Use Case: Addressing challenges in potato farming with Cropin Intelligence

Samitha R Babu
|

Share this:

This blog delves into Cropin Intelligence capabilities, with a specific emphasis on optimizing decision-making at the farm level. Through a detailed examination of a potato farm case study, we illustrate how our intelligence solutions effectively address key challenges agri-businesses encounter.

Optimizing Potato Production with AI

A potato producer aimed to optimize in-season farm management to mitigate yield loss and enhance sourcing/procurement intelligence. To realize these goals, the company partnered with Cropin.

Let us now see how Cropin’s comprehensive approach utilizes a range of AI models, including:

Yield Estimation Model:

This powerful tool combines weather and remote sensing datasets from satellite imagery to estimate potato yields at key stages throughout the crop cycle. It allows for better procurement planning and forward contracting through accurate predictions at maturity.

Cropin employs a scientifically rigorous sampling method to account for a farm's diverse characteristics, enabling improved accuracy. Cropin’s intelligence module empowers users to visualize plot heterogeneity based on raw indices like NDVI, NDRE, LSWI, SAVI, EVI, etc., enabling them to pinpoint areas to conduct sampling for precise yield estimation. Such sampling activities can be done for multiple purposes, such as yield estimation, soil testing, nutrient checks, quality controls, etc.

crop-health-model

Crop Health and Crop Stage Progression Models:

Cropin's satellite imagery analysis offers insights into plant health parameters like canopy greenness (overall plant health), nitrogen uptake (for insights into the distribution of fertilizer application), and water stress (an anomaly in plant water content was linked to a faulty sprinkler in one case). The comprehensive Crop Stage Progression model detects growth stages, overall growth rate & lifecycle progression of the crop and predicts harvest windows when crops reach maturity. It ensures the planning of harvest activities and timely harvesting for optimal quality.

crop-health-model1

 

Disease Early Warning System:

By analyzing weather data, growth stage information, crop knowledge graphs, and agronomy science expertise, Cropin's system provided early warnings of potential potato diseases such as late or early blight, allowing for proactive interventions with mitigation strategies.

Customization and Knowledge for Enhanced Precision

Cropin's platform leverages a vast knowledge graph built on 14 years of experience as a baseline. These models are fine-tuned using client-specific data on varieties and locations. The "hypertuning" with historical data ensures highly accurate advisories and recommendations, further enhanced by Cropin's ability to customize solutions within 30 days.

A recent collaboration with a Philippine pineapple grower exemplifies this approach. By hypertuning Plot Intelligence models using historical data, Cropin achieved a remarkable 90% accuracy in yield estimation for that specific crop and location.

Sustainability Monitoring and Reporting

The Cropin Cloud platform goes beyond yield estimation. It also monitors, reports, and validates sustainability practices. The platform provides insights on carbon footprint, water footprint, and soil health with tillage, cover crop, and deforestation analysis. It provides both the year and percentage of deforestation. This helps food producers make informed, responsible sourcing decisions.

sus-monitoringThese examples illustrate how Cropin's AI-powered Intelligence solutions empower agricultural enterprises to achieve improved efficiency, sustainability, and profitability. Through collaboration with Cropin, companies can access valuable insights and make data-driven decisions that benefit their bottom line and the environment.

Conclusion

Cropin's Intelligence AI solutions empower agri-stakeholders right from optimizing farm operations to guiding policy decisions. Cropin's technology drives efficiency, sustainability, and profitability. Real-time monitoring, yield predictions, and disease warnings support farm-level decision-making. Additionally, Cropin ensures EUDR compliance with deforestation-free tracking throughout the supply chain. By harnessing Cropin's AI, agricultural stakeholders can navigate a complex landscape and build a more secure and sustainable future.

Explore the potential of AI in improving farming operations through enhanced yield estimation, proactive crop management, waste reduction, and promoting adherence to sustainable practices in our on-demand webinar.

Recommended resources for you

Satellite-vs-IoT-feature-image

Satellite Monitoring versus IoT Devices, Which is Better for Agriculture

Today, agriculture is far more challenging and competitive than ever. Climate change, unpredictable weather events, pests, diseases, and weeds create a dynamic and unpredictable environment for crop growth and production.

Why technology is your biggest ally in the pre-sowing stage

The spectre of World Hunger has never seemed closer. It's an age-old problem that's been compounded by overpopulation...

How Can Precision Agriculture Help to Optimize Costs and Reduce Waste for Seed Production Companies

The seed industry, the foundation of the global $5 trillion food system....

The Four-pillar Approach Development Agencies Must Take to Transform Indian Agriculture

Agriculture is India's backbone, supporting millions of livelihoods....

The Role of Data Analytics in Modern Agriculture

Agriculture stands at a crossroads. While feeding a burgeoning population presents unprecedented...