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Soybean is one of the ten greatest crops in the world, answering forbillion-dollar businesses every year. This crop suffers from insect herbivorythat costs millions from producers. Hence, constant monitoring of the cropfoliar damage is necessary to guide the application of insecticides. However,current methods to measure foliar damage are expensive and dependent onlaboratory facilities, in some cases, depending on complex devices. To copewith these shortcomings, we introduce an image processing methodology tomeasure the foliar damage in soybean leaves. We developed a non-destructiveimaging method based on two techniques, Otsu segmentation and Bezier curves, toestimate the foliar loss in leaves with or without border damage. Weinstantiate our methodology in a mobile application named BioLeaf, which isfreely distributed for smartphone users. We experimented with real-world leavescollected from a soybean crop in Brazil. Our results demonstrated that BioLeafachieves foliar damage quantification with precision comparable to that ofhuman specialists. With these results, our proposal might assist soybeanproducers, reducing the time to measure foliar damage, reducing analyticalcosts, and defining a commodity application that is applicable not only to soy,but also to different crops such as cotton, bean, potato, coffee, andvegetables.

BioLeaf: a professional mobile application to measure foliar damage caused by insect herbivory