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The advent of artificial intelligence (AI) in animal husbandry, particularly in pig interaction recognition (PIR), offers a transformative approach to enhancing animal welfare, promoting sustainability, and bolstering climate resilience. This innovative methodology not only mitigates labor costs but also significantly reduces stress levels among domestic pigs, thereby diminishing the necessity for constant human intervention. However, the raw PIR datasets often encompass irrelevant porcine features, which pose a challenge for the accurate interpretation and application of these datasets in real-world scenarios. The majority of these datasets are derived from sequential pig imagery captured from video recordings, and an unregulated shuffling of data often leads to an overlap of data samples between training and testing groups, resulting in skewed experimental evaluations. To circumvent these obstacles, we introduced a groundbreaking solution—the Semi-Shuffle-Pig Detector (SSPD) for PIR datasets. This novel approach ensures a less biased experimental output by maintaining the distinctiveness of testing data samples from the training datasets and systematically discarding superfluous information from raw images. Our optimized method significantly enhances the true performance of classification, providing unbiased experimental evaluations. Remarkably, our approach has led to a substantial improvement in the isolation after feeding (IAF) metric by 20.2% and achieved higher accuracy in segregating IAF and paired after feeding (PAF) classifications exceeding 92%. This methodology, therefore, ensures the preservation of pertinent data within the PIR system and eliminates potential biases in experimental evaluations. As a result, it enhances the accuracy and reliability of real-world PIR applications, contributing to improved animal welfare management, elevated food safety standards, and a more sustainable and climate-resilient livestock industry. [ABSTRACT FROM AUTHOR]

Dystocia is a complication that occurs at parturition either due to foetal or maternal factors. This condition has been well studies in domesticated species. However, there is very little information on dystocia in the agouti (Dasyprocta leporina). The agouti is utilized for its meat in South America and the Caribbean. More recently, farming of these animals intensively is being practiced in the Neo-tropics. This case report attempted to provide some insight into dystocia in the agouti which has been rarely reported in animals in captivity. A female agouti weighing approximately 3 kg (kg), which was in the last stage of pregnancy, was found dead in its cage. The vulva of the animal had the hind-limbs of the offspring protruding. Upon necropsy the animal had little fat reserves and had two foetuses in the right horn of the uterus. The feet of on offspring were dislocated and exposed at the level of the vulva. Each foetus weighed approximately 200 g. The foetuses were well formed with fur, teeth and eyes. The placenta was attached to each of the foetuses. The pathological findings suggested that dystocia resulted in secondary uterine inertia, which was the cause of death of the adult female agouti. To prevent the recurrence of this situation the gestation should be staged (timed) using ultrasonography. Animals which are in their third stage of gestation should be monitored using cameras or with personnel at the facility to assist agoutis which are having difficulties at parturition. [ABSTRACT FROM AUTHOR]

Non-typhoid salmonellosis is a common and problematic foodborne zoonotic disease in which pork and pork products can be an important potential source of infection. To prevent this disease, important efforts to monitor the situation in the main source, livestock, are conducted in most developed countries. In the European Union, European Food Safety Agency (EFSA) and European Center for Disease Control (ECDC) compile information at the member-state level, even though important differences in production systems and surveillance systems exist. Here, Salmonella surveillance systems in one of the main sources of foodborne salmonellosis, swine, and humans in Spain were reviewed to identify potential gaps and discuss potential ways of integration under a "One-Health" approach. Despite the extensive information generated through the surveillance activities, source attribution can be only routinely performed through ad-hoc outbreak investigations, and national reports on human outbreaks do not provide sufficiently detailed information to gain a better understanding of the epidemiology of the pathogen. Human and animal monitoring of Salmonella would benefit from a better exchange of information and collaboration. Analysis of spatio-temporal trends in livestock and humans could help to identify likely sources of infection and to target surveillance efforts in areas with higher prevalence or where specific strains are found. [ABSTRACT FROM AUTHOR]