At Canpro Nutrition Association, we believe that setting and maintaining high industry standards is crucial for ensuring the quality, safety, and reliability of protein products. Our Industry Standards initiative is at the core of our efforts to advance the protein sector and foster consumer trust.

At Canpro Nutrition Association, we believe that transparency and traceability are fundamental to building trust in the protein sector. Our Quality Traceability Systems standards ensure that every protein product can be traced from its source to the consumer, guaranteeing quality, safety, and authenticity at every step of the supply chain.

Why Traceability Matters

• Food Safety: Enables rapid identification and isolation of potential safety issues
• Quality Assurance: Verifies adherence to quality standards throughout the production process
• Consumer Trust: Provides transparency that builds consumer confidence in protein products
• Sustainability: Allows for verification of sustainable sourcing and production practices

Key Components of Quality Traceability Systems

1. Batch Identification

• Unique identifiers for each production batch
• Standards for lot coding and product marking
• Guidelines for maintaining batch integrity throughout processing

2. Record-Keeping

• Requirements for comprehensive and accurate record-keeping
• Standards for data collection at each stage of production
• Guidelines for secure data storage and accessibility

3. Supplier Management

• Criteria for supplier approval and ongoing evaluation
• Requirements for supplier traceability systems
• Guidelines for integrating supplier data into the overall traceability system

4. Recall Procedures

• Standards for product recall plans
• Requirements for regular mock recall exercises
• Guidelines for communication during recall situations

Implementing Traceability Systems

Technology Solutions

• Recommendations for traceability software and hardware
• Guidelines for integrating traceability systems with existing ERP systems
• Standards for data security and privacy protection

Staff Training

• Requirements for employee training on traceability procedures
• Guidelines for creating a culture of traceability within organizations

Continuous Improvement

• Standards for regular audits and assessments of traceability systems
• Guidelines for incorporating feedback and technological advancements

Benefits of Canpro Traceability Standards

• Enhanced food safety and quality control
• Improved operational efficiency and reduced waste
• Increased consumer confidence and brand loyalty
• Better preparedness for regulatory compliance
• Support for sustainability claims and certifications

Case Studies

Case Study 1: Implementing Farm-to-Table Traceability in Fish Maw Collagen Peptide Production

A leading fish maw collagen peptide manufacturer implemented a comprehensive traceability system to ensure the quality and sustainability of their products. The system included:

• Source Tracking: Each batch of fish maw was tagged with a unique identifier linking it to the specific fishery or aquaculture operation it came from.
• Processing Traceability: Every step of the extraction and hydrolysis process was documented, including enzyme types, reaction conditions, and quality control checks.
• Batch Coding: Final products were labeled with batch codes that could be traced back to the original raw materials and processing conditions.

Results:

• 30% reduction in product recalls due to early identification of quality issues
• Increased consumer confidence, leading to a 25% boost in sales
• Improved sustainability reporting, enhancing the company’s reputation

Case Study 2: Enhancing Quality Control through Advanced Traceability in Collagen Peptide Analysis

A fish maw collagen peptide testing laboratory integrated an advanced traceability system to improve the accuracy and reliability of their analytical processes. The system incorporated:

• Sample Tracking: Each sample was assigned a unique barcode, tracking its movement through various testing stages.
• Equipment Logging: All equipment used in the analysis was logged, including calibration status and maintenance records.
• Data Integration: Test results were automatically linked to sample information, reducing manual data entry errors.

Results:

• 50% reduction in sample mix-ups and data entry errors
• Improved turnaround time for sample analysis by 20%
• Enhanced ability to identify and resolve analytical discrepancies