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Intra-Canopy Sensing Using Multi-Rotor sUAS; A New Approach for Crop Stress Detection and Diagnosis

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  Transactions of the ASABE. (in press). (doi: 10.13031/trans.14342) @2021
Authors:   Christopher R Wiegman, Ramarao Venkatesh, Scott A. Shearer
Keywords:   Intra-Canopy Sensing, Remote Sensing, RGB Imagery, Stress Diagnosis, sUAS.

Highlights

Novel platform development for intra-canopy insertion of sensors from a multi-rotor sUAS.

Enables real time data acquisition from inside the crop canopy comparable to an ‘in-person‘ view.

System provides ideal data for utilization in modern CNN crop stress diagnosis workflows.

Abstract. Remote sensing is a critical tool in agriculture, giving producers the ability to monitor field conditions throughout the growing season. Although several remote sensing platforms are in use today, small Unmanned Aerial Systems (sUAS) provides the greatest flexibility with the highest resolution. As sUAS capabilities continue to increase (i.e., payload, flight time and speed) their potential in commercial agricultural row crop production is substantial. However, like other forms of remote sensing, traditional sUAS are limited to a nadir view of the target; only capturing the top portion of the crop canopy. Although disease epidemiology and stress origins vary, this limited view usually does not capture the impact of the stress within the initial manifestation. For example, stresses like macro-nutrient deficiencies in corn originate at the base of the plant and then move upward as nutrients translocate. By the time, the stress is detectable at the top of the canopy, the opportunity to mitigate yield loss will be limited. A new sUAS sensing technology platform is needed to sense beneath the upper portion of the canopy. The “stinger” concept, developed to meet this need, consists of a 4.0 m fiberglass rod, network, radio link and custom sensor mount. Utilizing this concept, a variety of sensors can be inserted into the crop canopy from a hovering sUAS. This “Stinger” concept, when combined with artificial intelligence (AI), significantly expands the capabilities of sUAS for diagnosis of crop stress in row crop production.

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