Modelling the odor profile of fungal Solid-State Fermentation

Area of Science:

• Food Science
• Biotechnology
• Sensory Analysis

Background:

• Consumer acceptance of alternative proteins hinges on sensory attributes, particularly odor.
• Understanding the microbial and biochemical processes influencing odor during production is crucial.

Purpose of the Study:

• To model odor profile development in alternative proteins produced via solid-state fermentation (SSF).
• To establish a framework for mechanistic odor prediction in food systems.

Main Methods:

• Utilized surplus bread crusts supplemented with perennial ryegrass protein and fermented with fungal cultures (Rhizopus oligosporus, Aspergillus oryzae, Neurospora intermedia).
• Analyzed volatile organic compounds (VOCs) using solid-phase microextraction (SPME) and gas chromatography-mass spectrometry (GC-MS).
• Developed and validated a mechanistic odor prediction model based on the Weber-Fechner law against quantitative descriptive analysis (QDA).

Main Results:

• Identified over 150 volatile organic compounds (VOCs) contributing to the odor profile.
• The mechanistic model successfully predicted changes in overall odor intensity and specific notes (sweet, baked, grass-like).
• Model correlations were weaker for fungal-derived descriptors like fruity, earthy, and herbal notes.

Conclusions:

• Fungal SSF significantly alters the odor profiles of alternative proteins.
• The developed mechanistic model provides a framework for predicting and potentially controlling odor in fermented food products.
• This research aids in optimizing SSF processes for enhanced consumer acceptance of alternative proteins.