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21 pages, 9107 KiB  
Article
Body Temperature Detection of Group-Housed Pigs Based on the Pairing of Left and Right Ear Roots in Thermal Images
by Rong Xiang, Yi Zhang, Hongjian Lin, Yingchun Fu, Xiuqin Rao, Jinming Pan and Chenghao Pan
Animals 2025, 15(5), 642; https://doi.org/10.3390/ani15050642 - 22 Feb 2025
Viewed by 206
Abstract
Body temperature is a critical indicator of pig health. This study proposes a non-contact method for detecting body temperature in group-housed pigs by extracting temperature data from thermal images of ear roots. Thermal images in the drinking trough area were captured using a [...] Read more.
Body temperature is a critical indicator of pig health. This study proposes a non-contact method for detecting body temperature in group-housed pigs by extracting temperature data from thermal images of ear roots. Thermal images in the drinking trough area were captured using a thermal camera, with real-time data transmitted to a monitoring room via optical fibers. The YOLO v11m-OBB model was utilized to detect the ear root areas with oriented bounding boxes, while a novel algorithm, the two-stage left and right ear root pairing algorithm (YOLO TEPA-OBB), paired the ear roots of individual pigs using center distance clustering and angular relationships in a polar coordinate system. The maximum temperature of the ear roots was extracted to represent the body temperature. Experimental results based on 749 ear roots show that the YOLO TEPA-OBB achieves 98.7% precision, 98.4% recall, and 98.7% mean average precision (mAP) in detecting ear roots, with an ear root pairing accuracy of 98.1%. The Pearson correlation coefficient (r) between predicted and reference temperatures is 0.989, with a mean bias of 0.014 °C and a standard deviation of 0.103 °C. This research facilitates real-time body temperature monitoring and precise health management for group-housed pigs. Full article
(This article belongs to the Section Pigs)
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<p>Thermal image collection system for pigs. <b>a</b>. Thermal camera; <b>b</b>. fiber-optic transceiver; <b>c</b>. temperature and humidity logger; <b>d</b>. switch; <b>e</b>. DVR; <b>f</b>. captured images.</p>
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<p>Flowchart for individual temperature detection of group-housed pigs. (‘1–4’ refers to the ear root bounding boxes, and “➀–➁” refers to the number of ear root pairs.).</p>
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<p>YOLO v11m-OBB network architecture.</p>
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<p>TEPA algorithm workflow. (<b>a</b>) Center distance calculation; (<b>b</b>) rough pairing; (<b>c</b>) calculation of base and outermost points; (<b>d</b>) extraction of outermost lines and intersection points; (<b>e</b>) left and right ear classification; (<b>f</b>) re-pairing. (‘1–4’ refers to the ear root bounding boxes, and “①–②” refers to the number of ear root pairs.).</p>
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<p>Visualization of pig body temperature distribution. (<b>a</b>) Original thermal image; (<b>b</b>) 3D body temperature distribution (top view); (<b>c</b>) 3D body temperature distribution (side view); (<b>d</b>) 3D body temperature distribution (3D view).</p>
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<p>Extraction of reference and predicted values. (<b>a</b>) Reference value extraction (ear root line in bold black); (<b>b</b>) predicted value extraction.</p>
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<p>Comparison of ear root detection model results. (<b>a</b>) Result of YOLOv8 nano-OBB; (<b>b</b>) result of YOLOv8 medium-OBB; (<b>c</b>) result of YOLOv11 nano-OBB; (<b>d</b>) result of YOLOv11 medium-OBB.</p>
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<p>Results of training and validation sets. (<b>a</b>) Training—bounding box loss; (<b>b</b>) training—classification loss; (<b>c</b>) validation—precision; (<b>d</b>) validation—recall; (<b>e</b>) validation—bounding box loss; (<b>f</b>) validation—classification loss; (<b>g</b>) validation—mean average precision at 50%; (<b>h</b>) validation—mean average precision at 50–95%.</p>
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<p>Center distance distribution between left and right ear root bounding boxes.</p>
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<p>Typical left and right ear root pairing errors.</p>
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<p>Statistical results of body temperature detection. (<b>a</b>) Bias histogram; (<b>b</b>) hypothesis test for bias.</p>
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<p>Statistical results of body temperature detection. (<b>a</b>) Bias histogram; (<b>b</b>) hypothesis test for bias.</p>
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14 pages, 4683 KiB  
Article
Feeding Behaviour in Group-Housed Growing-Finishing Pigs and Its Relationship with Growth and Feed Efficiency
by Miriam Piles, Llibertat Tusell, Mónica Mora, Carolina Garcia-Baccino, Denis Cudrey, Claire Hassenfratz, Marie-José Mercat and Ingrid David
Vet. Sci. 2025, 12(2), 168; https://doi.org/10.3390/vetsci12020168 - 13 Feb 2025
Viewed by 531
Abstract
Feed consumption and feeding patterns influence the individual feed efficiency in group-housed livestock species. Using the meal as the unit of feeding behaviour, the main objectives of this research were to identify feeding behaviour (FB) traits that may indicate an individual’s [...] Read more.
Feed consumption and feeding patterns influence the individual feed efficiency in group-housed livestock species. Using the meal as the unit of feeding behaviour, the main objectives of this research were to identify feeding behaviour (FB) traits that may indicate an individual’s rank within the social hierarchy or its level of dominance among pen mates and to assess the relationship between growth and feed efficiency with the identified traits, as well as those describing individual feed consumption patterns. Data from 5516 pigs during the fattening period were used. Pens were equipped with an automatic concentrate feeder that recorded individual feed intake, time spent at the feeder, and body weight at each visit. A meal criterion was established. Then, different FB traits were computed: number of meals, number of visits to complete a meal, occupation time to complete a meal, time between first and last visit within a meal, feeding rate, feeding rate to complete a meal, and interval between meals. Social ranking (SR) traits were also calculated: position/order in which each animal accessed the feeder, ratio of visits to the feeder during preferred times, distribution among the cage mates of the total daily feed, number of visits, number of meals, and occupation time. Pigs that eat more and faster tend to have a poorer feed efficiency and higher final weight. Animals that eat more, more times, and occupy the feeder longer, eat mainly in the preferred period. They could be considered dominant, while others have to adapt their feeding schedules to off-peak times. Full article
(This article belongs to the Special Issue Genetic Improvement and Reproductive Biotechnologies)
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<p>Boxplots of individual meal criterion for each animal from each breed.</p>
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<p>Daily evolution of total number of meals (TNM) and number of visits to the feeder to complete a meal (NVM) (<b>A</b>,<b>C</b>). Hourly evolution of TNM and NVM (<b>B</b>,<b>D</b>).</p>
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<p>Daily evolution of occupation time in a meal (OTM) and time to complete a meal (TM) (<b>A</b>,<b>C</b>). Hourly evolution of OTM and TM (<b>B</b>,<b>D</b>).</p>
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<p>Daily evolution of feeding rate (FR) and feeding rate to complete a meal (FRM) (<b>A</b>,<b>C</b>). Hourly evolution of FR and FRM (<b>B</b>,<b>D</b>).</p>
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<p>Daily evolution of feed intake (FIM) (<b>A</b>) and hourly evolution of FIM (<b>B</b>).</p>
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<p>Phenotypic correlations between productive performance (i.e., growth and feed efficiency), feeding, and social behaviour traits in pigs from breed 1. Black crosses (X) indicate non-significant correlations between variables. The colour and its intensity correspond to the value of the correlations, ranging from high and positive (dark red) to high and negative (dark blue). Refer to <a href="#vetsci-12-00168-t001" class="html-table">Table 1</a> for the abbreviations and detailed descriptions of the variables.</p>
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11 pages, 1814 KiB  
Case Report
A Positive-Reinforcement Training Regimen for Refined Sample Collection in Laboratory Pigs
by Rachel Layton, David Beggs, Andrew Fisher, Peter Mansell, Sarah Riddell, Daniel Layton, David T. Williams and Kelly J. Stanger
Animals 2025, 15(4), 471; https://doi.org/10.3390/ani15040471 - 7 Feb 2025
Viewed by 577
Abstract
Positive-reinforcement training of laboratory pigs can reduce the reliance on forced manual restraint and anaesthesia for sample collection, reducing stress and physiological disruption. Training regimens for laboratory pigs typically rely on specialised equipment for restraint, such as Panepinto slings, with a time investment [...] Read more.
