Behaviour Of Pigs Research Articles

Factors influencing the activity ranges of feral pigs (Sus scrofa) across four sites in eastern Australia

Context Understanding the home-range size and the ecological drivers that influence the spatial distribution of feral pigs is of paramount importance for exotic-disease modelling and the improvement of pest management programs. Aims To investigate various factors affecting home- and core-range size and test selection of habitat, to better inform disease modelling and pest management programs. Methods In this study, 59 GPS-collared feral pigs were tracked over four sites in eastern Australia between 2017 and 2021. Using minimum convex polygon (MCP) and the nearest-neighbour–local convex hull (k-LoCoH) as home-range estimators and foliage projective cover (FPC) as an estimator of landscape-scale shelter, we investigated the influence of sex, site, season, year and body weight on range size and tested selection of habitat by using chi-squared and Jacob’s index tests. Key results Home-range sizes were highly variable, with k-LoCoH90 (home) ranges between 0.08 and 54.97 km2 and k-LoCoH50 (core) ranges between 0.01 and 7.02 km2. MCP90 ranged between 0.15 and 242.30 km2, with MCP50 being between 0.07 and 60.61 km2. Sex and site both significantly (P < 0.001) influenced home-range size, but season and year did not. Home-range size was shown to increase with body mass for both sexes (P = 0.001). Importantly, the data indicated that feral pigs prefer habitat within 20–40% FPC (woodland), whereas open forests (51–80% FPC) and closed forests (>80% FPC) were actively avoided. Typically, use of open vegetation (1–10% FPC) was also avoided, but this behaviour varied and was dependent on site. Conclusion Feral pig ranges are influenced by sex, site and body mass but not by season and year. Broad-scale selection for shelter indicated that feral pigs prefer habitat between 20% and 40% FPC. Implications Targeting or avoiding such areas respectively for control or monitoring tool placement may result in improved, efficient outcomes to monitor or manage feral pig populations. Feral pig distribution modelling may also find benefit in the consideration and further study of the above factors and the influence of food and water sources on the activity ranges and behaviour of feral pigs.

Influence of the type of local heating and its energy saving on the productivity and behaviour of suckling pigs

Influence of the type of local heating and its energy saving on the productivity and behaviour of suckling pigs

Water scarcity exacerbates feral ungulate use of ephemeral savanna waterholes in northern Australia

Context Australian savannas evolved in the absence of hooved mammals and are therefore prone to disturbance from exotic ungulates. Several ungulate species have established feral populations in Australia’s northern savannas. Because most ungulate species have high water requirements, seasonal and interannual changes in water availability are likely to affect their behaviour and the extent of their impacts on native ecosystems. However, few studies have investigated how water scarcity affects feral ungulate use of waterpoints in Australia. Aims The aim of this study was to determine whether seasonal and interannual water scarcity affected the visitation behaviours of feral pigs, cattle and water buffalo at ephemeral savanna waterholes within Limmen National Park, Northern Territory, Australia. Methods We used motion-triggered wildlife cameras to study feral ungulate visitation and behaviour at 20 waterholes. Generalised linear mixed-effects models were used to investigate whether the number of visits, duration of visits and number of individuals visiting waterholes varied with year and dry season progression. We also investigated whether these factors affected the amount of time ungulates spent foraging, drinking and wallowing at waterholes. Key results All three species visited waterholes more often, for longer periods and in larger numbers during a drought year compared with an average rainfall year. Cattle and buffalo spent more time drinking from waterholes during the drought, and pigs and cattle spent longer periods foraging. Buffalo also wallowed more during the drought. Responses to dry season progression varied among species. Cattle visited waterholes more frequently, for longer durations and in larger herd sizes as the dry season progressed, whereas buffalo use did not change. Pigs only increased their visitation to waterholes when water scarcity was most extreme, at the end of the dry season during the drought. Conclusions Our results demonstrate that water scarcity exacerbates feral ungulate use of savanna waterholes. Management and control programs for feral ungulates in Australian savannas may benefit from targeting different species under specific water scarcity conditions. Implications Because climate change is predicted to reduce surface water availability in northern Australia, feral ungulate use of savanna waterholes may intensify, risking further biodiversity losses and irreversible ecosystem damage.

