By Somesh Utkar
Fall armyworm infestations do not move slowly. Once they take hold, these infestations spread across districts within weeks, cutting through staple crops that millions of families depend on.
The damage is rarely gradual. Fields that appeared healthy days earlier can show visible signs of stress before farmers understand the cause. By the time an infestation is confirmed, losses are already underway. For smallholder farmers facing these infestations, time is of the essence.
Most smallholder farms operate with narrow margins and have limited access to technical support. A delayed response to threats can mean higher input costs, reduced yields, and direct income loss. In regions where small-scale agriculture sustains both livelihoods and local food supplies, a localized fall armyworm outbreak can quickly become a broader risk to the community.
Traditional pest infestation monitoring depends largely on manual scouting, which often means delayed alerts. Outbreaks often expand faster than information about them can move. This is where artificial intelligence (AI) in agriculture, combined with satellite data, offers an advantage to smallholder farmers.
By analyzing crop conditions across large areas, AI systems can detect early warning signals that are difficult to see from the ground. These are just some of the lessons gleaned from Omdena’s applied AI farming project, which involved satellite-based detection of fall armyworm across regions of Africa.
Click here to see more...