Office for Technology Commercialization

Predicting Crop Nitrogen Status with Remote Sensing

Technology #20180415

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Remote sensing of nitrogen status in potato cropsPotato fieldPredicting Crop Nitrogen Status (CNS)
Carl Rosen, PhD
Department Head and Professor, CFANS Soil, Water & Climate
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David Mulla, PhD
Professor, CFANS Soil, Water & Climate
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Yuxin Miao, PhD
Assistant Professor of Precision Agriculture and Nutrient Management and Associate Director of Precision Agriculture Center, CFANS Soil, Water & Climate
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Managed By
Kevin Nickels
Technology Licensing Officer 612-625-7289
Patent Protection

Provisional Patent Application Filed

In-season prediction of crop nitrogen status

This new technology can estimate CNS (crop nitrogen status) using remote sensing and the nitrogen nutrition index (NNI). These estimates produce actionable insights on the optimum nitrogen fertilizer use efficiency to maximize agronomic production. This new system helps forecast end-of-season crop yield and quality. For example, remote sensing based CNS measurements on a given date can forecast end-of-season crop yield and quality for a given field—and within a field. While this precision agriculture technology was developed for irrigated potato cropping systems, it could be adopted for use in other high-value agronomic or horticultural crops.

Precision nitrogen applications for intensively managed crops

Remote sensing offers superior temporal and spatial resolution that can supplement or even replace existing methods for managing in-season nitrogen applications. While the adoption of remote sensing in precision agriculture is rapidly accelerating, no system to date can directly and accurately determine crop nitrogen status (CNS) from remote sensing alone. Previous methods have relied on imagery to directly predict CNS. However, these methods lack accuracy and may require an in-field reference strip, which is logistically challenging. Remote sensing, on the other hand, can more accurately predict both CNS as well as other parameters (e.g., canopy cover or above ground nitrogen concentration).

Phase of Development

  • Proof of concept. Algorithm developed and tested.


  • Optimizes agronomic production and maximizes fertilizer use efficiency
  • Predicts end of season crop yield and quality based on crop nitrogen status
  • Increases temporal and spatial resolution compared to existing methods


  • Precision agriculture solution for intensively managed crops
  • Predicts crop nitrogen status and in-season fertilizer requirement
  • Remote sensing combined with the nitrogen nutrition index
  • Produces actionable insights on the optimum nitrogen fertilizer rate
  • Assists producers in adaptively managing in-season nitrogen


  • Precision agriculture
  • In-season nitrogen fertilizer applications
  • Yield quantity and quality forecasting
  • High-value agronomic and horticultural crops, crops grown on sandy soils vulnerable to nutrient losses, and irrigated cropping systems

Interested in Licensing?
The University relies on industry partners to further develop and ultimately commercialize this technology. The license is for the sale, manufacture or use of products claimed by the patents. Please contact Kevin Nickels to share your business needs and licensing and technical interest in this technology.