4.7 Article

Assessing the Effect of Drought on Winter Wheat Growth Using Unmanned Aerial System (UAS)-Based Phenotyping

期刊

REMOTE SENSING
卷 13, 期 6, 页码 -

出版社

MDPI
DOI: 10.3390/rs13061144

关键词

Unmanned Aerial System (UAS); drought monitoring; wheat breeding; phenotyping; canopy features; winter wheat phenology

资金

  1. Texas A&M AgriLife Crop Improvement Initiative
  2. Texas A&M AgriLife Research Cropping System Program
  3. Texas Wheat Producers Board
  4. USDA-NIFA Hatch Project [TEX09438]

向作者/读者索取更多资源

The study revealed that drought significantly limits wheat productivity. By utilizing unmanned aerial systems to collect data, it is possible to effectively monitor the effects of drought on wheat growth and productivity.
Drought significantly limits wheat productivity across the temporal and spatial domains. Unmanned Aerial Systems (UAS) has become an indispensable tool to collect refined spatial and high temporal resolution imagery data. A 2-year field study was conducted in 2018 and 2019 to determine the temporal effects of drought on canopy growth of winter wheat. Weekly UAS data were collected using red, green, and blue (RGB) and multispectral (MS) sensors over a yield trial consisting of 22 winter wheat cultivars in both irrigated and dryland environments. Raw-images were processed to compute canopy features such as canopy cover (CC) and canopy height (CH), and vegetation indices (VIs) such as Normalized Difference Vegetation Index (NDVI), Excess Green Index (ExG), and Normalized Difference Red-edge Index (NDRE). The drought was more severe in 2018 than in 2019 and the effects of growth differences across years and irrigation levels were visible in the UAS measurements. CC, CH, and VIs, measured during grain filling, were positively correlated with grain yield (r = 0.4-0.7, p < 0.05) in the dryland in both years. Yield was positively correlated with VIs in 2018 (r = 0.45-0.55, p < 0.05) in the irrigated environment, but the correlations were non-significant in 2019 (r = 0.1 to -0.4), except for CH. The study shows that high-throughput UAS data can be used to monitor the drought effects on wheat growth and productivity across the temporal and spatial domains.

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