What Are Sheep Doing? Tri-Axial Accelerometer Sensor Data Identify the Diel Activity Pattern of Ewe Lambs on Pasture

Application of Precision Technologies to Characterize Animal Behavior: A Review

This study aims to evaluate the state of precision livestock farming (PLF)'s spread, utilization, effectiveness, and evolution over the years. PLF includes a plethora of tools, which can aid in a number of laborious and complex tasks. These tools are often used in the monitoring of different animals, with the objective to increase production and improve animal welfare. The most frequently monitored attributes tend to be behavior, welfare, and social interaction. This study focused on the application of three types of technology: wearable sensors, video observation, and smartphones. For the wearable devices, the focus was on accelerometers and global positioning systems. For the video observation, the study addressed drones and cameras. The animals monitored by these tools were the most common ruminants, which are cattle, sheep, and goats. This review involved 108 articles that were believed to be pertinent. Most of the studied papers were very accurate, for most tools, when utilized appropriate; some showed great benefits and potential.

Worms and welfare: Behavioural and physiological changes associated with gastrointestinal nematode parasitism in lambs

Parasitism with gastrointestinal nematodes (GIN) is a worldwide issue impacting negatively on animal production, health, and welfare. Therefore, early diagnostic signs of parasitism are required to allow for timely interventions. The objective of this study was to evaluate the behavioural and physiological changes in lambs associated with GIN infection. We used 30, 8-month-old Romney-cross wethers, that were administered anthelmintics until faecal egg counts (FEC) were zero and housed in an indoor facility. The study lasted 9 weeks, which comprised a 3-week pre-treatment, and a 6-week treatment phase. Lambs were randomly assigned to one of two treatments (n = 15/treatment) trickle-dosed with: 1) 1500 infective third stage larvae (L3) three days/week for 6 weeks (27,000 total L3; challenged), or 2) water 3 days/week for 6 weeks (control). Within each pen there were 5 pairs of lambs (balanced for liveweight), with each pair comprising a challenged and control lamb. Blood, faecal, and saliva samples were collected 1 week pre-treatment and weekly for 6 weeks of treatment. Behaviour was observed (e.g., feeding, lying, standing) from video-camera recordings using scan sampling every 5 min for 8 h, 1 day pre-treatment and on the day immediately prior to physiological sampling across the 6-week treatment phase (7 days in total). Accelerometers were attached to each lamb to continuously monitor behaviour from 3 weeks pre-treatment and for the remainder of the study. Liveweight, body condition, faecal soiling and faecal consistency scoring were performed weekly as was lipidomic analysis of plasma samples. From week 2 of treatment, challenged lambs spent less time feeding and more time lying than control lambs until week 5 of treatment (P ≤ 0.01). At week 3 of treatment, elevated lipids (mainly triglycerides and phospholipids), loose faeces and faecal soiling around the anus were observed in challenged lambs compared with controls (P ≤ 0.05). From week 4 of treatment, FEC were elevated in the challenged compared to control lambs (P ≤ 0.05). There was also lower liveweight gain at 4 and 5 weeks of treatment in the challenged lambs compared with control lambs (P ≤ 0.05). These results show a clear timeline of changes in behaviour (e.g., feeding and lying), lipids such as triglycerides, and digestive function (e.g., faecal soiling) suggestive of GIN subclinical disease, which show promise for use in future studies on early identification of subclinical GIN parasitism in lambs.

Behavioral Fingerprinting: Acceleration Sensors for Identifying Changes in Livestock Health

During disease or toxin challenges, the behavioral activities of grazing animals alter in response to adverse situations, potentially providing an indicator of their welfare status. Behavioral changes such as feeding behavior, rumination and physical behavior as well as expressive behavior, can serve as indicators of animal health and welfare. Sometimes behavioral changes are subtle and occur gradually, often missed by infrequent visual monitoring until the condition becomes acute. There is growing popularity in the use of sensors for monitoring animal health. Acceleration sensors have been designed to attach to ears, jaws, noses, collars and legs to detect the behavioral changes of cattle and sheep. So far, some automated acceleration sensors with high accuracies have been found to have the capacity to remotely monitor the behavioral patterns of cattle and sheep. These acceleration sensors have the potential to identify behavioral patterns of farm animals for monitoring changes in behavior which can indicate a deterioration in health. Here, we review the current automated accelerometer systems and the evidence they can detect behavioral patterns of animals for the application of potential directions and future solutions for automatically monitoring and the early detection of health concerns in grazing animals.

Sheep Nocturnal Activity Dataset

Monitoring sheep’s behavior is of paramount importance, because deviations from normal patterns may indicate nutritional, thermal or social stress, changes in reproductive status, health issues, or predator attacks. The night period, despite being a more restful period in which animals are theoretically sleeping and resting, represents approximately half of the life cycle of animals; therefore, its study is of immense interest. Wearable sensors have become a widely recognized technique for monitoring activity, both for their precision and the ease with which the sensorized data can be analyzed. The present dataset consists of data from the sensorization of 18 Serra da Estrela sheep, during the nocturnal period between 18 November 2021 and 16 February 2022. The data contain measurements taken by ultrasound and accelerometry of the height from neck to ground, as well as measurements taken by an accelerometer in the monitoring collar. Data were collected every 10 s when the animals were in the shelter. With the collection of data from various sensors, active and inactive periods can be identified throughout the night, quantifying the number and average time of those periods.

