Risk factors differ for viable and low viable crushed piglets in free farrowing pens

A review of sound-based pig monitoring for enhanced precision production

Pig farming is experiencing significant transformations, driven by technological advancements, which have greatly improved management practices and overall productivity. Sound-based technologies are emerging as a valuable tool in enhancing precision pig farming. This review explores the advancements in sound-based technologies and their role in improving precision pig farming through enhanced monitoring of health, behavior, and environmental conditions. When strategically placed on farms, non-invasive technologies such as microphones and sound sensors can continuously collect data without disturbing the animals, making them highly efficient. Farmers using sound data, can monitor key factors such as respiratory conditions, stress levels, and social behaviors, leading to improved animal welfare and optimized production. Advancements in sensor technology and data analytics have enhanced the capabilities of sound-based precision systems in pig farming. The integration of machine learning and artificial intelligence (AI) is further enhancing the capacity to interpret complex sound patterns, enabling the automated detection of abnormal behaviors or health issues. Moreover, sound-based precision technologies offer solutions for improving environmental sustainability and resource management in pig farming. By continuously monitoring ventilation, feed distribution, and other key factors, these systems optimize resource use, reduce energy consumption, and detect stressors such as heat and poor air quality. The integration of sound technologies with other precision farming tools, such as physiological monitoring sensors and automated feeding systems, further enhances farm management and productivity. However, despite the advantages, challenges remain in terms of low accuracy and high initial costs, and further research is needed to improve specificity across different pig breeds and environmental conditions. Nonetheless, acoustic technologies hold immense promise for pig farming, offering enhanced management, an optimized performance, and improved animal welfare. Continued research can refine these tools and address the challenges, paving the way for a more efficient, profitable, and sustainable future for the industry.

Productive and metabolomic consequences of arginine supplementation in sows during different gestation periods in two different seasons

BACKGROUND

The prolificacy of sows (litter size at birth) has markedly increased, leading to higher post-natal mortality. Heat stress can exacerbate this issue. Arginine plays an important role in several physiological pathways; its effect on gestating sows can depend on the period of supplementation. This study evaluated the effects of arginine supplementation on the productive performance and physiological status of sows during different gestation periods and seasons, using a multi-omics approach.

METHODS

A total of 320 sows were divided into 4 groups over 2 seasons (warm/cold); a control group (CO) received a standard diet (including 16.5 g/d of arginine) and 3 other groups received the standard diet supplemented with 21.8 g/d of arginine (38.3 g/d of arginine) either during the first 35 d (Early35), the last 45 d (Late45) or throughout the entire gestation period (COM). The colostrum was analyzed for nutritional composition, immunoglobulins and metabolomic profile. Urine and feces were analyzed on d 35 and 106 for the metabolomic and microbial profiles. Piglet body weight and mortality were recorded at birth, d 6, d 26, and on d 14 post-weaning.

RESULTS

Interactions between arginine and season were never significant. The Early35 group had a lower percentage of stillborn (P < 0.001), mummified (P = 0.002) and low birthweight (LBW) piglets (P = 0.02) than the CO group. The Late45 group had a lower percentage of stillborn piglets (P = 0.029) and a higher percentage of high birthweight piglets (HBW; P < 0.001) than the CO group. The COM group had a higher percentage of LBW (P = 0.004) and crushed piglets (P < 0.001) than the CO group. Arginine supplementation modifies the metabolome characterization of colostrum, urine, and feces. Creatine and nitric oxide pathways, as well as metabolites related to microbial activity, were influenced in all matrices. A slight trend in the beta diversity index was observed in the microbiome profile on d 35 (P = 0.064).

CONCLUSIONS

Arginine supplementation during early gestation reduced the percentage of stillborn and LBW piglets, while in the last third of pregnancy, it favored the percentage of HBW pigs and reduced the percentage of stillbirths, showing that arginine plays a significant role in the physiology of pregnant sows.

