97% Accuracy + 80% Cost Cut! Intelligent Grading Solves Agri-Food Sorting Woes

Labor shortages during peak seasons, inconsistent manual grading standards, high losses due to unidentifiable hidden defects, and soaring processing costs squeezing profits... These sorting pain points are restricting the large-scale development of agricultural product (fruits, nuts, vegetables) and food processing enterprises. As the market's demand for product quality standardization upgrades, traditional grading models are no longer compatible. An efficient, accurate, and intelligent automatic grading solution has become the key for enterprises to break through development bottlenecks.

4 Core Pain Points of Traditional Grading Models—Are You Experiencing Them?

Most processing enterprises rely on manual labor or traditional simple equipment for grading, with prominent core pain points:

• Low Efficiency & High Costs: "Hard to recruit workers" during peak seasons for manual sorting, with a per capita daily processing capacity of only 0.5-1 ton; traditional equipment performs single-dimensional grading (e.g., size only), with a processing capacity of less than 3 tons per hour. Labor + operation and maintenance costs account for over 60% of total processing costs.
• Poor Grading Accuracy & Unstable Quality: Subjective deviations exist in manual visual judgment; hidden indicators such as sugar content and internal lesions cannot be identified, with an accuracy rate of only 60%-70%. Traditional equipment lacks intelligent detection modules, prone to mis-sorting and missed sorting, affecting brand reputation.
• High Losses & Profit Drain: Unidentifiable defective products entering the market lead to a return rate of 15%-20%; defective products can also contaminate entire batches of goods. For the fruit processing industry alone, the annual grading loss rate exceeds 10%.
• No Traceability & High Compliance Risks: Traditional models lack data recording, making it difficult to achieve full-process quality traceability and failing to meet strict food quality supervision requirements.

Core Breakthrough: Intelligent Automatic Grading System Restructures the Value of Grading Links

Compared with traditional models, our automatic grading system relies on core technologies such as AI visual recognition and optical detection, realizing a leap from "experience-based judgment" to "data-driven decision-making". It forms core advantages in four dimensions: efficiency, accuracy, cost, and compliance:

1. Efficiency Multiplication: 1 Hour Equals 7 Workers’ 1 Day of Work—No More Anxiety During Peak Seasons

• Leap in Processing Efficiency: A single line processes 6-15 tons per hour (12-15 tons for medium-sized fruits such as citrus and apples), equivalent to 7 workers’ 1 day of work; dual channels can reach up to 20 tons per hour, adapting to peak season capacity.
• Full-Process Automation: From feeding, testing, grading to packaging, the entire process is unattended, enabling 24/7 continuous operation and completely solving labor shortages during peak seasons.

2. Precise Grading: 97% Accuracy + Multi-Dimensional Full Inspection—Eliminate Hidden Defects

• Multi-Dimensional Full Inspection: Accurately identifies explicit indicators such as appearance defects (spots, insect eyes, etc.), size, and weight; simultaneously identifies hidden indicators such as sugar content and internal lesions through non-destructive testing, achieving comprehensive screening.
• 97% Accuracy Rate: AI algorithms trained on millions of samples, with an error rate of<3%, far exceeding the 70% accuracy of manual work; supports personalized modeling for more than 20 categories.

3. Cost Reduction & Efficiency Improvement: 80% Cost Savings + 10% Loss Reduction—Direct Profit Growth

• Significant Cost Reduction: Replaces manual labor to reduce labor costs by over 40%; comprehensive processing costs drop from 600-800 yuan/ton to less than 100 yuan/ton, saving over 80%.
• Significant Loss Reduction: Loss rate decreases from over 10% to less than 3%, and return rate drops to below 5%, directly boosting profit margins.

4. Compliance & Traceability: Full Data Recording—Adapts to Quality Supervision Requirements

• Full-Process Traceability: Automatically records grading time, grade, testing indicators and other data, forming queryable files, adapting to supervision requirements, and reducing compliance risks.
• Data-Driven Decision-Making: Backend data analysis provides a basis for capacity optimization and quality improvement, facilitating refined operations.

Take Action Now: Unlock a New Solution for Cost Reduction & Efficiency Improvement in Grading

Traditional grading models have become an obstacle to development. Choosing the right intelligent automatic grading system is the key for processing enterprises to enhance core competitiveness.

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