Abstract

Unmanned aircraft systems (UAS) provide an efficient way to phenotype crop morphology with spectral traits such as plant height, canopy cover and various vegetation indices (VIs) providing information to elucidate genotypic responses to the environment. In this study, we investigated the potential use of UAS-derived traits to elucidate biomass, nitrogen and chlorophyll content in sorghum under nitrogen stress treatments. A nitrogen stress trial located in Nebraska, USA, contained 24 different sorghum lines, 2 nitrogen treatments and 8 replications, for a total of 384 plots. Morphological and spectral traits including plant height, canopy cover and various VIs were derived from UAS flights with a true-color RGB camera and a 5-band multispectral camera at early, mid and late growth stages across the sorghum growing season in 2017. Simple and multiple regression models were investigated for sorghum biomass, nitrogen and chlorophyll content estimations using the derived morphological and spectral traits along with manual ground truthed measurements. Results showed that, the UAS-derived plant height was strongly correlated with manually measured plant height (r = 0.85); and the UAS-derived biomass using plant height, canopy cover and VIs had strong exponential correlations with the sampled biomass of fresh stalks and leaves (maximum r = 0.85) and the biomass of dry stalks and leaves (maximum r = 0.88). The UAS-derived VIs were moderately correlated with the laboratory measured leaf nitrogen content (r = 0.52) and the measured leaf chlorophyll content (r = 0.69) in each plot. The methods developed in this study will facilitate genetic improvement and agronomic studies that require assessment of stress responses in large-scale field trials.

Highlights

  • Following rice, wheat, corn, and barley, sorghum is the fifth most important cereal crop worldwide (Ramatoulaye et al, 2016)

  • When used individually in the simple exponential models, either normalized difference red edge (NDRE) or RGB vegetation index (RGBVI) resulted in lower correlations (r = 0.66 for NDRE, r = 0.57 for RGBVI); the combination of them using the multiple exponential model largely improved the correlation with fresh biomass (r = 0.82)

  • The moderate to strong correlations (r varied from 0.55 to 0.88) found between the Unmanned aircraft systems (UAS)-derived plant morphological and spectral traits and the sorghum late-season biomass, nitrogen, and chlorophyll contents in this study indicates that UAS should be useful for phenotyping

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Summary

Introduction

Wheat, corn, and barley, sorghum is the fifth most important cereal crop worldwide (Ramatoulaye et al, 2016). It is widely used in human consumption, animal feed, and biofuel production (Stanton et al, 2017). Sorghum Phenotyping Using UAS (63.93 million tons) (FAOSTAT, 2017). Serving as the biomass crop for biofuel production, sorghum has the advantages of an annual growth cycle, high caloric value, and low management cost (Fernandes et al, 2018). The benefits of sorghum as a biomass crop could be further enhanced if genotypes with high tolerance to stresses such as reduced nitrogen or water deficit can be more identified, which will be facilitated by integrating sorghum genotyping and phenotyping technologies

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