Vineyard Imaging & Phenology AI Study
Commercial grape growers still make critical spray, thinning, and harvest calls by subjective eye. We pair consistent row-by-row smartphone camera surveys with manual physiological ground truth across Thompson Seedless vines at our private testbed in Sindagi taluk, Vijayapura district.
High-value crops require objective spatial data
In table grapes and raisins, income swings dramatically based on bunch uniformity, disease outbreak timing, and the final fresh-to-raisin drying ratio.
Canopy & Berry Uniformity
Did the growth regulator doses work evenly across vineyard rows? Conventional sampling checks 2-3 vines. Smartphone cart video surveys can record every vine canopy on both sides.
Early Downy & Powdery Mildew
Mildew spreads invisibly until whole sectors are damaged. High-resolution camera imagery flags subtle leaf spotting and sporulation before farm-wide canopy collapse.
Brix Curve & Raisin Grade
Sugar develops unevenly within a vineyard block. Linking individual row imagery with refractometer Brix and raisin recovery percentages optimizes selective harvest timing.
51-Row Vineyard Block Explorer
Simulate data collection across the 51 numbered rows at our Sindagi taluk test vineyard. Move the slider to inspect canopy density, berry sizing, Brix sugar projection, and disease risk metrics.
Row Survey: Row 18 of 51
Camera Cart SurveyedFour-Phase Field Study Protocol
A structured, multi-season scientific campaign conducted at our Thompson Seedless vineyard in Sindagi taluk, Vijayapura district.
Bud Break, Shoot Architecture & Berry Sizing
Reference vines tagged across the plot. A lightweight push cart equipped with mounted smartphone cameras traverses rows weekly, capturing vines from both canopy flanks alongside manual vernier caliper measurements.
Veraison (Colour Change) & Sugar Accumulation
Survey frequency increases to 2 passes per week. Hand refractometer Brix measurements taken on marked bunches across micro-zones, tracking sugar accumulation curves against visual bunch color.
Row-by-Row Harvest & Fresh Weight Logging
Total harvested fruit weighed per row to evaluate early-season canopy coverage and bunch count estimates directly against final row biomass.
Drying Yard Recovery & Raisin Grading
Bunches tracked through the drying shed to log fresh-to-raisin conversion ratios and grade final color and size against in-season vision data.
Student Fellowship & Faculty Collaboration
We recruit 2nd and 3rd year horticulture and engineering students, providing hands-on AI field research experience, bus transit coverage, and formal credit.
For Students
- • Role: Operate the smartphone imaging cart, record physiological measurements on tagged vines, maintain structured field logs.
- • Time Commitment: Weekly visits Oct-Dec; 1-2 visits per week Jan-March (scheduled flexibly around college exam timetables).
- • Benefits: Local bus transit reimbursement, hands-on exposure to precision AI, formal certificate, and recommendation letter from Arun Patil.
For Faculty Advisors
- • Advisory Scope: Guidance on physiological indicators, growth regulator trials, and validation methodology.
- • Field Access: The test vineyard serves as an open outdoor laboratory for student capstone projects and observational studies.
- • Attribution: Student and faculty contributors receive formal credit on resulting dataset releases and agronomic benchmark reports.