Template-Type: ReDIF-Article 1.0 Author-Name: Roman Bumbálek Author-Workplace-Name: Department of Technology and Cybernetics, Faculty of Agriculture and Technology, University of South Bohemia in Ceske Budejovice, Ceske Budejovice, Czech Republic Author-Name: Jean de Dieu Marcel Ufitikirezi Author-Workplace-Name: Department of Technology and Cybernetics, Faculty of Agriculture and Technology, University of South Bohemia in Ceske Budejovice, Ceske Budejovice, Czech Republic Author-Name: Tomáš Zoubek Author-Workplace-Name: Department of Technology and Cybernetics, Faculty of Agriculture and Technology, University of South Bohemia in Ceske Budejovice, Ceske Budejovice, Czech Republic Author-Name: Sandra Nicole Umurungi Author-Workplace-Name: Department of Technology and Cybernetics, Faculty of Agriculture and Technology, University of South Bohemia in Ceske Budejovice, Ceske Budejovice, Czech Republic Author-Name: Radim Stehlík Author-Workplace-Name: Department of Technology and Cybernetics, Faculty of Agriculture and Technology, University of South Bohemia in Ceske Budejovice, Ceske Budejovice, Czech Republic Author-Name: Zbyněk Havelka Author-Workplace-Name: Department of Technology and Cybernetics, Faculty of Agriculture and Technology, University of South Bohemia in Ceske Budejovice, Ceske Budejovice, Czech Republic Author-Name: Radim Kuneš Author-Workplace-Name: Department of Technology and Cybernetics, Faculty of Agriculture and Technology, University of South Bohemia in Ceske Budejovice, Ceske Budejovice, Czech Republic Author-Name: Petr Bartoš Author-Workplace-Name: Department of Technology and Cybernetics, Faculty of Agriculture and Technology, University of South Bohemia in Ceske Budejovice, Ceske Budejovice, Czech Republic Author-Workplace-Name: Department of Applied Physics and Technology, Faculty of Education, University of South Bohemia in Ceske Budejovice, Ceske Budejovice, Czech Republic Title: Computer vision-based approaches to cattle identification: A comparative evaluation of body texture, QR code, and numerical labelling Abstract: Cattle identification systems are advancing to meet the growing demands of precision livestock management, traceability, and ethical animal treatment. This study investigates three methods: body texture recognition, QR code collars, and numerical labelling, implemented using the YOLOv8 convolutional neural network. Each method was evaluated in terms of accuracy, scalability, adaptability to dynamic herd changes, and operational efficiency under various environmental conditions. Body texture recognition, while leveraging unique natural patterns and achieving a mean Average Precision (mAP50-95) of 0.78 proved limited by its reliance on frequent dataset retraining to accommodate changes in herd composition and susceptibility to misidentification in larger herds. QR code collars demonstrated adaptability in dynamic herds by enabling pre-trained convolutional neural networks to assign reserved codes to new animals without retraining, while removing animals involves simply deleting their codes from the system. This approach also achieved an mAP50-95 of 0.71, which was lower than the body texture-based approach, but offered greater flexibility in herd management. Despite this adaptability, this method demonstrated significant challenges in real-world environments. Occlusion caused by feeders, barriers, or animal movements, along with low-resolution imaging and poor lighting conditions, can compromise detection accuracy, particularly in larger herds with obstructive barn layouts. The numerical labelling method emerged as the most effective solution to dynamic cattle identification, achieving the highest mAP50-95 of 0.84. It provided a scalable and highly accurate approach that integrates seamlessly with automated systems. Unlike traditional body marking techniques such as ear notching and branding, numerical labelling is less invasive, painless, and highly scalable, aligning with ethical livestock management practices while maintaining consistent accuracy across diverse environmental conditions. Keywords: animal welfare, convolutional neural networks, herd monitoring, livestock biometrics, object detection, precision livestock farming Journal: Czech Journal of Animal Science Pages: 383-396 Volume: 70 Issue: 9 Year: 2025 DOI: 10.17221/66/2025-CJAS File-URL: http://cjas.agriculturejournals.cz/doi/10.17221/66/2025-CJAS.