Abstract
The ability of an animal to adapt to transient environmental difficulties and regain its pre-challenge state is known as resilience, and it is a dynamic and multifaceted characteristic. The ability of the herd to adapt to often shifting and uncertain environmental conditions can be strengthened by resilient animals. The capacity of contemporary technologies to capture many performance metrics of individual animals in real time is a significant advancement in assessing the resilience of farm animals. Resilience, however, cannot be measured directly; instead, quantitative resilience indicators must be derived from mathematical models with biologically meaningful characteristics. This work aimed to review and demonstrate, via examples, several modeling methodologies used with this new type of data (high-frequency recording) in order to identify and measure animal reactions to disturbances.
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