MicrosoftProductionEvidence: Medium65/100

Map My Crop Transforms Sugarcane Farming for Indian Growers

Map My Crop, in partnership with Microsoft, ADT Baramati, and Oxford University, deployed an AI-driven Satellite Crop Monitoring Platform that transformed traditional sugarcane farming practices in Baramati, Maharashtra, India. The solution included real-time remote sensing, AI-based agronomic advisory, and Variable Rate Application fertilizer mapping, enabling farmers to act on data-driven insights for better yield and resource management. The project compared AI-managed plots versus traditionally managed ones, showing substantial gains: onboarding over 1000 farmers in days, reducing input costs by 41%, improving yields from 70 to 120 tons/acre, and minimizing necessary farm visits by 75%. AI-powered analysis on the Microsoft platform provided direct recommendations for irrigation, nutrient use, and pest control, improving both operational efficiency and overall crop health. AI-predicted crop growth metrics like plant height, cane weight, and sucrose content showed consistent improvement. By integrating AI with remote sensing and precision agriculture, Map My Crop's platform demonstrated scalability, sustainability, and the potential for significant gains in productivity and profitability, serving as a replicable model for smart farming across India.

Organization
Map My Crop
Industry
Agriculture
Location
India
Published
February 2025

Reported outcomes

70-120%

quantified impactOther quantified impact

2 daysquantified impact−41%cost−75%quantified impact

Strategic outcomes

Scale & capacityOnboarded farmers at scaleCost efficiencyReduced input costsNew product / capabilityEnabled precision fertilizer mappingSpeed & agilityReduced farm visit dependence
Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Quantified impact: 2 days

mapmycrop.comFeb 11, 2025Case studyInferred claimMedium evidence strength

Onboarded 1000+ farmers in 2 days

Normalized claim

Cost: 41% decrease

mapmycrop.comFeb 11, 2025Case studyInferred claimMedium evidence strength

41% reduction in average input costs

Normalized claim

Quantified impact: 70-120% increase

mapmycrop.comFeb 11, 2025Case studyInferred claimMedium evidence strength

Yield increase from 70 to 120 tons/acre (71% gain); sugarcane varieties improved >40%

Normalized claim

Quantified impact: 75% decrease

mapmycrop.comFeb 11, 2025Case studyInferred claimMedium evidence strength

75% reduction in on-site farm visits through remote monitoring

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
Customer
Map My Crop, ADT Baramati
Provider
Microsoft
Maturity
Production
Linked source
mapmycrop.com

Map My Crop, in partnership with Microsoft, ADT Baramati, and Oxford University, deployed an AI-driven Satellite Crop Monitoring Platform that transformed traditional sugarcane farming practices in Baramati, Maharashtra, India

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 3 of 3

  • 1AI-Driven Satellite Crop Monitoring for Sugarcane
  • 2Automated Agronomic Advisory
  • 3Variable Rate Precision Fertilizer Application
  • High input costs and suboptimal yields in traditional sugarcane farming
  • Limited access to real-time, actionable crop health intelligence
  • Inefficient resource management due to lack of data-driven decision tools
  • Multiple manual farm visits required for monitoring, adding costs and effort
  • Deployment of an AI-driven satellite crop monitoring and advisory platform
  • Use of Variable Rate Application maps for precise fertilizer use
  • Real-time analysis of remote sensing data on the Microsoft platform
  • Automated agronomic advice for irrigation, pest, and nutrient management
Technologies
  • Onboarded 1000+ farmers in 2 days
  • 41% reduction in average input costs
  • Yield increase from 70 to 120 tons/acre (71% gain); sugarcane varieties improved >40%
  • 75% reduction in on-site farm visits through remote monitoring
  • Improved plant metrics: height, internodes, tiller count, leaf width, cane weight, sucrose content
Architecture

AI-driven platform ingests remote sensing (satellite) data, analyzes field-level crop variables, and delivers actionable VRA maps and agronomic advice to farmers. All computation and analytics executed on Microsoft cloud infrastructure, with data returned to dashboards for farmers and partners.

Implementation partners1
Sources & evidence1
Evidence: Medium65/100Evidence strength
  • Customer explicitly identified
  • Deployment status explicitly supported
  • Primary source available
  • Quantified outcome available
  • Technical implementation details available
Type: Case StudyPublished: Feb 11, 2025Publisher: mapmycrop.comEvidence: PrimaryConfidence: High

AI-generated summary. Verify important details with the linked sources before relying on this case.

Explore related AI use cases

Was this useful?

Community

Comments

Loading comments...

Similar cases