computer-vision
Computer vision is the computational technology that automatically extracts meaningful information from digital images through analysis and interpretation. In plant science, it enables researchers to rapidly monitor and measure plant characteristics—including growth, disease symptoms, and morphological traits—at scales impractical with manual observation. This capability accelerates breeding programs, improves crop management, and facilitates large-scale phenotyping and ecological research.
open_in_new WikipediaPubMed · 2026-05-21
Researchers built a large, labeled dataset of kiwifruit vine photos and GPS-tagged videos to train computers to automatically track which growth stage each plant is in — from dormant bud through fruit set — replacing slow, expensive manual scouting across orchards.
The dataset contains 1,665 annotated images covering phenological stages from bud break through fruit set, organized by plant structure, gender, and growth stage.
A custom 17-class growth-stage system was developed by adapting the standard BBCH scale — merging visually similar stages and removing categories that were too ambiguous to label reliably.
Georeferenced (GPS-tagged) videos with manual ground-truth maps were included specifically to validate automated counting algorithms at the spatial level, not just image recognition accuracy.
