Discrimination and growth tracking of fungi contamination in peaches using electronic nose

Area of Science:

• Food Science
• Mycology
• Analytical Chemistry

Background:

• Fungal contamination poses a significant threat to peach quality and safety.
• Accurate and early detection of spoilage fungi is crucial for preventing economic losses and ensuring consumer health.
• Traditional methods for fungal detection can be time-consuming and destructive.

Purpose of the Study:

• To develop and validate a non-destructive electronic nose (E-nose) method for detecting fungal contamination in peaches.
• To correlate E-nose volatile compound analysis with fungal load and species.
• To assess the potential of E-nose technology for discriminating fungal contamination in peaches.

Main Methods:

• Peaches were artificially inoculated with common spoilage fungi (Botrytis cinerea, Monilinia fructicola, Rhizopus stolonifer).
• Samples were stored for varying periods, and E-nose was used to analyze volatile organic compounds.
• Fungal colony counts were determined and compared with E-nose data using statistical analyses like Principal Component Analysis (PCA) and Partial Least Squares Regression (PLSR).

Main Results:

• Changes in volatile compounds detected by the E-nose correlated significantly with the total amount and species of fungi present.
• Terpenes and aromatic compounds were identified as key contributors to the E-nose response.
• PCA scores showed a strong correlation with fungal colony counts, and PLSR effectively predicted fungal load.

Conclusions:

• The E-nose provides a rapid, non-destructive, and accurate method for detecting and quantifying fungal contamination in peaches.
• The technology demonstrates high discrimination accuracy, highlighting its potential for real-time food safety monitoring.
• E-nose analysis of volatile compounds offers a promising alternative to conventional methods for assessing peach spoilage.