Janice M. Siegford

Effects of early weaning and social isolation on the expression of glucocorticoid and mineralocorticoid receptor and 11β-hydroxysteroid dehydrogenase 1 and 2 mRNAs in the frontal cortex and hippocampus of piglets

Pigs weaned at young ages show more abnormal and aggressive behaviors and cognitive deficits compared to later weaned pigs. We investigated the effects of age, weaning and/or social isolation on the expression of genes regulating glucocorticoid response [glucocorticoid receptor (GR), mineralocorticoid receptor (MR), 11beta-hydroxysteroid dehydrogenases 1 and 2 (11beta-HSD1 and 11beta-HSD2)] in the frontal cortex and hippocampus. Early- (EW; n = 6) and conventionally-weaned (CW; n = 6) piglets were weaned at 10 and 21 days after birth, respectively. Non-weaned (NW) piglets of both ages (NW; n = 6/group) remained with their dams. Immediately before euthanasia, half of CW, EW and NW animals were socially isolated for 15 min at 12 (EW, NW) and 23 (CW, NW) days of age. Differences in amounts of 11beta-HSD1, 11beta-HSD2, GR and MR mRNA were determined by quantitative real-time RT-PCR and data subjected to multivariate linear mixed model analysis. When compared with NW piglets at 12 days of age, the hippocampi of EW piglets showed decreased gene expression (P < 0.01). Social isolation decreased gene expression (P < 0.05) in the frontal cortex of all piglets. Twelve-day-old piglets showed higher MR mRNA in the frontal cortex (P < 0.01) and lower 11beta-HSD2 and GR mRNA (P < 0.05) in the hippocampus compared to 23-day-old animals. Results indicate that EW affected the hippocampus of piglets at 12 days of age, while social isolation affected frontal cortex regardless of age. These results may be correlated with behavioral and cognitive changes reported in EW piglets.

Investigation of changes in global gene expression in the frontal cortex of early-weaned and socially isolated piglets using microarray and quantitative real-time RT-PCR.

We hypothesize that early-weaned piglets experience aberrant expression of stress-responsive genes in the frontal cortex, a key brain area involved in cognitive function and behavior organization. To test this hypothesis, female early-weaned piglets (EW; n = 6) were weaned 10 days after birth, while non-weaned piglets (NW; n = 6) were left with their dams. Half of EW (n = 3) and NW (n = 3) animals were socially isolated (SI) for 15 min at 12 days of age, when all animals (n = 12) were euthanized and tissue collected. The effects of EW and SI were examined by gene expression profiling using cDNA microarray hybridizations, generated from a porcine brain cDNA library. A total of 103 genes were differentially expressed (P < 0.05, fold change >1.25) among four direct comparisons. Forty-two genes had known functions, from which 24 showed relevant brain-related functions. Quantitative real-time polymerase chain reaction (Q-RT-PCR) was used to confirm regulation of expression of a subset of 6 genes with important brain functions, selected from the microarray outcomes. In non-weaned animals, a significant suppression of mRNA abundance for carboxypeptidase E, 14-3-3 protein and phosphoprotein enriched in astrocytes 15 kDa was observed in response to SI. Also, in early-weaned animals, diazepam binding inhibitor and actin-related protein 2/3 complex mRNA levels were suppressed in response to SI. Results suggest that social isolation of non- and early-weaned piglets may impact expression of genes involved in regulation of neuronal function, development, and protection in the frontal cortex of young pigs.

Environmental Aspects of Ethical Animal Production

Livestock and poultry producers face a number of challenges including pressure from the public to be good environmental stewards and adopt welfare-friendly practices. In response, producers often implement practices beyond those required for regulatory compliance to meet consumer demands. However, environmental stewardship and animal welfare may have conflicting objectives. Examples include pasture-based dairy and beef cattle production where high-fiber diets increase methane emissions compared with grain feeding practices in confinement. Grazing systems can contribute to nitrate contamination of surface and groundwater in some areas of the world where grazing is the predominant land use. Similarly, hoop housing for sows, an alternative to indoor gestation crates, can increase the risk of nutrient leaching into soil and groundwater. Direct air emissions may also increase with unconfined animal production as a result of less opportunity to trap and treat emissions, as well as the result of increased cage space and greater surface area per mass of excreta. Coupling welfare-friendly and organic production practices may require greater nutrient inputs to reach the same production end point, resulting in less efficient nutrient use and greater losses to the environment. Dual systems might additionally increase environmental contamination by pathogens. When swine are housed in welfare-friendly huts, Salmonella may cycle more freely between swine and their environment; however, population numbers of pathogenic bacteria may not be different between the indoor and outdoor systems evaluated. Alternatively, these dual purpose systems may reduce antibiotic and hormonal releases to the environment. Finally, intensity of resource use may be different under welfare-friendly and organic practices. In most situations, welfare-friendly production will require more land area per animal or per unit of product. Energy inputs into such systems, from feed production to rearing to product distribution, may also differ from prevalent industrial production practices. Clearly, consumers and producers considering the benefits and costs of ethical animal production practices need to understand the system-wide environmental impacts of these approaches to meeting demand for animal products.

