Protecting the cultural heritage of ancient bone artifacts is now possible. Near-infrared hyperspectral imaging and radiocarbon dating together to make the invisible visible. An innovative method developed by an Italian team is emerging that will revolutionize the field of archaeology and radioca
Innovative near-infrared hyperspectral imaging technology allows non-destructive analysis of collagen in archaeological bones, preserving precious material while providing crucial data for radiocarbon dating and human evolution studies.
The group has developed a new technique for analyzing archaeological bones that, for the first time, makes it possible to quantify and map at high resolution the presence of collagen, the invisible protein that is essential for making radiocarbon dates and thus obtaining new information on human evolution.
Many of the rarest prehistoric bones found by archaeologists are enormously precious and are considered to be part of our cultural and historical patrimony. Bones can provide a great deal of information about ancient populations’ lives: what they ate, their reproductive habits, their diseases and the migrations they undertook. However, bones cannot give us all the information we so covet. Their potential to convey information is limited by how much collagen is preserved in them.
It is extremely difficult, costly, and time-consuming to analyze all the bones present at one archaeological site for collagen preservation, most importantly, it would result in the destruction of valuable material. In fact, human fossils and/or bone artifacts are increasingly rarer and more precious over time.
This technique is expected to support the selection of samples to be submitted to radiocarbon analysis at many sites where previous attempts have not been possible because of poor preservation. Thus, this experimental approach can provide quantitative information related to the average collagen content present in the whole sample submitted for investigation. The examination can be performed not only in small and localized areas , but it can also consider the entire surface of the sample, thus producing a higher and much more significant amount of data.
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