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/cjs-202509-0001.txt Handle: RePEc:caa:jnlcjs:v:70:y:2025:i:9:id:66-2025-CJAS Template-Type: ReDIF-Article 1.0 Author-Name: Kristýna Klímová Author-Workplace-Name: Department of Animal Science, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic Author-Name: Kristýna Lokvencová Author-Workplace-Name: Department of Animal Science, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic Author-Name: Ivan Bahelka Author-Workplace-Name: Department of Animal Science, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic Author-Name: Kateřina Zadinová Author-Workplace-Name: Department of Animal Science, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic Author-Name: Roman Stupka Author-Workplace-Name: Department of Animal Science, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic Author-Name: Jaroslav Čítek Author-Workplace-Name: Department of Animal Science, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic Title: Estimation of lean meat percentage in pig carcass with the use of objective methods with regard to sex Abstract: In the Czech Republic, the pig carcass classification is mandatory in slaughterhouses processing over 200 pigs weekly. As breeding practices evolve to enhance lean meat yield, it is essential to update regression equations used in classification systems. This study presents new regression models for the Fat-O-Meater II (FOM II) device, using computed tomography (CT) as the reference method. Separate equations were developed for barrows, gilts, and boars to improve the accuracy of lean meat percentage (LMC) estimation. To calibrate the CT method, 24 carcasses were selected across a range of backfat thicknesses and sexes. CT scans were performed on chilled left carcass halves, followed by manual dissection to determine the true LMC. A correction model was applied to align the CT-derived LMC with dissection results. Subsequently, 128 carcasses were measured using FOM II and CT to develop sex-specific regression equations using ordinary least squares. The models revealed sex-specific differences in prediction accuracy. Gilts achieved an R2 of 0.66 and RMSEP of 1.35; barrows had higher R2 (0.759) and greater RMSEP (1.46); boars showed the most consistent composition (R2 = 0.734, RMSEP = 1.14). Compared to the standard method, gilts and boars had slightly higher LMC (+0.03% and +0.82%), while barrows had lower LMC (-0.14%). These differences translated into economic impacts, with gains of CZK 1.23 and CZK 4.33 per gilt and boar carcass, respectively, and a loss of CZK 5.55 per barrow carcass. These results support the formulated hypotheses, and the fact that sex-specific calibration enhances classification accuracy and economic efficiency. Keywords: computed tomography, Fat-O-Meater II, lean meat percentage, pig carcass, sex Journal: Czech Journal of Animal Science Pages: 397-403 Volume: 70 Issue: 9 Year: 2025 DOI: 10.17221/72/2025-CJAS File-URL: http://cjas.agriculturejournals.cz/doi/10.17221/72/2025-CJAS.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/cjs-202509-0002.txt Handle: RePEc:caa:jnlcjs:v:70:y:2025:i:9:id:72-2025-CJAS Template-Type: ReDIF-Article 1.0 Author-Name: Filip Benko Author-Workplace-Name: Institute of Biotechnology, Faculty of Biotechnology and Food Sciences, Slovak University of Agriculture in Nitra, Nitra, Slovak Republic Author-Name: Tomáš Slanina Author-Workplace-Name: Institute of Applied Biology, Faculty of Biotechnology and Food Sciences, Slovak University of Agriculture in Nitra, Nitra, Slovak Republic Author-Name: Michal Ďuračka Author-Workplace-Name: AgroBioTech Research Centre, Slovak University of Agriculture in Nitra, Nitra, Slovak Republic Author-Name: Miroslava Kačániová Author-Workplace-Name: Institute of Horticulture, Faculty of Horticulture and Landscape Engineering, Slovak University of Agriculture in Nitra, Nitra, Slovak Republic Author-Workplace-Name: School of Medical and Health Sciences, University of Economics and Human Sciences in Warsaw, Warsaw, Poland Author-Name: Eva Tvrdá Author-Workplace-Name: Institute of Biotechnology, Faculty of Biotechnology and Food Sciences, Slovak University of Agriculture in Nitra, Nitra, Slovak Republic Author-Workplace-Name: Chair of Animal Breeding and Biotechnology, Institute of Veterinary Medicine and Animal Sciences, Estonian University of Life Sciences, Tartu, Estonia Title: Cryopreservative and antimicrobial properties of kaempferol on the post-thaw quality of turkey spermatozoa Abstract: At present, the low post-thaw quality of poultry semen presents a challenge to develop new strategies for its cryopreservation. The purpose of this research was to assess the impact of kaempferol (KAE) on post-thaw turkey sperm characteristics (motility, membrane and acrosome integrity, mitochondrial function), oxidative and microbial profile. Turkey semen (n = 40) was diluted and cryopreserved in modified Beltsville extender with 5, 10, and 25 µM of KAE or without it (cryopreserved control - CtrlC), while fresh semen served as negative