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Animals
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Swine Behavior and Welfare Monitoring: Ideas for the Way Forward
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Swine Behavior and Welfare Monitoring: Ideas for the Way Forward

A special issue of Animals (ISSN 2076-2615). This special issue belongs to the section "Pigs".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 9850

Special Issue Editors

Prof. Yuzhi Li

E-Mail Website
Guest Editor
West Central Research and Outreach Center, University of Minnesota, Morris, MN, USA
Interests: swine behavior; welfare
Prof. Clover Bench

E-Mail Website
Guest Editor
Dept of Agricultural, Food and Nutritional Sciences, University of Alberta, Edmonton, AB, Canada
Interests: applied domestic animal behaviour; applied ethology

Special Issue Information

Dear Colleagues,

Pork is the most consumed meat in the world. As swine production keeps expanding to feed an increasing population, swine behavior and welfare has attracted attention from academia, the pork industry, and the general public at large. Sustainable swine production systems and practices are expected to ensure good animal welfare, allow pigs to perform natural and normal behaviors, and prevent the development of abnormal behavior. The monitoring of behavior and welfare in pigs is the key to evaluating production systems and practices. However, on-farm monitoring of swine behavior and welfare can be challenging and time consuming. Over the last two decades, animal scientists have utilized emerging technology to overcome this challenge.

The aim of this special issue is to showcase recent developments in monitoring swine behavior and welfare at both the lab and on-farm levels. Original research and review papers that address monitoring individual or group pig behavior under production conditions, including those capable of identifying pigs with compromised or enhanced welfare, or predicting harmful behaviors will be the focus of this issue. Technical notes and short communications that validate new technology in swine behavior and welfare monitoring are also welcomed for submission.

Prof. Yuzhi Li
Prof. Clover Bench
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Animals is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Monitoring pig behavior
  • Tracking individual pigs
  • Automation of behavioral monitoring
  • Livestock precision farming
  • Predicting behavior
  • Swine welfare assessment

Published Papers (5 papers)

