G4T Certification – Scoring Software Model Framework

Good 4 Farming (G4T) Digital Compliance & Scoring Architecture
Developed for Kenya Coffee School

1. Purpose of the Scoring System

The G4T Scoring Software Model is a digital evaluation engine designed to:

  • Objectively score farms against G4T pillars
  • Store soil lab and field inspection data
  • Track regenerative progress over time
  • Generate certification level automatically
  • Produce audit-ready compliance reports

The system must be:

  • Transparent
  • Data-driven
  • Scalable across counties
  • Compatible with SIG-based field reporting
  • Cloud-enabled with offline field capture

2. System Architecture Overview

Core Modules

  1. Farm Registration Module
  2. Soil Lab Data Input Module
  3. Pest & Input Logbook Module
  4. Field Inspection Module
  5. Scoring Engine
  6. Certification Level Generator
  7. Dashboard & Reporting
  8. Audit History Tracker

3. Scoring Logic Framework

Pillar Weight Distribution (Core Algorithm)

PillarWeight
Soil Health & Nutrient Management30%
Circular IPM20%
Nutrient Efficiency (Xylem/Phloem Alignment)15%
Root & Nematode Management15%
Climate Resilience20%

Total = 100%

4. Scoring Structure (Detailed Rubric Model)

Each pillar contains measurable indicators scored on a 0–5 scale:

0 = Non-compliant
1 = Very weak
2 = Partial compliance
3 = Acceptable
4 = Strong
5 = Full regenerative alignment

PILLAR 1 – Soil Health (30%)

Indicators

  1. Annual Soil Test Submitted (Mandatory Gate)
  2. Soil pH within 5.5–6.5
  3. EC within safe threshold
  4. Organic matter improvement trend
  5. Balanced NPK correction plan
  6. Micronutrient management plan

Formula:

Pillar1_Score = (Sum of indicator scores ÷ Max possible score) × 30

If Soil Test = Not submitted → Auto-fail (score capped at 40% overall)

PILLAR 2 – Circular IPM (20%)

Indicators:

  • Pest scouting log frequency
  • % biological vs synthetic input use
  • Botanical pest control usage
  • Preventive strategy documentation
  • Chemical phase-down plan

Bonus Multiplier: If biological inputs >70% → +2% overall system bonus

PILLAR 3 – Nutrient Efficiency (15%)

Indicators:

  • Proper N application timing
  • Phosphorus applied based on soil data
  • Potassium for fruit development
  • Root health observation records
  • Over-fertilization avoidance

PILLAR 4 – Nematode & Root Health (15%)

Indicators:

  • Nematode assessment conducted
  • Bio-nematicide usage
  • Organic matter incorporation
  • Crop rotation or soil break practices
  • Root vigor field rating

PILLAR 5 – Climate Resilience (20%)

Indicators:

  • Shade integration %
  • Mulching coverage
  • Water conservation system
  • Soil erosion control
  • Tree diversity count

5. Certification Level Automation Logic

After final weighted score:

Final ScoreCertification Level
85–100%G4T Advanced Regenerative
70–84%G4T Regenerative
65–69%G4T Transitional
<65%Not Certified

6. Data Model (Database Structure)

Tables

Farm_Profile

  • Farm_ID
  • Owner_Name
  • County
  • Farm_Size
  • Registration_Date
  • SIG_Affiliation

Soil_Test_Record

  • Test_ID
  • Farm_ID
  • Date
  • pH
  • EC
  • N
  • P
  • K
  • Ca
  • Mg
  • Zn
  • B
  • Organic_Carbon

Pest_Log

  • Log_ID
  • Farm_ID
  • Date
  • Pest_Type
  • Biological_Input_Used
  • Synthetic_Input_Used
  • Action_Taken

Inspection_Score

  • Inspection_ID
  • Farm_ID
  • Pillar1
  • Pillar2
  • Pillar3
  • Pillar4
  • Pillar5
  • Total_Score
  • Certification_Level

7. Scoring Algorithm (Pseudo-Code)

For each Farm:

Calculate Pillar1
Calculate Pillar2
Calculate Pillar3
Calculate Pillar4
Calculate Pillar5

Total_Score = Sum(Pillar1..Pillar5)

If Soil_Test_Submitted = False:
    Total_Score = Min(Total_Score, 40)

If Biological_Input_Percentage > 70:
    Total_Score += 2

If Total_Score >= 85:
    Level = "Advanced Regenerative"
Else If Total_Score >= 70:
    Level = "Regenerative"
Else If Total_Score >= 65:
    Level = "Transitional"
Else:
    Level = "Not Certified"

8. Dashboard Features

The digital interface should include:

  • County-based performance map
  • Soil health trend graphs (3–5 year view)
  • EC and pH tracking chart
  • Biological vs synthetic input ratio graph
  • Carbon improvement index
  • Alert system (pH imbalance, high EC)

9. Progressive Improvement Index (PII)

The system should calculate year-over-year improvement:

PII = (Current Year Score - Previous Year Score)

Positive PII = Regenerative progress
Negative PII = Requires intervention

10. Compliance Safeguards

  • Digital timestamped soil lab uploads
  • Inspector ID verification
  • GPS-tagged farm inspections
  • Random audit selection algorithm
  • Data tampering detection

11. SIG-Level Aggregation Model

County-level dashboard should show:

  • Average Soil Health Score
  • Average IPM Compliance
  • Climate Adaptation Index
  • Certification distribution
  • Risk cluster alerts

This allows Kenya Coffee School to:

  • Identify weak regions
  • Deploy targeted training
  • Align bio-supply distribution
  • Track national regenerative adoption

12. Future Expansion Modules

  • Carbon credit integration scoring
  • Export traceability API
  • QR code farm verification system
  • Buyer access portal
  • Blockchain compliance layer (optional)

Conclusion

The G4T Scoring Software Model transforms certification from a checklist into a dynamic, measurable, data-backed regenerative performance system.

It ensures:

  • Scientific accountability
  • Farmer progression tracking
  • Soil-first integrity
  • Market transparency