Álvaro García
Animal well-being is gaining prominence in developed countries, with focused efforts on establishing science-based assessment indicators. Three animal well-being evaluation systems exist worldwide for dairy cattle at the present time: Farmers Assuring Responsible Management in the USA (FARM), New Zealand Code of Welfare, and Welfare Quality in Europe. FARM in the USA sets the standards for dairy animal care and environmental stewardship through on-farm evaluations. The Code in New Zealand outlines minimum standards for the care and management of dairy cattle to promote animal welfare. Welfare Quality in Europe is a research project funded by the EU aimed at developing science-based welfare assessment protocols for dairy cattle and other livestock species. Prioritizing animal well-being not only ensures compliance with ethical standards but also enhances farm productivity, contributing to the establishment of a social license to operate. Research indicates that animals raised in welfare-conscious environments exhibit improved growth rates, feed efficiency, and reproductive success.
Despite progress, challenges persist in implementing standardized protocols to enhance farm animals’ quality of life. However, the emergence of precision livestock farming (PLF) offers promise for real-time well-being assessment using diverse indicators. Facilitated by collaborations between engineering researchers and the livestock sector, PLF connects technology like image, sound, and movement sensors, coupled with algorithms, for automated well-being monitoring. Integrating these technological advancements into well-being protocols will be pivotal, alongside ensuring farmer acceptance and effective utilization of PLF solutions through data visualization.
Cow well-being: where Lameness, Body Condition, and Mastitis Intersect.
Lameness
Lameness reduces mobility and can lead to weight loss, while poor body condition worsens lameness, creating a cycle of discomfort. Concurrently, mastitis causes pain and affects milk production and quality. Preventative measures like hygiene practices and udder health monitoring reduce mastitis incidence, supported by maintaining optimal body condition and minimizing lameness. Recognizing this interrelationship allows for comprehensive management approaches to improve cow welfare. Lameness is a major cause of economic losses on dairy farms, making early detection crucial. Flexible sensor-based systems aid in identifying lameness early, allowing for timely intervention through various management measures. Automated lameness detection techniques, including accelerometer-based systems, pressure plates/load cells, and 3D video cameras, offer diverse approaches. Each method contributes to monitoring cow health, with 3D cameras providing a comprehensive assessment of posture and movement, aiding in precise lameness identification. Integration of these techniques ensures holistic monitoring and early intervention, promoting better cow health and farm profitability.
Imaging technology (3D cameras) represent a significant advancement in automated lameness detection, offering several advantages over other techniques. These cameras provide comprehensive data capture, offering detailed information about cow posture and movement in three dimensions. This depth of information allows for a more thorough analysis of gait abnormalities associated with lameness, enhancing the accuracy of detection. Importantly, 3D cameras operate without direct contact with the animals, eliminating the need for specialized infrastructure and reducing the risk of injury to the cows. This non-contact measurement also facilitates ease of implementation, as it does not require individual animals to walk over specialized equipment. Furthermore, 3D cameras enable continuous monitoring of cow behavior and movement patterns without disturbing the animals, allowing for early detection of lameness symptoms and insights into the condition’s progression over time. These systems are scalable and can be deployed in various settings, from individual animal monitoring to larger-scale herd surveillance, making them suitable for different farm sizes and management practices. While initial setup costs may be higher, ongoing advancements in technology are driving down the overall cost of 3D camera systems, making them increasingly cost-effective for dairy farmers.
Body condition score changes
Body condition scoring (BCS) is crucial for dairy cow welfare and management, reflecting their health, metabolic status, and milk composition. Traditionally, BCS involves visually assessing and palpating specific body areas, but this method is subjective and requires extensive training. Precision livestock farming (PLF) offers solutions with vision-based systems using thermal, 2D, and 3D imaging technologies to automate BCS assessment, reducing subjectivity and enhancing efficiency.
Recently, 3D sensors have gained traction for measuring dairy cattle’s energy reserves. Four automated BCS systems, utilizing 3D sensors positioned on the cow’s rump and lumbar regions, are commercially available. Validation studies, particularly in the 3.00–3.75 BCS range common among Holstein cows, show promising results. These automated systems provide regular BCS scores, enhancing their utility in both commercial and research settings. Including BCS in Welfare Quality protocols emphasizes its importance as an animal-based indicator linked to animal feed. Precision livestock farming technologies advance individual cow assessment through continuous real-time monitoring, enhancing health and welfare evaluation protocols.
Mastitis
Mastitis poses significant challenges in dairy farming, impacting both animal welfare and profitability. While control measures like teat immersion have reduced contagious pathogens, emerging strains and antimicrobial concerns necessitate ongoing research.
Automated mastitis detection offers benefits such as early treatment and reduced antibiotic use, improving cow health and farm economics. Diagnostic methods, including somatic cell count (SCC) and infrared thermography (IRT), aid in surveillance and early detection.
The cost of subclinical mastitis is substantial and diverse. High somatic cell counts lead to milk price penalties, culling of chronically affected cows, and reduced milk yield. Herds with high cell counts incur expenses for individual testing, bacteriology testing, and advice. Additionally, antibiotic dry cow therapy for the entire herd increases costs compared to selective therapy. Some causes of high somatic cell count, like Staph aureus, may lead to clinical mastitis during lactation, adding to treatment costs.
Implications
In conclusion, addressing well-being concerns such as lameness, body condition, and mastitis in dairy farming is paramount for ensuring the health, productivity, and overall well-being of cows. While significant progress has been made through legislative measures, research initiatives, and the development of precision livestock farming technologies, challenges persist in implementing standardized protocols and maximizing their impact on farm animal quality of life.
Automated detection systems, advanced measurement techniques, and innovative solutions offer promising avenues for early intervention, reduced antibiotic use, and enhanced management practices. By integrating these technologies into routine farm operations and welfare assessment protocols, we can revolutionize the way we monitor and manage dairy cow well-being.
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