Understanding the composition of the microbial community and its functional capacity during weaning is important for pig production as bacteria play important roles in the pig’s health and growth performance. However, limited information is available regarding the composition and function of the gut microbiome of piglets in early-life. Therefore, we performed 16S rRNA gene and whole metagenome shotgun sequencing of DNA from fecal samples from healthy piglets during weaning to measure microbiome shifts, and to identify the potential contribution of the early-life microbiota in shaping piglet health with a focus on microbial stress responses, carbohydrate and amino acid metabolism. The analysis of 16S rRNA genes and whole metagenome shotgun sequencing revealed significant compositional and functional differences between the fecal microbiome in nursing and weaned piglets. The fecal microbiome of the nursing piglets showed higher relative abundance of bacteria in the genus Bacteroides with abundant gene families related to the utilization of lactose and galactose. Prevotella and Lactobacillus were enriched in weaned piglets with an enrichment for the gene families associated with carbohydrate and amino acid metabolism. In addition, an analysis of the functional capacity of the fecal microbiome showed higher abundances of genes associated with heat shock and oxidative stress in the metagenome of weaned piglets compared to nursing piglets. Overall, our data show that microbial shifts and changes in functional capacities of the piglet fecal microbiome resulted in potential reductions in the effects of stress, including dietary changes that occur during weaning. These results provide us with new insights into the piglet gut microbiome that contributes to the growth of the animal.

Porcine respiratory disease complex is an economically important disease in the swine industry. Early detection of the disease is crucial for immediate response to the disease at the farm level to prevent and minimize the potential damage that it may cause. In this paper, recent studies on the application of artificial intelligence (AI) in the early detection and monitoring of respiratory disease in swine have been reviewed. Most of the studies used coughing sounds as a feature of respiratory disease. The performance of different models and the methodologies used for cough recognition using AI were reviewed and compared. An AI technology available in the market was also reviewed. The device uses audio technology that can monitor and evaluate the herd’s respiratory health status through cough-sound recognition and quantification. The device also has temperature and humidity sensors to monitor environmental conditions. It has an alarm system based on variations in coughing patterns and abrupt temperature changes. However, some limitations of the existing technology were identified. Substantial effort must be exerted to surmount the limitations to have a smarter AI technology for monitoring respiratory health status in swine.

In animal farming, timely estrus detection and prediction of the best moment for insemination is crucial. Traditional sow estrus detection depends on the expertise of a farm attendant which can be inconsistent, time-consuming, and labor-intensive. Attempts and trials in developing and implementing technological tools to detect estrus have been explored by researchers. The objective of this review is to assess the automatic methods of estrus recognition in operation for sows and point out their strong and weak points to assist in developing new and improved detection systems. Real-time methods using body and vulvar temperature, posture recognition, and activity measurements show higher precision. Incorporating artificial intelligence with multiple estrus-related parameters is expected to enhance accuracy. Further development of new systems relies mostly upon the improved algorithm and accurate data provided. Future systems should be designed to minimize the misclassification rate, so better detection is achieved.

The importance of backfat thickness in sows lies in its correlation with nutritional status, reproductive performance, and overall health. Identifying the optimum backfat thickness is crucial for determining the ideal energy reserves needed to support successful reproduction and lactation. This research aimed to determine optimal backfat thickness (BFT) of sows in relation to reproductive and lactation performance. In this study, 32 lactating sows were housed in a controlled environment and assigned to four groups based on their BFT before farrowing: <17.00 mm, 17.00–17.99 mm, 18.00–18.99 mm, and ≥19.00 mm. The data were analyzed with One-way analysis of variance, and the association between backfat thickness and sow reproductive performance was examined through Spearman’s correlation analysis using SAS software. The results revealed no significant difference between the groups in total born, total born alive, and litter size weaned, but the piglets’ survival rate during the lactation period is lower from sows with BFT < 17.00. Moreover, piglet birth weight and body weight at Day 3 were significantly lower in sows with BFT < 17.00 mm. The BFT of sows at weaning showed significant differences among the groups associated with the backfat thickness before farrowing. No significant difference was found in the duration of farrowing. The return-to-estrus interval was longer in sows with <17.00 mm BFT than in those with 17.00–17.99 mm, 18.00–18.99 mm, and ≥19.00 mm backfat thickness, with estrus intervals of 7.17, 6.25, 5.31, and 5 days after weaning, respectively. Numerically, calculated milk yield (MY) is lowest in sows with BFT < 17.00, and the highest MY was obtained from sows with BFT 18.00–18.99 mm. In conclusion, sows with at least 17.00 mm BFT before farrowing are ideal for increasing the lifetime productivity of sows. This study provides valuable insights into the importance of sow management during gestation for subsequent reproductive success.

Journal of Animal Science and Technology (JAST) is a peer-reviewed, open access journal publishing original research, review articles and notes in all fields of animal science. Topics covered by the journal include: genetics and breeding, physiology, nutrition of monogastric animals, nutrition of ruminants, animal products (milk, meat, eggs and their by-products) and their processing, grasslands and roughages, livestock environment, animal biotechnology, animal behavior and welfare.

Journal of Animal Science and Technology (JAST) is a peer-reviewed, open access journal publishing original research, review articles and notes in all fields of animal science. Topics covered by the journal include: genetics and breeding, physiology, nutrition of monogastric animals, nutrition of ruminants, animal products (milk, meat, eggs and their by-products) and their processing, grasslands and roughages, livestock environment, animal biotechnology, animal behavior and welfare.