评估探测犬对油类的识别能力

IF 1.3 4区 生物学 Q4 BEHAVIORAL SCIENCES
Mallory T. DeChant , Paul C. Bunker , Nathanial J. Hall
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引用次数: 0

摘要

狗被用来检测油类以支持泄漏修复和保护工作,但人们对油类气味的风化和老化对狗的概括能力和区分未风化油类与老化/风化焦油球油的能力的影响知之甚少。我们使用三选一程序和自动嗅觉仪对三只狗进行了检测未风化油类气味的训练。我们评估了警犬从四种不同的风化/焦油球样本中分辨出未风化目标油类的能力。三只狗都成功地从四种非目标风化油中分辨出了未风化目标油,准确率分别为 96%、97% 和 100%。在油类辨别测试之后,在一项新的辨别测试中测试了狗将未风化目标油类与海滩上的新型天然气味(塑料瓶盖、鸟类羽毛和岩石)区分开来的能力,准确率分别为 95%、100% 和 100%。这些数据表明,通过明确的训练,狗可以成功分辨出未风化的油类和风化的油类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of the capability of oil specific discrimination in detection dogs

Dogs are used for oil detection to support spill remediation and conservation, but little is known about the effects of weathering and aging of oil odorants on dogs’ ability to generalize and discriminate unweathered oil from aged/weathered tar ball oil. Three dogs were trained to detect unweathered oil odorant using a three-alternative choice procedure and automated olfactometers. We evaluated dogs’ ability to discriminate unweathered target oil from four different weathered/tar ball samples. All three dogs successfully discriminated the unweathered target oil from the four nontarget weathered oils with an accuracy of 96%, 97%, and 100%. After the oil discrimination test, dogs’ ability to discriminate unweathered target oil from novel natural odorants on a beach (plastic bottle lid, bird feathers, and rocks) was tested in a novel discrimination test yielding an accuracy of 95%, 100%, and 100%. These data suggest dogs are successful in discriminating unweathered oil from weathered oil with explicit training.

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来源期刊
Behavioural Processes
Behavioural Processes 生物-动物学
CiteScore
2.70
自引率
7.70%
发文量
144
审稿时长
4-8 weeks
期刊介绍: Behavioural Processes is dedicated to the publication of high-quality original research on animal behaviour from any theoretical perspective. It welcomes contributions that consider animal behaviour from behavioural analytic, cognitive, ethological, ecological and evolutionary points of view. This list is not intended to be exhaustive, and papers that integrate theory and methodology across disciplines are particularly welcome.
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