Feral pig (Sus scrofa) activity and landscape feature revisitation across four sites in eastern Australia

Quantifying feral pig movements and understanding the fine-scale ecological drivers of feral pig landscape use are important factors for optimising pest management programs. We tracked 59 GPS-collared feral pigs at four sites in eastern Australia between 2017 and 2021, for a mean of 375 ± 277 (s.d.) days. The mean number of successful GPS fixes was 15 577 ± 11 833 (s.d.) and these were recorded at 30-min intervals. We calculated mean hourly and daily distances travelled to determine feral pig activity and investigated the influence of sex, site, season and time of day on this activity. We also investigated the proximity of highly active sites to habitat covariates, along with intensity and frequency of site use. Male daily movement, 4.9 km (95% CI = 4.2, 5.6 km), was significantly greater than it was for females, 3.6 km (95% CI = 3.0, 4.1 km) and males maintained a high level of activity all night, while female activity was predominantly crepuscular. Study site was a significant determinant of daily movement, but season was not, across either sex or site. Highly-visited site selection was negatively associated with distance from creeks, dams, cultivation, open herbaceous vegetation and medium woody vegetation. Both medium woody vegetation and dam sites had the longest duration of use (3 and 2.7 h respectively) and the shortest time between visitations (14.5 and 13 h respectively). Quantifying feral pig activity and key habitat feature preference are important steps in improving management programs. Better prediction of feral pig movement and behaviour allows for more targeted placement of control tools, potentially increasing encounter rates.

RESEARCH ON IDENTIFICATION AND CLASSIFICATION METHOD OF IMBALANCED DATA SET OF PIG BEHAVIOR

To address the problem of the low accuracy and poor robustness of modeling methods for imbalanced data sets of pig behavior identification and classification, the three commonly used re-sampling methods of under-sampling, SMOTE and Borderline-SMOTE are compared, and an adaptive boundary data augmentation algorithm AD-BL-SMOTE is proposed. The activity of the pigs was measured using triaxial accelerometers, which were fixed on the backs of the pigs. A multilayer feed-forward neural network was trained and validated with 21 input features to classify four pig activities: lying, standing, walking, and exploring. The results showed that re-sampling methods are an effective way to improve the performance of pig behavior identification and classification. Moreover, AD-BL-SMOTE could yield greater improvements in classification performance than the other three methods for balancing the training data set. The overall major mean accuracy of lying, standing, walking, and exploring by pigs A, B and C was significantly improved by using AD-BL-SMOTE, reaching 91.8%, 93.0% and 96.0%, respectively.

The long and short of showers: Effects of shower duration on behaviour, thermal comfort and soiling of organic growing-finishing pigs with access to outdoor runs

Showers can be used in the outdoor run to improve thermal comfort and provide environmental enrichment for growing-finishing pigs. Showers may also reduce ammonia emissions by preventing excessive soiling in summer. Few studies have addressed water cooling measures for pigs in systems with concrete outdoor runs, and none have considered the operation of showers outdoors. We therefore investigated the effect of showers in the outdoor run on pigs’ use of different pen areas, thermal comfort, and soiling of the pigs and the pen in multi-farm experiments in Austria and Switzerland. In a pilot experiment on three organic farms involving a total of 428 growing-finishing pigs in 15 groups with two to three assessment days each, we compared groups with access to showers to groups without showers. A subsequent larger trial (referred to as SHORT/LONG experiment) compared two different shower programmes (SHORT = 10-minutes; LONG = 30-minutes shower activation per hour), comprising a total of 472 pigs in 20 groups on three farms with six to seven assessment days each. The treatments SHORT and LONG were alternately applied with at least three replicates per farm. We assessed the pigs’ behaviour (activity, lying posture), respiratory rate and cleanliness as well as soiling of the pens on a group level. The pilot experiment revealed increased activity (p = 0.03) and reduced lateral lying (p = 0.08) in pigs with access to showers compared to pigs without, which supports the potential of showers to improve thermal comfort. In the SHORT/LONG experiment, we found interactions between treatment and outdoor temperature: The proportion of pigs under the shower (p < 0.01), lateral lying in the shower area (p = 0.01) and respiratory rate (p < 0.01) increased more with rising temperatures in treatment LONG than in SHORT. In both treatments, high temperatures increased the use of the outdoor run (p = 0.02) and the shower area (p < 0.001) as well as the soiling of pigs (p < 0.01), while at the same time reducing activity in the shower area (p = 0.02). Interestingly, fewer pigs were present in the shower area during and at the end of shower activation compared to the time before (p < 0.001), indicating avoidance of the water spray. This casts doubt on whether showers, apart from reducing heat stress, provide appropriate means to allow all aspects of species-specific thermoregulation. Our results suggest complex interactions between outdoor temperature, shower duration, pig behaviour, and soiling (with potential impact on ammonia emission), which require further investigation especially in open-air settings.

