Quantitative Prediction and Kinetic Modelling for the Thermal Inactivation of Brochothrix thermosphacta in Beef Using...

Area of Science:

• Food Science
• Microbiology
• Spectroscopy

Background:

• Controlling microbial growth, like Brochothrix thermosphacta, is crucial for meat safety during thermal processing.
• Traditional methods for monitoring microbial inactivation are often time-consuming and labor-intensive.

Purpose of the Study:

• To investigate the feasibility of using hyperspectral imaging (HSI) for simulating the thermal inactivation of Brochothrix thermosphacta in beef.
• To develop kinetic models for microbial inactivation based on HSI data.
• To assess HSI's potential for real-time monitoring of microbial safety in meat.

Main Methods:

• Hyperspectral imaging (HSI) was employed in the 400-1000 nm range to analyze beef samples undergoing thermal processing (40-60 °C).
• Weibull and modified Gompertz models were developed using full spectral variables, featured spectral variables, and principal component scores from HSI data.
• Partial least squares regression (PLSR) was used to quantify Brochothrix thermosphacta populations.

Main Results:

• Specific wavebands (412 nm and 735 nm) showed a strong correlation with surviving Brochothrix thermosphacta populations.
• PLSR models demonstrated satisfactory quantification of Brochothrix thermosphacta, with R_v² = 0.826 and RMSE = 0.341 log CFU/g.
• The Weibull model combined with HSI at 735 nm accurately predicted thermal inactivation kinetics (R² = 0.937).

Conclusions:

• Hyperspectral imaging (HSI) shows significant potential for quantifying and monitoring microbial populations in meat during heating.
• HSI coupled with kinetic modeling offers a promising non-destructive approach for assessing microbial inactivation in food processing.
• This technique can enhance food safety by providing real-time data on microbial inactivation kinetics.