Periodicity Intensity of the 24 h Circadian Rhythm in Newborn Calves Show Indicators of Herd Welfare

Circadian rhythms are a process of the sleep-wake cycle that regulates the physical, mental and behavioural changes in all living beings with a period of roughly 24 h. Wearable accelerometers are typically used in livestock applications to record animal movement from which we can estimate the activity type. Here, we use the overall movement recorded by accelerometers worn on the necks of newborn calves for a period of 8 weeks. From the movement data, we calculate 24 h periodicity intensities corresponding to circadian rhythms, from a 7-day window that slides through up to 8-weeks of data logging. The strength or intensity of the 24 h periodicity is computed at intervals as the calves become older, which is an indicator of individual calf welfare. We observe that the intensities of these 24 h periodicities for individual calves, derived from movement data, increase and decrease synchronously in a herd of 19 calves. Our results show that external factors affecting the welfare of the herd can be observed by processing and visualising movement data in this way and our method reveals insights that are not observable from movement data alone.

Goat Kidding Dataset

The detection of kidding in production animals is of the utmost importance, given the frequency of problems associated with the process, and the fact that timely human help can be a safeguard for the well-being of the mother and kid. The continuous human monitoring of the process is expensive, given the uncertainty of when it will occur, so the establishment of an autonomous mechanism that does so would allow calling the human responsible who could intervene at the opportune moment. The present dataset consists of data from the sensorization of 16 pregnant and two non-pregnant Charnequeira goats, during a period of four weeks, the kidding period. The data include measurements from neck to floor height, measured by ultrasound and accelerometry data measured by an accelerometer existing at the monitoring collar. Data was continuously sampled throughout the experiment every 10 s. The goats were monitored both in the goat shelter (day and night) and during the grazing period in the pasture. The births of the animals were also registered, both in terms of the time at which they took place, but also with details regarding how they took place and the number of offspring, and notes were also added.

Industry 4.0 and Precision Livestock Farming (PLF): An up to Date Overview across Animal Productions

Precision livestock farming (PLF) has spread to various countries worldwide since its inception in 2003, though it has yet to be widely adopted. Additionally, the advent of Industry 4.0 and the Internet of Things (IoT) have enabled a continued advancement and development of PLF. This modern technological approach to animal farming and production encompasses ethical, economic and logistical aspects. The aim of this review is to provide an overview of PLF and Industry 4.0, to identify current applications of this rather novel approach in different farming systems for food producing animals, and to present up to date knowledge on the subject. Current scientific literature regarding the spread and application of PLF and IoT shows how efficient farm animal management systems are destined to become. Everyday farming practices (feeding and production performance) coupled with continuous and real-time monitoring of animal parameters can have significant impacts on welfare and health assessment, which are current themes of public interest. In the context of feeding a rising global population, the agri-food industry and industry 4.0 technologies may represent key features for successful and sustainable development.

Extensive Sheep and Goat Production: The Role of Novel Technologies towards Sustainability and Animal Welfare

Simple Summary

New technologies have been recognized as valuable in controlling, monitoring, and managing farm animal activities. It makes it possible to deepen the knowledge of animal behavior and improve animal welfare and health, which has positive implications for the sustainability of animal production. In recent years, successful technological developments have been applied in intensive farming systems; however, due to challenging conditions that extensive pasture-based systems show, technology has been more limited. Nevertheless, awareness of the available technological solutions for extensive conditions can increase the implementation of their adoption among farmers and researchers. In this context, this review addresses the role of different technologies applied to sheep and goat production in extensive systems. Examples related to precision livestock farming, omics, thermal stress, colostrum intake, passive immunity, and newborn survival are presented; biomarkers of metabolic diseases and parasite resistance breeding are discussed.

Abstract

Sheep and goat extensive production systems are very important in the context of global food security and the use of rangelands that have no alternative agricultural use. In such systems, there are enormous challenges to address. These include, for instance, classical production issues, such as nutrition or reproduction, as well as carbon-efficient systems within the climate-change context. An adequate response to these issues is determinant to economic and environmental sustainability. The answers to such problems need to combine efficiently not only the classical production aspects, but also the increasingly important health, welfare, and environmental aspects in an integrated fashion. The purpose of the study was to review the application of technological developments, in addition to remote-sensing in tandem with other state-of-the-art techniques that could be used within the framework of extensive production systems of sheep and goats and their impact on nutrition, production, and ultimately, the welfare of these species. In addition to precision livestock farming (PLF), these include other relevant technologies, namely omics and other areas of relevance in small-ruminant extensive production: heat stress, colostrum intake, passive immunity, newborn survival, biomarkers of metabolic disease diagnosis, and parasite resistance breeding. This work shows the substantial, dynamic nature of the scientific community to contribute to solutions that make extensive production systems of sheep and goats more sustainable, efficient, and aligned with current concerns with the environment and welfare.