Dissertation
Evaluation of water stress in horticultural crops using proximal and remote sensing techniques
Doctor of Philosophy (PhD), Washington State University
01/2018
Handle:
https://hdl.handle.net/2376/112062
Abstract
Crop stress monitoring is a critical aspect of crop management and breeding programs. In this research, sensing techniques were applied to assess plant performance under water stress in grapevine, and potato. In grapevines, multispectral and thermal infrared cameras mounted on an unmanned aerial vehicle (UAV) and an agricultural utility vehicle (AUV) were utilized to assess water stress in a Cabernet Sauvignon vineyard. Plant performance under different subsurface irrigation rates were evaluated. Visible-near infrared (350-2500 nm) spectral reflectance data were acquired from the vine leaves. In 2016, plants were irrigated (continuous and pulsed) at 30, 60, and 90 cm depth, with 15, 30, and 60% of the standard irrigation volume (100%, 0 cm depth, referred as control) established by the grower in commercial production management. In 2017, the treatments included four irrigation rates (40, 60, 80, 100%) and four irrigation depths (90, 60, 30, 0 cm). In 2016, normalized difference vegetation index (NDVI), green normalized vegetation index (GNDVI) and canopy temperature extracted from aerial images (UAV) were significantly correlated to yield and stomatal conductance (p < 0.01). Normalized multiband drought index (NMDI) and photochemical reflectance index (PRI) were also correlated to stomatal conductance. Normalized difference spectral indices (NDSI) 664-498 nm and 982-859 nm were consistently correlated with stomatal conductance. Specific spectral responses to crop stress in relationship with stomatal conductance are reported.
During 2015 and 2016 seasons, nine potato varieties under two (100 and 65%) and three (100, 65, and 45% with respect to evapotranspiration) irrigation rates, respectively, were evaluated in field. In 2016, plants were affected by early die syndrome. Proximal hyperspectral and thermal infrared images were acquired. Crop water stress index was correlated to stomatal conductance (p < -0.49). Spectral ratios were identified from hyperspectral reflectance data using techniques based on their correlations with yield. In 2015, spectral ratio 525/1305 nm was correlated with yield (irrigation treatments); while, in 2016, spectral ratio 512/2500 nm was correlated with yield (interaction between irrigation treatments and early die syndrome). The study demonstrates crop sensing as a mechanism to detect biotic and abiotic stress in plants for precision agriculture or plant phenotyping applications.
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Details
- Title
- Evaluation of water stress in horticultural crops using proximal and remote sensing techniques
- Creators
- Carlos Zuniga
- Contributors
- Sindhuja Sankaran (Advisor)Lav R Khot (Committee Member)Pete Jacoby (Committee Member)Richard N Knowles (Committee Member)Troy Peters (Committee Member)
- Awarding Institution
- Washington State University
- Academic Unit
- Department of Biological Systems Engineering
- Theses and Dissertations
- Doctor of Philosophy (PhD), Washington State University
- Number of pages
- 98
- Identifiers
- 99900581623601842
- Language
- English
- Resource Type
- Dissertation