scholarly journals Chemical Compositions of African Trade Bracelets (Manillas) via Energy Dispersive X-Ray Fluorescence

Author(s):  
Mike Kuntz ◽  
Jennifer Ferguson ◽  
Vincent Iduma ◽  
Renee Kuzava ◽  
Mark Benvenuto

Sixteen small, west African trade bracelets called manillas, and one large, African trade bracelet referred to as a king manilla based on its size, were analyzed via energy dispersive x-ray fluorescence spectrometry and compared for the following elements: copper, zinc, tin, lead, antimony, and arsenic. The composition of the bracelets varied widely in the amount of lead present, especially when compared to the official amounts of lead allowed by the various manufacturing concerns. The king manilla showed a markedly different chemistry than the sixteen smaller manillas, consistent with the belief such large manillas were not manufactured in the same location as the small.

2015 ◽  
Vol 94 (4) ◽  
pp. 460-467 ◽  
Author(s):  
Christina Papachristodoulou ◽  
Konstantinos Stamoulis ◽  
Panagiotis Tsakos ◽  
Christina Vougidou ◽  
Vasileios Vozikis ◽  
...  

2014 ◽  
Vol 43 (2) ◽  
pp. 47-53 ◽  
Author(s):  
Toshio MIYAZAKI ◽  
Shin-ichi YAMASAKI ◽  
Noriyoshi TSUCHIYA ◽  
Satoshi OKUMURA ◽  
Ryoichi YAMADA ◽  
...  

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Tong Chen ◽  
Xingpu Qi ◽  
Zaiyong Si ◽  
Qianwei Cheng ◽  
Hui Chen

Abstract In this work, a method was established for discriminating geographical origins of wheat flour based on energy dispersive X-ray fluorescence spectrometry (ED-XRF) and chemometrics. 68 wheat flour samples from three different origins were collected and analyzed using ED-XRF technology. Firstly, the principal component analysis method was applied to analyze the feasibility of discrimination and reduce data dimensionality. Then, Competitive Adaptive Reweighted Sampling (CARS) was used to further extract feature variables, and 12 energy variables (corresponding to mineral elements) were identified and selected to characterize the geographical attributes of wheat flour samples. Finally, a non-linear model was constructed using principal component analysis and quadratic discriminant analysis (QDA). The CARS-PCA-QDA model showed that the accuracy of five-fold cross-validation was 84.25%. The results showed that the established method was able to select important energy channel variables effectively and wheat flour could be classified based on geographical origins with chemometrics, which could provide a theoretical basis for unveiling the relationship between mineral element composition and wheat origin.


1977 ◽  
Vol 49 (12) ◽  
pp. 1734-1737 ◽  
Author(s):  
John A. Boslett ◽  
Robert L. R. Towns ◽  
Robert G. Megargle ◽  
Karl H. Pearson ◽  
Thomas C. Furnas

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