Food preference predicts speed of approach on a runway task by dogs
Cameron, Kristie; de Garnham, Jane; Jensen, K.; Bizo, L.A.
Date
2019-07-05Citation:
Cameron, K E., de Garnham, J., Jensen, K., & Bizo, L A. (2019). Food preference predicts speed of approach on a runway task by dogs. Pet Behaviour Science, 8, 1-10. doi:10.21071/pbs.v0i8.11179Permanent link to Research Bank record:
https://hdl.handle.net/10652/4911Abstract
The effective and quick assessment of food preference is important when attempting to identify foods that might function as effective reinforcers in dogs. In the current experiment, more highly preferred foods were expected to be associated with faster approaches in a subsequent runway task. Eight dogs experienced combinations of two of six types of raw food in a paired preference assessment. These included the dog’s staple diet, to identify a rank order of preference for the foods. A different raw food was offered as the staple in two preference tests. In the runway task, the dogs were required to walk five metres to obtain a small amount of their most preferred, least preferred or staple foods and latency of approach to the foods was recorded. The results showed that the staple foods were not preferred as highly as the other foods and that each dog displayed unique and stable preferences for the different foods. The approach latencies were faster for their most-preferred food compared to their least preferred and the staple foods. The use of a runway to assess reinforcer effectiveness combined an effortful behaviour to obtain food while also requiring the dogs to make a choice, thus precluding the need for more complicated and time-consuming methods of preference assessment. The application of this method for fast and effective identification of preferred reinforcers is currently being investigating further to inform pet owners and behavioural scientists better about simple methods that they might use to identify highly preferred foods for use as reinforcers in training and behavioural testing.