QUALYfruit: AI and computer vision for precision agriculture

From data to decisions: Artificial Intelligence that optimizes field yield, improves product quality, and promotes more sustainable agriculture.

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The challenges of the agricultural sector

Climate change, sustainability, and productivity impose new challenges on agriculture. Traditional tools are no longer enough: data and automation are needed. Thanks to computer vision and AI, it is now possible to monitor quality, reduce waste, and optimize the entire production process for more efficient and sustainable agriculture.

Impact of climate changeon crop yield

Extreme weather events, rising temperatures, and drought are altering crop growth conditions, compromising agricultural production stability. To tackle these challenges, it is essential to monitor plant development and promptly adapt agronomic strategies.

What can AI do?

Accurately estimates field yield, providing objective data for agricultural management and the insurance sector.

Monitors plant and fruit growth, enabling targeted interventions to improve quality and optimize harvesting.

Greater sustainabilityand resource optimization

Inefficient use of water, fertilizers, and pesticides increases costs and environmental impact. Reducing waste and optimizing resource use is now essential for ensuring the economic and environmental sustainability of the agricultural supply chain.

What can AI do?

Optimizes the distribution of water and fertilizers, adapting to the specific needs of each plant to reduce waste and costs.

Detects plant diseases early, allowing targeted interventions only in affected areas, reducing chemical usage.

Quality control: the key factor for competitiveness

The market demands higher quality standards and strict supply chain traceability. Identifying defects and issues in crops early ensures better products, reduces waste, and optimizes selection and processing.

What can AI do?

Analyzes images of fruits and plants, automating the detection of defects, damage, and diseases with precision.

Supports production planning, allowing wineries and suppliers to organize in advance to meet production needs.

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Our solution: AI for precision agriculture

Orobix has developed QUALYfruit, an Artificial Intelligence system for managing agricultural production, designed to optimize productivity, product quality, and process sustainability. QUALYfruit is a Decision Support System (DSS) specifically designed for the viticulture and fruit-growing sectors. The platform collects, analyzes, and interprets data to help farmers make informed decisions. It uses computer vision to analyze images of fruits and plants taken in the field, on agricultural vehicles, or during sorting and processing.

AI platform

Quality analysis

AI analyzes grape images to detect damages or defects that could compromise wine quality. All collected data is transformed into georeferenced maps to highlight critical areas and optimize interventions.

Automated quality control

Greater precision in grape selection

Disease monitoring

The system detects diseases like downy mildew or powdery mildew early, enabling targeted treatments and reducing pesticide use.

Early disease diagnosis

Reduction of chemical treatments

Yield estimation and production management

AI analyzes grape clusters to accurately estimate production volume, supporting more efficient harvest management.

Accurate yield predictions

Optimization of the production process

Grapes, apples, and all types of agricultural products

QUALYfruit was originally developed for the viticulture sector but can be used to analyze any type of fruit or vegetable. Specifically for apples, it can be used for:

  • quality analysis during intake;
  • detection of contaminants during sorting;
  • color analysis to determine ripeness classification;
  • leaf defect analysis to identify potential diseases;
  • generation of georeferenced maps for targeted intervention planning.

Why Adopt AI in Agriculture?

AI is transforming agriculture, making it more efficient and sustainable

Faster, data-driven decisions

Real-time analysis for targeted actions

Better quality and waste reduction

More precise selection, less waste

Optimized resource use

Targeted irrigation and treatments

Greater market competitiveness

Increases crop value and reduces production costs

Learn more:

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