To help farmers detect mite infestations, a team of entomologists, computer scientists, and biologists led by UC Riverside entomologist Amy Murillo has created a new insect detection system. The team’s work is detailed in the journal Scientific Reports.
In recent years, concern for the well-being of livestock has given rise to more farms where poultry are allowed to roam. Though this freedom improves the quality of chickens’ lives, free-range chickens are still subject to insect infestations.
“The trend in egg sales is ‘cage free,’ but that doesn’t necessarily mean the chickens are insect free,” Murillo said.
Of particular concern to scientists is the northern fowl mite, which Murillo said feeds on chicken blood and lives on hens in feathers surrounding “the butt area of the chicken.”
In addition to the economic consequences of infected hens laying fewer eggs, mites can make the chickens sick and cause lesions to develop on their skin.
To devise their detection system, Murillo’s team identified three key chicken pastimes closely linked to chickens’ well-being: pecking, preening, and dustbathing. The team hypothesized they would see a big increase in preening and dustbathing among infected chickens because these activities keep feathers clean.
The team placed motion sensors into tiny backpacks the chickens could wear without discomfort. The next challenge was translating data from these sensors into algorithms that could be detected as behaviors.
In order to train a computer to recognize chicken behaviors, Alireza Abdoli, a doctoral student in computer science at UCR, had to take an unusual approach. He created an algorithm for the computer that considers the shape that the backpack sensor data makes on a graph, as well as features of the data such as mean and max.
“Most algorithms use either shape or features, but not both,” Abdoli said. “Our approach is exciting because it increases the accuracy of the data so much and is key to making good decisions about the chickens’ health.”
Not only does this new approach increase the reliability of scientists’ observations, it also increases the number of animals and length of time they can be tracked.