Overview
Discover how growers, consultants, and farm operations use Cropwise Explorer to make better decisions, save time, and improve their operations. These examples demonstrate practical applications of Explorer's capabilities.
Story 1: Early Detection Saves a Soybean Crop
Situation
A grower in Brazil managing 2,000 hectares of soybeans used Cropwise Explorer's weekly insights to monitor field conditions during the critical flowering stage.
Discovery
- Weekly Field Insight notification highlighted an anomaly in Field 12
- NDVI imagery showed a circular pattern of declining vegetation in one corner
- Pattern size: approximately 15 hectares
Action Taken
- Grower opened Explorer to examine the anomaly in detail
- Compared current NDVI to imagery from previous week
- Noticed the pattern had expanded
- Directed scout to that specific GPS location
- Scout identified early-stage spider mite infestation
Outcome
| Metric | Result |
|---|---|
| Time to Detection | 5 days earlier than visual scouting would have caught |
| Area Affected | 15 hectares identified before spread |
| Treatment Area | Targeted application to affected zone only |
| Cost Savings | 60% reduction in treatment costs vs whole-field application |
| Yield Impact | Crop recovered fully; no yield loss in treated area |
Key Lesson
"Without Explorer's anomaly alert, this infestation would have spread across the entire field before we noticed it. The targeted treatment saved us significant input costs and protected our yield."
Story 2: Optimizing Fertilizer Applications with Variable Rate
Situation
A large grain operation in Europe managing 5,000 hectares of winter wheat historically applied uniform fertilizer rates across all fields. Rising input costs prompted a search for efficiency.
Approach
- Used Cropwise Explorer to analyze NDVI patterns across all fields
- Created productivity maps using historical yield data and multi-year NDVI
- Identified consistent zones: high, medium, and low productivity
- Generated NDVI-based prescriptions for nitrogen applications
- Exported prescriptions directly to John Deere equipment
Prescription Strategy
| Zone | Historical Yield | NDVI Pattern | Nitrogen Rate Applied |
|---|---|---|---|
| High Productivity | 9.0 t/ha | Consistently high NDVI | 180 kg/ha (standard rate) |
| Medium Productivity | 7.5 t/ha | Moderate NDVI | 160 kg/ha (-11%) |
| Low Productivity | 5.5 t/ha | Consistently low NDVI | 140 kg/ha (-22%) |
Rationale
Low productivity zones showed consistent yield limitations unrelated to nitrogen. Reducing N application in these areas eliminated waste without sacrificing yield potential.
Results
- Nitrogen Savings: 12% overall reduction in N application
- Cost Savings: €45/ha average across operation
- Total Savings: €225,000 across 5,000 hectares
- Yield Impact: No yield reduction; maintained average of 7.4 t/ha
- Environmental Benefit: Reduced nitrogen use in areas with low N response
Key Lesson
"Variable rate prescriptions based on productivity maps allowed us to apply inputs where they generate returns and reduce waste in areas that don't respond. The ROI was immediate and measurable."
Story 3: Scouting Efficiency for a Consultancy
Situation
An independent agronomy consultant serves 35 grower clients across 15,000 hectares. With limited time during peak season, prioritization was essential but difficult. Previous approach: visit each client's fields in rotation, risking missed issues.
Challenge
- Cannot visit every field every week
- Need to identify which fields require immediate attention
- Clients expect proactive communication
- Travel time reduces actual field time
New Workflow with Explorer
- Monday Morning: Review Weekly Field Insights for all clients
- Prioritization: Identify fields with anomalies or significant changes
- Communication: Proactively contact clients about potential issues
- Route Planning: Build scouting route around priority fields
- Field Visits: Focus on areas flagged by Explorer
- Documentation: Add field observations linked to satellite data
Results After One Season
| Metric | Before Explorer | With Explorer | Improvement |
|---|---|---|---|
| Fields scouted per day | 8-10 fields | 15-20 fields | +90% |
| Time spent traveling | 40% of day | 25% of day | -38% |
| Issues caught early | ~60% | ~90% | +50% |
| Client satisfaction | Reactive calls | Proactive alerts | Significant improvement |
Client Feedback
"My consultant now calls me about problems before I even know they exist. Last year, I felt like I was always behind. This year, we stayed ahead of every issue."
Key Lesson
"Explorer changed my business model. I can serve more clients better by letting the satellite data tell me where to focus. Travel time is now productive time because I know exactly what I'm going to see before I leave the truck."
Story 4: Validating Crop Protection Decisions
Situation
A Syngenta AgriEdge specialist works with growers to optimize crop protection programs. After recommending a new fungicide application, they needed to demonstrate effectiveness to the grower.
Approach
- Identified field with early disease pressure
- Selected a test block for targeted fungicide application
- Captured NDVI imagery immediately before application
- Applied fungicide treatment
- Captured follow-up imagery 10 days post-application
- Used Side-by-Side Comparison and NDVI Change Report
Analysis
Before vs After Comparison:
- Untreated area showed declining NDVI over 10 days (spreading disease)
- Treated area maintained stable NDVI (disease progression halted)
- Clear visual boundary between treated and untreated zones
Presented to Grower
- Generated NDVI Change Report showing treated vs untreated zones
- Quantified difference: treated zone showed 0.15 NDVI improvement relative to untreated
- Visual evidence from satellite confirmed ground observations
Outcome
- Grower adopted treatment program for remaining fields
- Objective data replaced anecdotal evidence
- Trust established through visual proof
- Season-long monitoring documented cumulative benefit
Key Lesson
"With Explorer, I can show growers exactly what happened after a treatment, not just tell them. The visual evidence from satellite imagery builds trust and closes sales."
