Mr. Tyler G. Smith Profile

Tyler G. Smith

at Univ of Nebraska-Lincoln

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Proceedings Article | 4 June 2022 Presentation + Paper

Leveraging multispectral imagery for fertigation timing recommendations through the N-time automated decision support system

Jackson Stansell, Joe Luck, Tyler Smith, Hongfeng Yu, Daran Rudnick, Brian Krienke

Proceedings Volume 12114, 1211402 (2022) https://doi.org/10.1117/12.2622783

KEYWORDS: Image processing, Analytics, Multispectral imaging, Image filtering, Decision support systems, Nitrogen, Binary data, Reflectivity, Algorithm development, Satellites

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Multispectral imagery captured from aerial robots, aircraft, and satellites provides data that may be leveraged to quantify crop nitrogen (N) status. While multispectral imagery is commercially accessible, there are few systems designed to transform multispectral imagery into actionable recommendations and prescriptions for farmers. N-Time Fertigation Management System (N-Time) was developed as an autonomous software decision support system (DSS) that analyzed multispectral imagery and applied a N recommendation algorithm to produce a binary action recommendation and accompanying prescription for an imminent fertilizer application via a center pivot irrigation system (fertigation). N-Time FMS automated the sensor-based fertigation management framework (SBFM) which utilized multispectral images of the crop canopy to inform the number and timing of fertigation applications made throughout the growing season. The framework involved a frequent (i.e. weekly) monitoring and recommendation cycle for which manual execution of computational processes for a single field required more than two hours. N-Time reduced the time requirement per field including user interaction to 7.4 minutes for 12 cm/pixel resolution multispectral imagery (i.e. UAV captured) and 3.1 min for 3 m/pixel multispectral imagery (i.e. satellite captured). N-Time also demonstrated greater than 99% agreement with computational outputs produced through manual execution with non-specialized software. During 2020 and 2021, N-Time was used to implement SBFM in research trials on approximately 320 ha of production-scale irrigated grain maize. These trials demonstrated that SBFM produced higher nitrogen use efficiency than the grower’s best management in 94% of implementations and higher profitability than the grower’s best management in 59% of implementations.

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