By Andi Anderson
Eggs and poultry are important sources of protein worldwide, supporting a major agricultural industry.
However, hatcheries face several challenges, including embryo mortality, fertility detection, chick sex identification, and egg quality evaluation. These processes are often costly, time-consuming, and destructive.
A research team from the University of Illinois Urbana-Champaign is using advanced imaging technologies to address these issues.
They conducted multiple studies using near-infrared spectroscopy and hyperspectral imaging combined with artificial intelligence to evaluate chicken eggs before and during early incubation.
Their latest research focuses on predicting chick embryo mortality. Embryo death in hatcheries can exceed ten percent, affecting economic viability, production efficiency, and animal welfare.
“If there is a genetic disorder or other inherent issue, some eggs don't produce healthy chicks, and the embryo dies. This poses a health hazard, as dead embryos can harbor bacteria. If we can detect and remove them early in the incubation period, we can avoid biosecurity issues,” said lead author Md. Wadud Ahmed.
The researchers scanned eggs before incubation and after four days in incubators. Using machine learning, they identified patterns that distinguished living embryos from dead ones. The best-performing model achieved up to ninety-seven percent accuracy by day four, offering a faster and safer alternative to traditional testing methods.
Another study focused on chick sex determination. Currently, male chicks are culled after hatching, which raises animal welfare concerns.
“Male chicks are considered a byproduct because they don't lay eggs and they are not economically feasible for meat production. Around 6 billion male chicks are culled annually in the U.S., which raises serious animal welfare, economic, and biosecurity issues for the hatchery. If we can identify the embryos early, we can avoid the culling of males and use the eggs for table eggs or in food production,” Ahmed said.
Using hyperspectral imaging and machine learning, researchers achieved seventy-five percent accuracy in identifying embryo sex at early incubation.
The team also studied egg fertility, shell strength, shell thickness, and yolk ratio.
“Conventional testing methods are destructive; for example, to measure the shell strength, you need to break the eggs. Our primary focus is to develop non-destructive, cost-effective methods,” said Mohammed Kamruzzaman.
The researchers are now working to automate the system for commercial hatcheries.
“We are working on developing a system with a robotic arm that can separate the eggs,” he said.
Their findings show strong potential to improve efficiency, animal welfare, and food safety in the poultry industry.
Photo Credit: gettyimages-chubarovy
Categories: Illinois, Livestock, Poultry