Animal's well-being, growth, and production are modulated by environmental conditions, and managemental practices and can be deleteriously affected by global warming phenomenon. In the recent years, unprecedented climatic fluctuations like sustained higher temperatures and humidity, heat waves, and solar flares have led to economic losses in $ billions to both milk and meat industry. It is estimated that by 2050, the US dairy industry alone will borne more than $1.7 billion loss. As human dependency on animal products like milk, meat, and eggs for nutrition is exponentially rising, there is urgency for maximum production. The high yielding animals are already under tremendous metabolic pressure making them more susceptible to adverse climatic conditions. When exposed to heat stress, livestock display a variety of behavioral and physiological acclimatization as essential survival strategies, but at the cost of decreased milk, meat, or egg production. Most of the studies have explored the heat stress in animals and its effect on different milk productions in a specific region or country. A clear understanding of the impact of global warming on dairy enterprise is yet to be comprehended. So this exploratory study will analyze impact of global warming on current milk production trends, economics, and future perspectives.

Heat stress in dairy animals and current milk production trends, economics, and future perspectives: the global scenario

The effects of cow-related factors on rectal temperature, respiration rate, and temperature-humidity index thresholds for lactating cows exposed to heat stress.

Milk is a foodstuff widely consumed around the world originating from a variety of different species, animal management and production systems. In recent years, consumers have placed a much greater emphasis on the authenticity and origin of some food products often willing to pay a premium price for such products that is, for example ‘Grass-Fed Dairy’. Therefore, it is important to establish methods to assess both quality and authentication of milk and dairy products for increased food security and consumer protection. Accordingly, NMR-based, GC–MS-based, and LC–MS-based metabolomics have been established as useful tools in the analysis of dairy products, such as raw and processed milk. This short-review provides an updated and critical overview on the most useful metabolomics-based platforms and the most useful multivariate statistical tools available for metabolomic data interpretation.

Application of metabolomics to assess milk quality and traceability

Over the past four decades the dietary needs of the global population have been elevated, with increased consumption of animal products predominately due to the advancing economies of South America and Asia. As a result, livestock production systems have expanded in size, with considerable changes to the animals’ management. As grazing animals are commonly grown in herds, economic and labour constraints limit the ability of the producer to individually assess every animal. Precision Livestock Farming refers to the real-time continuous monitoring and control systems using sensors and computer algorithms for early problem detection, while simultaneously increasing producer awareness concerning individual animal needs. These technologies include automatic weighing systems, Radio Frequency Identification (RFID) sensors for individual animal detection and behaviour monitoring, body temperature monitoring, geographic information systems (GIS) for pasture evaluation and optimization, unmanned aerial vehicles (UAVs) for herd management, and virtual fencing for herd and grazing management. Although some commercial products are available, mainly for cattle, the adoption of these systems is limited due to economic and cultural constraints and poor technological infrastructure. This review presents and discusses PLF applications and systems for grazing animals and proposes future research and strategies to improve PLF adoption and utilization in today’s extensive livestock systems.

/pdf/precision-livestock-farming-applications-plf-for-grazing-1udcqfqn.pdf

Precision Livestock Farming Applications (PLF) for Grazing Animals

Live sheep export has become a public concern. This study aimed to test a non-contact biometric system based on artificial intelligence to assess heat stress of sheep to be potentially used as automated animal welfare assessment in farms and while in transport. Skin temperature (°C) from head features were extracted from infrared thermal videos (IRTV) using automated tracking algorithms. Two parameter engineering procedures from RGB videos were performed to assess Heart Rate (HR) in beats per minute (BPM) and respiration rate (RR) in breaths per minute (BrPM): (i) using changes in luminosity of the green (G) channel and (ii) changes in the green to red (a) from the CIELAB color scale. A supervised machine learning (ML) classification model was developed using raw RR parameters as inputs to classify cutoff frequencies for low, medium, and high respiration rate (Model 1). A supervised ML regression model was developed using raw HR and RR parameters from Model 1 (Model 2). Results showed that Models 1 and 2 were highly accurate in the estimation of RR frequency level with 96% overall accuracy (Model 1), and HR and RR with R = 0.94 and slope = 0.76 (Model 2) without statistical signs of overfitting.

/pdf/non-invasive-sheep-biometrics-obtained-by-computer-vision-ylmc18n74r.pdf

Non-Invasive Sheep Biometrics Obtained by Computer Vision Algorithms and Machine Learning Modeling Using Integrated Visible/Infrared Thermal Cameras

The objective of this study was to measure the impacts of summer heat events on physiological parameters (body temperature, respiratory rate and panting scores), grazing behaviour and production parameters of lactating Holstein Friesian cows managed on an Automated Robotic Dairy during Australian summer. The severity of heat stress was measured using Temperature-Humidity Index (THI) and impacts of different THIs-low (≤72), moderate (73-82) and high (≥83)-on physiological responses and production performance were measured. There was a highly significant (p ≤ 0.01) effect of THI on respiratory rate (66.7, 84.7 and 109.1/min), panting scores (1.4, 1.9 and 2.3) and average body temperature of cows (38.4, 39.4 and 41.5 °C), which increased as THI increased from low to moderate to high over the summer. Average milk production parameters were also significantly (p ≤ 0.01) affected by THI, such that daily milk production dropped by 14% from low to high THI, milk temperature and fat% increased by 3%, whilst protein% increased by 2%. The lactation stage of cow had no significant effect on physiological parameters but affected (p ≤ 0.05) average daily milk yield and milk solids. Highly significant (p ≤ 0.01) positive correlations were obtained between THI and milk temperature, fat% and protein% whilst the reverse was observed between THI and milk yield, feed intake and rumination time. Under moderate and high THI, most cows sought shade, spent more time around watering points and showed signs of distress (excessive salivation and open mouth panting). In view of the expected future increase in the frequency and severity of heat events, additional strategies including selection and breeding for thermotolerance and dietary interventions to improve resilience of cows need to be pursued.

https://minerva-access.unimelb.edu.au/bitstream/handle/11343/246400/PMC7278445.pdf

Heat Stress Impacts on Lactating Cows Grazing Australian Summer Pastures on an Automatic Robotic Dairy.

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Heat Stress Impacts on Lactating Cows Grazing Australian Summer Pastures on an Automatic Robotic Dairy.