Systems to Monitor the Individual Feeding and Drinking Behaviors of Growing Pigs Based on Machine Vision

Feeding and drinking behaviors are important in pig breeding. Although many methods have been developed to monitor them, most are too expensive for pig research, and some vision-based methods have not been integrated into equipment or systems. In this study, two systems were designed to monitor pigs’ feeding and drinking behaviors, which could reduce the impact of the image background. Moreover, three convolutional neural network (CNN) algorithms, VGG19, Xception, and MobileNetV2, were used to build recognition models for feeding and drinking behaviors. The models trained by MobileNetV2 had the best performance, with the recall rate higher than 97% in recognizing pigs, and low mean square error (RMSE) and mean absolute error (MAE) in estimating feeding (RMSE = 0.58 s, MAE = 0.21 s) and drinking durations (RMSE = 0.60 s, MAE = 0.12 s). In addition, the two best models trained by MobileNetV2 were combined with the LabVIEW software development platform, and a new software to monitor the feeding and drinking behaviors of pigs was built that can automatically recognize pigs and estimate their feeding and drinking durations. The system designed in this study can be applied to behavioral recognition in pig production.

Human-animal interactions during on-farm truck loading of finishing pigs for slaughter transport

Finishing pigs and transport drivers (TDs) interact closely when pigs are loaded for transport, which can be very stressful for both. We aimed to investigate relationships between TD handling actions and pig behaviours during loading for slaughter transport. In total 2,476 finishing pigs were loaded by 18 TDs (2 women, 16 men) during 18 loadings at 18 pig farms in Sweden over a 6 month period. Tactile, vocal and visual TD handling actions were recorded and characterized as ‘moderately-strongly negative’, ‘mildly negative’ or ‘positive’. In the pigs, ‘stress related’, ‘flow’, ‘disrupted flow’ and ‘relaxed’ behaviours were recorded in all animals within 2 m in front of the TDs, using continuous video recordings, and summarized in 5-s intervals. Logistic models were constructed to estimate associations between actions and behaviours, including the preceding one or two intervals. The odds of stress related behaviour in the pigs was found to increase 5.4 and 4.1 times when a moderately-strongly negative and any negative TD action, respectively, occurred in the same interval. When a moderately-strongly negative and any negative TD action occurred in the preceding interval, the odds of stress related behaviour increased 2.0 times and 1.4 times, respectively. The odds of disrupted flow increased 1.6 times when any negative TD action occurred in the same interval. Furthermore, the odds of moderately-strongly negative TD action increased 5.4, 3.4 and 1.9 times, and the odds of any negative TD action increased 3.6, 2.9 and 2.1 times when stress related pig behaviour occurred in the same interval, the preceding interval and the interval before that, respectively. Positive TD action in the same or preceding interval was associated with relaxed pig behaviour. This study suggests a reciprocal relationship between TD actions and pig behaviour, which provides an opportunity to improve TD actions through training in order to reduce stress behaviours in pigs.

Correction: Use of two novel trailer types for transportation of pigs to slaughter. I. Effects on trailer microclimate, pig behaviour, physiological response, and meat quality under Canadian summer conditions

Correction: Use of two novel trailer types for transportation of pigs to slaughter. I. Effects on trailer microclimate, pig behaviour, physiological response, and meat quality under Canadian summer conditions

Correction: Use of two novel trailer types for transportation of pigs to slaughter. II. Effects on trailer microclimate, pig behaviour, physiological response, and meat quality under Canadian winter conditions

Correction: Use of two novel trailer types for transportation of pigs to slaughter. II. Effects on trailer microclimate, pig behaviour, physiological response, and meat quality under Canadian winter conditions

Pigs as Pets: Early Human Relations with the Sulawesi Warty Pig (Sus celebensis).

