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Unlocking the Potential of  High-Resolution Satellite Imagery for Soybean (Glycine max (L.) Merr.) Phenotyping  and Maturity Estimation in Plant Breeding            
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  • Anastasios Mazis,
  • Adam Barbeau,
  • Julien Linares,
  • Pringale Kumar Das,
  • Jeremiah Barr,
  • Nathan Coles
Anastasios Mazis
Corteva AgriScience, University of Nebraska- Lincoln

Corresponding Author:[email protected]

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Adam Barbeau
Corteva AgriScience
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Julien Linares
Corteva AgriScience
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Pringale Kumar Das
Corteva AgriScience
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Jeremiah Barr
Corteva AgriScience
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Nathan Coles
Corteva AgriScience
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Abstract

    Plant breeding programs demand efficient and accurate methods for crop phenotyping, especially for economically important crops like soybeans. High-resolution satellite and drone imagery are alternatives to ground data collection to monitor crops in a time, cost, and labor efficient way. Drone imagery offers localized and high-resolution data but has limitations in coverage and operator skills. In contrast, high-resolution satellite imagery provides broad-scale views of research sites without the need of a human data collector or pilot.
    Our study investigates the potential of high-resolution satellite imagery (50 cm GSD) as an alternative to drone imagery for assessing soybean physiological maturity and monitoring the crop condition in a small plot breeding program. We compare the efficacy of satellite against UAV by generating various multi-spectral vegetation indices (VI) to predict maturity and assessing crop canopy characteristics (green cover and NGE) . Eleven satellite derived VI were compared to UAV derived values, with NDVI (R2= 0.84), EVI2 (R2= 0.83), TVI (R2= 0.83) and IPVI (R2= 0.83) displaying the highest correlation between the two methods. Satellite-derived NDVI was also efficient in distinguishing the maturity of varieties among and across maturity groups when compared against UAV imagery. Within location heritability was high with values ranging between H2= 0.77 and H2= 0.93.
    With advances in spatial resolution, satellites can now provide detailed insights into crop health, productivity, and resource management. Our findings reveal the promise of high-resolution satellite imagery as a valuable tool in small plot phenotyping with the potential to further scale breeding programs.