EarthSense is creating dramatic new possibilities for crop breeders, plant health products developers, crop scientists, and field agronomists.
Our first robot—TerraSentia—improves the quantity, accuracy, cost and speed of in-field plant trait data collection, especially for under-canopy traits that cannot be obtained by other technologies.
Our machine vision and machine learning based analytics seamlessly convert field data to specific, actionable information about plant-traits.
Following our successful 2019 field season, we have improved TerraSentia hardware, software, and analytics based on these pioneering users' experience.
TerraSentia uses a variety of sensors—including visual cameras, LIDAR and other on-board sensors—to autonomously collect data on traits for plant health, physiology, and stress response.
TerraSentia’s unique dataset delivers high-value under-canopy plant traits including stand-count, stem width, plant height, LAI, etc.
We have deployed TerraSentia in corn, soybean, wheat, sorghum, vegetable crops, orchards, and vineyards.
We've developed a cloud-based platform that will let you easily teach TerraSentia to automatically measure a variety of key traits.
In 2019, we have worked with leading private- and public-sector organizations to accurately detect and quantify high-value traits in corn, soybean, wheat, sorghum, etc.
We are now teaching TerraSentia to measure early vigor, corn ear height, soybean pods, plant biomass, and to detect and identify diseases and abiotic stresses.