The Sulawesi warty pig (S. celebensis) is a wild and still-extant suid that is endemic to the Indonesian island of Sulawesi. It has long been theorised that S. celebensis was domesticated and/or deliberately introduced to other islands in Indonesia prior to the advent of the Neolithic farming transition in the region. Thus far, however, there has been no empirical support for this idea, nor have scientists critiqued the argument that S. celebensis was a pre-Neolithic domesticate in detail. Here, it is proposed that early foragers could have formed a relationship with S. celebensis that was similar in essence to the close association between Late Pleistocene foragers in Eurasia and the wild wolf ancestors of domestic dogs. That is, a longstanding practice of hunter-gatherers intensively socialising wild-caught S. celebensis piglets for adoption into human society as companion animals ('pets') may have altered the predator-prey dynamic, brought aspects of wild pig behaviour and reproduction under indirect human selection and control, and caused changes that differentiated human-associated pigs from their solely wild-living counterparts.

Evaluation of computer vision for detecting agonistic behavior of pigs in a single-space feeding stall through blocked cross-validation strategies

Agonistic behavior at feeding spaces is associated with both welfare and feed intake issues in swine farming. Studying interactive social behaviors of group-housed pigs provides valuable information to improve their production and welfare. The aims of this study were to (1) develop a deep learning pipeline based on convolutional neural network (CNN) and long short-term memory (LSTM) to classify videos depicting four types of interactive behavior between pigs in a single-space feeding stall and (2) validate the CNN + LSTM pipeline through various blocked validation strategies. Four categories of behaviors were classified in this study: head-to-body contact (including gentle nosing, casual contact between head/ears of a pig with a feeding pig, head knocking, tail biting, and pushing); levering where the feeding pig was lifted from behind by another pig; mounting in which the feeding pig was mounted by another pig; and no-contact when a second pig entered the feeding stall without physical contact with the feeding pig. Behavior at the feeding stall was filmed twice, three weeks apart, for two consecutive days each week using six groups of grow-finish pigs (10 per group) housed in pens equipped with FIRE® feeders. This resulted in a total of 15,679 30-frame video episodes for classification. Random validation, blocking-by-time validation, and blocking-by-feeder validation were utilized for training-validation data split. The size of training sets was held constant (N = 7,500) through all validation scenarios. The average validation accuracies were 0.968(±0.001), 0.860(±0.033), 0.766(±0.026), and 0.860(±0.010) for random validation, blocking-by-time validation, and blocking-by-feeder validation (at Feeder 1 and at Feeder 2), respectively. The results indicate that the CNN + LSTM pipeline yielded acceptable predictive performance in random validation. However, performance was substantially worse in blocking-by-time and blocking-by-feeder validations. More work is needed for algorithm generalization to improve its robustness across a variety of real-life application scenarios. We provide public access to the dataset and the code.

Strategies to manage barn feed supply to prolong and hold late finishing pigs during a supply chain disruption.

The U.S. pork production system is sensitive to supply chain disruptions, including those that can create challenges of feed delivery and feed management during the event of a foreign animal disease outbreak. Therefore, the objective was to evaluate feeding strategies during a prolonged feed availability shortage in group-housed finishing pigs and assess the impacts on pig performance. A total of 1,407 mixed-sex pigs (92 ± 11 kg BW) were randomly allocated to one of five treatments across 60 pens (N = 12 pens per treatment, 22 pigs per pen) and were blocked by initial body weight (BW) within the replicate, over a 21-d test period. Treatments were fed for 14 d (P1), and thereafter all pens returned to ad libitum access to a standard commercial diet for 7 d (P2). Treatments included: 1) Pens fed ad libitum (CON); 2) Pens fed at 1.45X ME maintenance requirement daily of CON diet (1.45X); 3) Pens fed 2X ME maintenance requirement daily of CON diet (2X); 4) Tightened feeders to the lowest setting, fed ad libitum of CON diet (CF); and 5) whole corn kernels, fed ad libitum (WC). P1 and P2 BW and feed disappearance were recorded to calculate ADG, ADFI, and G:F. Data were analyzed with pen as the experimental unit and least-squares means values reported by treatment. Compared to CON, pens fed 1.45X, 2X, CF, and WC treatments had significantly reduced P1 ADG (1.09 vs. 0.02, 0.34, 0.72, 0.41 kg/d, respectively), ADFI (3.21 vs. 1.42, 1.90, 2.49, 2.40 kg/d, respectively) and G:F (P < 0.05). During P2, ADG and G:F were increased (P < 0.05) compared to CON across all treatments. However, ADFI increased only in the 2X, CF, and WC diet from the CON (P < 0.05). Overall (days 0 to 21), all strategies attenuated BW, ADG, and ADFI (P < 0.01) compared to CON. However, G:F was only reduced (P < 0.01) in 1.45X and WC, but not 2X and CF (P > 0.05) compared to CON. In conclusion, all strategies explored could extend feed budgets. Even though these strategies were successful, increased BW variability was reported with more restrictive strategies. Further, adverse pig behaviors and welfare implications needs to be considered in adopting any restrictive feeding strategy.

