Template-Type: ReDIF-Article 1.0 Author-Name: Sang-O Park Author-Workplace-Name: Institute of Animal Life Science, Kangwon National University, Chuncheon, Republic of Korea Title: Application strategy for sustainable livestock production with farm animal algorithms in response to climate change up to 2050: A review Abstract: Global warming caused by climate change can increase heat stress and greenhouse gas (GHG) emissions, leading to food problems and livestock crises. Thus, pre-emptive responses are required to mitigate the food problems and livestock crises. The potential of a livestock crisis caused by global warming highlights the need for sustainable livestock production in response to climate change using a farm animal algorithm in order to address the population increase and avoid food problems in the future. In particular, the demand for animal-based foods has increased. Such a climate change threatens the livestock environment, production, reproductive efficiency, animal behaviour and welfare, while increasing the heat stress, livestock malodours, and GHG emissions. For these reasons, it is necessary to understand the concurrent mechanisms related to these effects of global warming, animal nutrition, animal feeding and management, animal heat stress and in ovo injection, and carbon neutral livestock. Climate-smart livestock systems are being implemented to overcome the livestock crisis caused by climate change and to maintain sustainable livestock production. This review emphasises the importance of sustainable livestock production using farm animal algorithms in response to a future livestock crisis caused by climate change in 2050. Keywords: carbon neutral, livestock crisis, heat stress, in ovo, smart livestock Journal: Czech Journal of Animal Science Pages: 425-441 Volume: 67 Issue: 11 Year: 2022 DOI: 10.17221/172/2022-CJAS File-URL: http://cjas.agriculturejournals.cz/doi/10.17221/172/2022-CJAS.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/cjs-202211-0001.txt Handle: RePEc:caa:jnlcjs:v:67:y:2022:i:11:id:172-2022-CJAS Template-Type: ReDIF-Article 1.0 Author-Name: Fang Wang Author-Workplace-Name: Animal Nutritional Genome and Germplasm Innovation Research Center, College of Animal Science and Technology, Hunan Agricultural University, Changsha, P.R. China Author-Name: Linfeng Lei Author-Workplace-Name: Animal Nutritional Genome and Germplasm Innovation Research Center, College of Animal Science and Technology, Hunan Agricultural University, Changsha, P.R. China Author-Workplace-Name: Hunan International Joint Laboratory of Animal Intestinal Ecology and Health, Laboratory of Animal Nutrition and Human Health, College of Life Sciences, Hunan Normal University, Changsha, P.R. China Author-Name: Zhaobin Wang Author-Workplace-Name: Hunan International Joint Laboratory of Animal Intestinal Ecology and Health, Laboratory of Animal Nutrition and Human Health, College of Life Sciences, Hunan Normal University, Changsha, P.R. China Author-Name: Yulong Yin Author-Workplace-Name: Animal Nutritional Genome and Germplasm Innovation Research Center, College of Animal Science and Technology, Hunan Agricultural University, Changsha, P.R. China Author-Name: Huansheng Yang Author-Workplace-Name: Hunan International Joint Laboratory of Animal Intestinal Ecology and Health, Laboratory of Animal Nutrition and Human Health, College of Life Sciences, Hunan Normal University, Changsha, P.R. China Author-Name: Zhe Yang Author-Workplace-Name: Animal Nutritional Genome and Germplasm Innovation Research Center, College of Animal Science and Technology, Hunan Agricultural University, Changsha, P.R. China Author-Name: Jiashun Chen Author-Workplace-Name: Animal Nutritional Genome and Germplasm Innovation Research Center, College of Animal Science and Technology, Hunan Agricultural University, Changsha, P.R. China Title: Differentially expressed genes in the longissimus dorsi muscle between the Chinese indigenous Ningxiang pig and Large White breed using RNA sequencing Abstract: High intramuscular fat content of pigs improves pork quality and increasing intramuscular fat deposition is a long-term goal in the husbandry of pigs reared