ArticleScientific data2023
Hyperspectral images of grapevine leaves including healthy leaves and leaves with biotic and abiotic symptoms.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
5 citing papers in PubMed.
- Monitoring Water Stress in Grapevine (Plants (Basel, Switzerland) · 2026Article
- A dataset for vineyard disease detection via multispectral imaging.Data in brief · 2025Article
- A multi-spectral and hyperspectral image dataset for evaluating chemical traits and the water status of avocado, olive and grape through leaf dehydration under laboratory conditions.Scientific reports · 2025Article
- A CARS-SPA-GA Feature Wavelength Selection Method Based on Hyperspectral Imaging with Potato Leaf Disease Classification.Sensors (Basel, Switzerland) · 2024Article
- Hyperspectral images of grapevine leaves including healthy leaves and leaves with biotic and abiotic symptoms.Scientific data · 2023Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A hyperspectral imaging database was collected on two hundred and five grape plant leaves. Leaves were measured with a hyperspectral camera in the visible/near infrared spectral range under controlled conditions. This dataset contains hyperspectral acquisition of grape leaves of seven different varieties. For each variety, acquisitions were performed on healthy leaves and leaves with foliar symptoms caused by different grapevine diseases showing clear symptoms of biotic or abiotic stress on other organs. For each leaf, chemical measurements such as chlorophyll and flavonol contents were also performed.
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Registered trials
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