Postweaning growth and feeding behaviour in pigs: effect of heavier hybrid and weaning intact litters in farrowing pens for loose-housed sows

Abrupt weaning of four-week-old pigs is associated with multiple stressors. Housing pigs in intact litters is a way to reduce the stress associated with moving and mixing of unfamiliar pigs. Furthermore, higher weaning weight may improve pigs’ robustness against postweaning stressors. In the present study, it was investigated whether: (1) A heavier pig hybrid, and (2) weaning intact litters in the farrowing pen for loose-housed sows could increase postweaning feeding behaviour and growth. Two sow hybrids (DanBred LY (DB) and Topigs Norsvin TN70 (TN)) and two weaning strategies (the litter stayed intact in the farrowing pen after removing the sow (STAY), or two litters were moved and mixed in conventional weaner pens (MOVE)) were compared in a 2 × 2 factorial design. In total, 57 litters from four batches were included in the study. The TN hybrid sows gave birth to heavier piglets but smaller litter sizes and had more functional teats than DB sows. At weaning, TN pigs were heavier than DB. The number of feed trough (FT) visits on the day before weaning was low in both hybrids. On the day after weaning, the number of FT visits was higher in MOVE compared to STAY, and in TN-STAY compared to DB-STAY. The average daily gain the first two days postweaning was negative in both hybrids and weaning strategies but more pronounced in DB than TN, and STAY tended to lose more weight than MOVE. Over the entire 28-day postweaning period, there was an interaction between hybrid and weaning strategy in that TN-STAY (392 g/d) had higher growth than both TN-MOVE (251 g/d) and DB-MOVE (283 g/d), whereas growth of DB-STAY (316 g/d) was intermediate. In addition, higher weaning weight was associated with a lower number of FT visits and greater weight loss the first two days postweaning but higher growth over the 28-day postweaning period. The results show that abrupt weaning at four weeks of age causes weight loss the first days postweaning despite being housedas intact litters, most likely due to low feed consumption. However, the combination of a heavier pig hybrid and housing intact litters in the farrowing pen postweaning resulted in a higher growth performance over the 28-day postweaning period. In conclusion, pigs that are heavier at weaning reach better growth performance in the longer term, despite having the largest acute postweaning growth depression and fewest FT visits on the day before and after weaning.

An efficient anchor‐free method for pig detection

Given the rapid growth of commercial pig farms, the need to automatically monitor pig behaviour becomes more important in order to assist farmers. Recent advances in convolutional neural networks may pave the way for new solutions. However, the primary task of individual pig detection under real-world conditions is still a challenging task. Previous studies used anchor-based frameworks that are unsuitable for such crowded scenarios with extreme overlapping. Furthermore, most applications focus on specific levels of brightness, farm facilities, or pig species without considering generalization. To tackle these problems, an anchor-free pig detection method based on pig centre localization is first proposed. Then, a novel negative training data augmentation technique is introduced using examples from outside the training distribution. Furthermore, using the test time augmentation technique is proposed to improve the model performance. Experiments are conducted on two online pig detection datasets; the network surpasses state-of-the-art results for both datasets. It is also found that the proposed method outperforms the latest anchor-free techniques commonly used in crowded scenarios. The method can detect pigs individually, even if their bounding boxes overlap strongly or occlude each other. Moreover, the real-time system achieves an improvement of 10% in F measure $F_{\text{measure}}$ when testing in unconstrained real-world conditions.

