Comparative Aerial and Ground Based High Throughput Phenotyping for the Genetic Dissection of NDVI as a Proxy for Drought Adaptive Traits in Durum Wheat.

Giuseppe E Condorelli,Marco Maccaferri,Maria Newcomb,Roberto Tuberosa,Giuseppe Sciara,Jeffrey W White,Andrew N French,Rick Ward,Pedro Andrade-Sanchez

doi:10.3389/fpls.2018.00893

Abstract

High-throughput phenotyping platforms (HTPPs) provide novel opportunities to more effectively dissect the genetic basis of drought-adaptive traits. This genome-wide association study (GWAS) compares the results obtained with two Unmanned Aerial Vehicles (UAVs) and a ground-based platform used to measure Normalized Difference Vegetation Index (NDVI) in a panel of 248 elite durum wheat (Triticum turgidum L. ssp. durum Desf.) accessions at different growth stages and water regimes. Our results suggest increased ability of aerial over ground-based platforms to detect quantitative trait loci (QTL) for NDVI, particularly under terminal drought stress, with 22 and 16 single QTLs detected, respectively, and accounting for 89.6 vs. 64.7% phenotypic variance based on multiple QTL models. Additionally, the durum panel was investigated for leaf chlorophyll content (SPAD), leaf rolling and dry biomass under terminal drought stress. In total, 46 significant QTLs affected NDVI across platforms, 22 of which showed concomitant effects on leaf greenness, 2 on leaf rolling and 10 on biomass. Among 9 QTL hotspots on chromosomes 1A, 1B, 2B, 4B, 5B, 6B, and 7B that influenced NDVI and other drought-adaptive traits, 8 showed per se effects unrelated to phenology.

Highlights

Global warming and the increasing frequency and severity of drought events unequivocally underline the urgency to select crops able to sustain growth in rainfed conditions, when grown in Mediterranean countries, where climatic change is expected to exacerbate yield uncertainty (Ortiz et al, 2008; Kelley et al, 2015; Kyratzis et al, 2017)
This study compared Normalized Difference Vegetation Index (NDVI) field phenotyping based on the emerging Unmanned Aerial Vehicles (UAVs)-based platforms vs. the standard ground-based methods targeting an elite durum wheat collection suitable for genome-wide association study (GWAS) analysis and representative of global durum breeding
The durum panel proved informative for the identification of quantitative trait loci (QTL) for NDVI, Soil-Plant Analysis Development (SPAD), leaf rolling (LR), and biomass

Summary

Introduction

Global warming and the increasing frequency and severity of drought events unequivocally underline the urgency to select crops able to sustain growth in rainfed conditions, when grown in Mediterranean countries, where climatic change is expected to exacerbate yield uncertainty (Ortiz et al, 2008; Kelley et al, 2015; Kyratzis et al, 2017). The selection of drought-resistant cultivars increasingly relies on the use of yield-related proxies selected either directly (Reynolds and Tuberosa, 2008) or via marker-assisted selection once the quantitative trait loci (QTLs) underpinning the variability of the relevant trait are identified (Langridge and Reynolds, 2015; Maccaferri et al, 2016; Mason et al, 2018). A potential limitation of ground-based phenotyping platforms is the considerably longer time required to complete the measurements as compared to UAV-based remote sensing which allows phenotyping over a larger area in less time, an important prerequisite to minimize the effects due to daily fluctuations in environmental conditions, inevitable in large-scale experiments (Tuberosa, 2012). A potential advantage of ground-based platforms is the increased data resolution as result of shorter distances between sensors and plant targets. Empirical data are needed to compare benefits of the different platforms for different experimental objectives

Methods

Results

Discussion

Conclusion