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Kvantron Smart Sorter
Vegetable sorting system powered by computer vision
Kvantron Smart Sorter
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Technological Base
Industrial cameras, specialized lighting, computer vision and machine learning algorithms for analyzing each product in the flow.
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What It Analyzes
Quality, size, shape, color, and defect presence for every vegetable in real time.
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Sorting Result
Automatic decision-making for further product routing on processing and packaging lines.
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What tasks does Kvantron Smart Sorter solve?
Sorting of Vegetable Crops
- Potato sorting
- Onion sorting
- Quality control of vegetables before packing
Separation and Rejection
- Dividing products by fractions
- Removal of defective, damaged or contaminated items
- Detection of foreign objects in the flow
Automation & Statistics
- Replacing or reducing manual visual inspection
- Improved batch consistency
- Lower human factor influence
- Quality statistics per batch and shift
Which parameters are controlled by the system
Size and Fraction
Determines product dimensions and assigns to the corresponding size group. For potatoes, it evaluates length, width, diameter. For onions, it assesses size, shape, and conformity to commercial grade.
Shape
Detects shape irregularities: elongated, deformed, damaged, or non-standard objects. Forms a uniform commercial batch and improves packaging quality.
Color & Appearance
Analyzes color and deviations from the standard: greening, darkening, spots, rot, peel damage, speckling, spoilage signs.
Surface Defects
Detects mechanical damage, cuts, cracks, rot, stains, contaminants, sprouts, immature, over-dried, or non-standard objects.
Foreign Bodies
Finds stones, lumps of soil, plant residues, fragments of packaging, and other items that differ from vegetables in shape, color, or texture.
Potato Sorting
Classifies tubers by size, shape, and quality. Monitors mechanical damage, cuts, cracks, green spots, rot, sprouts, and dirt.
Onion Sorting
Controls size, shape, color, skin damage, darkening, stains, rot, sprouts, and contamination. Removes non-standard and spoiled bulbs.
Operating Principle
Vegetables are fed onto a conveyor or inspection table and pass through the control zone. In this zone, industrial cameras and lighting matched to the specific product and line conditions are installed.
Processing Stages
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Image Acquisition
Cameras capture products in the flow at the required frequency and resolution.
01. -
Object Segmentation
Algorithms separate vegetables from the background, determine contours and position of each object.
02. -
Parameter Measurement
The system calculates size, shape, area, color characteristics, and other features.
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Defect Detection
Software analyzes the product surface and detects deviations from the norm.
04. -
Classification
Each object receives a category: good product, non-standard, defect, foreign item, or assigned fraction.
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Signal to Actuator
If necessary, the system sends a command to the rejector, air valve, pneumatic actuator, diverter, or other sorting mechanism.
06. -
Statistics Collection
All results are recorded in the system: number of checked objects, defect rate, category distribution, and batch quality dynamics.
07.
Platform Features
- set sorting rules for each product;
- create various recipes for potato, onion, and other crops;
- set size, color, and defect thresholds;
- control camera and lighting operation;
- operate actuators;
- display real-time quality statistics;
- store images of defective objects;
- generate reports for batches and shifts;
- integrate with external enterprise systems.
Complex Implementation Options
The system is engineered for your specific processing line and can be adapted for various product feed schemes.
- inspection module above conveyor;
- control system for roller or belt conveyors;
- sorting module with pneumatic rejector;
- system for product distribution into multiple channels;
- complex with several cameras for multi-side inspection;
- solution with extra lighting for complex surfaces;
- control cabinet with industrial PC and operator interface.
System Advantages
Reduced Manual Labor
Automatic control reduces dependence on manual sorting operators and increases result consistency.
Stable Batch Quality
The system applies the same evaluation criteria to all flow objects.
Real-Time Operation
The solution analyzes products directly on the line and instantly commands sorting or rejection.
Flexible Product Settings
Separate control recipes can be used for different crops, varieties, sizes, and customer requirements.
Control of Multiple Features
Size, shape, color, surface defects, and foreign objects are analyzed in one processing cycle.
Statistics & Quality Traceability
The company receives objective data on batch quality, defect dynamics, and technological process efficiency.
What Companies Gain
Implementing a vegetable sorting system enables:
- higher finished product quality;
- lower defect rates in packaging;
- reduced manual sorting costs;
- faster identification of raw material or process problems;
- product division by commercial categories;
- increased line productivity;
- digital quality statistics for each batch.
Which companies benefit from the system
Vegetable Processing Plants
Potato Producers & Suppliers
Onion Producers & Suppliers
Packing Lines
Agroholdings
Warehouse & Sorting Complexes
Food Industry Enterprises
Raw Prep Lines Before Processing
Tailored Setup for Your Needs
Each crop has unique features: shape, color, contamination, moisture, movement speed, feeding method, sorting requirements. The Kvantron Smart Sorter is customized for each object and product.
At implementation, define:
- list of controlled defects;
- fraction requirements;
- line speed;
- product feeding scheme;
- type of cameras & lighting;
- rejection method;
- report format;
- integration requirements with customer equipment.
Service & Support
Need help? Contact us in any convenient way.
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+7 (4912) 72-22-701.
Call
Support specialists are available around the clock and are ready to help with any questions.
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2.
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