Positive-reinforcement training of laboratory pigs can reduce the reliance on forced manual restraint and anaesthesia for sample collection, reducing stress and physiological disruption. Training regimens for laboratory pigs typically rely on specialised equipment for restraint, such as Panepinto slings, with a time investment that may not be justified for short-term studies. These training regimens also commonly rely on pigs being lifted into sling restraints, which is not practical for studies involving large pigs. We developed and assessed a rapid, three-phase, positive-reinforcement training regimen for both individually housed and group-housed laboratory pigs to facilitate the collection of minimally invasive samples consciously and voluntarily. The time to complete each phase of training in both individually housed and group-housed pigs was recorded. The behaviour of the individually housed pigs was assessed via an ethogram of behaviours exhibited during a human approach test, and stress response was assessed by analysing salivary corticosterone. The rapid, positive-reinforcement training regimen successfully facilitated oral swabbing, rectal swabbing and rectal thermometer insertion from individually housed (within 18 days) and group-housed (within 6 days) pigs. The trained pigs displayed increasing positive behaviours, no or very few negative behaviours and corticosterone levels within normal limits throughout the study. This training regimen provides a practical and welfare-positive tool for the collection of minimally invasive samples from both small and large laboratory pigs, with a low time investment of 2–5 min/pig/day without the need for specialised restraint equipment. Full article
(This article belongs to the Special Issue Care and Well-Being of Laboratory Animals)
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<p>Methods of facilitating voluntary sample collection in laboratory pigs. Image of Panepinto crank-up sling with boat winch mechanism for restraint (<b>a</b>), with samples collected from pigs raised in a sling (<b>b</b>) or standing still (<b>c</b>).</p>
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<p>Grouped housing appears to positively impact pig training. Outcomes of pig training are presented schematically, with each line representing an individual pig from either the group-housed or individually housed groups. Coloured boxes represent time taken to perform the trained task and categorised as either fast (0–30 s, green), medium (31–60 s, yellow), slowly (61–180 s, orange) or unsuccessful (&gt;180 s, red) for Phase 1—time to approach (<b>a</b>), Phase 2—time to enter pig sling frame (<b>b</b>) and Phase 3—time to stand in correct sling position (<b>c</b>). Grey boxes represent data from the previous training phase. Time to successfully complete each phase of training was recorded and presented to the nearest 30 s (<b>d</b>) for all pigs that successfully completed all three training phases.</p>
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<p>Positive welfare implications of a positive-reinforcement training regime for laboratory pigs. Results of pig training on welfare is presented as negative behaviour score (<b>a</b>), positive behaviour score (<b>b</b>) and salivary corticosterone (<b>c</b>) for trained (n = 4) and untrained (n = 1) individually housed pigs. Red dotted horizontal line indicates maximum level of salivary corticosterone in non-stressed pigs as reported in the published literature. Error bars indicate the range.</p>
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12 pages, 1985 KiB  
Article
Preliminary Research on Dietary Supplementation of Potassium Magnesium Sulphate on Transport Stress in Finishing Pigs Prior to Slaughter
by Bailei Cui, Yunxia Xiong, Xiaolu Wen, Shengnan Wu, Yi Huang, Hao Xiao, Shuting Cao, Zongyong Jiang, Li Wang and Shenglan Hu
Animals 2025, 15(3), 362; https://doi.org/10.3390/ani15030362 - 27 Jan 2025
Viewed by 660
Abstract
Transport stress prior to slaughter frequently induces a stress response, negatively affecting meat quality. This study investigated the impact of dietary potassium magnesium sulphate (PMS) supplementation during the fattening stage on the stress response and meat quality in finishing pigs subjected to transport [...] Read more.
