Positive identification of human remains is the very first step in anthropological analysis, and the task may be particularly difficult in the case of fragmented bones. Histomorphometry methods have been developed to discriminate human from nonhuman bones, based on differences in the size and shape of Haversian systems between the two groups. Those methods all focus on a very specific type of bone, section, and zone. Therefore, the objective of this study was to test the efficiency of four histomorphometric methods on a sample of fragmented bones. The sample is composed of 37 archaeological and fresh specimens, 25 nonhumans (Bos taurus, Equus caballus, Sus scrofa, Capreolus, Canis familiaris, Cervus elaphus, Ovis, and Capra) and 12 humans (Homo sapiens). Eight histomorphometric criteria were collected from all intact osteons visible on each fragment and then inserted into the corresponding discriminate function of each method. The results were compared with the real origin to establish rates of correct classification for each method. The methods of Martiniaková et al. (2006) and Crescimanno and Stout (2012) obtained very low percentages of good classification (32 % and 67 %). Those of Cattaneo et al. (1999) obtained 94 % correct classification, but only after a correction of the units of measurement for Haversian canal area in their formula. The methods of Dominguez and Crowder (2012) obtained an 86 % rate for well-classified specimens. Some of the methods tested here contain errors in the original publication that make them unusable in their current state. Plus, it seems that histomorphometric methods developed from specific areas are more difficult to apply to fragments. A reduced number of intact osteons analyzed may partially affect the reliability of the method by being unrepresentative of the entire microstructure. Therefore, this study demonstrates that one should be cautious with the use of histomorphometric methods to distinguish human and nonhuman fragmented bone until further research can refine these methods to achieve greater reliability.Copyright © 2020 Elsevier B.V. All rights reserved.
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