Datasets › EarlyNSD

EarlyNSD (Early Nutrient Stress Detection of Plants)

6 Aug 2024 archive 2025-07-28

Early detection of plant nutritional deficiencies, followed by corrective actions, is essential for sustaining crop yield. However, identifying these early signs in plant leaves remains challenging, even with computer-aided diagnostic tools, due to their often subtle nature. To address this, we introduce a public dataset focused on three cucurbits: ash gourd, bitter gourd, and snake gourd. We chose to focus on these cucurbits due to their significant impact on global vegetable production. The dataset includes 2,700 segmented and augmented leaf images, capturing early indicators of nitrogen and potassium deficiencies alongside a healthy control group. This dataset, to the best of our knowledge, is the first to specifically target the critical early stage of nutritional stress in plants.

Benchmarks archive 2025-07-28

All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

First row (archive order)PaperCode
Image Classification EarlyNSD DenseNet121_256x256_Nutrispace Test accuracy 0.9062 Nutrispace: A novel color space to enhance deep learning... — 3 Compare

Papers archive 2025-07-28

1 shown of 1 paper with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 1. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

ATTRIBUTION 4.0 INTERNATIONAL

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • EarlyNSD

1 variant name, as the archive lists them.

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