control (CtrlN). Following thawing, parameters were evaluated including sperm motility, membrane and acrosome integrity, mitochondrial functionality, DNA fragmentation index, apoptosis status, global reactive oxygen species (ROS) generation, lipid peroxidation (LPO) and protein oxidation. Bacterial identification was performed by matrix-assisted laser desorption/ionisation mass spectrometry. Our data suggest that motility, membrane and acrosome integrity, mitochondrial activity continuously increased correspondingly to KAE concentration versus CtrlC (P < 0.05) while cell apoptosis, ROS generation, LPO and protein oxidation were significantly decreased in KAE treated groups versus CtrlC (P < 0.05). Bacterial growth was suppressed in all KAE-treated groups, which acted synergistically with penicillin to eradicate most bacterial strains from cryopreserved samples versus CtrlN. Finally, our results suggest that KAE possesses strong antioxidant and antimicrobial properties which may be used to improve commercially available extenders for more effective preservation of turkey spermatozoa. Keywords: extender, flavonoid, freezing, poultry, reproduction Journal: Czech Journal of Animal Science Pages: 404-413 Volume: 70 Issue: 9 Year: 2025 DOI: 10.17221/79/2025-CJAS File-URL: http://cjas.agriculturejournals.cz/doi/10.17221/79/2025-CJAS.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/cjs-202509-0003.txt Handle: RePEc:caa:jnlcjs:v:70:y:2025:i:9:id:79-2025-CJAS Template-Type: ReDIF-Article 1.0 Author-Name: Tereza Paulová Author-Workplace-Name: Department of Microbiology, Nutrition and Dietetics, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic Author-Workplace-Name: Department of Nutritional Physiology and Animal Product Quality, Institute of Animal Science Prague (IAS), Prague, Czech Republic Author-Name: Karel Novák Author-Workplace-Name: Department of Genetics and Breeding of Farm Animals, Institute of Animal Science Prague (IAS), Prague, Czech Republic Author-Name: Eva Pěchoučková Author-Workplace-Name: Department of Microbiology, Nutrition and Dietetics, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic Author-Workplace-Name: Department of Nutritional Physiology and Animal Product Quality, Institute of Animal Science Prague (IAS), Prague, Czech Republic Title: Antimicrobial properties of secondary metabolites of Cannabis sativa: A promising natural alternative for livestock health Abstract: In addition to their practical importance as a medicinal plant, animal feed and a source of materials for the textile and construction industry, industrial varieties of Cannabis sativa L. (hemp in a wider sense) provide an alternative for controlling infectious diseases in livestock. Despite the genetic divergence between two primary groups of cannabis, i.e. medicinal cannabis and technical hemp, hemp plants also produce a wide spectrum of secondary metabolites. These include the main classes of cannabinoids and terpenoids, as well as representatives of flavonoids, stilbenoids, steroids, alkaloids, spiroindans, dihydrophenanthrenes, and lignanamides. Many of them exhibit antibiotic activity which can substitute or complement the use of traditional antibiotics in animal husbandry. For example, the cannabinoid fraction exhibits activity against the Gram-positive bacteria and some fungi. While the activity against Gram-negative bacteria is not characteristic of cannabinoids, these pathogens can still be affected by hemp terpenoids and flavonoids. The synergy among the secondary metabolite fractions or between the hemp metabolites and traditional antibiotics is also a favourable factor. The search for alternatives to traditional antibiotics is further driven by the increasing prevalence of genetically determined antibiotic resistance among veterinary pathogens, which poses the additional risk of transferring resistance traits to the human pathogens. The content of antibiotically active compounds in hemp can be enhanced through selection among existing genotypes, targeted breeding, cultivation conditions, and even by specific elicitation of secondary metabolites with the natural antibiotic function in the disease resistance of the plant. The switch to hemp metabolites is also supported by their compatibility as natural components of plant-based animal feed, and by favourable economic considerations. Keywords: antibiotic, cannabidiol, cattle, hemp, poultry, Staphylococcus, THC Journal: Czech Journal of Animal Science Pages: 357-382 Volume: 70 Issue: 9 Year: 2025 DOI: 10.17221/85/2025-CJAS File-URL: http://cjas.agriculturejournals.cz/doi/10.17221/85/2025-CJAS.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/cjs-202509-0004.txt Handle: RePEc:caa:jnlcjs:v:70:y:2025:i:9:id:85-2025-CJAS