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• W3028452367 abstract "Crop improvement is necessary for food security asthe global population is expected to exceed 9 billion by 2050. Limitations in water resources and more frequentdroughts and floods will make it increasingly difficult to manage agriculturalresources and increase yields. Therefore, we must improve our ability to monitoragronomic research plots and use the information they provide to predictimpacts of moisture stress on crop growth and yield. Towards this end, agronomistshave used reductions in leaf expansion rates as a visible ‘plant-based’indicator of moisture stress. Also, modeling researchers have developed crop modelssuch as AquaCrop to enable quantification of the severity of moisture stressand its impacts on crop growth and yield. Finally, breeders are using UnmannedAircraft Systems (UAS) in field-based High-Throughput Phenotyping (HTP) toquickly screen large numbers of small agronomic research plots for traitsindicative of drought and flood tolerance. Here we investigate whether soybeancanopy cover and color time series from high-resolution UAS ortho-images can becollected with enough spatial and temporal resolution to accurately quantifyand differentiate agronomic research plots, pinpoint the timing of the onset ofmoisture stress, and constrain crop models such as AquaCrop to more accuratelysimulate the timing and severity of moisture stress as well as its impacts oncrop growth and yield. We find that canopy cover time series derived frommultilayer UAS image ortho-mosaics can reliably differentiate agronomicresearch plots and pinpoint the timing of reductions in soybean canopyexpansion rates to within a couple of days. This information can be used toconstrain the timing of the onset of moisture stress in AquaCrop resulting in amore realistic simulation of moisture stress and a lower likelihood ofunderestimating moisture stress and overestimating yield. These capabilitieswill help agronomists, crop modelers, and breeders more quickly developvarieties tolerant to moisture stress and achieve food security." @default.
• W3028452367 created "2020-05-29" @default.
• W3028452367 creator A5046948414 @default.
• W3028452367 date "2019-06-10" @default.
• W3028452367 modified "2023-09-23" @default.
• W3028452367 title "Remote Sensing of Soybean Canopy Cover, Color, and Visible Indicators of Moisture Stress Using Imagery from Unmanned Aircraft Systems" @default.
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