Transport stress prior to slaughter frequently induces a stress response, negatively affecting meat quality. This study investigated the impact of dietary potassium magnesium sulphate (PMS) supplementation during the fattening stage on the stress response and meat quality in finishing pigs subjected to transport stress. The experiment involved two phases. Initially, 48 finishing pigs (68.00 ± 0.40 kg) were randomly allocated into two groups: a control group receiving a basal diet (CON) and a PMS-supplemented group receiving the basal diet with 0.50% PMS. Each group was housed in six pens, with four pigs per pen. After 60 days of feeding, in the second phase, two pigs from each pen were randomly selected for slaughter, with one pig subjected to a 4 h transportation stress prior to slaughter. Pigs were categorized into four treatment groups based on diet and stress: (1) control without transport stress, (2) control with transport stress, (3) PMS-supplemented without transport stress, and (4) PMS-supplemented with transport stress. Serum, jejunum, and longissimus thoracis muscle (LM) samples were collected. The results indicated that dietary PMS supplementation did not significantly affect growth performance during the fattening stage (p > 0.05). However, following transport, the PMS pigs showed a reduction in norepinephrine and cortisol concentrations (p = 0.09, p < 0.05) and a significant increase in serum glutathione peroxidase (GSH-Px) activity (p < 0.05). Furthermore, PMS supplementation significantly increased serum catalase (CAT), total antioxidant capacity (T-AOC), alkaline phosphatase (AKP) activity, and high-density lipoprotein cholesterol (HDL-C) levels (p < 0.05), while significantly reducing cholesterol (CHO) levels (p < 0.05). Transport stress adversely affected the intestinal health of finishing pigs, as evidenced by a decrease in intestinal villus height (0.05 < p < 0.1), a condition ameliorated by PMS supplementation. Additionally, transported pigs exhibited a higher drip loss24h in LM (p < 0.05), which was also alleviated through PMS supplementation. In conclusion, PMS supplementation mitigates transport stress and improves meat quality in finishing pigs. Full article
(This article belongs to the Special Issue Nutritional Strategies for Healthy Pork Meat)
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<p>The design of the PMS and transportation treatment of finishing pigs.</p>
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<p>The jejunal morphology of finishing pigs in experimental treatments. (<b>A</b>) CON, (<b>B</b>) PMS, (<b>C</b>) T-CON, (<b>D</b>) T-PMS.</p>
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13 pages, 535 KiB  
Article
Availability of Zinc, Copper, Iron, Manganese, and Selenium in Feed Ingredients and Sources in Pigs
by Yohan Choi, Junseon Hong, Jihwan Lee and Minju Kim
Agriculture 2025, 15(2), 171; https://doi.org/10.3390/agriculture15020171 - 14 Jan 2025
Viewed by 441
Abstract
This study evaluated the trace mineral availability of zinc (Zn), copper (Cu), iron (Fe), manganese (Mn), and selenium (Se) in major feed ingredients, including corn, wheat, soybean meal (SBM), and fish meal (FM). Additionally, we assessed the bioavailability of these minerals in pigs [...] Read more.
This study evaluated the trace mineral availability of zinc (Zn), copper (Cu), iron (Fe), manganese (Mn), and selenium (Se) in major feed ingredients, including corn, wheat, soybean meal (SBM), and fish meal (FM). Additionally, we assessed the bioavailability of these minerals in pigs supplemented with inorganic, organic, and nano-sized forms prepared via hot-melt extrusion (HME). A total of 64 barrows (Yorkshire × Landrace × Duroc crossbreds) with an average initial body weight of 26.61 ± 4.12 kg were housed individually in metabolic cages. Pigs were allocated to eight experimental diets in a completely randomized design, with eight replicates per diet group. The apparent total tract digestibility (ATTD) of Zn and Cu was significantly higher in SBM and FM than in the other ingredients (p < 0.05). SBM exhibited higher ATTD and standardized total tract digestibility (STTD) for Fe and Mn than corn, wheat, and FM (p < 0.05). Corn and wheat demonstrated significantly greater digestibility of Se than SBM and FM (p < 0.05). Supplementation with nano-sized minerals prepared by HME increased the digestibility of Zn and Cu, as well as their concentrations in pigs’ serum and liver, while reducing the fecal excretion of these minerals (p < 0.05). Organic mineral forms significantly enhanced Se bioavailability, improving its digestibility and concentrations in the liver and pancreas compared to the inorganic form (p < 0.05). In growth performance, organic and nano-sized mineral sources significantly improved growth rate without the increase in feed intake (p < 0.05). In conclusion, Zn and Cu from high-protein ingredients such as SBM and FM were more digestible than those from grains. Furthermore, plant-based ingredients, such as corn, wheat, and SBM, exhibited greater digestibility of Fe and Se. Among the trace mineral sources, the organic and HME-nano forms improved the bioavailability of Zn, Cu, and Se, while reducing their fecal excretion, thereby enhancing the efficiency of mineral utilization. Full article
(This article belongs to the Special Issue Assessment of Nutritional Value of Animal Feed Resources)
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<p>HME processing method on trace minerals.</p>
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12 pages, 417 KiB  
Article
Effects of Dietary Bromide, Magnesium and Tryptophan and Immunocastration on Growth Performance and Behaviour of Entire Male Pigs
by Frank R. Dunshea, Ian McCauley and Robert J. Smits
Animals 2024, 14(24), 3685; https://doi.org/10.3390/ani14243685 - 20 Dec 2024
Viewed by 409
Abstract
The growth of boars may be inhibited because of aggressive and/or sexual activity. Dietary Br, Mg and tryptophan (Trp) as well as immunocastration may reduce these behaviours. In Experiment 1, 200 boars and 40 barrows were allocated to six groups of four pens [...] Read more.
The growth of boars may be inhibited because of aggressive and/or sexual activity. Dietary Br, Mg and tryptophan (Trp) as well as immunocastration may reduce these behaviours. In Experiment 1, 200 boars and 40 barrows were allocated to six groups of four pens of 10 pigs per treatment. Control and immunocastrate (Improvac-vaccinated at 13 and 17 weeks, Imp) boars and barrows were fed a finisher ration while the others were fed diets supplemented with Mg (5 g Mg proteinate/kg), Br (140 mg NaBr/kg) and Trp (5 g Trp/kg). In experiment 2, 300 boars were stratified by weight and within three weight classes allocated to two pens of ten pigs per treatment. Control and Imp boars were fed a finisher ration while the other diets were supplemented with Br, Trp or both Br and Trp. In Experiment 1, average daily gain (ADG) was not affected by diet but the Imp boars had higher ADG than controls. Feed intake (FI) tended to be higher in all treatments compared to controls except for the Trp group. In Experiment 2, Imp boars had higher ADG and FI than other treatments while Br+Trp boars had higher ADG and FI than controls. These data suggest that immunocastration and dietary Trp and Br show promise for improving performance in group-housed boars. Full article
(This article belongs to the Special Issue Feed Additives in Pig Feeding: 2nd Edition)
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<p>Effect of dietary neuroleptic or Improvac and weight class on average daily gain between 17 and 22 weeks of age. The error bars are the least significant difference (LSD) for weight × treatment = 134 g/d.</p>
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22 pages, 13410 KiB  
Article
Use of Transcriptomics to Identify Candidate Genes for Hematopoietic Differences Between Wujin and Duroc Pigs
by Peng Ji, Ping Wang, Qihua Li, Lin Gao, Yan Xu, Hongbin Pan, Chunyong Zhang, Jintao Li, Jun Yao and Qingcong An
Animals 2024, 14(23), 3507; https://doi.org/10.3390/ani14233507 - 4 Dec 2024
Viewed by 591
Abstract
Hematopoiesis is a complex physiological process that ensures renewal of blood cells to maintain normal blood circulation and immune function. Wujin pigs exhibit distinct characteristics such as tender meat, high fat storage, strong resistance to roughage, robust disease resistance, and oxidation resistance. Therefore, [...] Read more.
