TTADDA-UAV: A Multi-Season RGB and Multispectral UAV Dataset of Potato Fields Collected in Japan and the Netherlands
What's in it
Background information This collection is the result of multiple studies conducted under the Transition to a Data-Driven Agriculture (TTADDA) project. The TTADDA project aims to boost productivity through a data-centric potato production system that supports circular agricultural practices. Potato phenotyping is crucial for creating high-yielding, resilient, and sustainable potato crops, which are essential in global food systems. To support this goal, a multi-season UAV dataset from five potato trials—three in Japan and two in the Netherlands was collected. Each trial field was divided into small plots, each planted with a specific cultivar to assess varietal performance. Data included UAV based imagery (RGB and multispectral), manual yield and ground coverage measurements, and on-site weather data. The combination of sensor versatility, diverse potato varieties, and varying climate and soil conditions between Japan and the Netherlands makes this dataset highly valuable and potentially reusable for a wide range of applications. Furthermore, the data adheres to the MIAPPE (Minimal Information About Plant Phenotyping Experiment) standard thus ensuring consistency and clear …
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