Development of a novel Bluetooth Low Energy device for proximity and location monitoring in grazing sheep.

Monitoring animal location and proximity can provide useful information on behaviour and activity, which can act as a health and welfare indicator. However, tools such as global navigation satellite systems (GNSS) can be costly, power-hungry and often heavy, thus not viable for commercial uptake in small ruminant systems. Developments in Bluetooth Low Energy (BLE) could offer another option for animal monitoring, however, BLE signal strength can be variable, and further information is needed to understand the relationship between signal strength and distance in an outdoor environment and assess factors which might affect its interpretation in on-animal scenarios. A calibration of a purpose-built device containing a BLE reader, alongside commercial BLE beacons, was conducted in a field environment to explore how signal strength changed with distance and investigate whether this was affected by device height, and thus animal behaviour. From this calibration, distance prediction equations were developed whereby beacon distance from a reader could be estimated based on signal strength. BLE as a means of localisation was then trialled, firstly using a multilateration approach to locate 16 static beacons within an ∼5 400 m2 section of paddock using 6 BLE readers, followed by an on-sheep validation where two localisation approaches were trialled in the localisation of a weaned lamb within ∼1.4 ha of adjoining paddocks, surrounded by nine BLE readers. Validation was conducted using 1 days' worth of data from a lamb fitted with both a BLE beacon and separate GNSS device. The calibration showed a decline in signal strength with increasing beacon distance from a reader, with a reduced range and earlier decline in the proportion of beacons reported at lower reader and beacon heights. The distance prediction equations indicated a mean underestimation of 12.13 m within the static study, and mean underestimation of 1.59 m within the on-sheep validation. In the static beacon localisation study, the multilateration method produced a mean localisation error of 22.02 m, whilst in the on-sheep validation, similar mean localisation errors were produced by both methods - 19.00 m using the midpoint and 23.77 m using the multilateration method. Our studies demonstrate the technical feasibility of localising sheep in an outdoor environment using BLE technology; however, potential commercial application of such a system would require improvements in BLE range and accuracy.

Review: Exploring the use of precision livestock farming for small ruminant welfare management.

Small ruminant (sheep and goat) production of meat and milk is undertaken in diverse topographical and climatic environments and the systems range from extensive to intensive. This could lead to different types of welfare compromise, which need to be managed. Implementing Precision Livestock Farming (PLF) and other new or innovative technologies could help to manage or monitor animal welfare. This paper explores such opportunities, seeking to identify promising aspects of PLF that may allow improved management of welfare for small ruminants using literature search (two reviews), workshops in nine countries (France, Greece, Ireland, Israel, Italy, Norway, Romania, Spain, and the United Kingdom) with 254 stakeholders, and panels with 52 experts. An investigation of the main welfare challenges that may affect sheep and goats across the different management systems in Europe was undertaken, followed by a prioritisation of animal welfare issues obtained in the nine countries. This suggested that disease and health issues, feed access and undernutrition/malnutrition, maternal behaviour/offspring losses, environmental stressors and issues with agonistic behavioural interactions were important welfare concerns. These welfare issues and their indicators (37 for sheep, 25 for goats) were categorised into four broad welfare indicator categories: weight loss or change in body state (BWC), behavioural change (BC), milk yield and quality (MY), and environmental indicators (Evt). In parallel, 24 potential PLF and innovative technologies (8 for BWC; 10 for BC; 4 for MY; 6 for Evt) that could be relevant to monitor these broad welfare indicator categories and provide novel approaches to manage and monitor welfare have been identified. Some technologies had the capacity to monitor more than one broad indicator. Out of the 24 technologies, only 12 were animal-based sensors, or that could monitor the animal individually. One alternative could be to incorporate a risk management approach to welfare, using aspects of environmental stress. This could provide an early warning system for the potential risks of animal welfare compromise and alert farmers to the need to implement mitigation actions.

Topics and trends in Mountain Livestock Farming research: a text mining approach.

Pasture-based and small-scale livestock farming systems are the main source of livelihood in the mountain primary sector, ensuring socioeconomic sustainability and biodiversity in rural communities throughout Europe and beyond. Mountain livestock farming (MLF) has attracted substantial research efforts from a wide variety of scientific communities worldwide. In this study, the use of text mining and topic modelling analysis drew a detailed picture of the main research topics dealing with MLF and their trends over the last four decades. The final data corpus used for the analysis counted 2 679 documents, of which 92% were peer-reviewed scientific publications. The number of scientific outputs in MLF doubled every 10 years since 1980. Text mining found that milk, goat and sheep were the terms with the highest weighed frequency in the data corpus. Ten meaningful topics were identified by topic analysis: T1-Livestock management and vegetation dynamics; T2-Animal health and epidemiology; T3-Methodological studies on cattle; T4-Production system and sustainability; T5-Methodological studies; T6-Wildlife and conservation studies; T7-Reproduction and performance; T8-Dairy/meat production and quality; T9-Land use and its change and T10-Genetic/genomic studies. A hierarchical clustering analysis was performed to explore the interrelationships among topics, and three main clusters were identified: the first focused on sustainability, conservation and socioeconomic aspects (T4; T6 and T9), the second was related to food production and quality (T7 and T8) and the last one considered methodological studies on mountain flora and fauna (T1; T2; T3; T5 and T10). The 10 topics identified represent a useful and a starting source of information for further and more detailed analysis (e.g. systematic review) of specific research or geographical areas. A truly holistic and interdisciplinary research approach is needed to identify drivers of change and to understand current and future challenges faced by livestock farming in mountain areas.

Characterisation of terminal sire sheep farm systems, based on a range of environmental factors: a case study in the context of genotype by environment interactions using Charollais lambs.

The objective of this study was to define different terminal sire flock environments, based on a range of environmental factors, and then investigate the presence of genotype by environment interactions (G×E) between the environments identified. Data from 79 different terminal sire flocks (40 Texel, 21 Charollais and 18 Suffolk), were analysed using principal coordinate and non-hierarchical cluster analyses, the results of which identified three distinct environmental cluster groups. The type of grazing, climatic conditions and the use of vitamins and mineral supplements were found to be the most important factors in the clustering of flocks. The presence of G×E was then investigated using data from the Charollais flocks only. Performance data were collected for 12 181 lambs, between 1990 and 2010, sired by 515 different sires. Fifty six of the sires had offspring in at least two of the three different cluster groups and pedigree information was available for a total of 161 431 animals. Traits studied were the 21-week old weight (21WT), ultrasound muscle depth (UMD) and log transformed backfat depth (LogUFD). Heritabilities estimated for each cluster, for each trait, ranged from 0.32 to 0.45. Genetic correlations estimated between Cluster 1 and Cluster 2 were all found to be significantly lower than unity, indicating the presence of G×E. They were 0.31 (±0.17), 0.68 (±0.14) and 0.18 (±0.21) for 21WT, UMD and LogUFD, respectively. Evidence of sires re-ranking across clusters was also observed. Providing a suitable strategy can be identified, there is potential for the optimisation of future breeding programmes, by taking into account the G×E observed. This would enable farmers to identify and select animals with an increased knowledge as to how they will perform in their specific farm environment thus reducing any unexpected differences in performance.