
• To analyze the application of multivariate statistical techniques in interpreting analytical results for food authenticity.

Main Methods:

• Instrumental analysis: Ion chromatography, High-Performance Liquid Chromatography (HPLC), Atomic Absorption Spectrophotometry (AAS), electronic nose, and Mass Spectrometry (MS).
• Sensory analysis.
• Multivariate analysis: Principal Component Analysis (PCA), Discriminant Analysis (DA), Cluster Analysis (CA), Canonical Analysis (CA), and Factor Analysis (FA).

Main Results:

• The review synthesizes findings from various analytical techniques applied to vegetable quality control.
• Multivariate analysis effectively processes data from these methods to identify patterns and classify samples.
• Eight comprehensive tables summarize the results and conclusions.

Conclusions:

• A combination of advanced instrumental techniques and sensory evaluation, supported by robust statistical analysis, is essential for ensuring vegetable authenticity and quality.
• These methods provide a framework for detecting adulteration and verifying product integrity throughout the food chain.