Hematopoiesis is a complex physiological process that ensures renewal of blood cells to maintain normal blood circulation and immune function. Wujin pigs exhibit distinct characteristics such as tender meat, high fat storage, strong resistance to roughage, robust disease resistance, and oxidation resistance. Therefore, using Wujin pigs as models may offer valuable insights for hematopoietic-related studies. In this study, twelve healthy 35-day-old piglets, including six Wujin and six Duroc piglets of similar weight, were selected from each of the Wujin and Duroc pig groups and housed in single cages. After 30 days of feeding, blood and bone marrow samples were collected. Routine blood indices and hematopoietic-related serum biochemical indexes of Wujin and Duroc pigs were determined, and bone marrow gene expression levels were analyzed using transcriptomics. (1) Hemoglobin (Hb) and Mean Corpuscular Hemoglobin Concentration (MCHC) levels in Wujin pigs were significantly higher than in Duroc pigs (p < 0.05), and platelet counts and serum Hb levels in Wujin pigs were significantly lower than in Duroc pigs (p < 0.05). (2) A total of 312 significantly differentially expressed genes were identified between the pigs. Their functions were mainly related to blood systems, inflammation, and oxidation. Six differentially expressed genes may be related to hematopoietic function. (3) By combining the differential genes screened through sequencing with Weighted Gene Co-expression Network Analysis results, 16 hematopoietic function differential genes were obtained, mainly focusing on immunity, inflammation, and induction of apoptosis functions. Differences were present in the immune and inflammatory responses between Wujin pigs and Duroc pigs, suggesting that differences in hematopoietic function between the two breeds were related to antioxidant capacity and disease resistance. Full article
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<p>Heat map of expression correlation between two samples. The order of sample size is based on the clustering results related to the samples. The clustering trees corresponding to the samples are displayed on the top and right sides of the figure. The color reflects the correlation between samples.</p>
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<p>Volcano map of differentially expressed genes. The two vertical dashed lines represent a two-fold expression difference threshold, and the horizontal dashed line corresponds to a <span class="html-italic">p</span>-value of 0.05 threshold.</p>
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<p>Hierarchical clustering analysis of differentially expressed genes. The abscissa (<span class="html-italic">x</span>-axis) represents the sample names and their clustering results, whereas the ordinate (<span class="html-italic">y</span>-axis) represents the differentially expressed genes and their clustering results. The color indicates the gene expression levels in the sample, shown as log10 values.</p>
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<p>Classification statistics of GO secondary node annotations for differentially expressed genes.</p>
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<p>Bubble diagram of GO enrichment. (<b>a</b>) Biological Process GO enrichment plot; (<b>b</b>) Cellular Component GO enrichment dotplot; (<b>c</b>) Molecular Function GO enrichment dotplot.</p>
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<p>Bubble diagram of GO enrichment. (<b>a</b>) Biological Process GO enrichment plot; (<b>b</b>) Cellular Component GO enrichment dotplot; (<b>c</b>) Molecular Function GO enrichment dotplot.</p>
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<p>Detailed statistics of KEGG classification of differentially expressed genes.</p>
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<p>Differential gene KEGG enrichment bubble map.</p>
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<p>Heat map of module-trait correlations. The modules, represented by different colors on the left, contain a group of co-expressed genes. The first row of data indicates the correlation between a trait and a module, with the numbers in brackets representing the significance of the results.</p>
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<p>MEpink-enriched GO entry annotation categorization statistical chart.</p>
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<p>MEpink-enriched KEGG pathway annotation categorization statistics.</p>
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<p>MEblack-enriched GO entry annotation categorization statistical chart.</p>
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<p>MEblack-enriched KEGG pathway annotation categorization statistics.</p>
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<p>RT-qPCR results after removing unannotated genes. * <span class="html-italic">p</span>-values &lt; 0.05.</p>
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16 pages, 6692 KiB  
Article
Behavior Tracking and Analyses of Group-Housed Pigs Based on Improved ByteTrack
by Shuqin Tu, Haoxuan Ou, Liang Mao, Jiaying Du, Yuefei Cao and Weidian Chen
Animals 2024, 14(22), 3299; https://doi.org/10.3390/ani14223299 - 16 Nov 2024
Viewed by 848
Abstract
Daily behavioral analysis of group-housed pigs provides critical insights into early warning systems for pig health issues and animal welfare in smart pig farming. In this study, our main objective was to develop an automated method for monitoring and analyzing the behavior of [...] Read more.
Daily behavioral analysis of group-housed pigs provides critical insights into early warning systems for pig health issues and animal welfare in smart pig farming. In this study, our main objective was to develop an automated method for monitoring and analyzing the behavior of group-reared pigs to detect health problems and improve animal welfare promptly. We have developed the method named Pig-ByteTrack. Our approach addresses target detection, Multi-Object Tracking (MOT), and behavioral time computation for each pig. The YOLOX-X detection model is employed for pig detection and behavior recognition, followed by Pig-ByteTrack for tracking behavioral information. In 1 min videos, the Pig-ByteTrack algorithm achieved Higher Order Tracking Accuracy (HOTA) of 72.9%, Multi-Object Tracking Accuracy (MOTA) of 91.7%, identification F1 Score (IDF1) of 89.0%, and ID switches (IDs) of 41. Compared with ByteTrack and TransTrack, the Pig-ByteTrack achieved significant improvements in HOTA, IDF1, MOTA, and IDs. In 10 min videos, the Pig-ByteTrack achieved the results with 59.3% of HOTA, 89.6% of MOTA, 53.0% of IDF1, and 198 of IDs, respectively. Experiments on video datasets demonstrate the method’s efficacy in behavior recognition and tracking, offering technical support for health and welfare monitoring of pig herds. Full article
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<p>Process diagram of tracking and behavioral time statistics for group-housed pigs.</p>
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<p>Flow chart of Pig-ByteTrack algorithm.</p>
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<p>The flow chart of the Byte data association algorithm.</p>
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<p>Comparison of tracking box between Pig-ByteTrack and ByteTrack.</p>
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<p>Comparison of Pig-BytetTrack, ByteTrack and TransTrack results on private datasets.</p>
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<p>The visualized tracking results comparison of Pig-BytetTrack, ByteTrack, and TransTrack.</p>
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<p>The visualized tracking results of Pig-BytetTrack in the 10 min videos. (The red arrows in the figure indicate pigs with id transformations).</p>
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<p>Pig behavior statistics for videos 14–17.</p>
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19 pages, 5406 KiB  
Article
An Automatic Movement Monitoring Method for Group-Housed Pigs
by Ziyuan Liang, Aijun Xu, Junhua Ye, Suyin Zhou, Xiaoxing Weng and Sian Bao
Animals 2024, 14(20), 2985; https://doi.org/10.3390/ani14202985 - 16 Oct 2024
Viewed by 936
Abstract
Continuous movement monitoring helps quickly identify pig abnormalities, enabling immediate action to enhance pig welfare. However, continuous and precise monitoring of daily pig movement on farms remains challenging. We present an approach to automatically and precisely monitor the movement of group-housed pigs. The [...] Read more.
