Capabilities

• External defect detection — identification of discoloration, damage, deformation, or spoilage on product surfaces;

• Foreign material detection — spotting bones, shells, plastic, or metal fragments in raw or processed foods;

• Internal quality analysis — evaluation of bread porosity, uniform filling distribution, presence of mold, or cooking degree;

• Dimensional control — measurement of product size, shape, and volume for grading;

• Digital reporting and MES/ERP integration — instant transmission of inspection results for analytics and corrective actions.

Implementation Example

Mobile Synetra Iris platform for vegetable quality inspection in greenhouses.

What the system does

• Analyzes size, shape, color, and ripeness of crops on the plant;

• Detects defects such as cracks, rot, and spotting;

• Assesses maturity for harvest prediction;

• Generates a quality heat map of yield.

Result

• 95% removal of underripe and defective produce before harvest;

• Harvest efficiency increased by up to 40%;

• Manual sorting labor reduced by 3–4 workers per shift;

• Retail compliance rate — up to 98%.

Capabilities

• Quality-based sorting — separating defective from market-grade products;

• Size and weight classification — automatic distribution into categories and calibers;

• Color and ripeness analysis — grading fruits, vegetables, nuts, or roasted goods by appearance;

• High-speed rejection — pneumatic or mechanical diverters remove defective units instantly;

• Flexible configuration — quick criteria changes for different batches.

Implementation Example

Synetra LineScan on a potato processing line.

What the system does

• Measures size, shape, color, and density of tubers;

• Detects rot, green spots, cracks, and mechanical damage;

• Sorts potatoes into categories and directs them into bins.

Result

• 100% elimination of sorting errors;

• Sorting accuracy up to 96%;

• Waste reduction — 30% less usable product discarded;

• Labor savings — minus 4 operators per shift.

Capabilities

• Fill-level and sealing verification — detection of underfilling, leaks, or faulty seals;

• Quantity tracking — automated counting of items per package or batch, eliminating manual tally errors;

• Serialization and labeling — barcode and DataMatrix scanning for each item;

• Aggregation — linking individual units to cases or pallets;

• MES/ERP integration — real-time data transfer for warehouse and shipment tracking.

Implementation Example

Synetra PackTrack for dry food packaging lines.

What the system does

• Monitors packaging integrity and label presence;

• Reads QR/DataMatrix and stores batch data;

• Weighs products for underfill detection.

Result

• 100% inventory accuracy;

• 95% elimination of labeling and mispack errors;

• Automation replaced 3 quality controllers per shift.

Capabilities

• PPE detection — verifying gloves, masks, coats, and caps on personnel;

• Equipment cleanliness monitoring — spotting residue or contamination on conveyors, blades, or packaging surfaces;

• Compliance of equipment design — IP67/IP69K camera housings for wet cleaning and harsh environments;

• Workplace safety monitoring — detecting unauthorized access, spills, smoke, or fire;

• Audit documentation — automated photo and video records for HACCP, ISO 22000, and external audits.

Implementation Example

Synetra Iris for hygiene control in food factories.

What the system does

• Monitors PPE compliance at sanitary gates;

• Detects hygiene procedure violations;

• Records data for internal and external audits.

Result

• Sanitation violations reduced by 90%;

• PPE compliance monitoring fully automated;

• Incident response time under 2 seconds.

Capabilities

• Date and expiration check — reading and validating printed or laser-engraved markings;

• Format and content verification — ensuring codes and dates match production orders;

• 2D code scanning (DataMatrix, QR) — ISO/IEC-compliant grading of print quality;

• Serialization — assigning unique IDs to products with regulatory reporting;

• Aggregation — linking group packaging codes with included items.

Implementation Example

Synetra Iris on a meat product labeling line.

What the system does

• Reads barcodes, DataMatrix, production date, and expiration date;

• Matches data against production orders;

• Captures inspection photo records for traceability.

Result

• 100% elimination of date and code errors;

• Complaints from distributors reduced 6x;

• Simplified audits and recall handling.

Advantages of Implementing Machine Vision in Agro-Processing

• Enhanced product quality and safety;

• Lower defect and waste levels across the supply chain;

• Automated control, sorting, and reporting;

• Full traceability from raw materials to packaged goods.

Why Choose Us

• Proprietary image processing algorithms for food applications;

• AI-powered recognition of defects, labels, and codes;

• Seamless integration with packaging, sorting, and ERP systems;

• 24/7 technical support from deployment to operation.