Blood spatters and saliva at crime scenes can accurately reveal the age of a missing victim or suspect.
A new forensic test developed by scientists at King's College London utilises a technique which uses artificial intelligence to analyse age-related biomarkers.
The technique was able to predict the age of sample donors to within an average of four years.
The team identified 16 key genetic biomarkers for ageing and tested them using data from 1,156 blood samples.
This is the first study to test next generation sequencing and machine learning technologies together to estimate age from blood and saliva samples."
With the help of AI "machine learning" software, the researchers found that blood provided a good way to guess a person's age. Other tests revealed similar results from saliva.
The findings appear in the journal Forensic Science International.
Senior author Dr Denise Syndercombe-Court, also from King's College London, said: "Through further research, these findings could provide a basis for combined
analysis techniques that would be of substantial value in forensic investigations in the future."
Dr Denise Syndercombe-Court, is a reader in Forensic Science specialising in identification of people using DNA and other genetically inherited factors. Experienced in both criminal and civil matters, providing reports for the legal profession dealing with human identification and relationship testing, including paternity.