Technological Tools for the Early Detection of Bovine Respiratory Disease in Farms
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Date
2022
Authors
Puig Escrig, Andrea
Ruiz, Miguel
Bassols, Marta
Fraile Sauce, Lorenzo José
Armengol Gelonch, Ramon
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Abstract
Classically, the diagnosis of respiratory disease in cattle has been based on observation of
clinical signs and the behavior of the animals, but this technique can be subjective, time-consuming
and labor intensive. It also requires proper training of staff and lacks sensitivity (Se) and specificity
(Sp). Furthermore, respiratory disease is diagnosed too late, when the animal already has severe
lesions. A total of 104 papers were included in this review. The use of new advanced technologies
that allow early diagnosis of diseases using real-time data analysis may be the future of cattle
farms. These technologies allow continuous, remote, and objective assessment of animal behavior
and diagnosis of bovine respiratory disease with improved Se and Sp. The most commonly used
behavioral variables are eating behavior and physical activity. Diagnosis of bovine respiratory disease
may experience a significant change with the help of big data combined with machine learning,
and may even integrate metabolomics as disease markers. Advanced technologies should not be a
substitute for practitioners, farmers or technicians, but could help achieve a much more accurate
and earlier diagnosis of respiratory disease and, therefore, reduce the use of antibiotics, increase
animal welfare and sustainability of livestock farms. This review aims to familiarize practitioners
and farmers with the advantages and disadvantages of the advanced technological diagnostic tools
for bovine respiratory disease and introduce recent clinical applications.
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Animals, 2022, vol. 12, art. 2623.