Cleansing data from an electronic feeding station to improve estimation of feed efficiency

Electronic feeding stations (EFS) are frequently used to automatically record feeding behaviour in pigs, but the resulting data often require cleansing. In this study, several filters were used to cleanse the data from an EFS on a commercial farm, spanning a period of 2147 days (2,709,600 records or visits, corresponding to 2748 pigs). The raw data of each animal was filtered based on three main parameters: fattening duration, feed ingested and live mass. Anomalies that affected EFS readings included aspects related to animal handling (e.g., changes of pen, deaths; affecting 26.1%), maintenance failures (e.g., obstructions, feed mass calibration; affecting 4.4%) and malfunctioning of the animal weighing scale (e.g., calibration, anomalies in the load cell; affecting 10.6%). A detailed analysis of the mass curves of each animal helped identify and categorise three typical errors: 1) large fluctuations of animal mass over a short period of time (affecting 7.3%); 2) poor calibration of the animal weighing scale (affecting 3.3%); and 3) absence of data from the weighing scale (affecting 1.9%). Once the raw data were filtered, feed efficiency was calculated, resulting in a mean value of 0.434, which is consistent with the literature. After filtering the first dataset, another dataset was used from the same farm to validate the results, with similar findings. Overall, the filtering methodology used helped to automate data analysis from EFS and improved the estimation of feeding efficiencies for individual animals. • EFS are frequently used to automatically record feed intake and mass of pigs. • An automated data cleansing process was developed to eliminate anomalous EFS data. • Anomalies were related to animal handling and weighing scale malfunctioning. • Data cleansing process produced reliable individual feed efficiency estimations.

Automated Behavior Recognition and Tracking of Group-Housed Pigs with an Improved DeepSORT Method

Pig behavior recognition and tracking in group-housed livestock are effective aids for health and welfare monitoring in commercial settings. However, due to demanding farm conditions, the targets in the pig videos are heavily occluded and overlapped, and there are illumination changes, which cause error switches of pig identify (ID) in the tracking process and decrease the tracking quality. To solve these problems, this study proposed an improved DeepSORT algorithm for object tracking, which contained three processes. Firstly, two detectors, YOLOX-S and YOLO v5s, were developed to detect pig targets and classify four types of pig behaviors including lying, eating, standing, and other. Then, the improved DeepSORT was developed for pig behavior tracking and reducing error changes of pig ID by improving trajectory processing and data association. Finally, we established the public dataset annotation of group-housed pigs, with 3600 images in a total from 12 videos, which were suitable for pig tracking applications. The advantage of our method includes two aspects. One is that the trajectory processing and data association are improved by aiming at pig-specific scenarios, which are indoor scenes, and the number of pig target objects is stable. This improvement reduces the error switches of pig ID and enhances the stability of the tracking. The other is that the behavior classification information from the detectors is introduced into the tracking algorithm for behavior tracking. In the experiments of pig detection and behavior recognition, the YOLO v5s and YOLOX-S detectors achieved a high precision rate of 99.4% and 98.43%, a recall rate of 99% and 99.23, and a mean average precision (mAP) rate of 99.50% and 99.23%, respectively, with an AP.5:.95 of 89.3% and 87%. In the experiments of pig behavior tracking, the improved DeepSORT algorithm based on YOLOX-S obtained multi-object tracking accuracy (MOTA), ID switches (IDs), and IDF1 of 98.6%,15, and 95.7%, respectively. Compared with DeepSORT, it improved by 1.8% and 6.8% in MOTA and IDF1, respectively, and IDs had a significant decrease, with a decline of 80%. These experiments demonstrate that the improved DeepSORT can achieve pig behavior tracking with stable ID values under commercial conditions and provide scalable technical support for contactless automated pig monitoring.

Olfactory enrichment using a maternal pheromone improved post-weaning pig performance and behavior.

