Use of drinkers by finisher pigs depend on drinker location, pig age, time of day, stocking density and tail damage.

Water is a vital nutrient for mammals, including the pig. Despite this, the use of drinkers and water have not yet been explicitly quantified across the finisher period. The current study aimed at gaining greater insight into finisher pigs' drinker use and its relation to drinker location, age, time of day, stocking density, enrichment provision and tail damage. The experiment included 110 pens of finisher pigs over a 9-week period, with two drinker cups per pen. Pens had a stocking density of either 0.73 m2/pig (n = 54 pens, 18 pigs per pen) or 1.21 m2/pig (n = 56 pens, 11 pigs per pen), were either provided with straw (n = 54, 150 g per pig and day) or not (n = 56), and had pigs with either undocked (n = 50) or docked tails (n = 60). Drinker use was recorded automatically by water-flow meters and summed to L and number of activations per hour and pig. Pens never experiencing a tail damage event (at least one pig in the pen with a bleeding tail) were used to investigate the normal drinker use of finisher pigs (n = 56). The water use of pigs increased from 3.7 to 8.2 L per pig and day during the 9 weeks, and this increase was mainly seen during the two large peaks of the diurnal pattern within the pigs' active period (06:00-18:00 h). No such increase was seen in the activation frequency at average 50 activations per pig and day. A decrease in stocking density increased both water use and activation frequency during the active period, suggesting that pigs at the standard space allowance and pig:drinker ratio could be restricted in their access to the drinking cups. The pigs also seemed to prefer to use the drinking cup closest to the feeder. Water use and activation frequency did not change the last 3 days prior to an event of tail damage, but general differences were seen between pens with and without a tail damage event. The current results may explain the success of previous studies in classifying tail damage pens from pens without tail damage using sensor data on drinker use.

Influence of temperature during incubation on the mRNA levels of temperature sensitive ion channels in the brain of broiler chicken embryos.

Thermosensation is crucial for the survival of any organism. In animals, changes in brain temperature are detected via sensory neurons, their cell bodies are located in the trigeminal ganglia. Transient receptor potential (TRP) ion channels are the largest temperature sensing family. In mammals, 11 thermoTRPs are known, as in poultry, there are only three. This research further elucidates TRP mRNA expression in the brain of broiler embryo's. Three incubation treatments were conducted on 400 eggs each: the control (C) at 37.6 °C; T1 deviating from C by providing a + 1 °C heat stimuli during embryonic day (ED) 15-20 for 8 h a day; and T2, imposing a + 2 °C heat stimuli. After each heat stimuli, 12 eggs per treatment were taken for blood sampling from the chorioallantoic membrane and brain harvesting. Incubation parameters such has residual yolk (free embryonic) weight, chick quality and hatch percentage were collected. After primer optimization, 22 target genes (13 TRPs and 9 non-TRPs) were measured on mRNA of the brain using a nanofluidic biochip (Fluidigm Corporation). Four target genes (ANO2, TRPV1, SCN5A, TRAAK) have a significant treatment effect - independent of ED. Another four (TRPM8, TRPA1, TRPM2, TRPC3) have a significant treatment effect visible on one or more ED. Heat sensitive channels were increased in T2 and to a lesser degree in T1, which could be part of an acclimatisation process resulting in later life heat tolerance by increased heat sensitivity. T2, however, resulted in a lower hatch weight, quality and hatchability. No hormonal differences were detected.

Prediction of Tail Biting Events in Finisher Pigs from Automatically Recorded Sensor Data.

Tail biting in pigs is an animal welfare problem, and tail biting should be prevented from developing into tail damage. One strategy could be to predict events of tail biting so that the farmer can make timely interventions in specific pens. In the current investigation, sensor data on water usage (water flow and activation frequency) and pen temperature (above solid and slatted floor) were included in the development of a prediction algorithm for tail biting. Steps in the development included modelling of data sources with dynamic linear models, optimisation and training of artificial neural networks and combining predictions of the single data sources with a Bayesian ensemble strategy. Lastly, the Bayesian ensemble combination was tested on a separate batch of finisher pigs in a real-life setting. The final prediction algorithm had an AUC > 0.80, and thus it does seem possible to predict events of tail biting from already available sensor data. However, around 30% of the no-event days were false alarms, and more event-specific predictors are needed. Thus, it was suggested that farmers could use the alarms to point out pens that need greater attention.

Pen Fouling in Finisher Pigs: Changes in the Lying Pattern and Pen Temperature Prior to Fouling.

Pen fouling, where the pigs choose to rest in their designated excretion area (the slatted floors) and excrete in their designated resting area (the solid floors), is an undesired behaviour and should be prevented when possible. One strategy to prevent fouling is early detection by means of either animal or environmental measures changing prior to fouling. The aim of the present study was to investigate whether the lying pattern of pigs and the temperature in the pen changed the last 5 days prior to an event of fouling and whether this differed from pens without an event of fouling (controls). Fouling events was recorded at pen level when at least half of the solid floor was wet with excreta and/or urine (day0). Each fouling pen was paired with a control pen that had not been scored as a fouling pen prior to or at least 1 week after the fouling event. Fouling and control pens were either not provided with straw or provided daily with 150 g of straw per pig. Percentage of pigs lying on the solid floor and the slatted floor (36 events) as well as pen temperature above the solid and slatted floor (24 events) was analysed using four linear mixed effects models. The percentage of pigs lying on the solid floor decreased (40-24%; P < 0.05) while the number of pigs lying on the slatted floor increased (14-24%; P < 0.05) from day-2 to day0 only in the fouling pens, with differences seen between fouling and control pens on the same days (P < 0.01). However, these changes and differences was only seen in pens without straw. Also only in pens without straw did pen temperature above the solid floor decrease from day-2 to day0 (18.6-17.6°C; P < 0.001), with differences seen between fouling and control pens only on day0 (P < 0.05). In contrast, pen temperature measured above the slatted floor did not change, independent of whether the pen was provided with straw or not. Thus, in pens not provided with straw, both the lying pattern of pigs and pen temperature above the solid floor have potential as early detectors of pen fouling.

Can tail damage outbreaks in the pig be predicted by behavioural change?

Tail biting, resulting in outbreaks of tail damage in pigs, is a multifactorial welfare and economic problem which is usually partly prevented through tail docking. According to European Union legislation, tail docking is not allowed on a routine basis; thus there is a need for alternative preventive methods. One strategy is the surveillance of the pigs' behaviour for known preceding indicators of tail damage, which makes it possible to predict a tail damage outbreak and prevent it in proper time. This review discusses the existing literature on behavioural changes observed prior to a tail damage outbreak. Behaviours found to change prior to an outbreak include increased activity level, increased performance of enrichment object manipulation, and a changed proportion of tail posture with more tails between the legs. Monitoring these types of behaviours is also discussed for the purpose of developing an automatic warning system for tail damage outbreaks, with activity level showing promising results for being monitored automatically. Encouraging results have been found so far for the development of an automatic warning system; however, there is a need for further investigation and development, starting with the description of the temporal development of the predictive behaviour in relation to tail damage outbreaks.