for meat production. There are significant phenotypic differences between the Ningxiang (NX) pigs (an indigenous Chinese breed) and Large White (LW) pigs (a western, lean-type breed). The present work aimed to gain insight into the longissimus dorsi muscle transcriptome between the two pig breeds. We investigated the molecular basis of these differences by comparing their transcriptome profiles. RNA-seq technology was used to identify the differentially expressed genes (DEGs) in the longissimus dorsi muscle of the NX and LW pigs. We obtained 692 million clean reads using transcriptome sequencing of muscle samples from the two pig breeds. A total of 885 DEGs were identified, including 469 upregulated and 416 downregulated genes in the NX pigs compared with the LW pigs. Using KEGG pathway analysis, it was found that the significant DEGs were mainly enriched in metabolism-related pathways, such as lipid metabolism and biosynthesis, and glucose metabolism or biosynthesis. Quantitative real-time PCR confirmed the differential expression of eight selected DEGs in both pig breeds. qPCR results showed that the RNA-seq results were reliable. Several DEGs were candidate functional genes related to the lipid metabolism, including CD36, LIPE, MCAT, LPIN1, ANGPTL4, PPARD, SCD, INSR, MOGAT, IGF1, AKT2 and JAK2. Our results provide a comprehensive basis for the investigation of the differences in transcriptional regulation of the muscles between divergent phenotypes. Keywords: differentially expressed genes, fatty-type breed, intramuscular fat deposition, lean-type breed Journal: Czech Journal of Animal Science Pages: 442-453 Volume: 67 Issue: 11 Year: 2022 DOI: 10.17221/103/2022-CJAS File-URL: http://cjas.agriculturejournals.cz/doi/10.17221/103/2022-CJAS.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/cjs-202211-0002.txt Handle: RePEc:caa:jnlcjs:v:67:y:2022:i:11:id:103-2022-CJAS Template-Type: ReDIF-Article 1.0 Author-Name: Cem Tirink Author-Workplace-Name: Department of Animal Science, Faculty of Agriculture, Igdir University, Igdir, Turkey Author-Name: Hasan Önder Author-Workplace-Name: Department of Animal Science, Faculty of Agriculture, Ondokuz Mayis University, Samsun, Turkey Author-Name: Sabri Yurtseven Author-Workplace-Name: Department of Animal Science, Faculty of Agriculture, Harran University, Sanliurfa, Turkey Author-Name: Zeliha Kaya Akil Author-Workplace-Name: Department of Animal Science, Faculty of Agriculture, Harran University, Sanliurfa, Turkey Title: Comparison of some non-linear functions to describe the growth for Linda geese with CART and XGBoost algorithms Abstract: The aim of this study was to determine the best non-linear function describing the growth of the Linda goose breed. To achieve this aim, five non-linear functions, such as exponential, logistic, von Bertalanffy, Brody and Gompertz, were employed to define the live weight-age relationship for male and female Linda geese. In the study, 2 397 body weight-age records from 75 females and 66 males collected from three days to 17 weeks of age were evaluated using the "easynls" and "nlstools" packages for growth modelling of the Linda goose in R software. Each model was analysed in the live weight records of all the geese separately for males and females. To measure the predictive quality of the growth functions used individually here, model goodness of fit criteria, such as the coefficient of determination (R2), adjusted coefficient of determination (R2adj), root mean square error (RMSE), Akaike's information criterion (AIC) and Bayesian information criterion (BIC) were implemented. Among the evaluated non-linear functions, von Bertalanffy model gave the best fit of describing the growth curve of female and male Linda geese. Based on the "rpart", "rpart.plot", and "caret" R packages, the CART and XGBoost algorithms were specified in the prediction of live weight of Linda geese at 17 weeks of age from the growth parameters of the von Bertalanffy model and the sex factor. XGBoost produced better results in superiority compared with the CART algorithm. In conclusion, it could be suggested that the von Bertalanffy model might help geese breeders to determine the appropriate slaughtering time, feeding regimes, and overcome flock management problems. The results of the XGBoost algorithm might present a good reference for breeders to establish breed standards and selection strategies of Linda geese in the growth parameters for breeding purposes. Keywords: body weight, goose growth curve, non-linear models, XGBoost, CART Journal: Czech Journal of Animal Science Pages: 454-464 Volume: 67 Issue: 11 Year: 2022 DOI: 10.17221/129/2022-CJAS File-URL: http://cjas.agriculturejournals.cz/doi/10.17221/129/2022-CJAS.