The post-weaning environment in commercial pig nursery buildings is typically devoid of both the sow and her semiochemicals. Among other factors, the loss of maternal odors may contribute to post-weaning stress. In this work, we report four studies (studies 1-4) using 192 weaned pigs to evaluate the effects of a maternal pheromone (MP) containing Myristic Acid and Skatole on weaned pig behavior and performance. Study 1 examined behavior among weaned pigs with a focus on lying, aggression and feeding behaviors. All studies used body weight gain and the percentage of pigs that lost weight the first 7 days after weaning as key response variables. The MP stimulated early feeding behavior and reduced aggressive behaviors among weaned pigs (p < 0.01). In study one, pigs were over 4 kg heavier 16 weeks post-weaning when the MP was present for 48 h post-weaning compared to control pigs (p = 0.05). The three other studies used a 7-days bioassay to assess the best dose and form of delivery of the MP among weaned pigs. The single measure that responded uniformly was the percentage of pigs that lost body weight in the first 7 days after weaning. Among control pigs in four separate studies, 25% of the weaned pigs in each study lost body weight by 7 days after weaning, while in 3 of the 4 bioassay studies, 0% of MP-exposed pigs lost weight after weaning (one study had 6% of pigs losing body weight with the MP). This MP effect is both highly statistically significant and, if found on commercial farms, would have a large positive economic benefit. Simultaneously, having fewer pigs losing weight and exhibiting less aggressive behavior will improve the health and welfare of weaned pigs. Providing biologically-relevant olfactory enrichment can improve pig health and welfare.

Племенная ценность кормового поведения свиней

Abstract. The purpose of the research is to develop a comprehensive assessment system with new indicators of feed behavior and feed conversion in Duroc pigs based on a selection index. Research methods. The Herdsman database was used, which includes the processing of data on fattening characteristics and feeding behavior of 764 heads of Duroc pigs that have passed test fattening at automatic feeding stations. 13 indicators were evaluated, of which 7 indicators of feeding behavior and 6 – fattening characteristics. The evaluation of breeding value animals according to studied traits was carried out using the BLUP Animal Model methodology. Results. When determining the weight coefficients of final index equation, which included all the studied traits, we relied on the chosen principle, according to which 50 % was given to weight coefficients of feeding behavior traits and 50 % to the weights of the fattening indicators. Also, in accordance with this principle, in feeding behavior indicators, 25 % was allocated for feed conversion, and the same amount in fattening indicators – for the average daily weight gain. The obtained values of the coefficients presented the general structure of the selection index: Itotal = 0.5I1 + 0.5I2 = 0.0241 (TPD) + 0.0439 (ADFI) – 0.0376 (NVD) – 0.0322 (TPV) – 0.0074 (FR) + 0.0376 (FPV) – 0.5343 (FCR) + 0.0531 (Age1) + 0.0778 (Age0) + 0.1217 (BW1) + 0.1027 (BW0) + 0.0331 (BWG) + 0.4557 (ADG). The results obtained showed the difference between the minimum and maximum index, which was 76 sigma points. Also, according to distribution according the categories of RBV (relative breeding value) among 14 pigs with an index greater than 120 units, 30.8 % have the category “unconditional improver” and 25.8 % – the category “improver”. Scientific novelty. These results show the direct impact of feeding behavior and feed conversion on the refinement of animal’s genetic potential, which will improve the system of selection and genomic evaluation of animals.

Dry and unwary are best conditions for baiting wild pigs (Sus scrofa)

Wild pigs (Sus scrofa) are a highly destructive invasive species throughout North and South America, Australia, and many island nations. Where invasive, their populations are targeted for control to reduce damage. Controlling wild pigs often involves baiting to draw them into traps or entice them to consume a toxic bait. However, baiting can have mixed success in congregating wild pigs to focal areas long enough for control measures to ultimately be implemented. We sought to evaluate how environmental conditions (i.e., precipitation) and negative stimuli (i.e., proxy for exposure to previous control efforts) influenced use of bait sites by wild pigs. We compared visitation to bait sites during dry (2019–2020) and wet (2021) years, and between wild pigs that had been previously trapped and released in southcentral Alabama and northcentral Texas, USA. We found that drier years substantially increased use of bait sites by wild pigs (i.e., 119–136 % increase over 17 days). Similarly, wild pigs that did not experience negative stimuli had increased use of bait sites (i.e., 30–31 % increase over 17 days). We recommend that managers intensify their control efforts during drier periods to take advantage of susceptible behaviors of wild pigs during these times. We also recommend that control efforts focus on eliminating the potential for surviving wild pigs which may experience negative stimuli (e.g., narrow misses during trapping, shooting some wild pigs from a group, sub-lethal doses from toxic baits) and become educated against future efforts.