Continuous movement monitoring helps quickly identify pig abnormalities, enabling immediate action to enhance pig welfare. However, continuous and precise monitoring of daily pig movement on farms remains challenging. We present an approach to automatically and precisely monitor the movement of group-housed pigs. The instance segmentation model YOLOv8m-seg was applied to detect the presence of pigs. We then applied a spatial moment algorithm to quantitatively summarize each detected pig’s contour as a corresponding center point. The agglomerative clustering (AC) algorithm was subsequently used to gather the pig center points of a single frame into one point representing the group-housed pigs’ position, and the movement volume was obtained by calculating the displacements of the clustered group-housed pigs’ center points of consecutive frames. We employed the method to monitor the movement of group-housed pigs from April to July 2023; more than 1500 h of top-down pig videos were recorded by a surveillance camera. The F1 scores of the trained YOLOv8m-seg model during training were greater than 90% across most confidence levels, and the model achieved an mAP50-95 of 0.96. The AC algorithm performs with an average extraction time of less than 1 millisecond; this method can run efficiently on commodity hardware. Full article
(This article belongs to the Section Pigs)
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<p>Experimental conditions: (<b>a</b>) draft of the pigpen; (<b>b</b>) installation position of the dual sensor surveillance camera; (<b>c</b>) top-down camera view of the pigsty floor.</p>
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<p>Designed workflow of the pig movement monitoring method.</p>
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<p>Model structure of YOLOv8-seg: the segmentation and detection tasks begin with the (<b>a</b>) original image and output an (<b>b</b>) image with a bounding box and segmentation contour.</p>
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<p>Distinguishing the center point of a predicted pig contour. The images in the columns are described as follows: (1) prediction image, (2) mean coordinate, (3) least squares, (4) signed area, and (5) spatial moment. The different pig behavior patterns depicted in each row are as follows: (<b>a</b>) lying, (<b>b</b>) sitting, and (<b>c</b>) standing.</p>
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<p>Running times of different algorithms based on the test video (1166 frames): (<b>a</b>) Time spent on each frame. (<b>b</b>) Total time spent in progress (average of 30 repetitions).</p>
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<p>Complete distribution information of group pig positions. The information was obtained from 13 May to 8 July 2023, and every pig position was drawn at a given point.</p>
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<p>Changes in the position information over time: (<b>a</b>) Pigs positioned during two periods from 13 May to 9 June 2023 and 10 June to 8 July 2023. (<b>b</b>) The statistical variation in the number of pigs appearing in different regions during the two periods.</p>
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<p>Daily summed movement distances of group-housed pigs from 13 May 2023 to 8 July 2023.</p>
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<p>Movement characteristics of pigs in terms of days with the longest, shortest, and median movement distances; every subfigure starts at 0 a.m. and ends at 12 p.m.</p>
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<p>Various distribution locations of group-housed pigs: (<b>a</b>) pigs lying close to the corner; (<b>b</b>) pigs congregating near the door; (<b>c</b>) herd of pigs eating.</p>
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18 pages, 5897 KiB  
Article
Tracking and Behavior Analysis of Group-Housed Pigs Based on a Multi-Object Tracking Approach
by Shuqin Tu, Jiaying Du, Yun Liang, Yuefei Cao, Weidian Chen, Deqin Xiao and Qiong Huang
Animals 2024, 14(19), 2828; https://doi.org/10.3390/ani14192828 - 30 Sep 2024
Viewed by 1032
Abstract
Smart farming technologies to track and analyze pig behaviors in natural environments are critical for monitoring the health status and welfare of pigs. This study aimed to develop a robust multi-object tracking (MOT) approach named YOLOv8 + OC-SORT(V8-Sort) for the automatic monitoring of [...] Read more.
Smart farming technologies to track and analyze pig behaviors in natural environments are critical for monitoring the health status and welfare of pigs. This study aimed to develop a robust multi-object tracking (MOT) approach named YOLOv8 + OC-SORT(V8-Sort) for the automatic monitoring of the different behaviors of group-housed pigs. We addressed common challenges such as variable lighting, occlusion, and clustering between pigs, which often lead to significant errors in long-term behavioral monitoring. Our approach offers a reliable solution for real-time behavior tracking, contributing to improved health and welfare management in smart farming systems. First, the YOLOv8 is employed for the real-time detection and behavior classification of pigs under variable light and occlusion scenes. Second, the OC-SORT is utilized to track each pig to reduce the impact of pigs clustering together and occlusion on tracking. And, when a target is lost during tracking, the OC-SORT can recover the lost trajectory and re-track the target. Finally, to implement the automatic long-time monitoring of behaviors for each pig, we created an automatic behavior analysis algorithm that integrates the behavioral information from detection and the tracking results from OC-SORT. On the one-minute video datasets for pig tracking, the proposed MOT method outperforms JDE, Trackformer, and TransTrack, achieving the highest HOTA, MOTA, and IDF1 scores of 82.0%, 96.3%, and 96.8%, respectively. And, it achieved scores of 69.0% for HOTA, 99.7% for MOTA, and 75.1% for IDF1 on sixty-minute video datasets. In terms of pig behavior analysis, the proposed automatic behavior analysis algorithm can record the duration of four types of behaviors for each pig in each pen based on behavior classification and ID information to represent the pigs’ health status and welfare. These results demonstrate that the proposed method exhibits excellent performance in behavior recognition and tracking, providing technical support for prompt anomaly detection and health status monitoring for pig farming managers. Full article
(This article belongs to the Section Pigs)
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<p>Part of group-housed pig images.</p>
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<p>The overall structure of V8-Sort.</p>
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<p>The pipeline of the YOLOv8n algorithm.</p>
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<p>The flowchart of OC-SORT.</p>
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<p>OC-SORT tracking process for pigs.</p>
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<p>Comparison between V8-Sort and other tracking methods on public datasets.</p>
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<p>Comparison between V8-Sort and other tracking methods on private datasets.</p>
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<p>The visual results of V8-Sort on the public dataset.</p>
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<p>The tracking results visualization of V8-Sort on the private dataset.</p>
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<p>The visualization of long-term tracking results. (The first row shows the tracking results for videos 2001 and 3010, and the second, third, and fourth rows, respectively, depict the tracking results of two frames from videos 2002, 2003 and 2004).</p>
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<p>Time allocation and proportion of pig behaviors.</p>
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<p>The proportional occurrence of the four behaviors.</p>
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13 pages, 1479 KiB  
Article
Short Immobilization in a Sling Does Not Lead to Increased Salivary Cortisol Levels in Pigs
by Sara Puy, Marta Giral and Dolores C. García-Olmo
Animals 2024, 14(19), 2760; https://doi.org/10.3390/ani14192760 - 24 Sep 2024
Cited by 1 | Viewed by 805
Abstract
The goal of the present study was to evaluate the potential stress developed in farm hybrid pigs and miniature laboratory pigs briefly restrained in a sling, by measuring salivary cortisol levels. The study was performed in 20 healthy pigs grouped into three groups: [...] Read more.
