VineSignal improves the efficiency and sustainability of vineyard management by providing advanced, actionable insights into vine and soil health.

About

Deep Planet has developed scalable and cost-effective precision agriculture tools for vineyards and farms. Our tools leverage satellite imagery and machine learning to provide comprehensive vineyard management support, quantify soil organic carbon, biodiversity and improve sustainability of farming practices. We are supported by ESA, H2020 and Innovate UK.

Key Benefits

VineSignal’s actionable insights create value for growers, producers, retailers and industry bodies by enabling them to frequently and cost-effectively measure and monitor crop and soil health, support the adoption of regenerative practices and improve farm management decisions.


Growers and producers

  • Improve management efficiency and sustainability through decision support insights
  • Reduce inputs, e.g., irrigation water use, fertiliser and pesticide inputs
  • Reduce input costs
  • Optimise crop health and productivity
  • Improve soil health


Retailers

  • Decarbonise supply chains through carbon insetting
  • Measure and report on regenerative practices
  • Measure GHG (greenhouse gas) emissions
  • Generate carbon credits from carbon insetting initiatives
  • Obtain carbon neutral certification


Industry bodies

  • Monitor crop and soil health at scale
  • Report on historical changes and regional dynamics


Applications

Deep Planet’s VineSignal platform provides predictive insights to growers, producers, industry associations and retailers to support efficient and sustainable vineyard management decisions. VineSignal uses data from satellite imagery, sensors, weather stations, crop agronomy and historical data, and advanced machine learning models to help optimise harvest logistics, improve quality and consistency, reduce inputs, improve soil health and support sustainability initiatives. The platform focuses on four key areas:


Soil health and sustainability: soil organic carbon and nutrients (NPK) monitoring.

  • Understand the spatial variation in soil organic carbon (SOC) and nutrients (NPK) at farm and regional levels to optimise compost and fertiliser application.
  • Baseline, measure and monitor changes in SOC and nutrients availability to measure the effects of different farming practices.
  • Report on historical changes in SOC and nutrients.
  • Generate carbon credits from carbon insetting and regenerative farming initiatives.
  • Obtain carbon neutral certification by verifying improvements in the amount of soil carbon.


Vineyard health: disease and anomaly detection, vine vigour monitoring.

  • Optimise and reduce pesticide application through accurate predictions of disease probability.
  • Identify disease hotspots through historical disease occurrence maps.
  • Target pesticide application through disease variability maps.
  • Optimise vineyard management decisions by understanding the variability in vine health and vigour.


Irrigation and water management: soil moisture interpolation, evapotranspiration monitoring.

  • Optimise and reduce irrigation water inputs by understanding the variation in soil moisture across the farm and to a depth of 1.5 metres. 
  • Support irrigation decision-making with maps visualising evapotranspiration, i.e., the loss of water through plants and soil.


Harvest logistics: harvest date and yield prediction, maturity maps.

  • Optimise harvest costs by accurately planning harvest dates, e.g. labour and machinery planning, transport logistics.
  • Efficiently schedule/reschedule during harvest in response to environmental changes with regular updates on predicted harvest dates.
  • Support accurate coordination and transparency between wineries and growers, avoiding reworking costs.
  • Identify locations for maturity sampling to achieve accurate representation of the variation in maturity. 
  • Identify grapes for quality upgrade and downgrade opportunities.
  • Identify areas of the vineyard for selective harvesting opportunities.


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