DEVELOPMENT OF A WIRELESS BODY-MOUNTED SENSOR TO MONITOR LOCATION AND ACTIVITY OF LAYING HENS IN A NON-CAGE HOUSING SYSTEM

A novel wireless body-mounted sensor was developed to remotely monitor the location and activity of laying hens within non-cage housing systems. Legislation and social demand in the U.S. and Europe is pushing the poultry industry to transition primarily to non-cage housing systems. However, non-cage systems typically house hens in groups of tens of thousands, which makes it nearly impossible for caretakers to visually assess the health, welfare, or movement of all individual hens or to follow a particular hen over time. In the present study, laying hens were fitted with a lightweight (10 g) wireless body-mounted sensor to monitor their location in space relative to key resources and general level of physical activity. Sensor data were validated by correlating them to video-based observations of the sensor-wearing hen. In experiment 1, overall agreement of at least 84% was consistently obtained between data from the sensor system and video concerning the hens proximity to specific resources including nestboxes, perches, water, and feeder. Presented data were collected from three 30 min observations from each of three laying hens. In experiment 2, the accelerometer data from a back-mounted sensor were correlated to video-based observations from two 30 min observation sessions from each of two laying hens in order to demonstrate the feasibility of automated activity classification using the developed sensor system.

Assessing Activity and Location of Individual Laying Hens in Large Groups Using Modern Technology

Simple Summary Tracking of individual animals within large groups is increasingly possible offering an exciting opportunity to researchers. Whereas previously only relatively indistinguishable groups of individual animals could be observed and combined into pen level data, we can now focus on individual actors and track their activities across time and space with minimal intervention and disturbance. We describe several tracking systems that are currently in use for laying hens and review each, highlighting their strengths and weaknesses, as well as environments or conditions for which they may be most suited, and relevant issues to fit the best technology for the intended purpose. Abstract Tracking individual animals within large groups is increasingly possible, offering an exciting opportunity to researchers. Whereas previously only relatively indistinguishable groups of individual animals could be observed and combined into pen level data, we can now focus on individual actors within these large groups and track their activities across time and space with minimal intervention and disturbance. The development is particularly relevant to the poultry industry as, due to a shift away from battery cages, flock sizes are increasingly becoming larger and environments more complex. Many efforts have been made to track individual bird behavior and activity in large groups using a variety of methodologies with variable success. Of the technologies in use, each has associated benefits and detriments, which can make the approach more or less suitable for certain environments and experiments. Within this article, we have divided several tracking systems that are currently available into two major categories (radio frequency identification and radio signal strength) and review the strengths and weaknesses of each, as well as environments or conditions for which they may be most suitable. We also describe related topics including types of analysis for the data and concerns with selecting focal birds.

Laying hen movement in a commercial aviary: Enclosure to floor and back again

Many producers in the laying hen industry, including in North America, are phasing out conventional cages in response to consumer demands and sometimes subsequent legislation. Alternative housing systems such as aviaries are being implemented in an attempt to improve hen welfare. Aviaries provide additional space and resources to groups of hens, including a litter area on the floor. However, little is known about hen movement between tiered enclosures and floor litter areas in aviary systems. Diurnal rhythms and social attraction may result in peak times of movement that could lead to overcrowding of areas, or alternatively hen preferences may lead to some areas not being fully utilized. We monitored hen movement between tiered enclosures and litter areas, including movement on and off the outer perch, across the day at peak, mid and end of lay in a commercial aviary. Hens moved onto and off of the open litter area across the day, transitioning between tiered enclosures, outer perches, open litter areas, and litter areas under tiered enclosures. At certain times of day, there were periods of greater hen movement down to the open litter area and between litter areas. For example, more hens were typically observed exiting enclosures, jumping from perches to open litter, and traveling between open litter and litter under tiered enclosures in the morning (all P ≤ 0.001). In all but one instance, more hens were observed on open litter areas in the afternoon than at other times of day (all P ≤ 0.029). However, hen re-entry to tiered enclosures showed less circadian patterning. Hen movement was observed between areas of interest at all sampled time periods, indicating hens use all areas of the system. Further research should examine whether all individual hens do move between areas equally, including within levels of the tiered enclosure, or if crowding occurs on the outer perches or in the litter during times of peak movement.

