SmartCane/python_app/harvest_detection_experiments/_archive/PACKAGE_MANAGEMENT.md

SmartCane Project - Package Management & Crop Analysis

Quick Start

For New Team Members

1. Open R/RStudio
2. Set working directory to the project root: setwd("path/to/smartcane")
3. Run: source("r_app/package_manager.R")
4. Type y when prompted
5. Wait for completion ✅

For Existing Team Members (After Git Pull)

Same steps as above - the script will check for updates automatically.

Crop Analysis Messaging System

Overview

The crop_analysis_messaging.R script provides automated field monitoring with intelligent alerting based on crop index (CI) analysis. It compares weekly satellite data to detect uniformity issues and performance changes.

Message Determination Logic

Uniformity Thresholds (CV = Coefficient of Variation)

Threshold	CV Range	Category	Action
Excellent	≤ 0.08	✅ Excellent	Monitor only
Good	0.08 - 0.15	✅ Good	Monitor only
Moderate	0.15 - 0.25	⚠️ Alert	Review management
Poor	> 0.25	🚨 Urgent	Immediate action

Additional Alert Triggers

• Low Acceptable Area: < 40% of field within ±25% of mean CI
• Very Strong Clustering: Moran's I > 0.95 (indicates management issues)
• Declining Trends: Combined with poor uniformity = escalated urgency

Message Categories & Examples

🚨 URGENT Messages:

• 🚨 URGENT: Poor field uniformity detected - immediate management review required
• 🚨 CRITICAL: Poor uniformity with declining trend - emergency intervention needed

⚠️ ALERT Messages:

• ⚠️ Alert: Moderate field variation detected - low acceptable area - review management uniformity
• ⚠️ Alert: Good uniformity but very strong clustering detected - check management practices

✅ POSITIVE Messages:

• ✅ Excellent: Optimal field uniformity and stability
• ✅ Great: Good uniformity with improvement trend

💡 OPPORTUNITY Messages:

• 💡 Opportunity: X% of field performing well - replicate conditions in remaining areas

Spatial Pattern Analysis

• Moran's I Interpretation: Measures spatial autocorrelation
  • 0.7-0.85: Normal field continuity
  • 0.85-0.95: Strong spatial pattern (monitor)

  • 0.95: Very strong clustering (management concern)

Farm-Wide Summary Statistics

• Field Distribution: Percentage in each uniformity category
• Area Analysis: Hectares improving/declining/stable
• Consistency Checks: Flags inconsistent CV vs Entropy readings
• Alert Rate: Typically 15-20% of fields for healthy monitoring

Package Management

What This Script Does

1. Initializes renv - Creates isolated package environment
2. Checks package versions - Compares installed vs required
3. Installs/Updates packages - Only if needed
4. Creates lockfile - renv.lock for exact reproducibility
5. Generates reports - Console output + package_manager.log

Key Features

• ✅ Minimum version requirements (allows patch updates)
• ✅ Critical package locking (tmap v4 for new syntax)
• ✅ Automatic installation of missing packages
• ✅ Console + Log output for debugging
• ✅ Cross-platform compatibility

Required Packages & Versions

Package	Min Version	Purpose
tmap	4.0.0	CRITICAL - New syntax used
tidyverse	2.0.0	Data manipulation
sf	1.0.0	Spatial data
terra	1.7.0	Raster processing
rmarkdown	2.21.0	Report generation
spdep	1.2.0	NEW - Spatial statistics for Moran's I

Crop Analysis Usage

# Basic usage (defaults to weeks 30 vs 29, simba farm)
Rscript crop_analysis_messaging.R

# Custom analysis
Rscript crop_analysis_messaging.R 32 31 other_farm

# Or from R console
source("r_app/crop_analysis_messaging.R")

Output Interpretation

• Field-by-field analysis: Individual field metrics and alerts
• Summary section: Total alerts and problem fields
• Farm-wide statistics: Overall uniformity distribution
• Consistency checks: Spatial pattern validation

Workflow

Development Workflow

1. 👨‍💻 Developer: Make changes → run package_manager.R → test → commit + push
2. 👥 Teammate: Pull → run package_manager.R → test
3. 🚀 Production: Pull → run package_manager.R → deploy

Crop Analysis Workflow

1. 📊 Weekly Data: New satellite mosaics arrive
2. 🔄 Analysis: Run crop_analysis_messaging.R
3. 📋 Review: Check alerts and prioritize fields
4. 🚜 Action: Implement management recommendations
5. 📈 Monitor: Track improvements in next week's analysis

Files Created

• renv.lock - Exact package versions (commit this!)
• package_manager.log - Installation log (don't commit)
• renv/ folder - Package cache (don't commit)

Troubleshooting

"Package failed to install"

• Check internet connection
• Update R to latest version
• Install system dependencies (varies by OS)

"Version conflicts"

• Delete renv/ folder
• Run script again for clean install

"renv not working"

• Install manually: install.packages("renv")
• Restart R session
• Run script again

Team Guidelines

1. Always run package_manager.R after pulling changes
2. Commit renv.lock to git (not renv/ folder)
3. Don't modify package versions in scripts - use this manager
4. Report issues in the log file to team
5. Review crop alerts weekly and prioritize urgent fields first
6. Document management actions taken in response to alerts

Crop Analysis Best Practices

Alert Prioritization

1. 🚨 URGENT alerts: Address within 24-48 hours
2. ⚠️ ALERT messages: Schedule for next management cycle
3. 💡 OPPORTUNITIES: Implement when resources available

Field Investigation Guidelines

• High CV + Low Acceptable Area: Check irrigation uniformity
• Very Strong Clustering: Look for management zone boundaries
• Declining Trends: Investigate nutrition or disease issues
• Spatial Patterns: Consider soil variability or equipment patterns

Validation Steps

1. Cross-reference alerts with field observations
2. Check weather data for recent stress events
3. Validate spatial patterns with drone imagery if available
4. Document management responses and track improvements

Advanced Usage

Restore from lockfile only:

renv::restore()

Add new package requirement:

1. Edit REQUIRED_PACKAGES in package_manager.R
2. Run the script
3. Commit updated renv.lock

Check status without changes:

source("r_app/package_manager.R")
# Then just read the log or run generate_package_report()