Logistic Regression Analysis Factors Affecting Sperm Motility and Abnormal Sperm Morphology in Boars

The Effects of Claw Health and Bone Mineral Density on Lameness in Duroc Boars

To investigate the effects of claw lesion types and bone mineral density on lameness in boars, the data of claw lesion score, gait score, and bone mineral density, measured by a Miniomin ultrasound bone densitometer, were collected from a total of 739 Duroc boars. Firstly, we discovered that the prevalence of claw lesions was as high as 95.26% in boars. The percentage of lameness of boars with SWE was higher than those with other claw lesions. Meanwhile, the results showed that the probability of lameness was higher in boars with lower bone mineral density (p < 0.05). Logistic regression models, including variables of boar age, body weight, serum mineral level, and housing type, were used to identify the influencing factors of bone mineral density in this study. The results found that bone mineral density increases with age before reaching a maximum value at 43 months of age, and begins to decrease after 43 months of age. Elevated serum Ca levels were significantly associated with an increase in bone mineral density (p < 0.05). Aside from the above findings, we also made an interesting discovery that boars in the individual pen model significantly increased bone mineral density compared to those in the individual stall model. In conclusion, claw lesions and bone mineral density were significantly associated with lameness. Age, serum Ca, and housing type are the potential influencing factors for bone mineral density in boars.

Cluster analysis and potential influencing factors of boars with different fertility

The fertility of boars is intimately tied to the pig farm's economic benefits. This study aimed to rapidly categorize boars of different fertility and investigate the factors influencing the categorization using the production data in a large pig farm in northern China, including 11,163 semen collection records of Yorkshire boars (215), 11,163 breeding records and 8770 records of farrowing performance of Yorkshire sows (4505), as well as 4720 records of selection indices (sire line index and dam line index) for boars and sows (215 and 4505) between 2017 and 2020. The boar population was classified by two-step cluster analysis, followed by factor analysis to minimize the dimensionality of data variables and eliminate multicollinearity, and then using ordinal logistic regression model to investigate the risk variables impacting boar fertility categorization. Results showed that the two-step clustering divided the 215 boars into three subgroups: high-fertility (n = 61, 28.4%), medium-fertility (n = 127, 59.1%) and low-fertility (n = 27, 12.6%). The high-fertility boars were shown to be substantially greater than the medium-fertility or low-fertility boars (p < 0.05) in average total litter size, number of born alive, and number of healthy piglets of mated sows. Compared with low-fertility boars, the high-fertility boars were also significantly higher (p < 0.05) in the pregnancy rate and farrowing rate of mated sows. However, the three boar subgroups showed no difference (p > 0.05) in semen quality information (average sperm motility, average sperm density, and average sperm volume). Collinearity diagnosis indicated severe multicollinearity among the 20 data variables, which were reduced to 8 factor variables (factors 1-8) by factor analysis, and further collinearity diagnosis exhibited no multicollinearity among the 8 factor variables. Ordered logistic regression analysis revealed a significant and positive correlation (p < 0.05) of boar fertility with factor 2 (average total litter size, number of born alive, number of healthy piglets), factor 4 (average number of weak piglets and average weak piglet rate), factor 6 (sire line index of boars and dam line index of boars), factor 8 (pregnancy rate and farrowing rate), highlighting factor 2 as the most important factor influencing the classification of boar fertility. Our results indicate that the two-step cluster analysis can be used as a simple and effective method to screen boars with different fertility and that farm producers should pay attention to the recording of the reproductive performance of the mated sows due to its role as the risk factor for classification of boar fertility.

Tenets in Microbial Endocrinology: A New Vista in Teleost Reproduction

Climate vulnerability and induced changes in physico-chemical properties of aquatic environment can bring impairment in metabolism, physiology and reproduction in teleost. Variation in environmental stimuli mainly acts on reproduction by interfering with steroidogenesis, gametogenesis and embryogenesis. The control on reproductive function in captivity is essential for the sustainability of aquaculture production. There are more than 3,000 teleost species across the globe having commercial importance; however, adequate quality and quantity of seed production have been the biggest bottleneck. Probiotics are widely used in aquaculture as a growth promoter, stress tolerance, pathogen inhibition, nutrient digestibility and metabolism, reproductive performance and gamete quality. As the gut microbiota exerts various effects on the intestinal milieu which influences distant organs and pathways, therefore it is considered to be a full-fledged endocrine organ. Researches on Gut-Brain-Gonad axis (GBG axis) and its importance on physiology and reproduction have already been highlighted for higher mammals; however, the study on fish physiology and reproduction is limited. While looking into the paucity of information, we have attempted to review the present status of microbiome and its interaction between the brain and gut. This review will address a process of the microbiome physiological mechanism involved in fish reproduction. The gut microbiota influences the BPG axis through a wide variety of compounds, including neuropeptides, neurotransmitter homologs and transmitters. Currently, research is being conducted to determine the precise process by which gut microbial composition influences brain function in fish. The gut-brain bidirectional interaction can influence brain biochemistry such as GABA, serotonin and tryptophan metabolites which play significant roles in CNS regulation. This review summarizes the fact, how microbes from gut, skin and other parts of the body influence fish reproduction through the Gut-Brain-Gonad axis.