MIRERC 040/2025: A Two-Stream Deep Learning Approach for Freshness Classification in Beef

Authors

  • Martin Muthomi Meru University of Science & Technology
  • Dr. Samson Munialo Meru University of Science & Technology
  • Dr. Mary Mwadulo Meru University of Science & Technology

Abstract

Meat is an essential part of the human diet, providing necessary nutrients and protein(Cocking et
al., 2020). However, during storage the quality of beef can go down due to chemical spoilage
thereby posing danger to human health (Catherine et al., 2021). The freshness of meat plays a
crucial role in determining its taste, nutritional value and potential health risks hence quality
(freshness) and safety are of paramount importance(Osei Mensah et al., 2022). One way to assess
the freshness of meat is through inspection. Meat’s shelf life will vary depending on how it was
processed or how it is stored. There is need for strict inspection measures since consumption of
spoiled or adulterated beef has serious implications on consumers’ health. In Kenya, as meat
consumption is high, beef inspection becomes very essential for food safety and quality.
In Kenya, annual red meat production is estimated at 362,815 Metric Tonnes (MT) of which beef
constitutes about 286,000 MT(Aklilu et al., 2002). Although there are around 2500 export
slaughterhouses available, only about 500 meat inspectors have been certified thus leaving a
massive inspection capacity gap (KEPSA 2019) posing a challenge to meat inspection. Kenyan
law as provided for in Kenya Meat Control Act (Cap 356) prescribes that meat inspection should
be performed exclusively by veterinarians. The process of Meat Inspection is clearly outlined in
the Kenya Meat Control Act (Cap 356) (1972). A thorough journey, which begins a day before the
animal is killed and ends at the market where meat ends up, involves inspections at the export
slaughter house, ante mortem checks, detailed post mortems and life at the shelves.
All these processes are supposed to be done by qualified meat inspectors who unfortunately are in
short supply. It is this shortage of personnel that results into a situation where inspecting officers
find themselves overstretched and as a result, they tend to focus on inspections at the slaughter
houses and cannot effectively concentrate on ensuring freshness of meat stocked on shelves. This
condition strains already existing workers and calls into question the efficiency of meat inspection
protocols as well as consumer confidence in beef safety and quality.

Additional Files

Published

2025-07-18

How to Cite

Muthomi, M. ., Dr. Samson Munialo, & Dr. Mary Mwadulo. (2025). MIRERC 040/2025: A Two-Stream Deep Learning Approach for Freshness Classification in Beef. MUST Institutional Research Ethics Review Committee System - MIRERC, 3. Retrieved from https://mirerc.must.ac.ke/index.php/MIRERC/article/view/39

Issue

Section

Environmental & Natuaral Sciences