Sugarbeet disease dataset

This dataset is a re-hosting of the Sugarbeet disease dataset, originally co-created by Anders Krogh Mortensen and hosted by Aarhus University at https://vision.eng.au.dk/sugarbeet-disease-dataset (archived version). We thank Department of Agroecology, Aarhus University for their foundational contribution to this data.

This dataset was collected from mid July to early September 2022 and contains high-resolution RGB images of sugarbeets from four stripe field experiments. Images were collected approximately weekly and geotagged.

A subset of the collected images were annotated pixelwise. For inqueries, please contact Anders Krogh Mortensen.

More details (including data collection, deep learning models and results) can be found in Nordic Beet Research’s Annual Reports:

• NBR annual report 2022 (page 53): https://www.nordicbeet.nu/wp-content/uploads/2023/02/nbr_aarsberetning_2022.pdf
• NBR annual report 2023 (page 54): https://www.nordicbeet.nu/wp-content/uploads/2024/02/nbr_aarsberetning-2023_web.pdf
• NBR annual report 2024 (page 68): https://www.nordicbeet.nu/wp-content/uploads/2025/02/nbr_aarsberetning-2024_web.pdf

Citation

If you use this dataset in your research or elsewhere, please cite/reference the following Nordic Beet Research’s Annual Report (2022):

@inbook{ece8b721f3fe497ba532c7f2ed9b0cfd,

title = “Kamera og kunstig intelligens til vurdering af sygdomstryk i sukkerroer”,

abstract = “Form{\aa}let med fors{\o}get er at unders{\o}ge, om et h{\o}j kvalitets farvekamera sammen med kunstig intelligens kan anvendes til automatisk genkendelse af bladsygdomme i sukkerroer.”,

author = “Mortensen, \{Anders Krogh\} and Hansen, \{Anne Lisbet\} and Ren{\’e} Gislum”,

year = “2023”,

month = jan,

language = “Dansk”,

pages = “53–56”,

booktitle = “Faglig beretning 2022”,

publisher = “NBR Nordic Beet Research Foundation”,

}