Orchid Photo & Metadata Management

Prompt 1 – Multi-criteria Filtering

Build functionality to filter and display orchids by any combination of metadata fields, including:
    •    Photographer / submitter ID
    •    Geographic region (country, province, GPS coordinate range)
    •    Elevation range
    •    Date / month of bloom
    •    Genus / species / hybrid
    •    Color (AI-extracted)
    •    Pollinator (if known)
    •    Growth habit (epiphytic, terrestrial, lithophytic)
    •    Mycorrhizal associations
The gallery view should update in real time as filters are applied.

Prompt 2 – Gallery Organization

Add views to organize plants and photos:
    •    All orchids submitted by a specific member
    •    All orchids photographed in a specific month or year
    •    All orchids native to a country (e.g., “Thailand”)
    •    All orchids with a specific flower color (e.g., “white”)
    •    Saved combinations of filters (e.g., “Madagascar + white flowers + night-blooming”).

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🧬 Correlation & Analysis

Prompt 3 – AI Correlation Discovery

Implement AI routines that scan metadata to suggest interesting correlations.
Example outputs:
    •    “Many orchids in Ecuador bloom in November at elevations >1500m.”
    •    “Night-blooming orchids from Madagascar tend to have white flowers and hawkmoth pollinators.”
    •    “Sarcochilus hybrids inherit petal symmetry from Parent A and lip pattern from Parent B.”

Prompt 4 – Hybrid Trait Analysis

Enable photo + tag input for hybrids. AI should:
    •    Parse parentage from the tag.
    •    Retrieve metadata on each parent species (color, size, bloom time, habitat, etc.).
    •    Compare offspring photo against parent traits.
    •    Generate a trait inheritance analysis (which features are from Parent A, which from Parent B, which are new).

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🗺️ Mapping & Conservation

Prompt 5 – Orchid Mapping

Integrate photo metadata with maps. Provide functions to:
    •    Display orchid distributions by country, region, or elevation band.
    •    Overlay bloom times to create seasonal maps.
    •    Show historical bloom records by date/location to track flowering shifts.
    •    Export maps for conservation use.

Prompt 6 – Phenology Tracking

When photo metadata includes date + location, record flowering events.
    •    Allow users to query: “Show orchids in flower in Ecuador in May 2022.”
    •    Enable conservation reports showing shifts in bloom timing over years.

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🔬 Research Integration

Prompt 7 – Mycorrhizal & Pollinator Data

Link orchid entries to associated databases on pollinators and mycorrhizal fungi.
    •    Allow queries like: “Show orchids associated with Rhizoctonia fungi in South America.”
    •    Cross-reference pollination syndromes with color/elevation data.

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⚡ With these, Famous AI has clear deliverables for every aspect:
    1.    Metadata filtering & gallery
    2.    Correlation discovery
    3.    Hybrid trait analysis
    4.    Mapping & phenology tracking
    5.    Pollinator & mycorrhizal associations
