An innovative method developed by an Italian team is emerging that will revolutionize the field of archaeology and radiocarbon dating and protect our cultural heritage. The researchers have used it with surprising results on archaeological bones, making the ‘invisible’ visible.
This important achievement—published in the journal Communications Chemistry—is the result of extensive research work coordinated by Professor Sahra Talamo, in which experts in the field of analytical chemistry from the University of Bologna and the University of Genoa collaborated.
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.
“Our results will offer significant advances for the study of human evolution,” says Talamo co-author of the study and director of the Radiocarbon dating lab BRAVHO at the University of Bologna, “as we will be able to minimize the destruction of valuable bone material, which is under the protection and enhancement of European cultural heritage and thus allow us to contextualize the valuable object by providing an accurate calendar age.”
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.
In order to combine the need to preserve the integrity of the artifacts as much as possible with the need to carry out radiocarbon analyses, the researchers therefore developed an innovative method that, thanks to a camera coupled with near-infrared, allows them to detect the average collagen content in the observed samples.
“We used imaging technology to quantify the presence of collag
