Abstract
Improvement of crop water use efficiency (CWUE), defined as crop yield per volume of water used, is an important goal for both crop management and breeding. While many technologies have been developed for measuring crop water use in crop management studies, rarely have these techniques been applied at the scale of breeding plots. The objective was to develop a high-throughput methodology for quantifying water use in a cotton breeding trial at Maricopa, AZ, USA in 2016 and 2017, using evapotranspiration (ET) measurements from a co-located irrigation management trial to evaluate the approach. Approximately weekly overflights with an unmanned aerial system provided multispectral imagery from which plot-level fractional vegetation cover ( f c ) was computed. The f c data were used to drive a daily ET-based soil water balance model for seasonal crop water use quantification. A mixed model statistical analysis demonstrated that differences in ET and CWUE could be discriminated among eight cotton varieties ( p < 0 . 05 ), which were sown at two planting dates and managed with four irrigation levels. The results permitted breeders to identify cotton varieties with more favorable water use characteristics and higher CWUE, indicating that the methodology could become a useful tool for breeding selection.
Highlights
Drought stress arising from water deficit is a leading cause of crop production losses worldwide
The results show that the drone-based fc and soil water balance modeling approach could effectively estimate seasonal cotton water use at this field site
0.19 kg of cotton fiber was produced per m3 of water consumed (i.e., crop water use efficiency (CWUE))
Summary
Drought stress arising from water deficit is a leading cause of crop production losses worldwide. Increases in CWUE can result both from improvements in agronomic management practices [3] and by developing improved crop cultivars that yield highly under water deficit conditions [4]. These pathways are often pursued independently within disciplinary boundaries, the most comprehensive solutions towards CWUE improvement will be achieved through multidisciplinary efforts. High-throughput plant phenomics, which involves deployment of crop sensing systems for rapid phenotyping of breeding populations, has potential to guide crop improvement efforts toward cultivars with increased tolerance to drought stress [4,7,8]. Further efforts are needed to solidify the role of information technology for practical advancement towards this goal
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