Crop Load Vision™

Automated crop load assessment and fruit sizing solution

DescriptionOverview of the initiative and its approach.

Crop Load Vision is a digital solution that supports orchard and vineyard managers in estimating crop load through artificial intelligence–based image analysis. The tool enables producers to assess fruit counts and distribution early in the season, supporting informed thinning, yield forecasting, and harvest planning.

TechnologyTechnology used by the initiative.

  • Mobile app
  • Cloud
  • Artificial intelligence (AI)

Crop Load Vision™ uses mobile computer vision and sensor technology to detect, count, and size fruit in real time, leveraging data analytics and cloud connectivity for instant results and integration with farm management records.

TargetUsers, groups, or communities targeted by the initiative.

  • Large size farms
  • Medium size farms
  • Farm advisors
  • Agriculture cooperatives

Crop Load Vision™ targets fruit growers, farm advisors and cooperatives seeking to digitize crop load assessments and improve decision-making for orchard management and labor allocation.

Business modelHow the initiative delivers and sustains its value.

  • Subscription

Crop Load Vision is offered as a subscription-based digital service . Pricing is linked to access to the AI-powered analysis tools and cloud-based data services, providing ongoing decision support throughout the growing season.

ImpactThe observed or intended effects of the initiative.

Crop Load Vision™ can enable faster, more accurate crop load assessments, reduce labor costs, minimize double-counting errors, and support data-driven decisions for yield optimization and resource allocation in fruit production.

Four BettersThe FAO Four Betters supported by the initiative.

  • Better production
  • Better environment

Sustainable Development GoalsSustainable Development Goals associated with the initiative.

  • SDG 9: Industry, innovation, and infrastructure
  • SDG 12: Responsible consumption and production
For detailed description of each attribute and parameter, check the AgriTech Observatory Taxonomy >

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Source: FAO AgriTech Observatory

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