Detection of jumping and landing force in laying hens using wireless wearable sensors

Increased mobility of hens in noncaged housing presents possibilities for bone breakage due to crash landings from jumps or flights between perches or housing infrastructure. Because bone breakage is a welfare and economic concern, understanding how movement from different heights affects hen landing impact is important. By tracking 3-dimensional bird movement, an automated sensor technology could facilitate understanding regarding the interaction between noncage laying hens and their housing. A method for detecting jumps and flight trajectories could help explain how jumps from different heights affect hen landing impact. In this study, a wearable sensor-based jump detection mechanism for egg-laying hens was designed and implemented. Hens were fitted with a lightweight (10 g) wireless body-mounted sensor to remotely sample accelerometer data. Postprocessed data could detect occurrence of jumps from a perch to the ground, time of jump initiation, time of landing, and force of landing. Additionally, the developed technology could estimate the approximate height of the jump. Hens jumping from heights of 41 and 61 cm were found to land with an average force of 81.0 ± 2.7 N and 106.9 ± 2.6 N, respectively, assuming zero initial velocity (P < 0.001). This paper establishes the technological feasibility of using body-mounted sensor technology for jump detection by hens in different noncage housing configurations.

Moving GIS Research Indoors: Spatiotemporal Analysis of Agricultural Animals

A proof of concept applying wildlife ecology techniques to animal welfare science in intensive agricultural environments was conducted using non-cage laying hens. Studies of wildlife ecology regularly use Geographic Information Systems (GIS) to assess wild animal movement and behavior within environments with relatively unlimited space and finite resources. However, rather than depicting landscapes, a GIS could be developed in animal production environments to provide insight into animal behavior as an indicator of animal welfare. We developed a GIS-based approach for studying agricultural animal behavior in an environment with finite space and unlimited resources. Concurrent data from wireless body-worn location tracking sensor and video-recording systems, which depicted spatially-explicit behavior of hens (135 hens/room) in two identical indoor enclosures, were collected. The spatial configuration of specific hen behaviors, variation in home range patterns, and variation in home range overlap show that individual hens respond to the same environment differently. Such information could catalyze management practice adjustments (e.g., modifying feeder design and/or location). Genetically-similar hens exhibited diverse behavioral and spatial patterns via a proof of concept approach enabling detailed examinations of individual non-cage laying hen behavior and welfare.

Remote Activity Classification of Hens Using Wireless Body Mounted Sensors

This paper presents the design and implementation of a machine learning based activity classification mechanism for hens using a wearable sensor system. Legislation and social demands in the U.S. and Europe are pushing the poultry industry towards the usage of non-cage housing systems. However, non-cage systems typically house hens in groups of hundreds or thousands, which makes it nearly impossible for caretakers to visually assess the health, welfare, or movement of individual hens or to follow a particular hen over time. In the study, laying hens were fitted with a lightweight (10 g) wireless body-mounted sensor to remotely sample activity data. Specific machine learning mechanisms are used on the features extracted from activity data to identify a target set of activities of the hens. The paper establishes technological feasibility of using such body-mounted sensor systems for accurate hen activity monitoring in a non-cage housing system.

Individual consistency of feather pecking behavior in laying hens: once a feather pecker always a feather pecker?

The pecking behavior [severe feather, gentle feather, and aggressive pecks (AP)] of individual White Shaver non-cage laying hens (n = 300) was examined at 21, 24, 27, 32, and 37 weeks. Hens were housed in 30 groups of 10 hens each and on 3 cm litter with access to a feeder, perch, and two nest boxes. The number of severe feather pecks given (SFPG) and received (SFPR) was used to categorize hens as feather peckers (P), victims (V), neutrals (N), or feather pecker-victims (PV) at each age. Hens categorized as PV exhibited pecking behaviors similar to P and received pecks similar to V. SFP given were correlated with APs given, but not with gentle feather pecks (GFP) given throughout the study. State-transition plot maps illustrated that 22.5% of P remained P, while 44% of PV remained PV throughout the duration of the study. Lifetime behavioral categories identified hens as a consistent feather pecker (5%), consistent neutral (3.9%), consistent victim (7.9%), consistent feather pecker-victim (29.4%), or inconsistent (53.8%) in their behavioral patterns throughout their life. Consistent feather peckers performed more SFP than hens of other categories, and consistent neutral hens received fewer GFP than consistent feather PV. No differences in corticosterone or whole blood serotonin levels were observed among the categories. Approximately, half of the population was classified as a feather pecker at least once during the study, while the remainder was never categorized as a feather pecker. Therefore, even if the development and cause of feather pecking may be multifactorial, once the behavior has been developed, some hens may persist in feather pecking. However, as some hens were observed to never receive or perform SFP, emphasis should be made to select for these hens in future breeding practices.