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Research

11 pages, 246 KiB  
Article
Identifying Early-Life Behavior to Predict Mothering Ability in Swine Utilizing NUtrack System
by Savannah Millburn, Ty Schmidt, Gary A. Rohrer and Benny Mote
Animals 2023, 13(18), 2897; https://doi.org/10.3390/ani13182897 - 13 Sep 2023
Viewed by 901
Abstract
Early indicator traits for swine reproduction and longevity support economical selection decision-making. Activity is a key variable impacting a sow’s herd life and productivity. Early-life activities could contribute to farrowing traits including gestation length (GL), number born alive (NBA), and number weaned (NW). [...] Read more.
Early indicator traits for swine reproduction and longevity support economical selection decision-making. Activity is a key variable impacting a sow’s herd life and productivity. Early-life activities could contribute to farrowing traits including gestation length (GL), number born alive (NBA), and number weaned (NW). Beginning at 20 weeks of age, 480 gilts were video recorded for 7 consecutive days and processed using the NUtrack system. Activity traits included angle rotated (radians), average speed (m/s), distance traveled (m), time spent eating (s), lying lateral (s), lying sternal (s), standing (s), and sitting (s). Final daily activity values were averaged across the period under cameras. Parity one data were collected for all gilts considered. Data were analyzed using linear regression models (R version 4.0.2). GL was significantly impacted by angle rotated (p = 0.03), average speed (p = 0.07), distance traveled (p = 0.05), time spent lying lateral (p = 0.003), and lying sternal (0.02). NBA was significantly impacted by time spent lying lateral (p = 0.01), lying sternal (p = 0.07), and time spent sitting (p = 0.08). NW was significantly impacted by time spent eating (p = 0.09), time spent lying lateral (p = 0.04), and time spent sitting (p = 0.007). This analysis suggests early-life gilt activities are associated with sow productivity traits of importance. Further examination of the link between behaviors compiled utilizing NUtrack and reproductive traits is necessitated to further isolate behavioral differences for potential use in selection decisions. Full article
(This article belongs to the Special Issue Swine Behavior and Welfare Monitoring: Ideas for the Way Forward)
10 pages, 257 KiB  
Article
Utilizing NUtrack to Access the Activity Levels in Pigs with Varying Degrees of Genetic Potential for Growth and Feed Intake
by Dalton Obermier, Melanie Trenahile-Grannemann, Ty Schmidt, Tom Rathje and Benny Mote
Animals 2023, 13(10), 1581; https://doi.org/10.3390/ani13101581 - 09 May 2023
Cited by 1 | Viewed by 1206
Abstract
Feed cost accounts for over two-thirds of the variable cost of production. In order to reduce feed costs without sacrificing production numbers, feed efficiency must be improved. Calorie expenditure has been difficult to quantify in the past but is understood to impact residual [...] Read more.
Feed cost accounts for over two-thirds of the variable cost of production. In order to reduce feed costs without sacrificing production numbers, feed efficiency must be improved. Calorie expenditure has been difficult to quantify in the past but is understood to impact residual feed intake (RFI) greatly. The objective of this work was to utilize an advanced computer vision system to evaluate activity levels across sex and sire groups with different expected breeding value combinations for growth and feed intake. A total of 199 pigs from four different sire groups (DNA Genetics Line 600) High Feed Intake/High Growth (HIHG), Low Feed Intake/High Growth (LIHG), High Feed Intake/Low Growth (HILG), and Low Feed Intake/Low Growth (LILG) were utilized at the UNL ENREC farm over 127 days. The NUtrack system allowed for individual monitoring of pigs in group housing to track daily activity traits. In total, HIHG pigs travelled less (p < 0.05; 139 vs. 150 km), spent more time lying (p < 0.05; 2421 vs. 2391 h), and less time eating (p < 0.05; 235 vs. 243 h) when compared to LILG pigs across time. The results suggest variation in activity occurs across the progeny of the sire groups selected to differentiate in growth and feed intake. Full article
(This article belongs to the Special Issue Swine Behavior and Welfare Monitoring: Ideas for the Way Forward)
14 pages, 2064 KiB  
Article
Evaluation of Precision Livestock Technology and Human Scoring of Nursery Pigs in a Controlled Immune Challenge Experiment
by Eduarda M. Bortoluzzi, Mikayla J. Goering, Sara J. Ochoa, Aaron J. Holliday, Jared M. Mumm, Catherine E. Nelson, Hui Wu, Benny E. Mote, Eric T. Psota, Ty B. Schmidt, Majid Jaberi-Douraki and Lindsey E. Hulbert
Animals 2023, 13(2), 246; https://doi.org/10.3390/ani13020246 - 10 Jan 2023
Cited by 5 | Viewed by 1890
Abstract
The objectives were to determine the sensitivity, specificity, and cutoff values of a visual-based precision livestock technology (NUtrack), and determine the sensitivity and specificity of sickness score data collected with the live observation by trained human observers. At weaning, pigs (n [...] Read more.
