In-field high throughput grapevine phenotyping with a consumer-grade depth camera
This addresses the manually intensive and time-consuming process of plant phenotyping for crop management, though it appears incremental as it applies existing depth camera technology to a specific agricultural task.
The paper tackled automated grapevine phenotyping by developing methods for canopy volume estimation and bunch detection and counting, demonstrating that these measurements can be effectively performed in the field using a consumer-grade depth camera mounted on an agricultural vehicle.
Plant phenotyping, that is, the quantitative assessment of plant traits including growth, morphology, physiology, and yield, is a critical aspect towards efficient and effective crop management. Currently, plant phenotyping is a manually intensive and time consuming process, which involves human operators making measurements in the field, based on visual estimates or using hand-held devices. In this work, methods for automated grapevine phenotyping are developed, aiming to canopy volume estimation and bunch detection and counting. It is demonstrated that both measurements can be effectively performed in the field using a consumer-grade depth camera mounted onboard an agricultural vehicle.