Distinguishing real from fake ivory products by elemental analyses: A Bayesian hybrid classification method

© 2017 Elsevier B.V. As laws tighten to limit commercial ivory trading and protect threatened species like whales and elephants, increased sales of fake ivory products have become widespread. This study describes a method, handheld X-ray fluorescence (XRF) as a noninvasive technique for elemental an...

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Main Authors: Kittisak Buddhachat, Janine L. Brown, Chatchote Thitaram, Sarisa Klinhom, Korakot Nganvongpanit
Format: Journal
Published: 2018
Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85010931833&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/47223
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-472232018-04-25T07:26:57Z Distinguishing real from fake ivory products by elemental analyses: A Bayesian hybrid classification method Kittisak Buddhachat Janine L. Brown Chatchote Thitaram Sarisa Klinhom Korakot Nganvongpanit © 2017 Elsevier B.V. As laws tighten to limit commercial ivory trading and protect threatened species like whales and elephants, increased sales of fake ivory products have become widespread. This study describes a method, handheld X-ray fluorescence (XRF) as a noninvasive technique for elemental analysis, to differentiate quickly between ivory (Asian and African elephant, mammoth) from non-ivory (bones, teeth, antler, horn, wood, synthetic resin, rock) materials. An equation consisting of 20 elements and light elements from a stepwise discriminant analysis was used to classify samples, followed by Bayesian binary regression to determine the probability of a sample being ‘ivory’, with complementary log log analysis to identify the best fit model for this purpose. This Bayesian hybrid classification model was 93% accurate with 9 2% precision in discriminating ivory from non-ivory materials. The method was then validated by scanning an additional ivory and non-ivory samples, correctly identifying bone as not ivory with > 95% accuracy, except elephant bone, which was 72%. It was less accurate for wood and rock (25–85%); however, a preliminary screening to determine if samples are not Ca-dominant could eliminate inorganic materials. In conclusion, elemental analyses by XRF can be used to identify several forms of fake ivory samples, which could have forensic application. 2018-04-25T07:26:57Z 2018-04-25T07:26:57Z 2017-03-01 Journal 18726283 03790738 2-s2.0-85010931833 10.1016/j.forsciint.2017.01.016 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85010931833&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/47223
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
description © 2017 Elsevier B.V. As laws tighten to limit commercial ivory trading and protect threatened species like whales and elephants, increased sales of fake ivory products have become widespread. This study describes a method, handheld X-ray fluorescence (XRF) as a noninvasive technique for elemental analysis, to differentiate quickly between ivory (Asian and African elephant, mammoth) from non-ivory (bones, teeth, antler, horn, wood, synthetic resin, rock) materials. An equation consisting of 20 elements and light elements from a stepwise discriminant analysis was used to classify samples, followed by Bayesian binary regression to determine the probability of a sample being ‘ivory’, with complementary log log analysis to identify the best fit model for this purpose. This Bayesian hybrid classification model was 93% accurate with 9 2% precision in discriminating ivory from non-ivory materials. The method was then validated by scanning an additional ivory and non-ivory samples, correctly identifying bone as not ivory with > 95% accuracy, except elephant bone, which was 72%. It was less accurate for wood and rock (25–85%); however, a preliminary screening to determine if samples are not Ca-dominant could eliminate inorganic materials. In conclusion, elemental analyses by XRF can be used to identify several forms of fake ivory samples, which could have forensic application.
format Journal
author Kittisak Buddhachat
Janine L. Brown
Chatchote Thitaram
Sarisa Klinhom
Korakot Nganvongpanit
spellingShingle Kittisak Buddhachat
Janine L. Brown
Chatchote Thitaram
Sarisa Klinhom
Korakot Nganvongpanit
Distinguishing real from fake ivory products by elemental analyses: A Bayesian hybrid classification method
author_facet Kittisak Buddhachat
Janine L. Brown
Chatchote Thitaram
Sarisa Klinhom
Korakot Nganvongpanit
author_sort Kittisak Buddhachat
title Distinguishing real from fake ivory products by elemental analyses: A Bayesian hybrid classification method
title_short Distinguishing real from fake ivory products by elemental analyses: A Bayesian hybrid classification method
title_full Distinguishing real from fake ivory products by elemental analyses: A Bayesian hybrid classification method
title_fullStr Distinguishing real from fake ivory products by elemental analyses: A Bayesian hybrid classification method
title_full_unstemmed Distinguishing real from fake ivory products by elemental analyses: A Bayesian hybrid classification method
title_sort distinguishing real from fake ivory products by elemental analyses: a bayesian hybrid classification method
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85010931833&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/47223
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