The burgeoning research and applications of technological advances are launching the development of precision livestock farming. Through sensors (cameras, microphones and accelerometers), images, sounds and movements are combined with algorithms to non-invasively monitor animals to detect their welfare and predict productivity. In turn, this remote monitoring of livestock can provide quantitative and early alerts to situations of poor welfare requiring the stockperson’s attention. While swine practitioners’ skills include translation of pig data entry into pig health and well-being indices, many do not yet have enough familiarity to advise their clients on the adoption of precision livestock farming practices. This review, intended for swine veterinarians and specialists, (1) includes an introduction to algorithms and machine learning, (2) summarizes current literature on relevant sensors and sensor network systems, and drawing from industry pig welfare audit criteria, (3) explains how these applications can be used to improve swine welfare and meet current pork production stakeholder expectations. Swine practitioners, by virtue of their animal and client advocacy roles, interpretation of benchmarking data, and stewardship in regulatory and traceability programs, can play a broader role as advisors in the transfer of precision livestock farming technology, and its implications to their clients.
Transport losses (dead and nonambulatory pigs) present animal welfare, legal, and economic challenges to the US swine industry. The objectives of this review are to explore 1) the historical perspective of transport losses; 2) the incidence and economic implications of transport losses; and 3) the symptoms and metabolic characteristics of fatigued pigs. In 1933 and 1934, the incidence of dead and nonambulatory pigs was reported to be 0.08 and 0.16%, respectively. More recently, 23 commercial field trials (n = 6,660,569 pigs) were summarized and the frequency of dead pigs, nonambulatory pigs, and total transport losses at the processing plant were 0.25, 0.44, and 0.69% respectively. In 2006, total economic losses associated with these transport losses were estimated to cost the US pork industry approximately $46 million. Furthermore, 0.37 and 0.05% of the nonambulatory pigs were classified as either fatigued (nonambulatory, noninjured) or injured, respectively, in 18 of these trials (n = 4,966,419 pigs). Fatigued pigs display signs of acute stress (open-mouth breathing, skin discoloration, muscle tremors) and are in a metabolic state of acidosis, characterized by low blood pH and high blood lactate concentrations; however, the majority of fatigued pigs will recover with rest. Transport losses are a multifactorial problem consisting of people, pig, facility design, management, transportation, processing plant, and environmental factors, and, because of these multiple factors, continued research efforts are needed to understand how each of the factors and the relationships among factors affect the well-being of the pig during the marketing process. In 1933 and 1934, the incidence of dead and nonambulatory pigs was reported to be 0. 08 and 0.16%, respectively. More recently, 23 commercial field trials (n = 6,660,569 pigs) were summarized and the frequency of dead pigs, nonambulatory pigs, and total transport losses at the processing plant were 0.25, 0.44, and 0.69% respectively. In 2006, total economic
Acute outbreaks of respiratory disease in swine at agricultural fairs in Michigan, USA, in 2015 raised concern for potential human exposure to influenza A virus. Testing ruled out influenza A virus and identified porcine hemagglutinating encephalomyelitis virus as the cause of influenza-like illness in the affected swine.
Three penetrating captive bolt (PCB) placements were tested on cadaver heads from swine with estimated body weight (BW) >200 kg (sows = 232.9 ± 4.1 kg; boars = 229.3 ± 2.6 kg). The objectives were to determine tissue depth, cross-sectional brain area, visible brain damage (BD), regions of BD, and bolt-brain contact; and determine relationships between external head dimensions and tissue depth at each placement. A Jarvis PAS – Type P 0.25R PCB with a Long Stunning Rod Nosepiece Assembly and 3.5 gr power loads was used at the following placements on heads from 111 sows and 46 boars after storage at 2-4° C for approximately 62 h before treatment: FRONTAL (F) – 3.5 cm superior to the optic orbits at midline, TEMPORAL (T) – at the depression posterior to the lateral canthus of the eye within the plane between the lateral canthus and the base of the ear, or BEHIND EAR (BE) – directly caudal to the pinna of the ear on the same plane as the eyes and targeting the middle of the opposite eye. For sows, the bolt path was in the plane of the brain for 42/42 (100%, 95% CI: 91.6-100.0%) F heads, 39/40 (97.5%, 95% CI: 86.8-99.9%) T heads, and 34/39 (87.5%, 95% CI: 72.6-95.7%) BE heads; for the heads that could reliably be assessed for BD damage was detected in 25/26 (96.2%, 95% CI: 80.4-99.9%) F heads, 24/35 (68.6%, 95% CI: 50.7-83.2%) T heads, and 5/40 (12.5%, 95% CI: 4.2-26.8%) BE heads. For boars, the bolt path was in the plane of the brain for 17/17 (100.0%, 95% CI: 80.5-100.0%) F heads, 18/18 (100.0%, 95% CI: 81.5-100.0%) T heads, and 14/14 (100.0%, 95% CI: 76.8-100.0%) BE heads; damage was detected in 11/12 (91.7%, 95% CI: 61.5-99.8%) F heads, 2/15 (13.3%, 95% CI: 1.7-40.5%) T heads, and 7/14 (50.0%, 95% CI: 23.0-77.0%) BE heads. Tissue depth was reported as mean ± standard error followed by 95% one-sided upper reference limit (URL). For sows, total tissue thickness was different (P < 0.05) between placements (F: 52.7 ± 1.0 mm, URL: 64.1 mm; T: 69.8 ± 1.4 mm, URL: 83.9 mm; BE: 89.3 ± 1.5 mm, URL: 103.4 mm). In boars, total tissue thickness was different (P < 0.05) between placements (F: 41.2 ± 2.1 mm, URL: 56.3 mm; T: 73.2 ± 1.5 mm, URL: 83.4 mm; BE: 90.9 ± 3.5 mm, URL: 113.5 mm). For swine > 200 kg BW, F placement may be more effective than T or BE due to less soft tissue thickness, which may reduce concussive force. The brain was within the plane of bolt travel for 100% of F heads with brain damage for 96.2% and 91.7% of F sow and boar heads, respectively.
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