Story 5: Post-Harvest Analysis Informs Next Season
Situation
A corn grower in the US Midwest experienced variable yields across fields, with some areas consistently underperforming. Wanted to understand why before next season's planning.
Analysis Process
- Import Yield Data: Brought harvest data into Explorer from John Deere monitor
- Compare to In-Season NDVI: Overlaid yield data on satellite imagery from key growth stages
- Identify Patterns: Found correlation between mid-season NDVI and final yield
- Generate Productivity Maps: Created stable zones across multiple seasons
- Investigate Causes: Combined data layers:
- NDVI showed where problems occurred
- Yield data confirmed impact
- Elevation data revealed drainage patterns
- Soil maps showed soil type variation
Findings
- Low Productivity Zone: Coincided with heavy clay soil + low-lying area
- Root Cause: Poor drainage caused water logging during wet spring
- Area Impact: 20 hectares consistently yielding 25% below field average
Actions for Next Season
- Installed tile drainage in affected zone
- Created prescription for different hybrid with better water tolerance
- Adjusted planting dates for that zone based on historical data
Projected Outcomes
- Expected yield improvement: 15-20% in previously underperforming zone
- ROI on drainage investment: Expected payback in 3 years
- Confidence in decision based on multiple data sources
Key Lesson
"Yield variability isn't random, it's pattern-based. Explorer helped me see those patterns clearly by combining satellite data with harvest results. Now I understand the 'why' behind my yield maps."
Story 6: Monitoring Large Operations Remotely
Situation
A farm manager overseeing operations across multiple regions totaling 12,000 hectares cannot physically visit all fields regularly. Needed a way to stay informed and coordinate with local team.
Setup
- All fields mapped in Cropwise Explorer
- Team members assigned to regions
- Weekly Field Insights enabled for email delivery
- Access shared across management team
Weekly Workflow
| Day | Activity |
|---|---|
| Monday | Weekly Field Insights arrive via email; review summary of all fields |
| Tuesday | Management meeting: discuss fields flagged for attention |
| Wednesday | Assign field visits to regional team members based on priorities |
| Thursday-Friday | Team executes scouting; adds observations to Explorer |
| Ongoing | Manager reviews team inputs and monitors remotely |
Benefits
- Visibility: Manager sees all operations without daily travel
- Coordination: Weekly priorities set based on real data
- Efficiency: Team focuses on what matters most each week
- Communication: Shared platform keeps everyone aligned
- Documentation: All observations and actions recorded
Key Lesson
"I can't be everywhere, but with Explorer, I feel like I am. The weekly summaries tell me exactly where to focus my attention, and I trust my team to execute based on what we see together in the platform."
Common Success Patterns
What Makes Users Successful with Explorer
✅ Habits of Successful Users:
- Check weekly: Review insights regularly, not just when problems are suspected
- Ground-truth: Verify satellite observations in the field before acting
- Combine data: Use multiple layers (imagery, yield, soil) for deeper understanding
- Document: Add notes and observations to build a valuable record
- Integrate: Connect Explorer to equipment and other tools in the workflow
- Involve the team: Share access with scouts, consultants, and operators
Top Use Cases by User Type
| User Type | Top 3 Use Cases |
|---|---|
| Growers | 1. Monitor all fields efficiently 2. Create variable rate prescriptions 3. Analyze post-harvest results |
| Large Operations | 1. Remote monitoring of multiple locations 2. Coordinate team activities 3. Compare performance across the operation |
| Consultants | 1. Prioritize scouting routes 2. Build trust with data-backed recommendations 3. Monitor many client fields efficiently |
| Sales/Advisors | 1. Demonstrate product effectiveness 2. Build relationships through proactive communication 3. Identify opportunities for conversations |
Measuring Success
Key Metrics to Track
How to measure the impact of using Cropwise Explorer:
| Category | Metric | How Explorer Helps |
|---|---|---|
| Efficiency | Fields monitored per day | Remote monitoring before field visits |
| Travel time reduction | Prioritized scouting routes | |
| Issues caught early | Anomaly detection and alerts | |
| Input Optimization | Input cost reduction | Variable rate prescriptions |
| Application precision | Targeted zones based on data | |
| Yield | Yield stability | Early problem detection prevents losses |
| Reduced yield variability | Management zone-based decisions | |
| Decision Quality | Speed of decision-making | Data available when needed |
| Confidence in decisions | Multiple data sources confirm observations |
Getting Started on Your Success Story
First Steps
- Week 1: Explore all your fields in Explorer; check boundaries and imagery
- Week 2: Enable Weekly Field Insights; customize notifications
- Week 3: Compare imagery dates; identify baseline patterns
- Week 4: Try creating your first prescription
- Week 5: Ground-truth an observation in the field
- Week 6: Review insights and share with your team
We love hearing how growers use Cropwise Explorer. Contact your account manager to share your success story and potentially be featured in future communications.
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