In order to base welfare assessment of dairy cattle on real-time measurement, integration of valid and reliable precision livestock farming (PLF) technologies is needed. The aim of this study was to provide a systematic overview of externally validated and commercially available PLF technologies, which could be used for sensor-based welfare assessment in dairy cattle. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic literature review was conducted to identify externally validated sensor technologies. Out of 1,111 publications initially extracted from databases, only 42 studies describing 30 tools (including prototypes) met requirements for external validation. Moreover, through market search, 129 different retailed technologies with application for animal-based welfare assessment were identified. In total, only 18 currently retailed sensors have been externally validated (14%). The highest validation rate was found for systems based on accelerometers (30% of tools available on the market have validation records), while the lower rates were obtained for cameras (10%), load cells (8%), miscellaneous milk sensors (8%), and boluses (7%). Validated traits concerned animal activity, feeding and drinking behavior, physical condition, and health of animals. The majority of tools were validated on adult cows. Non-active behavior (lying and standing) and rumination were the most often validated for the high performance. Regarding active behavior (e.g., walking), lower performance of tools was reported. Also, tools used for physical condition (e.g., body condition scoring) and health evaluation (e.g., mastitis detection) were classified in lower performance group. The precision and accuracy of feeding and drinking assessment varied depending on measured trait and used sensor. Regarding relevance for animal-based welfare assessment, several validated technologies had application for good health (e.g., milk quality sensors) and good feeding (e.g., load cells, accelerometers). Accelerometers-based systems have also practical relevance to assess good housing. However, currently available PLF technologies have low potential to assess appropriate behavior of dairy cows. To increase actors' trust toward the PLF technology and prompt sensor-based welfare assessment, validation studies, especially in commercial herds, are needed. Future research should concentrate on developing and validating PLF technologies dedicated to the assessment of appropriate behavior and tools dedicated to monitoring the health and welfare in calves and heifers.

Several precision livestock farming (PLF) technologies, conceived for optimizing farming processes, are developed to detect the physical and behavioral changes of animals continuously and in real-time. The aim of this review was to explore the capacity of existing PLF technologies to contribute to the assessment of pig welfare. In a web search for commercially available PLF for pigs, 83 technologies were identified. A literature search was conducted, following systematic review guidelines (PRISMA), to identify studies on the validation of sensor technologies for assessing animal-based welfare indicators. Two validation levels were defined: internal (evaluation during system building within the same population that were used for system building) and external (evaluation on a different population than during system building). From 2,463 articles found, 111 were selected, which validated some PLF that could be applied to the assessment of animal-based welfare indicators of pigs (7% classified as external, and 93% as internal validation). From our list of commercially available PLF technologies, only 5% had been externally validated. The more often validated technologies were vision-based solutions (n= 45), followed by load-cells (n= 28; feeders and drinkers, force plates and scales), accelerometers (n= 14) and microphones (n= 14), thermal cameras (n= 10), photoelectric sensors (n= 5), radio-frequency identification (RFID) for tracking (n= 2), infrared thermometers (n= 1), and pyrometer (n= 1). Externally validated technologies were photoelectric sensors (n= 2), thermal cameras (n= 2), microphone (n= 1), load-cells (n= 1), RFID (n= 1), and pyrometer (n= 1). Measured traits included activity and posture-related behavior, feeding and drinking, other behavior, physical condition, and health. In conclusion, existing PLF technologies are potential tools for on-farm animal welfare assessment in pig production. However, validation studies are lacking for an important percentage of market available tools, and in particular research and development need to focus on identifying the feature candidates of the measures (e.g., deviations from diurnal pattern, threshold levels) that are valid signals of either negative or positive animal welfare. An important gap identified are the lack of technologies to assess affective states (both positive and negative states).

