Validation System

Prepared for: Kumbi Cocoa LLC CEO

Prepared by: Michael Hoffman, North Star Group

Date: May 26, 2025

Executive Summary

Current cocoa quality assessment methods sample 0.03% of beans through manual cut tests. A

stationary testing device utilizing vacuum arm sampling, hyperspectral analysis, and 10-test

validation protocols may provide more comprehensive quality data for the global cocoa market.

This technology could enable improved quality documentation, more accurate pricing, and

enhanced supply chain transparency for farmers, processors, and buyers.

Quality Assessment Limitations:

● Inadequate sampling: Manual cut tests sample only 0.03% of cocoa beans, missing

quality variations

● Pricing disputes: Lack of objective data leads to 10-20% price misalignment

● Premium access barriers: Farmers cannot prove quality for Fairtrade premiums

($400/tonne) or specialty pricing ($2.57-$7.61/kg vs. $1.71/kg standard)

Fairtrade and specialty chocolate markets require documented quality standards that current

manual testing cannot adequately provide. Fairtrade certification commands premium pricing of

$400 per tonne above standard rates, while specialty single-origin cocoa can achieve

● Transparency gaps: Buyers question ethical sourcing claims without verifiable data

Financial Impact:

● Quality disputes and pricing penalties due to lack of transparent data

● Missed premium opportunities from insufficient quality documentation

● Processing inefficiencies from inconsistent raw material quality

● Reputation risk from inability to verify ethical sourcing claims

Research Findings: Current State of Cocoa Quality Testing

Key Research Discovery: Current cocoa quality assessment technology is severely limited,

relying primarily on:

1. Manual cut tests: Labor-intensive, slow, and sample only 0.03% of beans

2. Visual inspection: Subjective and inconsistent between assessors

3. Basic moisture testing: Limited scope, no comprehensive quality profiling

4. Paper-based certification: Prone to loss, fraud, and lacks real-time verification

Market Gap Opportunity: The absence of automated, comprehensive cocoa quality testing

represents a significant first-mover advantage for technology that can provide objective,

verifiable quality data.

Multi-Test Validation Protocol

The proposed system would conduct 10 independent hyperspectral scans per sample to

generate statistical data sets. This approach would:

● Create data reliability metrics through variance analysis across the 10 tests

Implementation would require partnership with specialized robotics manufacturers rather than

internal development. We would identify and guide a qualified robotics manufacturer through the

specific requirements for cocoa quality testing applications. This partnership approach would

involve defining technical specifications, overseeing prototype development, and ensuring the

final system meets cocoa industry standards. The selected manufacturer would handle

mechanical engineering, sensor integration, and software development while we provide cocoa

industry expertise, quality requirements, and market knowledge. This collaborative model

reduces development risk and leverages existing robotics capabilities while ensuring the system

addresses actual market needs.

● 10-test verification: Each sample undergoes 10 separate hyperspectral scans

● Statistical analysis: Multiple tests generate confidence intervals for quality metrics

● Processing time: Approximately 2 minutes per complete 10-test cycle

● Defect identification: Measures moisture content, Free Fatty Acid levels, mold, and

foreign matter

● Quality classification: Grading based on statistical averages from multiple tests

● Data consistency: Variance analysis across 10 tests identifies measurement reliability

The initial 10-test protocol addresses current technology limitations and provides statistical

confidence in results. As hyperspectral analysis algorithms improve through machine learning

and larger datasets, fewer tests per sample may achieve equivalent accuracy. Advanced pattern

to validate automated assessments, and creating visual documentation for buyers who require

photographic evidence of bean quality. The combination of spectral data and photographic

evidence provides comprehensive quality documentation that addresses both automated

analysis and human verification needs.

Blockchain Integration: Blockchain Explained: Blockchain technology creates an unchangeable

digital record of cocoa quality data that all parties can trust. Think of it as a tamper-proof digital

ledger where each quality test, farmer ID, GPS location, and batch number gets permanently

recorded with a timestamp. For cocoa, this means buyers can verify the exact farm origin, ethical

sourcing practices, and quality test results without relying on paper certificates that can be lost or

falsified. When Kumbi uploads quality data to the blockchain, buyers like Mars or Ferrero Rocher

can instantly verify the shipment's authenticity and quality history, supporting premium pricing

and meeting their ethical sourcing requirements.

Premium Pricing Scenario - Chain of Custody Example: *Consider farmer Joseph in Ghana who

grows high-quality cocoa on his 5-hectare certified organic farm. Currently, he sells to local

3. Visual Documentation: High-resolution photos of his beans are uploaded alongside test

data

4. Chain of Custody: Each step from farm to warehouse is blockchain-recorded with

timestamps and handlers

5. Buyer Verification: Mars Chocolate can instantly verify Joseph's organic certification, see

his quality test results, view photos of his actual beans, and trace the complete chain of

custody

6. Premium Access: With verified organic certification and Grade I quality documentation,

Joseph qualifies for specialty pricing of $4.15/kg instead of $1.71/kg - a 143% increase

The blockchain provides Mars with certainty that they are receiving verified organic, Grade I

Mars cannot confirm the quality claims and pays standard rates. This creates a direct financial

incentive for quality production and proper documentation.*

Visual Data Outputs:

● Measurement reliability: Statistical metrics indicating data consistency

● Quality documentation: Multi-test data may support pricing negotiations

● Data transparency: Statistical analysis provides objective quality metrics

● Market access: Comprehensive testing may meet certification requirements

● Pricing support: Quality data could justify premium pricing requests

For Factories (Including Kumbi's $263M Facility):

● Quality assessment: Multi-test validation provides comprehensive raw material analysis

● Risk management: Statistical data may reduce uncertainty in procurement decisions

● Process consistency: Detailed quality metrics support production planning

● Documentation: Comprehensive testing records support quality control processes

For Buyers:

● Documentation: Comprehensive test results support product specifications

Phase 1: Development (6 months)

● Prototype development with vacuum arm and hyperspectral analysis

● Initial testing at pilot cooperative in West Africa

3. Secure pilot customer for commercial testing

4. Establish premium pricing through verified quality data