Public education + dataset contribution
BudGuard
Identify bud rot and common plant diseases early. Contribute labeled healthy or diseased plant photos to improve machine learning research.
Disease Library
Start with the most common visible patterns
Bud Rot
fungal · severe
A high-risk flower disease where dense tissue can brown, collapse, and develop gray fungal growth from the inside out.
- Brown or gray tissue inside dense flowers
- Musty odor or soft collapse
- Gray fuzz in advanced cases
Powdery Mildew
fungal · moderate
White powder-like patches on leaf surfaces that can expand when airflow and humidity conditions favor fungal growth.
- White powdery patches
- Surface-level leaf coating
- Expansion across nearby leaves
Nutrient Deficiency
deficiency · moderate
A label for visible patterns such as yellowing, spotting, weak growth, or interveinal changes that may relate to nutrition or uptake context.
- Yellowing or interveinal chlorosis
- Localized spotting
- Tip or margin stress
Pest Damage
pest · moderate
Visible feeding marks, webbing, residue, leaf distortion, or insects that can be labeled for research and education.
- Stippling, scraping, or bite marks
- Webbing or black fecal dots
- Visible insects or eggs
Heat Stress
environmental · moderate
Environmental stress pattern often linked to hot canopy zones, intense light, leaf edge curl, or rapid room-condition shifts.
- Leaf edges curling upward
- Dry or brittle-looking upper growth
- Stress near hot or bright zones
Overwatering
environmental · moderate
Root-zone stress pattern linked to persistently wet media, weak dry-back, droop, or poor oxygen availability around roots.
- Drooping leaves despite wet media
- Slow growth or weak response
- Yellowing linked to poor root conditions
Contribute to research
Uploader-provided labels, confidence scores, and context fields make future model training and evaluation cleaner from the start.
Healthy photos matter
Healthy examples help models learn what normal tissue looks like across plant stages, lighting, and environments.
Privacy-forward intake
The upload path strips image metadata, never requires precise location, and asks for explicit rights and privacy consent.