Non-invasive image-based method for mass estimation of caterpillars of Lepidoptera

Live biomass is a key metric for monitoring insect development and survival, especially of larval species of Lepidoptera. Nonetheless, manual weighing is labor-intensive, can induce stress, and may introduce experimental bias. Here, we present a non-invasive, open-source ImageJ macro that enables repeated measurements of caterpillar silhouette area using computer vision tools. We validated this approach using larvae of five different lepidopteran species and found a strong correlation between the silhouette area and live biomass. The macro achieved high detection accuracy (∼98%) and was approximately six times faster than manual weighing. This approach can potentially allow for continuous monitoring of larval biomass while reducing handling and associated stress, providing a practical tool for experimental studies of Lepidoptera.