TY  - JOUR
PY  - 2012//
TI  - Bayesian integration of isotope ratio for geographic sourcing of castor beans
JO  - Journal of biomedicine and biotechnology
A1  - Webb-Robertson, Bobbie-Jo
A1  - Kreuzer, Helen
A1  - Hart, Garret
A1  - Ehleringer, James
A1  - West, Jason
A1  - Gill, Gary
A1  - Duckworth, Douglas
SP  - 450967
EP  - 450967
VL  - 2012
IS  - online
N2  - Recent years have seen an increase in the forensic interest associated with the poison ricin, which is extracted from the seeds of the Ricinus communis plant. Both light element (C, N, O, and H) and strontium (Sr) isotope ratios have previously been used to associate organic material with geographic regions of origin. We present a Bayesian integration methodology that can more accurately predict the region of origin for a castor bean than individual models developed independently for light element stable isotopes or Sr isotope ratios. Our results demonstrate a clear improvement in the ability to correctly classify regions based on the integrated model with a class accuracy of 60.9 ± 2.1% versus 55.9 ± 2.1% and 40.2 ± 1.8% for the light element and strontium (Sr) isotope ratios, respectively. In addition, we show graphically the strengths and weaknesses of each dataset in respect to class prediction and how the integration of these datasets strengthens the overall model.<p />  <p>Language: en</p>
LA  - en
SN  - 1110-7243
UR  - http://dx.doi.org/10.1155/2012/450967
ID  - ref1
ER  -