AI Vision + MAP: The Smart Dual Engines of Fresh-Cut Fruit Production Lines, Reshaping Supply Chain Efficiency

In the fresh-cut fruit industry, preserving quality and improving efficiency are perpetual challenges. When modified atmosphere packaging (MAP) technology meets AI visual recognition for SKU identification, a "smart revolution" from production line to supply chain is quietly underway—enabling accurate identification, automatic labeling, and end-to-end traceability. This not only locks in freshness but also ensures full supply chain control. In this article, Desigco briefly introduces the fruit-cut visual recognition system.

AI Vision Empowers Fresh-Cut Fruit Production: From “Manual Labor” to “Machine-Second Decisions”

With the explosive growth of instant retail, changing consumer demands have created new opportunities. Increasing health awareness has driven the trend of “snackification” of fruits, significantly boosting their penetration in daily diets. Fruits have become nutrient-supplementing snacks and “weight-loss tools,” enriching consumption scenarios and increasing purchase frequency. Fresh-cut fruit products meet consumers’ demands for convenience and variety in new contexts, gradually replacing the traditional model of queuing at fruit stores to buy, wash, and cut fruits by weight.

In modern fresh food factories, fresh-cut fruit preservation packaging has become a primary product to adapt to these consumption habits. However, as demand diversifies and products multiply, it is impractical to dedicate a separate production line for each SKU. Multiple products must be processed on the same line. Yet, in current fresh-cut production, SKU label management relies on manual checks, which are error-prone and cause continuous losses. Visual identification requires workers to closely inspect packaging boxes and quickly distinguish fruit types—a daunting challenge on high-volume production lines with visually similar products.

AI-Powered Visual Recognition System

To address this, visual recognition systems have emerged as a timely solution. Using high-precision cameras and deep learning algorithms, the system scans fresh-cut fruit products on the production line in real time, automatically identifies the product type, and transmits the information to the labeling system to match the corresponding SKU label. Equipped with high-resolution industrial cameras and multi-angle lighting, the system clearly captures the shape, color, and texture of fruit cuts through the packaging film:

- Distinguishes similar fruit pieces (similar colors/shapes)

- Identifies mixed fruit packs (single, double, or triple combinations)

- Detects defects (discoloration, mold, etc.)

System-Wide Integration for Proactive Control

The visual recognition system is positioned at the exit end of the MAP machine and the front end of the automatic labeling machine, forming a closed-loop workflow:
MAP completion → Visual recognition (category) → Data transmission to labeling system → Accurate printing and application

After front-end MAP (low-oxygen 3% O ₂ + high-nitrogen 90% N ₂ environment to inhibit ethylene release and extend shelf life to 15 days) and temperature control, the AI vision SKU data acts like a "command code," directly driving the downstream labeling system to achieve fully automated operation. Factories can also produce fruit cuts for different sales channels on the same line, adapting to rapidly changing market demands through product visual recognition and autonomous label switching. Desigco recommends the AI visual recognition system for the following reasons:

1 ️⃣ Improves Production Accuracy and Efficiency: Millisecond-level recognition speed matches high-speed production lines, significantly reducing errors and mix-ups, ensuring products proceed correctly.

two ️⃣Ensures 100percent Label Accuracy: Eliminates label errors due misidentification, safeguarding food safety compliance, consumer trust, and brand reputation. Accurate pricing labels also prevent sales losses or disputes.

3 ️⃣ Reduces Labor Dependency and Costs: Significantly cuts manual input in cutting and verification stages, lowering labor costs and costs associated with rework, scrap, and customer complaints caused human error.

four ️⃣Enhances Automation and Intelligence: Achieves end-to-end automation and smart closed-loop management from packaging, recognition, weighing, labeling to sorting.

five ️⃣Strengthens End-to-End Traceability: Accurate SKU identification ensures digital traceability from cutting and packaging to distribution, providing a solid foundation for quality control and batch management.