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ARS Home » Midwest Area » West Lafayette, Indiana » Livestock Behavior Research » Research » Publications at this Location » Publication #300934

Title: The science of animal welfare

Author
item Lay Jr, Donald

Submitted to: Journal of Animal Science
Publication Type: Abstract Only
Publication Acceptance Date: 12/13/2013
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: People differ in their culture, education, economic status, and values; thus they may view an animal’s welfare status as good or poor based on their individuality. However, regardless of these human differences in perception the actual state of welfare for the animal does exist in a range from good to poor; it is our difficulty to scientifically quantify this state which underlies our global debate on animal welfare. The science of animal welfare is one of collaboration and dependence of many sciences. Simply using one scientific discipline cannot ensure an adequate assessment of the state of welfare for any animal. An animal may be well fed, productive, free of disease, and in a state of physiologic homeostasis, yet suffer from poor welfare. It is the objective of the research, i.e. to solve a welfare problem, and its basis on sound scientific measures of welfare which defines it as Animal Welfare Science. Solid animal welfare research should measure those parameters that have real meaning to an animal’s state of welfare given the specific welfare problem at hand; and should strive to include the affective state of the animals in question. Our challenge is in assessing a subjective state; we have done quite well in assessing subjective states in humans and I believe we can be successful in non-human animals as well. An animal welfare scientist needs to be able to interpret data from multiple disciplines in an objective manner. The state of an animal’s welfare relies on complex interactions from many biological systems. Similar to the theory of Gestalt, an animal’s welfare is greater than the sum of its parts, thus measuring random parts will not provide the whole picture.