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/cjs-202211-0003.txt Handle: RePEc:caa:jnlcjs:v:67:y:2022:i:11:id:129-2022-CJAS Template-Type: ReDIF-Article 1.0 Author-Name: Oleksandr Malinovskyi Author-Name: Lukáš Veselý Author-Workplace-Name: Faculty of Fisheries and Protection of Waters, South Bohemian Research Centre of Aquaculture and Biodiversity of Hydrocenoses, University of South Bohemia in České Budějovice, Vodňany, Czech Republic Author-Name: Carlos Yanes-Roca Author-Workplace-Name: Faculty of Fisheries and Protection of Waters, South Bohemian Research Centre of Aquaculture and Biodiversity of Hydrocenoses, University of South Bohemia in České Budějovice, Vodňany, Czech Republic Author-Name: Tomáš Policar Author-Workplace-Name: Faculty of Fisheries and Protection of Waters, South Bohemian Research Centre of Aquaculture and Biodiversity of Hydrocenoses, University of South Bohemia in České Budějovice, Vodňany, Czech Republic Title: The effect of water temperature, prey availability and presence of conspecifics on prey consumption of pikeperch (Sander lucioperca) Abstract: In this study, the effect of water temperature, predator's sex, prey density, and the presence of conspecifics on prey consumption of pikeperch (Sander lucioperca) was experimentally tested. In Experiment 1, predators of both sexes [males: total length (TL) = 473 ± 22 mm and body weight (BW) = 1 070 ± 100 g and females: TL = 464 ± 12 mm and BW = 1 060 ± 100 g] were kept in separate tanks and exposed to different densities of prey (Pseudorasbora parva; 3, 6, 12, 24 and 48 prey fishes per tank) under fixed water temperatures of 4.5 °C, 8.5 °C, and 12.5 °C. After 63 days of this experiment, it was found that pikeperch predation was significantly affected by increasing water temperature. The effect of prey density was significant at all tested temperatures. Pikeperch females tended to have the higher prey consumption than males, although that trend was statistically insignificant. Results suggest that increased feeding demands at temperatures above 4.5 °C can lead to predator starvation in conditions of low prey availability. Due to the higher prey consumption, pikeperch females could be more vulnerable to low prey availability during their culture. In Experiment 2, pikeperch were kept at different densities of 1, 2, 4, and 8 individuals per tank supplied with a prey rate of 50 individuals per predator, ensuring ad libitum feeding rate. The average daily prey consumption was significantly higher in the tanks with multiple predators, accounting for 17.6 ± 3.57 prey fishes/day compared to 11.6 ± 2.33 prey fishes/day in the tank with a single predator. These results indicate that pikeperch predation activity and prey consumption can be significantly affected by the water temperature, prey availability, and the presence of conspecifics. The findings contribute to understanding the predatory function, natural feeding request of pikeperch and its potential importance for broodstock culture and broodstock final maturation for a successful spawning season. Also, this information can be used for better management of pikeperch pond aquaculture or bio-melioration process in open water bodies and ecosystems. Keywords: feeding behaviour, predation, competition, pond aquaculture, water bodies Journal: Czech Journal of Animal Science Pages: 465-473 Volume: 67 Issue: 11 Year: 2022 DOI: 10.17221/162/2022-CJAS File-URL: http://cjas.agriculturejournals.cz/doi/10.17221/162/2022-CJAS.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/cjs-202211-0004.txt Handle: RePEc:caa:jnlcjs:v:67:y:2022:i:11:id:162-2022-CJAS