The goal of the present study was to evaluate the potential stress developed in farm hybrid pigs and miniature laboratory pigs briefly restrained in a sling, by measuring salivary cortisol levels. The study was performed in 20 healthy pigs grouped into three groups: group HYB-F: hybrid female pigs (n = 12), housed at the CREBA facility (Lleida, Spain); group MIN-F: Specipig® miniature female pigs (n = 4), housed at the CREBA facility; group MIN-M: Specipig® miniature male pigs (n = 4), housed at the Almirall facility (Barcelona, Spain). Upon arrival, the animals were enrolled in a social habituation and training program, which included habituation to a restraint sling. The sling was a stainless steel structure with a canvas hammock which had four openings for placing the animal’s feet. The assessment of stress levels in the sling was carried out by measuring cortisol levels in saliva samples. Five saliva samples were collected from each animal over 4 days: Sample 1 (basal sample): taken after animals perceived the presence of the technicians in the pen; Sample 2: taken after animals saw the sling in the pen; Sample 3: taken when animals were in the sling; Sample 4: taken 1 min after the previous one; Sample 5: taken after animals were released back on the floor. In group HYB-F, five animals (5/12) showed strong resistance and could not be restrained in the sling on at least one day. All animals in the groups of miniature pigs could be restrained on all the days. Within each group, the manipulation phase did not affect salivary cortisol levels. Likewise, salivary cortisol levels did not change significantly across days in either group. In conclusion, salivary cortisol levels did not increase when pigs were lifted and briefly restrained in the sling, even though some of them (in particular, the hybrid pigs) showed apparent signs of stress. The lack of correlation between such apparent stress and salivary cortisol levels might be because the vocalizations and movements were not really signs of stress, but simply a way of releasing discomfort, learned in the process of socialization and habituation. In light of this unexpected conclusion, further studies are needed to collect other physiological and behavioral data to clarify what actually happens when pigs are restrained in a sling. Full article
(This article belongs to the Special Issue Integrating Ethics and Ethology in Laboratory Animal Welfare Research)
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<p>Images of some elements and moments of the experimental procedure. (<b>A</b>) Restraint sling. (<b>B</b>) The sling placed on the floor of the pen to habituate and train the pigs to be restrained. (<b>C</b>) One pig in the sling; meanwhile, the operator is taking a salivary sample. (<b>D</b>) Sampling after descending the animal from the restraining sling.</p>
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<p>Schematic representation of the different sample moments. Sample 1: basal sample; Sample 2: sample obtained when the animal saw the sling; Sample 3: first sample obtained when the animal is put into the sling; Sample 4: second sample taken when animal is in the sling, one minute later; Sample 5: sample extracted after lower the animal from the restraint sling.</p>
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<p>Graphical representation of the assessment of cortisol levels (ng/mL) in the five saliva samples collected during 4 consecutive days in the different groups. The meaning of the abbreviations S1 to S5 is described in the text (<a href="#sec2-animals-14-02760" class="html-sec">Section 2</a>). HYB-F: hybrid female; MIN-F: miniature female; MIN-M: miniature male. Data are expressed as mean ± SD. Only above SD bars are depicted for clarity. Each point is the mean of n animals.</p>
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<p>Graphical representation of the assessment of cortisol levels (ng/mL) in the five saliva samples collected during 4 consecutive days in the hybrid animal group (HYB-F) depending on the individual temperament (strugglers: animals which showed strong resistance; non-strugglers: animals showing only slight resistance or no resistance at all). The meaning of the abbreviations S1 to S5 is described in the text (<a href="#sec2-animals-14-02760" class="html-sec">Section 2</a>). Data are expressed as mean ± SD. Only above SD bars are depicted for clarity. Each point is the mean of 13–26 samples. *: statistically significant difference (<span class="html-italic">p</span> &lt; 0.05).</p>
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17 pages, 2918 KiB  
Article
Clostridium butyricum Prevents Diarrhea Incidence in Weaned Piglets Induced by Escherichia coli K88 through Rectal Bacteria–Host Metabolic Cross-Talk
by Jing Liang, Sihu Wang, Shasha Kou, Cheng Chen, Wenju Zhang and Cunxi Nie
Animals 2024, 14(16), 2287; https://doi.org/10.3390/ani14162287 - 6 Aug 2024
Cited by 1 | Viewed by 1055
Abstract
This study aimed to evaluate the effects of Clostridium butyricum (C. butyricum) on the prevention of the diarrhea rates and growth performances of weaned piglets induced by Escherichia coli K88 (E. coli K88). Twenty-four weaned piglets (6.92 ± 0.11 kg) [...] Read more.
