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    Field Trial

    Early Mildew Detection in Nashik Grape Vineyards

    How multispectral imaging and AI crop-health models flagged downy mildew stress days before visual symptoms across a 12-acre vineyard.

    Dindori, Nashik, MaharashtraGrapes (Thompson Seedless)18 June 2026

    9 days

    earlier detection vs. visual scouting

    41%

    reduction in blanket-spray passes

    100%

    canopy coverage per scan cycle

    ~3 hrs

    from flight to row-level advisory

    The Challenge

    The problem on the ground

    Downy mildew is the single largest threat to Nashik's grape economy. Once canopy symptoms become visible to the human eye, growers face an impossible choice: blanket-spray the entire vineyard and risk residue limits on export-bound fruit, or delay and accept bunch losses that can exceed a quarter of the harvest.

    The cooperating 12-acre estate near Dindori relied on weekly manual scouting across 9,000 vines. Scouting covered only a fraction of the canopy, and two recent seasons had seen infections spread for over a week before first detection.

    Our Approach

    What we deployed

    AnaVruksha deployed its Farm Doctor crop-intelligence stack on a weekly drone-scanning schedule. Multispectral imagery captured canopy reflectance signatures associated with early infection stress, and on-farm edge processing scored every vine row for anomaly within hours of each flight.

    When anomaly scores crossed the alert threshold, agronomists received row-level maps pinpointing suspected infection pockets, with plain-language advisories delivered through the Farmer Companion app. Suspected zones were then verified by targeted manual inspection before any spray decision.

    Technology Used

    Multispectral ImagingDeep LearningEdge ProcessingFarmer Companion App

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