A Direct Comparison of Remote Sensing Approaches for High-Throughput Phenotyping in Plant Breeding.

Maria Tattaris,Matthew P Reynolds,Scott C Chapman

doi:10.3389/fpls.2016.01131

Abstract

Remote sensing (RS) of plant canopies permits non-intrusive, high-throughput monitoring of plant physiological characteristics. This study compared three RS approaches using a low flying UAV (unmanned aerial vehicle), with that of proximal sensing, and satellite-based imagery. Two physiological traits were considered, canopy temperature (CT) and a vegetation index (NDVI), to determine the most viable approaches for large scale crop genetic improvement. The UAV-based platform achieves plot-level resolution while measuring several hundred plots in one mission via high-resolution thermal and multispectral imagery measured at altitudes of 30–100 m. The satellite measures multispectral imagery from an altitude of 770 km. Information was compared with proximal measurements using IR thermometers and an NDVI sensor at a distance of 0.5–1 m above plots. For robust comparisons, CT and NDVI were assessed on panels of elite cultivars under irrigated and drought conditions, in different thermal regimes, and on un-adapted genetic resources under water deficit. Correlations between airborne data and yield/biomass at maturity were generally higher than equivalent proximal correlations. NDVI was derived from high-resolution satellite imagery for only larger sized plots (8.5 × 2.4 m) due to restricted pixel density. Results support use of UAV-based RS techniques for high-throughput phenotyping for both precision and efficiency.

Highlights

High-throughput phenotyping, through the application of remote sensing tools, offers a rapid and non-destructive approach to plant screening (White et al, 2012)
The results of the current study demonstrate the advantage of airborne remote sensing as a tool to estimate a range of physiological and agronomic traits on a large scale in experimental plots
The generally strong correlations presented here between airborne indices and equivalent ground-based canopy temperature (CT) and Normalized Difference Vegetation Index (NDVI), as well as significant correlations between the airborne indices and yield/biomass, that were generally greater than the equivalent correlations with ground-based measurements, suggest that increased precision results from the use of the indices derived from imagery, in the stressed environments

Summary

Introduction

High-throughput phenotyping, through the application of remote sensing tools, offers a rapid and non-destructive approach to plant screening (White et al, 2012). Sensed spectral readings are based on the interaction between incoming radiation and target objects, resulting in a characteristic signature of reflected light. Such signatures are typically used to calculate spectral indices, which are a function of the light absorption properties of the plant at given wavelengths Based mainly on ground based proximal sensing approaches, CT shows a robust association with plant performance, especially under stress, being intimately associated with water status and stomatal conductance (Blum et al, 1982; Berliner et al, 1984; Amani et al, 1996) while NDVI can estimate relative crop biomass at different growth stages (Babar et al, 2006) as well as N deficiency and crop senescence rate (Blum et al, 1982; Reynolds et al, 1994, 1998; Raun et al, 2001; Babar et al, 2006; Olivares-villegas et al, 2007)

Methods

Results

Conclusion