This study aimed to evaluate the effects of Clostridium butyricum (C. butyricum) on the prevention of the diarrhea rates and growth performances of weaned piglets induced by Escherichia coli K88 (E. coli K88). Twenty-four weaned piglets (6.92 ± 0.11 kg) were randomly assigned to one of three treatment groups for a period of 21 days. Each group consisted of eight pigs, with each pig being housed in an individual pen. Group I received the control diet along with normal saline, Group II received the control diet along with E. coli K88, and Group III received the control diet supplemented with 5 × 108 CFU/kg of C. butyricum and E. coli K88. We examined alterations in rectal microbiota and metabolites, analyzed the incidence of diarrhea, and investigated the interactions between microbiota and metabolites through the application of Illumina MiSeq sequencing and liquid chromatography–mass spectrometry. The results showed that, from days 14 to 21, the diarrhea incidence in Group III decreased significantly by 83.29% compared to Group II (p < 0.05). Over the entire experimental duration, the average daily feed intake of Group III decreased significantly by 11.13% compared to Group I (p < 0.05), while the diarrhea incidence in Group III decreased by 71.46% compared to Group II (p < 0.05). The predominant microbial flora in the rectum consisted of Firmicutes (57.32%), Bacteroidetes (41.03%), and Proteobacteria (0.66%). Administering E. coli K88 orally can elevate the relative abundance of Megasphaera (p < 0.05). Conversely, the supplementation of C. butyricum in the diet reduced the relative abundance of Megasphaera (p < 0.05), while increasing the relative abundance of unclassified_f_Lachnospiraceae (p < 0.05). Rectal metabolomics analysis revealed that supplementing C. butyricum in the feed significantly altered the amino acids and fatty acids of the piglets infected with E. coli K88 (p < 0.05). The correlation analysis showed that the occurrence of diarrhea was inversely related to adipic acid (p < 0.05) and positively associated with (5-hydroxyindol-3-YL) acetic acid and L-aspartic acid (p < 0.05). Prevotella_1 exhibited a negative correlation with octadecanoic acid (p < 0.05). Prevotellaceae_UCG-005 showed a negative correlation with (5-hydroxyindol-3-YL) acetic acid (p < 0.05). The findings from this research study aid in probiotic development and the enhancement of healthy growth in weaned piglets. Full article
(This article belongs to the Section Animal Nutrition)
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<p>Venn diagram, rank–abundance and rarefaction curves of fecal microorganism in weaned piglets in different treatment groups. (<b>A</b>) Venn diagram; (<b>B</b>) rank–abundance curve; (<b>C</b>) rarefaction curve.</p>
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<p>Non-metric multidimensional scaling analysis (<b>A</b>) and partial least-squares discriminant analysis (<b>B</b>) at the OTU level for three treatment groups.</p>
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<p>Classification of the bacterial community composition across the three different treatment groups. (<b>A</b>) Relative abundance of bacterial phylum level and (<b>B</b>) relative abundance of bacterial genus level.</p>
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<p>Heatmap showing the most relative abundance of dominant bacterial OTUs. Note: the relative values are indicated by color intensity, with the legend indicated at the right corner.</p>
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<p>Two-dimensional score plots of fecal metabolites in three different treatment groups. (<b>A</b>,<b>B</b>) partial least-squares discriminant analysis (PLS-DA) in positive/negative ion modes, (<b>C</b>,<b>D</b>) PLS-DA replacement test in positive/negative ion mode, and (<b>E</b>,<b>F</b>) orthogonal partial least-squares discriminant analysis (OPLS-DA) in positive/negative ion mode (<span class="html-italic">n</span> = 6).</p>
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<p>Pathway enrichment map analysis of differential metabolites in feces between (<b>A</b>–<b>C</b>) using MetaboAnalystR 3.0. Note: the color of the circles from white to yellow to red denotes incremental fold change (−log(<span class="html-italic">p</span>)). The size of the circles from small to large indicates an increment of the impact of the pathway.</p>
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<p>Correlation between the body weight, diarrhea incidence, differential microbiota (at the genera level), and metabolites. (<b>A</b>) Correlation between body weight, diarrhea incidence, and microbiota. (<b>B</b>) Correlation between body weight, diarrhea incidence, and metabolites. (<b>C</b>) Correlation between microbiota and metabolites. Note: the strength (Spearman’s ρ value) and significance of correlations are shown as color in shades (red, positive correlation; blue, negative correlation). The values above/below zero represent positive/negative correlations. Significant correlations are noted by * <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01, *** <span class="html-italic">p</span> ≤ 0.001.</p>
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17 pages, 309 KiB  
Article
Dietary Triple-Strain Bacillus-Based Probiotic Supplementation Improves Performance, Immune Function, Intestinal Morphology, and Microbial Community in Weaned Pigs
by Lei Xue, Shenfei Long, Bo Cheng, Qian Song, Can Zhang, Lea Hübertz Birch Hansen, Yongshuai Sheng, Jianjun Zang and Xiangshu Piao
Microorganisms 2024, 12(8), 1536; https://doi.org/10.3390/microorganisms12081536 - 27 Jul 2024
Viewed by 1282
Abstract
Probiotics provide health benefits and are used as feed supplements as an alternative prophylactic strategy to antibiotics. However, the effects of Bacillus-based probiotics containing more than two strains when supplemented to pigs are rarely elucidated. SOLVENS (SLV) is a triple-strain Bacillus-based [...] Read more.
Probiotics provide health benefits and are used as feed supplements as an alternative prophylactic strategy to antibiotics. However, the effects of Bacillus-based probiotics containing more than two strains when supplemented to pigs are rarely elucidated. SOLVENS (SLV) is a triple-strain Bacillus-based probiotic. In this study, we investigate the effects of SLV on performance, immunity, intestinal morphology, and microbial community in piglets. A total of 480 weaned pigs [initial body weight (BW) of 8.13 ± 0.08 kg and 28 days of age] were assigned to three treatments in a randomized complete block design: P0: basal diet (CON); P200: CON + 200 mg SLV per kg feed (6.5 × 108 CFU/kg feed); and P400: CON + 400 mg SLV per kg feed (1.3 × 109 CFU/kg feed). Each treatment had 20 replicated pens with eight pigs (four male/four female) per pen. During the 31 d feeding period (Phase 1 = wean to d 14, Phase 2 = d 15 to 31 after weaning), all pigs were housed in a temperature-controlled nursery room (23 to 25 °C). Feed and water were available ad libitum. The results showed that the pigs in the P400 group increased (p < 0.05) average daily gain (ADG) in phase 2 and tended (p = 0.10) to increase ADG overall. The pigs in the P200 and P400 groups tended (p = 0.10) to show improved feed conversion ratios overall in comparison with control pigs. The pigs in the P200 and P400 groups increased (p < 0.05) serum immunoglobulin A, immunoglobulin G, and haptoglobin on d 14, and serum C-reactive protein on d 31. The pigs in the P200 group showed an increased (p < 0.01) villus height at the jejunum, decreased (p < 0.05) crypt depth at the ileum compared with other treatments, and tended (p = 0.09) to have an increased villus–crypt ratio at the jejunum compared with control pigs. The pigs in the P200 and P400 groups showed increased (p < 0.05) goblet cells in the small intestine. Moreover, the pigs in the P400 group showed down-regulated (p < 0.05) interleukin-4 and tumor necrosis factor-α gene expressions, whereas the pigs in the P400 group showed up-regulated occludin gene expression in the ileum. These findings suggest that SLV alleviates immunological reactions, improves intestinal microbiota balance, and reduces weaning stress in piglets. Therefore, SOLVENS has the potential to improve health and performance for piglets. Full article
(This article belongs to the Section Veterinary Microbiology)
10 pages, 4585 KiB  
Article
Does the Farming Method Influence the Porcine Vomeronasal Organ Condition? A Histological Study
by Violaine Mechin, Pietro Asproni, Eva Teruel, Marion Boutry, Alessandro Cozzi and Patrick Pageat
Animals 2024, 14(14), 2105; https://doi.org/10.3390/ani14142105 - 18 Jul 2024
Viewed by 863
Abstract
The vomeronasal organ (VNO) plays a key role in mammals, since it detects pheromones thus enabling social interactions between congeners. VNO inflammatory changes have been shown to severely impact animal life, leading to impaired social interactions in groups, such as in pigs. Environmental [...] Read more.
