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Sade, Z
Constas, K
Carver, S.M
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Authors
Sela, S
van-Es, H
McLellan, E
Melkonian, J
Marjerison , R
Constas, K
Prince Czarnecki, J.M
Wasson, L.L
Irby, J.T
Scholtes, A.B
Carver, S.M
Beeri, O
Pelta, R
Sade, Z
Shilo, T
Topics
Precision Nutrient Management
Applications of Unmanned Aerial Systems
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Type
Oral
Poster
Year
2016
2018
2022
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1. Using the Adapt-N Model to Inform Policies Promoting the Sustainability of US Maize Production

Maize (Zea mays L.) production accounts for the largest share of crop land area in the U.S. It is the largest consumer of nitrogen (N) fertilizers but has low N Recovery Efficiency (NRE, the proportion of applied N taken up by the crop). This has resulted in well-documented environmental problems and social costs associated with high reactive N losses associated with maize production. There is a potential to reduce these costs through precision management, i.e., better application timing, use... S. Sela, H. Van-es, E. Mclellan, J. Melkonian, R. Marjerison , K. Constas

2. Soybean Maturity Stage Estimation with Unmanned Aerial Systems

Many agronomic decisions in soybean production systems revolve around crop maturity. The primary objective of this research was to evaluate the ability of UAS to determine when soybeans have reached maturity stage sufficient for harvest aid application. A producer typically applies harvest aid chemicals when he or she perceives the crop has reached a critical level of maturity (R6.5) based on a subjective assessment. A convention is to apply harvest aids when 65% of soybean pods reach a mature... J.M. Prince czarnecki, L.L. Wasson, J.T. Irby, A.B. Scholtes, S.M. Carver

3. Multi-sensor Imagery Fusion for Pixel-by-pixel Water Stress Mapping

Evaluating water stress in agricultural fields is fundamental in irrigation decision-making, especially mapping the in-field water stress variability as it allows real-time detection of system failures or avoiding yield loss in cases of unplanned water stress. Water stress mapping by remote sensing imagery is commonly associated with the thermal or the short-wave-infra-red (SWIR) bands. However, integration of multi-sensors imagery such as radar imagery or sensors with only visible and near-infra-red... O. Beeri, R. Pelta, Z. Sade, T. Shilo