How Light-Based Analysis Can Determine the Sex of Blowfly Larvae

A new study from Texas A&M uses infrared light and machine learning to accurately and non-destructively determine the sex of blowfly larvae, a key breakthrough that could lead to more precise forensic timelines and time-of-death estimations.

7 Min Read
FTIR spectrometer performing chemical analysis on a blowfly larva during forensic investigation.

In a forensic investigation, the insects found on or near a body can provide a wealth of information. The study of these insects, known as forensic entomology, is a critical tool for estimating the post-mortem interval (PMI), or the time elapsed since death. The accuracy of this estimation, however, depends on many factors, both external (like temperature) and internal (like the species and sex of the insects). A significant challenge has always been determining the sex of fly larvae, as they lack visible sexual characteristics. A groundbreaking new study from Texas A&M shines fresh light—literally—on this problem, introducing an innovative technique that can determine the sex of a blowfly larva without destroying it.

The Problem with Sexing Fly Larvae

Flies are often the first insects to colonize human remains, and the timeline of their development is a key part of forensic entomology. The problem is that a fly’s developmental rate can be influenced by its sex. For instance, studies have shown that male blowflies often develop faster than females, which means that an estimation based on a mixed population of larvae could be inaccurate. At the larval stage, males and females are nearly impossible to distinguish visually, and current laboratory methods for doing so require destroying the insects for molecular analysis. This new research provides a much-needed alternative that is faster, more accurate, and non-destructive.

The Research: Finding a Chemical Signature

This Texas A&M study was designed to determine if male and female larvae of a specific blowfly species, Chrysomya rufifacies, have distinct chemical profiles that could be used for sex determination.

Methodology: From Larvae to a Light-Based “Fingerprint”

The researchers, led by doctoral student Aidan Holman and professor Dmitry Kurouski, used a handheld infrared spectroscopy device to scan live larvae.

Infrared spectroscopy is a technique that shines light on a sample and measures how its molecules respond. The way a sample scatters light creates a distinct “fingerprint” based on the molecular makeup of the insect, which the researchers found could indicate whether the insect was male or female. The spectra, which capture the composition of proteins and fats within the insect, were then used to train three different machine learning models to sort the larvae by sex.

Key Findings: High Accuracy with Machine Learning

The study’s results showed a clear and statistically significant difference between male and female larvae:

  • Distinct Chemical Signatures: The FTIR spectra revealed significant differences in the chemical composition of male and female larvae. The findings show that males consistently had a higher abundance of proteins, lipids, and hydrocarbons in their cuticles than females.
  • High Accuracy with Machine Learning: Two of the three machine learning models achieved a classification accuracy of over 90%, with the most successful at over 95%. This accuracy was maintained even with a portable, handheld device.
  • Non-Destructive and Fast: This technique is quick, requires only a handheld device, and does not destroy the samples, making it ideal for forensic field work.

The researchers believe this new method could provide significant value to real-world casework by informing the development of sex-specific growth curves for blowflies.

A New Era of Non-Destructive Analysis

This research represents a significant advancement in forensic entomology, offering a tool that is not only highly accurate but also well-suited to the realities of forensic investigations.

The Value of a Portable, Non-Destructive Method

The most significant takeaway from this study is the ability to sex a larva without destroying it. This is a game-changer for forensic entomologists, as it means they can now get a more accurate PMI estimate while preserving the larva for other analyses. Furthermore, the use of a handheld device means that this type of analysis could potentially be conducted directly at a crime scene, providing instant feedback to investigators and helping to guide the direction of the investigation. This is a perfect example of how technology can streamline and improve forensic workflows.

The Importance of the Data Set

The study’s findings on the importance of a large and robust training dataset for the machine learning models are also a critical lesson. It shows that while these tools are powerful, their accuracy is only as good as the data they are trained on. This is a reminder to the broader forensic community that as we adopt more automated and AI-based methods, the quality of our reference data and the rigor of our validation studies must be of the highest standard.

My Perspective: Maximizing Information from Every Sample

This research is highly relevant to my own work as a Senior DNA analyst. In my experience with STR DNA analysis, a core principle is to extract the maximum amount of usable information from every sample. This is particularly true for trace evidence, which may be limited and easily destroyed. The new FTIR method is a perfect parallel to this principle: it allows us to gather a crucial piece of information—sex—without altering the evidence, much like our non-destructive methods for initial screening of DNA. This kind of innovative thinking ensures that we get the most complete and accurate picture possible, a necessary step for sound crime scene reconstruction.

Conclusion

This study presents a groundbreaking new method for sexing blowfly larvae with a high degree of accuracy using portable FTIR spectroscopy and machine learning. By leveraging the distinct chemical signatures of male and female larvae, this approach offers a fast, non-destructive, and objective alternative to traditional methods. The findings are a significant step forward for forensic entomology, as they enable a more accurate post-mortem interval estimation and provide a powerful new tool for forensic investigators to use directly at the crime scene.

Original Research Paper

Holman, A. P., Pickett, D. N., West, H., Tarone, A. M., & Kurouski, D. (2025). Portable Fourier-transform infrared spectroscopy and machine learning for sex determination in third instar Chrysomya rufifacies larvae. Journal of Forensic Sciences, 70(4), 1329–1337. https://doi.org/10.1111/1556-4029.70054

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Forensic Analyst by Profession. With Simplyforensic.com striving to provide a one-stop-all-in-one platform with accessible, reliable, and media-rich content related to forensic science. Education background in B.Sc.Biotechnology and Master of Science in forensic science.
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