The vomeronasal organ (VNO) plays a key role in mammals, since it detects pheromones thus enabling social interactions between congeners. VNO inflammatory changes have been shown to severely impact animal life, leading to impaired social interactions in groups, such as in pigs. Environmental air is known to be strongly modified in farms, and it is suspected to be one of the causes of this alteration. This study aimed to compare via histology the VNOs of pigs housed in intensive conditions (n = 38) to those of pigs housed in free-range farming conditions (n = 35). VNO sections were stained in hematoxylin and eosin to assess the presence of nonsensory and sensory epithelium alterations and collagenolysis. The nonsensory epithelium was significantly more inflamed in animals in free-range farming conditions than those in intensive conditions (p < 0.0001) and was more strongly affected by signs of collagenolysis (p < 0.0001). The sensory epithelium seemed to be less altered by the different environmental conditions (p = 0.7267). These results suggest that species-typical pig behaviors, such as digging and rooting for food, could facilitate the presence of microparticles in the oral cavity and their entrance into the vomeronasal canals, leading to changes to the VNO. Full article
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<p>Distribution (%) of vomeronasal sensory epithelium alteration scores between pigs from free-range (N = 66) and intensive (N = 76) farming conditions. The data are shown as the percentage of VNOs assigned to each alteration score.</p>
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<p>Representative images of inflammation intensities in the VNSE: 0 = healthy epithelium without inflammation (<b>A</b>); 1 = weak inflammation (<b>B</b>); 2 = moderate inflammation (<b>C</b>); and 3 = strong inflammation (<b>D</b>), with the presence of inflammatory infiltrations (black arrows). Objective, ×20; scale bar = 200 µm.</p>
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<p>Distribution (%) of vomeronasal nonsensory epithelium alteration scores between pigs from free-range (N = 66) and intensive (N = 76) farming conditions. The data are shown as the percentage of VNOs assigned to each alteration score. *** indicates <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Representative images of inflammation intensities in the NSE: 1 = weak epithelium inflammation (<b>A</b>); 2 = moderate infiltration (<b>B</b>); and 3 = strong inflammation (<b>C</b>), with the presence of chronic inflammatory infiltration (black arrows). Objective, ×20; scale bar = 200 µm.</p>
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<p>Distribution (%) of collagenolysis scores between pigs from free-range (N = 56) and intensive (N = 42) farming conditions. The data are shown as the percentage of VNOs assigned to each score. *** indicates <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Distribution (%) of inflammation laterality between pigs from free-range (N = 31) and intensive (N = 38) farming conditions. The data are shown as the percentage of snouts with bilateral or unilateral VNSE inflammation.</p>
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18 pages, 2682 KiB  
Article
Effect on Feeding Behaviour and Growing of Being a Dominant or Subordinate Growing Pig and Its Relationship with the Faecal Microbiota
by Juan Ochoteco-Asensio, Gustavo Zigovski, Leandro Batista Costa, Raquel Rio-López, Adrià Clavell-Sansalvador, Yuliaxis Ramayo-Caldas and Antoni Dalmau
Animals 2024, 14(13), 1906; https://doi.org/10.3390/ani14131906 - 27 Jun 2024
Cited by 1 | Viewed by 1127
Abstract
Pigs are a social species, and they establish hierarchies for better use of resources and to reduce conflicts. However, in pig production, the opportunities for growth can differ between dominant and subordinate animals. In the present study, a system was tested to perform [...] Read more.
Pigs are a social species, and they establish hierarchies for better use of resources and to reduce conflicts. However, in pig production, the opportunities for growth can differ between dominant and subordinate animals. In the present study, a system was tested to perform a dominant versus subordinate test in growing pigs to investigate how the hierarchy affects feeding behaviour, growth, and gut microbiota assessed in faeces. Sixty-four animals housed in eight different pens were used, with four castrated males and four females in each one, weighing 18 kg at arrival and maintained during the whole growing period, until 140 kg. Three stool samples were obtained from the animals directly from the anus to avoid contamination of the faeces 58, 100, and 133 days after the start of the study to investigate the microbiota composition. The dominant animals had higher gains during the growing period than the subordinates. In addition, they were performing more visits to the feeder throughout the day. Differential abundance patterns were observed in five bacterial genera, with Oliverpabstia, Peptococcus, and Faecalbacterium being more abundant in dominant animals and Holdemanella and Acetitomaculum being overrepresented in subordinate ones. This microbial biomarker accurately classified dominant versus subordinate groups of samples with an AUC of 0.92. Full article
(This article belongs to the Section Animal Welfare)
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<p>Mean weight (kg) per phase and hierarchy class with standard deviation error bars. A statistically significant difference between submissive and dominant classes in phase three (<span class="html-italic">p</span> = 0.018) is indicated by an asterisk (*). No significant difference was observed between Intermediate and Dominant classes.</p>
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<p>Marginal effects plot between relative food intake (at pen level) and hierarchy (phase 2 (<b>A</b>) and phase 3 (<b>B</b>)). Higher hierarchy classes correspond to increased food consumption. The difference between submissive and dominant classes is statistically significant in both cases (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Marginal effects plots for phase 3: (<b>A</b>) number of visits and (<b>B</b>) percentage of time spent eating (10:00 h–13:59 h). Significant differences between dominant and submissive pigs are observed in all plots.</p>
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<p>Marginal effects plot illustrating the association between food intake and hierarchy change between phases 2 and 3 (<b>A</b>). A marginal effects plot illustrating the association between the food intake and hierarchy change between phases 2 and 3. The interaction between phase 3 and a worsened hierarchical change was found to present a significant negative effect (<span class="html-italic">p</span> &lt; 0.05). (<b>B</b>). A marginal effects plot illustrating the association between the relative feed rate and hierarchy change between phases 1 and 3. The interaction between phase 3 and a worsened hierarchical change was found to present a significant negative effect (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Normalised values for each of the behaviour measurements for both F840 (<b>A</b>) and M917 (<b>B</b>) across all phases. The values were normalised by dividing the original values by the median of their corresponding pens.</p>
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<p>Alpha and beta diversity results. (<b>A</b>): Box plot of the Shannon diversity index for each hierarchical class. Higher values indicate higher diversity. No significant differences were found. (<b>B</b>): Box plot of the Bray–Curtis distance for both hierarchical classes. Values between 0 and 1 indicate varying degrees of dissimilarity. No significant difference was found.</p>
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<p>NetMoss results of the differential bacteria between submissive and dominant classes. NetMoss plot showing the top 40 bacteria (vertical axis) with the highest NetMoss score (horizontal axis) in descending order. The colour of each line/bacteria represents the <span class="html-italic">p</span>-adjusted value of the difference in abundance between both classes. To the right, the same ranked bacteria are plotted for the logarithm of 2 of the fold-change abundance of the submissive over the dominant. A table of the bacteria found to be significantly (<span class="html-italic">p</span> adj. &lt; 0.05) more abundant in either group, sorted by descending order of the NetMoss score, is also shown.</p>
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