Training with Multiple Structurally Related Odorants Fails to Improve Generalization of Ammonium Nitrate Detection in Domesticated Dogs (Canis familiaris).

David C Dorman,Lucia Lazarowski,Melanie L Foster

doi:10.3390/ani11010213

David C Dorman, Lucia Lazarowski + Show 1 more

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https://doi.org/10.3390/ani11010213

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Abstract

Simple SummaryDomestic dogs are used by military and police forces to detect improvised explosive devices (IEDs) and other explosives. A challenge with training explosive detection dogs is that the ingredients used by someone to make an IED can vary. It is therefore critical that dogs be able to detect an IED with unfamiliar ingredients. This ability can be improved if the dog’s training allows them to categorize similar odors together. Many IEDs are created using ammonium nitrate, which was the focus of our study. Based on preliminary odor training performance, we equally assigned dogs to two experimental groups. Dogs in the first group were trained with two odors related to ammonium nitrate, while dogs in the second group were trained to six related odors. We anticipated that dogs trained to six odors would be more likely to form a category. However, this was not the case since dogs in both experimental groups were unable to form a category that allowed them to identify a novel ammonium nitrate mixture. Based on our results, the use of authentic explosive materials likely remains the most cost-effective and efficient way to train explosive scent detection dogs.A critical aspect of canine scent detection involves the animal’s ability to respond to odors based on prior odor training. In the current study, dogs (n = 12) were initially trained on an olfactory simple discrimination task using vanillin as the target odorant. Based on their performance on this task, dogs were assigned to experimental groups. Dogs in group 1 and 2 (n = 5 dogs/group; 1 dog/group were removed due to low motivation or high error rates) were trained with either two or six forms of ammonium nitrate (AN), respectively. Dogs were then assessed with a mock explosive with AN and powdered aluminum. Dogs in both groups failed to respond to the novel AN-aluminum odor. Mean success rates were 56 ± 5 and 54 ± 4% for groups 1 and 2, respectively. Overall, and individual dog performance was not statistically higher than chance indicating that dogs did not generalize from AN to a similar AN-based odorant at reliable levels desired for explosive detection dogs. These results suggest the use of authentic explosive materials, without the added complication of including category-learning methods, likely remains a cost-effective and efficient way to train explosive scent detection dogs.

Highlights

Many animal-based scent-training programs rely on the behavioral process of generalization [1]
We showed that dogs (n = 15) trained with pure ammonium nitrate (AN, NH4NO3) generalized at modest rates to other types of AN varying in source or form, such as fertilizer-grade AN (FAN) [15]
There were no differences in error rates or the number of trials to complete the pre-training phase between dogs assigned to group 1 (2 odorants; 34.5% ± 3.1 error rate, 269.4 ± 46.9 trials to criteria) and group 2, confirming that the matched-pair design resulted in groups that were equivalent in learning rate

Summary

Introduction

Many animal-based scent-training programs rely on the behavioral process of generalization [1]. In this context, generalization refers to an animal’s ability to categorize perceptually similar stimuli. Category formation allows an animal to respond to novel members of the category based on prior experience with stimuli that share similar physicochemical properties [1,2]. Stimulus generalization occurs as a function of perceptual similarity, with responses to novel stimuli decreasing as their similarity to the stimulus used to initially train the animal decreases, depicting a typical “generalization gradient” [3]. Category formation allows animals to appropriately respond to novel, previously un-encountered stimuli without prior explicit training. Successful category formation is demonstrated by positive transfer or generalization of responding to novel members of the category, whereas strict item-specific learning yields negative transfer results [5,6]

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