Enteral plasma supports brain repair in newborn pigs after birth asphyxia

Newborns exposed to birth asphyxia transiently experience deficient blood flow and a lack of oxygen, potentially inducing hypoxic-ischaemic encephalopathy and subsequent neurological damage. Immunomodulatory components in plasma may dampen these responses. Using caesarean-delivered pigs as a model, we hypothesized that dietary plasma supplementation improves brain outcomes in pigs exposed to birth asphyxia. Mild birth asphyxia was induced by temporary occlusion of the umbilical cord prior to caesarean delivery. Motor development was assessed in asphyxiated (ASP) and control (CON) piglets using neonatal arousal, physical activity and gait test parameters before euthanasia on Day 4. The ASP pigs exhibited increased plasma lactate at birth, deficient motor skills and increased glial fibrillary acidic protein levels in CSF and astrogliosis in the putamen. The expression of genes related to oxidative stress, inflammation and synaptic functions was transiently altered in the motor cortex and caudate nucleus. The number of apoptotic cells among CTIP2-positive neurons in the motor cortex and striatal medium spiny neurons was increased, and maturation of preoligodendrocytes in the internal capsule was delayed. Plasma supplementation improved gait performance in the beam test, attenuated neuronal apoptosis and affected gene expression related to neuroinflammation, neurotransmission and antioxidants (motor cortex, caudate). We present a new clinically relevant animal model of moderate birth asphyxia inducing structural and functional brain damage. The components in plasma that support brain repair remain to be identified but may represent a therapeutic potential for infants and animals after birth asphyxia.

Risk factors for antimicrobial use in Dutch pig farms: A cross-sectional study

BACKGROUND

Antimicrobial use (AMU) has decreased significantly in Dutch pig farms since 2009. However, this decrease has stagnated recently, with relatively high AMU levels persisting mainly among weaners. The aim of this study was to identify farm-level characteristics associated with: i) total AMU and ii) use of specific antimicrobial classes.

METHODS

In 2020, cross-sectional data from 154 Dutch pig farms were collected, including information on AMU and farm characteristics. A mixed-effects conditional Random Forest analysis was applied to select the subset of features that was best associated with AMU.

RESULTS

The main risk factors for total AMU in weaners were vaccination for PRRS in sucklings, being a conventional farm (vs. not), high within-farm density, and early weaning. The main protective factors for total AMU in sows/sucklings were E. coli vaccination in sows and having boars for estrus detection from own production. Regarding antimicrobial class-specific outcomes, several risk factors overlapped for weaners and sows/sucklings, such as farmer's non-tertiary education, not having free-sow systems during lactation, and conventional farming. An additional risk factor for weaners was having fully slatted floors. For fatteners, the main risk factor for total AMU was PRRS vaccination in sucklings.

CONCLUSIONS

Several factors found here to be associated with AMU. Some were known but others were novel, such as farmer's tertiary education, low pig aggression and free-sow systems which were all associated with lower AMU. These factors provide targets for developing tailor-made interventions, as well as an evidence-based selection of features for further causal assessment and mediation analysis.

Thermal imaging and computer vision technologies for the enhancement of pig husbandry: a review

Pig farming, a vital industry, necessitates proactive measures for early disease detection and crush symptom monitoring to ensure optimum pig health and safety. This review explores advanced thermal sensing technologies and computer vision-based thermal imaging techniques employed for pig disease and piglet crush symptom monitoring on pig farms. Infrared thermography (IRT) is a non-invasive and efficient technology for measuring pig body temperature, providing advantages such as non-destructive, long-distance, and high-sensitivity measurements. Unlike traditional methods, IRT offers a quick and labor-saving approach to acquiring physiological data impacted by environmental temperature, crucial for understanding pig body physiology and metabolism. IRT aids in early disease detection, respiratory health monitoring, and evaluating vaccination effectiveness. Challenges include body surface emissivity variations affecting measurement accuracy. Thermal imaging and deep learning algorithms are used for pig behavior recognition, with the dorsal plane effective for stress detection. Remote health monitoring through thermal imaging, deep learning, and wearable devices facilitates non-invasive assessment of pig health, minimizing medication use. Integration of advanced sensors, thermal imaging, and deep learning shows potential for disease detection and improvement in pig farming, but challenges and ethical considerations must be addressed for successful implementation. This review summarizes the state-of-the-art technologies used in the pig farming industry, including computer vision algorithms such as object detection, image segmentation, and deep learning techniques. It also discusses the benefits and limitations of IRT technology, providing an overview of the current research field. This study provides valuable insights for researchers and farmers regarding IRT application in pig production, highlighting notable approaches and the latest research findings in this field.