Understanding meat categorization is a fundamental component of veterinary education, especially within the context of food hygiene and public health. Veterinary students must grasp legal classifications of meat, which depend on variables such as species, age, quality, and processing techniques. This knowledge is essential for accurate meat inspection, labeling, and compliance with both national and international food safety standards. Despite prior exposure to muscle anatomy in anatomy course, students often face challenges in applying this knowledge to practical meat classification tasks. This study aimed to assess the effectiveness of three distinct instructional methods in improving veterinary students’ ability to identify meat categories and associated muscle structures: traditional classroom teaching, computer-based instruction using 3D models, and immersive virtual reality (VR). Participants included fourth-year veterinary students during the summer semester of the 2024/2025 academic year. To facilitate digital learning, a dedicated 3D model library “3DMeat” was developed as well as virtual reality environment. Results indicate that technology-enhanced instructional approaches, can significantly enhance student engagement and understanding of complex topics such as meat categorization. Initial test scores were highest in the group using 3D models (16.3 ± 4.1), followed by the traditional lecture-based group (15.6 ± 3.07), and the VR group (11.7 ± 5.1). However, a follow-up assessment conducted 2 weeks later revealed that VR group demonstrated the highest retention of knowledge. These findings suggest that although immediate performance may vary, immersive learning environments such as VR can foster stronger medium-term retention of complex material.

Listeria je patogen prenosiv hranom i predstavlja veliku opasnost za ljudsko zdravlje. Teški su simptomi praćeni visokom stopom mortaliteta većinom prouzročeni L. monocytogenes. Bez obzira na politiku nulte tolerancije, rod Listeria je još uvijek prisutan u sirovim proizvodima i proizvodima spremnim za konzumiranje, predstavljajući veliku opasnost za zdravlje ljudi. Za sada još u bliskoj budućnosti ne postoje studije o kontaminaciji hrane vrstama Listeria u Bosni i Hercegovini. Ovim istraživanjem htjeli smo dobiti osnovne podatke o količini kontaminiranosti hrane ovim patogenom. U studiji je analizirano ukupno 238 uzoraka hrane, pri čemu su u 105 uzorka bile različite vrste sirove hrane te 133 uzorka hrane spremne za konzumaciju (gotove hrane). Od ukupno 238 uzoraka, 18 uzoraka je bilo pozitivno na Listeria vrste. Nakon izolacije i detekcije, konfirmacija pozitivnih izolata Listeria spp. je provedena pomoću biokemijskog kita API® Listeria.

Meat inspection is an important part of education for every veterinary student. However, traditional teaching methods require the sacrifice of living animals, and are thus considered expensive, inadequate and inhumane. Development of novel technologies has provided opportunities for new, improved ways of education. Smart 3D Meat Inspection (S3DMI) is an elearning tool that allows veterinary medicine students to acquire required skills using virtual 3D models of animal organs and carcasses. These models can be manipulated and “cut” just like real organs, allowing students to learn this essential skill without the need for animal carcasses. Students are allowed to practice any part of meat inspection as many times necessary, at their own pace, without time, place or resources limitations. This type of education is considered superior to traditional methods. There is no need for sacrification of animals for educational purposes and the cost of education is greatly reduced, while the educational quality is uninterrupted. Models developed for S3DMI can also be adjusted for courses like animal anatomy and pathology, which also require the use of real animal cadavers. S3DMI is still in its developmental stages, but it has a great potential to minimalize the need for animal sacrifice in the education of future veterinarians, while ensuring the quality improvement.

The increase of global fish consumption brings with it the problem of fish mislabeling, which leads to economic losses for consumers or may even result in consumers’ health risk. Thus, continuous development of methods used in identification of exact fish species is essential. There are numerous modern identification methods, which use DNA or specific fish proteins as biomarkers, but they all come with various benefits and drawbacks. Protein-based methods include electrophoretic methods, ELISA, HPLC and MALDI-ToF Mass Spectrometry, while the methods that use DNA as a biomarker include PCR-RFLP, SSCP, qPCR, RAPD, FINS, DNA microarray, DNA barcoding, pyrosequencing and metabarcoding. There is a continuous development of new or improved methods. Most of the methods display a much better performance when analyzing raw or lightly processed fish, such as chilled or frozen, while heat treatment often leads to changes in the biomarker molecules, making the species identification difficult. The ideal method does not yet exist, but methods such as DNA barcoding, MALDI-ToF Mass Spectrometry and metabarcoding are the ones that show most potential.