Abstract
Simple SummaryAs lame cows produce less milk and tendto have other health problems, finding and treating lame cows is very importantfor farmers. Sensors that measure behaviors associated with lameness in cowscan help by alerting the farmer of those cows in need of treatment. This reviewgives an overview of sensors for automated lameness detection and discussessome practical considerations for investigating and applying such systems inpractice.Despite the research on opportunities toautomatically measure lameness in cattle, lameness detection systems are notwidely available commercially and are only used on a few dairy farms. However, farmers need to be aware of the lame cows in their herds in order treat themproperly and in a timely fashion. Many papers have focused on the automatedmeasurement of gait or behavioral cow characteristics related to lameness. Inorder for such automated measurements to be used in a detection system, algorithms to distinguish between non-lame and mildly or severely lame cowsneed to be developed and validated. Few studies have reached this latter stageof the development process. Also, comparison between the different approachesis impeded by the wide range of practical settings used to measure the gait or behavioralcharacteristic (e.g., measurements during normal farming routine or duringexperiments; cows guided or walking at their own speed) and by the differentdefinitions of lame cows. In the majority of the publications, mildly lame cowsare included in the non-lame cow group, which limits the possibility of alsodetecting early lameness cases. In this review, studies that used sensortechnology to measure changes in gait or behavior of cows related to lamenessare discussed together with practical considerations when conducting lamenessresearch. In addition, other prerequisites for any lameness detection system onfarms (e.g., need for early detection, real-time measurements) are discussed.
Highlights
To properly tackle the lameness problem, farmers need to be aware of the number of lame cows in their herd and the severity of their lameness
Their preliminary test showed that such systems have potential to separate lame from non-lame cows based on the differences in force-time behavior: lame cows used a lower step force and longer stance time with the lame limb compared to the sound limb
In spite of the amount of research available on measurement of gait and behavioral characteristics that are relevant to lameness detection, no efficient automated lameness detection system is available on the market yet
Summary
To properly tackle the lameness problem, farmers need to be aware of the number of lame cows in their herd and the severity of their lameness. The commonly accepted methodologies to quantify lameness rely on identifying changes in the gait and posture of the cows and are discussed in the first part of this review [1]. This is done using subjective methods such as visual observations leading to locomotion scores by the farmer, an employee, a veterinarian or an agricultural consultant. The wide range of practical settings during the experiments, together with the definitions used to distinguish non-lame from lame cows, impede comparison between the different automated approaches The factors obstructing such comparison and the need for specific characteristics (real-time/automated/continuous measurements, level of early detection, set-up size) of an automated lameness detection system are discussed
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