In a groundbreaking approach to tackling one of the tree fruit industry’s most elusive threats, researchers at Washington State University (WSU) are training dogs to detect Little Cherry Disease (LCD) — a devastating virus that compromises cherry crops and causes significant financial losses for growers.
The two-year study is aimed at developing faster and more accurate detection methods to identify LCD early in its spread. Unlike traditional laboratory testing, which can take a full day to analyze a single tree and often struggles to detect low pathogen levels, trained canines are proving to be remarkably efficient at spotting infections in their early stages.
Little Cherry Disease is notoriously difficult to identify due to its latent symptoms, which typically only become visible at harvest time. Infected trees produce undersized, sour, and unmarketable fruit, making early detection essential for orchard management. The virus can spread quickly through infected plant materials, grafting, or by pests such as mealybugs and leafhoppers — often leaving growers with no option but to remove and replace entire trees, a process that’s both costly and time-consuming.
As part of the research initiative, two detection dogs — Humma and Aika — were trained using scent-based identification techniques. Their trainer, an experienced handler from Idaho, utilized positive reinforcement and a game-like reward system to help the dogs learn to recognize the unique scent of LCD-infected trees. In preliminary testing, the canine duo demonstrated a combined detection accuracy of 99.72%, offering a compelling alternative to conventional diagnostic tools.
The project is supported by agricultural partners focused on innovation in fruit production and nursery practices. Researchers are now exploring the next phase of the study, including whether the dogs can accurately detect the disease in dormant trees and nursery environments — a key step toward scaling the method for commercial use.
According to the WSU research team, the long-term goal is to create a reliable, science-backed detection system that growers can deploy across the region. If successful, this dog-assisted approach could revolutionize how LCD is managed and pave the way for broader use of scent detection in agriculture.
