Estimating Biomass and Canopy Height With LiDAR for Field Crop Breeding.

James D C Walter,Glenn Mcdonald,James Edwards,Haydn Kuchel

doi:10.3389/fpls.2019.01145

Abstract

Above-ground biomass (AGB) is a trait with much potential for exploitation within wheat breeding programs and is linked closely to canopy height (CH). However, collecting phenotypic data for AGB and CH within breeding programs is labor intensive, and in the case of AGB, destructive and prone to assessment error. As a result, measuring these traits is seldom a priority for breeders, especially at the early stages of a selection program. LiDAR has been demonstrated as a sensor capable of collecting three-dimensional data from wheat field trials, and potentially suitable for providing objective, non-destructive, high-throughput estimates of AGB and CH for use by wheat breeders. The current study investigates the deployment of a LiDAR system on a ground-based high-throughput phenotyping platform in eight wheat field trials across southern Australia, for the non-destructive estimate of AGB and CH. LiDAR-derived measurements were compared to manual measurements of AGB and CH collected at each site and assessed for their suitability of application within a breeding program. Correlations between AGB and LiDAR Projected Volume (LPV) were generally strong (up to r = 0.86), as were correlations between CH and LiDAR Canopy Height (LCH) (up to r = 0.94). Heritability (H2) of LPV (H2 = 0.32–0.90) was observed to be greater than, or similar to, the heritability of AGB (H2 = 0.12–0.78) for the majority of measurements. A similar level of heritability was observed for LCH (H2 = 0.41–0.98) and CH (H2 = 0.49–0.98). Further to this, measurements of LPV and LCH were shown to be highly repeatable when collected from either the same or opposite direction of travel. LiDAR scans were collected at a rate of 2,400 plots per hour, with the potential to further increase throughput to 7,400 plots per hour. This research demonstrates the capability of LiDAR sensors to collect high-quality, non-destructive, repeatable measurements of AGB and CH suitable for use within both breeding and research programs.

Highlights

In recent years there has been much discussion regarding the role of high-throughput phenotyping (HTP) technologies within field crop breeding programs, focused primarily on the potential of these technologies to reduce the current disparity between the amount of phenotype and genotype data available to breeders (Cobb et al, 2013; Araus and Cairns, 2014)
The current study investigates the deployment of a LiDARbased system for the non-destructive estimation of Above-ground biomass (AGB) and canopy height (CH) across multiple environments, with this system based on the High-throughput Imaging Boom (HIB) described by Walter et al (2019)
Repeatability of multiple measurements taken at Roseworthy was generally high for both LiDAR Canopy Height (LCH) and LiDAR Projected Volume (LPV) measurements at both individual sample times (Table 3) and when pooling sample times (Figure 4)

Summary

Introduction

In recent years there has been much discussion regarding the role of high-throughput phenotyping (HTP) technologies within field crop breeding programs, focused primarily on the potential of these technologies to reduce the current disparity between the amount of phenotype and genotype data available to breeders (Cobb et al, 2013; Araus and Cairns, 2014). LiDAR for Field Crop Breeding of these technologies which interest field crop breeders: i) the ability to collect data faster than traditional methods; ii) the ability to collect higher-quality objective data than traditional methods; and (iii) the ability to collect data which cannot be collected through existing methods With these three aspects in mind, the trait of above-ground biomass (AGB) is a prime candidate to benefit from the potential advantages offered by HTP technologies. Above-ground biomass is traditionally measured through laborious and destructive methods, requiring crop cuts to be collected from field plots and dried in an oven before being weighed to assess the dry biomass of each sample This multistep process is prone to error, from variability in the area within the plot sampled, to the potential loss of material while cutting, transporting, and handling samples. For bread wheat (Triticum aestivum L.), AGB has been identified as a trait with much potential to exploit within breeding programs, in relation to yield improvements through harvest index and radiation use efficiency (Reynolds et al, 2012), water use efficiency (Richards et al, 2002), drought tolerance (Fischer and Wood, 1979), as well as potential advantages in crop competitiveness (Zerner et al, 2016)

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Discussion

Conclusion