Livestock production is a major contributor to greenhouse gas (GHG) emissions, so will play a significant role in the mitigation effort. Recent literature highlights different strategies to mitigate GHG emissions in the livestock sector. Animal welfare is a criterion of sustainability and any strategy designed to reduce the carbon footprint of livestock production should consider animal welfare amongst other sustainability metrics. We discuss and tabulate the likely relationships and trade-offs between the GHG mitigation potential of mitigation strategies and their welfare consequences, focusing on ruminant species and on cattle in particular. The major livestock GHG mitigation strategies were classified according to their mitigation approach as reducing total emissions (inhibiting methane production in the rumen), or reducing emissions intensity (Ei; reducing CH4 per output unit without directly targeting methanogenesis). Strategies classified as antimethanogenic included chemical inhibitors, electron acceptors (i.e. nitrates), ionophores (i.e. Monensin) and dietary lipids. Increasing diet digestibility, intensive housing, improving health and welfare, increasing reproductive efficiency and breeding for higher productivity were categorized as strategies that reduce Ei. Strategies that increase productivity are very promising ways to reduce the livestock carbon footprint, though in intensive systems this is likely to be achieved at the cost of welfare. Other strategies can effectively reduce GHG emissions whilst simultaneously improving animal welfare (e.g. feed supplementation or improving health). These win–win strategies should be strongly supported as they address both environmental and ethical sustainability. In order to identify the most cost-effective measures for improving environmental sustainability of livestock production, the consequences of current and future strategies for animal welfare must be scrutinized and contrasted against their effectiveness in mitigating climate change.

The performance of piglets in nurseries may vary depending on body weight, age at weaning, management, and pathogenic load in the pig facilities. The early events in a pig’s life are very important and may have long lasting consequences, since growth lag involves a significant cost to the system due to reduced market weights and increased barn occupancy. The present review evidences that there are several strategies that can be used to improve the performance and welfare of pigs at weaning. A complex set of early management and dietary strategies have been explored in sows and suckling piglets for achieving optimum and efficient growth of piglets after weaning. The management strategies studied to improve development and animal welfare include: (1) improving sow housing during gestation, (2) reducing pain during farrowing, (3) facilitating an early and sufficient colostrum intake, (4) promoting an early social interaction between litters, and (5) providing complementary feed during lactation. Dietary strategies for sows and suckling piglets aim to: (1) enhance fetal growth (arginine, folate, betaine, vitamin B₁₂, carnitine, chromium, and zinc), (2) increase colostrum and milk production (DL-methionine, DL-2-hydroxy-4-methylthiobutanoic acid, arginine, L-carnitine, tryptophan, valine, vitamin E, and phytogenic actives), (3) modulate sows’ oxidative and inflammation status (polyunsaturated fatty acids, vitamin E, selenium, phytogenic actives, and spray dried plasma), (4) allow early microbial colonization (probiotics), or (5) supply conditionally essential nutrients (nucleotides, glutamate, glutamine, threonine, and tryptophan).

Projected temperature rise in the upcoming years due to climate change has increased interest in studying the effects of heat stress in dairy cows. Environmental indices are commonly used for detecting heat stress, but have been used mainly in studies focused on the productivity-related effects of heat stress. The welfare approach involves identifying physiological and behavioural measurements so as to start heat stress mitigation protocols before the appearance of impending severe health or production issues. Therefore, there is growing interest in studying the effects of heat stress on welfare. This systematic review seeks to summarise the animal-based responses to heat stress (physiological and behavioural, excluding productivity) that have been used in scientific literature. Using systematic review guidelines set by PRISMA, research articles were identified, screened and summarised based on inclusion criteria for physiology and behaviour, excluding productivity, for animal-based resilience indicators. 129 published articles were reviewed to determine which animal-based indicators for heat stress were most frequently used in dairy cows. The articles considered report at least 212 different animal-based indicators that can be aggregated into body temperature, feeding, physiological response, resting, drinking, grazing and pasture-related behaviour, reactions to heat management and others. The most common physiological animal-based indicators are rectal temperature, respiration rate and dry matter intake, while the most common behavioural indicators are time spent lying, standing and feeding. Although body temperature and respiration rate are the animal-based indicators most frequently used to assess heat stress in dairy cattle, when choosing an animal-based indicator for detecting heat stress using scientific literature to establish thresholds, characteristics that influence the scale of the response and the definition of heat stress must be taken into account, e.g. breed, lactation stage, milk yield, system type, climate region, bedding type, diet and cooling management strategies.