AI-led Digital Agriculture Platform Propelling The Seed Value Chain

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With complete visibility from the R&D phase to effective distribution and sales, digitisation gives you the insights you need to choose the best seed varieties suitable for cultivation.

By the year 2050, global agriculture will be tasked with producing 70% more food as per UN Food and Agriculture Organization (FAO) estimates, while only 5% of additional land will be available by then to feed the growing population. As a result, the agriculture industry has turned to technology in search of a workable solution. Digitalization in agriculture and AI presents a real solution not just for food production and cultivation in the years to come, but also help seed manufacturers, distributors, and other stakeholders to identify key insights that help them identify, develop and nurture the best seed varieties for production and distribution.

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Efficient utilization of available resources for research and development

Comb all relevant data sources across channels for intelligence that directs you towards the most optimum seed varieties to choose from the countless options available. Having a digital footprint for each seed variety tested across regions enables end-to-end traceability for all options allowing you to zero in on the best seeds to be readied for development.

  • Crop health analysis
  • Yield forecast for different seed varieties
  • Data-driven seed selection at a regional level
  • Cross-regional field data collection and analysis
  • Enhanced traceability

Identify which seeds make the cut and which don’t

Digital technology ensures there is complete transparency from the moment the idea of a seed variety is conceived until when it is selected for multiplication. Cutting-edge tools such as satellite monitoring and AI allow you to evaluate the health of each seed variety and check its progress on a real-time basis. The most significant impact of digital agriculture is in the two-way channel of communication it establishes with the farmer allowing timely passage of information that ensures efficient on-field operations.

  • Growth and yield forecasts across regions
  • Timely weather updates and alerts
  • Better business-to-farmer communication
  • Empower farmers with the latest agronomic news
  • Automated alerts for every stage

Timely monitoring of demo plots (or field trials) under cultivation

Capturing data from demo plots while evaluating seed varieties for cultivation has traditionally been a manual and time-consuming process. Digitizing farms make this a far more efficient process by bringing all the information onto one single dashboard.

  • Complete monitoring of all demo plots
  • Remote monitoring through satellite imaging for 360-degree coverage
  • Ongoing crop health analysis using AI and ML
  • Growth and yield forecast
  • Rule-based weather advisory

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Effective distribution of finalized seed varieties to respective locations

The impact of digital agriculture in seed selection and development is not limited to identifying the best options for production. Digitizing each step in the process lets you keep a tab on every consignment shipped out of the warehouse right until it reaches the end consumer— the farmer.

  • Complete transparency of packaging and warehousing
  • End-to-end visibility for warehouse operations
  • Minimize errors from human involvement
  • Track every package right down to the SKU
  • Automated inventory management

Improve your marketing and sales strategy with data-driven insights

Market intelligence gleaned from regional-level historical weather and ground data is vital to identifying areas where certain crops work best. A data-driven approach to the sales and distribution strategy for different varieties of seeds based on an understanding of what works where is guaranteed to increase profit margins.

  • Regional- and district-level data and insights
  • Focused sales and distribution strategy
  • Historical data insights on seed performance by region
  • Data-driven selling to farmers
  • Build farmer trust and credibility

Cropin has partnered with several seed companies globally to build massive efficiencies in the seed value chain. To state one example of CropIn’s widespread adoption, a prominent multi-billion-dollar global seed company is currently leveraging our advanced digital solutions in as many as 25 countries, or in other words, across 90% of their global presence in the seed production segment. Such is the transformative impact of building technological efficiencies into a long and arduous life cycle of high-quality seeds.

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Cropin Apps

Applications for
digitization

Cropin Apps is an integrated portfolio of highly customizable apps and solutions that capture and digitise agri-data from the farm to the warehouse to the fork. These applications are designed to scale digital transformation across agriculture and allied industries including forestry, commodity, banking and insurance.

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ML-ready data pipelines for enhanced analytics

Cropin Data Hub is designed to deliver the power of unified data by enabling interfacing with all agri-data sources from on-the-field farm management apps, IoT devices, mechanization data from farming resources, drones in agriculture, remote sensing satellite information, weather data, and many more.                                                      

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Cropin Intelligence enables access to over 22 of Cropin’s contextual deep-learning AI models to help agri-businesses with insights and predictive intelligence. Built using the world's largest crop knowledge graph, these models have been field-tested and deployed worldwide while being fine-tuned to work with a range of specific crop varieties, conditions, and locations.

Aravind S

About the Author

Aravind is a seasoned leader in the agriculture intelligence space, heading the Earth Observation team at Cropin. With a focus on building tailored products for the agriculture sector, he leverages his expertise in machine learning, remote sensing, and agriculture to provide cutting-edge solutions for farmers. Aravind has a strong background in developing crop phenology models, yield estimation, and early warning systems and has worked with various data sources, including optical, radar, hyperspectral, and drone data.