Random forest–based electrical impedance spectroscopy for precise freshness classification of Holstein beef

Key Points

• High accuracy in freshness classification was achieved using random forest algorithms, reaching over 90%.
• The study employed electrical impedance spectroscopy to evaluate the freshness of Holstein beef in a controlled setting.
• This method shows promising results compared to traditional freshness evaluation techniques, enabling faster assessments.
• Further validation is needed across more diverse beef samples to confirm the robustness of this freshness classification method.