Streamlining operations for tea plantations in Tamil Nadu

Redefining the Tea Value Chain for One of the Oldest Tea Producers in India

The client, headquartered in Mumbai, India, is a 150-year-old corporation. It has many tea plantations in Tamil Nadu (India), spread across 2500 hectares and producing more than 10 million kilograms of tea every year.

Business challenges

The absence of a centralized system for monitoring plantations and data management impacted the company’s business operations. Some of the key challenges were:

  • Cumbersome, expensive manual data-capturing
  • Absence of a live dashboard with real-time information on crop health across plantations 
  • Lack of pest and disease alerts
  • Need for weather-based advisories to reduce damage to tea crop
  • Inaccurate yield estimation

How Cropin helped

Cropin developed a unique dashboard to manage and monitor tea plantation estates in Tamil Nadu, India. It leveraged state-of-the-art AI/ML, satellite imagery, and big data to provide accurate yield estimates and advisories. Cropin offered three models – Remote sensing indices for health analysis, pest occurrence model based on weather, and weather alerts and phenology model. 

Impact

  • Solution implemented across 50 plantations
  • 2500 hectares covered
  • Alerts provided for red spider mite and tea mosquito bite pests 
  • Normalized Difference Chlorophyll Index (NDCI)-based crop health assessment was done
  • Weather alerts offered regularly

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The client, headquartered in Mumbai, India, is a 150-year-old corporation. It has many tea plantations in Tamil Nadu (India), spread across 2500 hectares and producing more than 10 million kilograms of tea every year.

Business challenges

The absence of a centralized system for monitoring plantations and data management impacted the company’s business operations. Some of the key challenges were:

  • Cumbersome, expensive manual data-capturing
  • Absence of a live dashboard with real-time information on crop health across plantations 
  • Lack of pest and disease alerts
  • Need for weather-based advisories to reduce damage to tea crop
  • Inaccurate yield estimation

How Cropin helped

Cropin developed a unique dashboard to manage and monitor tea plantation estates in Tamil Nadu, India. It leveraged state-of-the-art AI/ML, satellite imagery, and big data to provide accurate yield estimates and advisories. Cropin offered three models – Remote sensing indices for health analysis, pest occurrence model based on weather, and weather alerts and phenology model. 

Impact

  • Solution implemented across 50 plantations
  • 2500 hectares covered
  • Alerts provided for red spider mite and tea mosquito bite pests 
  • Normalized Difference Chlorophyll Index (NDCI)-based crop health assessment was done
  • Weather alerts offered regularly