The objectives were to determine the sensitivity, specificity, and cutoff values of a visual-based precision livestock technology (NUtrack), and determine the sensitivity and specificity of sickness score data collected with the live observation by trained human observers. At weaning, pigs (n = 192; gilts and barrows) were randomly assigned to one of twelve pens (16/pen) and treatments were randomly assigned to pens. Sham-pen pigs all received subcutaneous saline (3 mL). For LPS-pen pigs, all pigs received subcutaneous lipopolysaccharide (LPS; 300 μg/kg BW; E. coli O111:B4; in 3 mL of saline). For the last treatment, eight pigs were randomly assigned to receive LPS, and the other eight were sham (same methods as above; half-and-half pens). Human data from the day of the challenge presented high true positive and low false positive rates (88.5% sensitivity; 85.4% specificity; 0.871 Area Under Curve, AUC), however, these values declined when half-and-half pigs were scored (75% sensitivity; 65.5% specificity; 0.703 AUC). Precision technology measures had excellent AUC, sensitivity, and specificity for the first 72 h after treatment and AUC values were >0.970, regardless of pen treatment. These results indicate that precision technology has a greater potential for identifying pigs during a natural infectious disease event than trained professionals using timepoint sampling. Full article
(This article belongs to the Special Issue Swine Behavior and Welfare Monitoring: Ideas for the Way Forward)
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16 pages, 1622 KiB  
Article
Identifying Early Indicators of Tail Biting in Pigs by Variable Selection Using Partial Least Squares Regression
by Veronika Drexl, Imme Dittrich, Thore Wilder, Sophie Diers and Joachim Krieter
Animals 2023, 13(1), 56; https://doi.org/10.3390/ani13010056 - 23 Dec 2022
Cited by 3 | Viewed by 1321
Abstract
This study examined relevant variables for predicting the prevalence of pigs with a tail lesion in rearing (REA) and fattening (FAT). Tail lesions were recorded at two scoring days a week in six pens in both REA (10 batches, 840 scoring days) and [...] Read more.
This study examined relevant variables for predicting the prevalence of pigs with a tail lesion in rearing (REA) and fattening (FAT). Tail lesions were recorded at two scoring days a week in six pens in both REA (10 batches, 840 scoring days) and FAT (5 batches, 624 scoring days). To select the variables that best explain the variation within the prevalence of pigs with a tail lesion, partial least squares regression models were used with the variable importance in projection (VIP) and regression coefficients (β) as selection criteria. In REA, five factors were extracted explaining 60.6% of the dependent variable’s variance, whereas in FAT five extracted factors explained 62.4% of the dependent variable’s variance. According to VIP and β, seven variables were selected in REA and six in FAT with the tail posture being the most important variable. In addition, skin lesions, treatment index in the suckling phase, water consumption (mean), activity time (mean; CV) and exhaust air rate (CV) were selected in REA. In FAT, additional musculoskeletal system issues, activity time (mean; CV) and exhaust air rate (mean; CV) were selected according to VIP and β. The selected variables indicate which variables should be collected in the stable to e.g., predict tail biting. Full article
(This article belongs to the Special Issue Swine Behavior and Welfare Monitoring: Ideas for the Way Forward)
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18 pages, 5942 KiB  
Article
The Application of 3D Landmark-Based Geometric Morphometrics towards Refinement of the Piglet Grimace Scale
by Maria E. Lou, Samantha T. Porter, Jason S. Massey, Beth Ventura, John Deen and Yuzhi Li
Animals 2022, 12(15), 1944; https://doi.org/10.3390/ani12151944 - 30 Jul 2022
Cited by 3 | Viewed by 3230
Abstract
Proper methods of assessment to objectively identify pain are essential for welfare improvements of piglets undergoing surgical castration on commercial farms. The Piglet Grimace Scale (PGS) is used to identify changes in facial expressions caused by acute pain in piglets undergoing tail docking [...] Read more.
Proper methods of assessment to objectively identify pain are essential for welfare improvements of piglets undergoing surgical castration on commercial farms. The Piglet Grimace Scale (PGS) is used to identify changes in facial expressions caused by acute pain in piglets undergoing tail docking and castration. However, subjective scoring methods are a concern for the validation of the PGS. The objectives of this study were to evaluate and refine the PGS through 3D landmark geometric morphometrics. Male piglets (n = 88) were randomly allocated to one of two treatments: castration and sham-castration. Piglet facial images were taken at four time points (before treatment, immediately post-treatment, 1 h post-treatment, and 4 h post-treatment) using a photogrammetry rig. Images were scored by four raters using five facial action units (FAUs): orbital tightening, ear position, temporal tension, lip contraction, and nose bulge/cheek tension. Three-dimensional facial models were generated and landmarked denoting 3 FAUs (orbital tightening, lip contraction, and nose bulge/cheek tension). Results suggest that orbital tightening and ear position may be reliable FAUs for the PGS. However, neither the PGS nor 3D landmark-based geometric morphometrics were able (both p > 0.10) to reliably identify facial indicators of pain in piglets undergoing castration. Full article
(This article belongs to the Special Issue Swine Behavior and Welfare Monitoring: Ideas for the Way Forward)
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