High-throughput physiological phenotyping of crop evapotranspiration at the plot scale

Authors: BAI, G - University Of Nebraska; BURDETTE, B - Utah State University; SCOBY, D - University Of Nebraska; IRMAK, S - Pennsylvania State University; LUCK, J - University Of Nebraska; NEALE, C - University Of Nebraska; SCHNABLE, J - University Of Nebraska; AWADA, G - University Of Nebraska; Kustas, William - Bill; GE, Y - University Of Nebraska

Submitted to: Field Crops Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/8/2024
Publication Date: N/A
Citation: N/A

Interpretive Summary: Developing drought-resistant crop varieties is an essential method to enhance crop yield and ensure food security under changing climate conditions. Platforms and instrumentation for Field High-Throughput Plant Phenotyping (FHTPP) are well developed to measure important traits in crop breeding. However, the plant phenotyping research has not focused on determining a key plant physiological process, crop water use or evapotranspiration (ET) that is strongly linked to crop yield. In this study, a novel method to integrate phenotyping data from a FHTPP system, the two-source energy balance model, and reference ET from weather data to estimate plot-scale ET is tested on five field experiments involving maize and soybean over two growing seasons. The results show that plot-scale accumulated ET captured the seasonal trend of plot water use and clearly differentiated irrigation treatments. Strong linear relationships are observed between plot-scale accumulated ET and grain yield, and appeared to be a more steady and stronger predictor of grain yield across the seasons than several other traditional plant traits. These results suggest that estimation of ET at small plot scale with this methodology will allow physiologists and breeders to effectively conduct phenotyping of water-use related traits and drought response evaluation in relation to yield potential of different crop varieties.

Technical Abstract: Platforms and instrumentation for Field High-Throughput Plant Phenotyping (FHTPP) are well developed to measure important traits in crop breeding. However, the research has focused on morphological and spectral traits; and approaches to estimate major physiological processes such as evapotranspiration (ET) for small experimental plots are lacking. In this study, we put forward a novel method to integrate phenotyping data (multispectral and thermal infrared images, canopy reflectance, and LiDAR point clouds) from a FHTPP system (NU-Spidercam), a simplified two-source energy balance model, and reference ET from weather data to estimate plot-scale ET. The method was tested on five field experiments involving maize and soybean over two growing seasons. The result showed that plot-scale accumulated ET captured the seasonal trend of plot water use and clearly differentiated irrigation treatments. Strong linear correlations were observed between plot-scale ET and grain yield, with R2 values ranging from 0.35 to 0.93. Plot-scale ET appeared to be a more steady and stronger predictor of grain yield across the seasons than several other morphological and spectral traits. This work enables the estimation of ET at small plot scale and empowers physiologists and breeders for high-throughput phenotyping of water-use related traits and drought response evaluation.