Ground-Based LiDAR Improves Phenotypic Repeatability of Above-Ground Biomass and Crop Growth Rate in Wheat.

Autor:	Deery DM; CSIRO Agriculture and Food, Canberra, ACT, Australia., Rebetzke GJ; CSIRO Agriculture and Food, Canberra, ACT, Australia., Jimenez-Berni JA; CSIRO Agriculture and Food, Canberra, ACT, Australia., Condon AG; CSIRO Agriculture and Food, Canberra, ACT, Australia., Smith DJ; CSIRO Agriculture and Food, Yanco, NSW, Australia., Bechaz KM; NSW Department of Primary Industries, Yanco, NSW, Australia., Bovill WD; CSIRO Agriculture and Food, Canberra, ACT, Australia.
Jazyk:	angličtina
Zdroj:	Plant phenomics (Washington, D.C.) [Plant Phenomics] 2020 May 26; Vol. 2020, pp. 8329798. Date of Electronic Publication: 2020 May 26 (Print Publication: 2020).
DOI:	10.34133/2020/8329798
Abstrakt:	Highly repeatable, nondestructive, and high-throughput measures of above-ground biomass (AGB) and crop growth rate (CGR) are important for wheat improvement programs. This study evaluates the repeatability of destructive AGB and CGR measurements in comparison to two previously described methods for the estimation of AGB from LiDAR: 3D voxel index (3DVI) and 3D profile index (3DPI). Across three field experiments, contrasting in available water supply and comprising up to 98 wheat genotypes varying for canopy architecture, several concurrent measurements of LiDAR and AGB were made from jointing to anthesis. Phenotypic correlations at discrete events between AGB and the LiDAR-derived biomass indices were significant, ranging from 0.31 ( P < 0.05) to 0.86 ( P < 0.0001), providing confidence in the LiDAR indices as effective surrogates for AGB. The repeatability of the LiDAR biomass indices at discrete events was at least similar to and often higher than AGB, particularly under water limitation. The correlations between calculated CGR for AGB and the LiDAR indices were moderate to high and varied between experiments. However, across all experiments, the repeatabilities of the CGR derived from the LiDAR indices were appreciably greater than those for AGB, except for the 3DPI in the water-limited environment. In our experiments, the repeatability of either LiDAR index was consistently higher than that of AGB, both at discrete time points and when CGR was calculated. These findings provide promising support for the reliable use of ground-based LiDAR, as a surrogate measure of AGB and CGR, for screening germplasm in research and wheat breeding. Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2020 David M. Deery et al.)
Databáze:	MEDLINE
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