Ludovisi Riccardo, Tauro Flavia, Salvati Riccardo, Khoury Sacha, Mugnozza Scarascia Giuseppe, Harfouche Antoine
Department for Innovation in Biological, Agro-food and Forest Systems, University of Tuscia, Viterbo, Italy.
Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom.
Front Plant Sci. 2017 Sep 27;8:1681. doi: 10.3389/fpls.2017.01681. eCollection 2017.
Poplars are fast-growing, high-yielding forest tree species, whose cultivation as second-generation biofuel crops is of increasing interest and can efficiently meet emission reduction goals. Yet, breeding elite poplar trees for drought resistance remains a major challenge. Worldwide breeding programs are largely focused on intra/interspecific hybridization, whereby L. is a fundamental parental pool. While high-throughput genotyping has resulted in unprecedented capabilities to rapidly decode complex genetic architecture of plant stress resistance, linking genomics to phenomics is hindered by technically challenging phenotyping. Relying on unmanned aerial vehicle (UAV)-based remote sensing and imaging techniques, high-throughput field phenotyping (HTFP) aims at enabling highly precise and efficient, non-destructive screening of genotype performance in large populations. To efficiently support forest-tree breeding programs, ground-truthing observations should be complemented with standardized HTFP. In this study, we develop a high-resolution (leaf level) HTFP approach to investigate the response to drought of a full-sib F partially inbred population (termed here 'POP6'), whose F was obtained from an intraspecific controlled cross between genotypes with highly divergent phenotypes. We assessed the effects of two water treatments (well-watered and moderate drought) on a population of 4603 trees (503 genotypes) hosted in two adjacent experimental plots (1.67 ha) by conducting low-elevation (25 m) flights with an aerial drone and capturing 7836 thermal infrared (TIR) images. TIR images were undistorted, georeferenced, and orthorectified to obtain radiometric mosaics. Canopy temperature () was extracted using two independent semi-automated segmentation techniques, eCognition- and Matlab-based, to avoid the mixed-pixel problem. Overall, results showed that the UAV platform-based thermal imaging enables to effectively assess genotype variability under drought stress conditions. derived from aerial thermal imagery presented a good correlation with ground-truth stomatal conductance () in both segmentation techniques. Interestingly, the HTFP approach was instrumental to detect drought-tolerant response in 25% of the population. This study shows the potential of UAV-based thermal imaging for field phenomics of poplar and other tree species. This is anticipated to have tremendous implications for accelerating forest tree genetic improvement against abiotic stress.
杨树是速生、高产的林木树种，将其作为第二代生物燃料作物进行种植越来越受到关注，并且能够有效实现减排目标。然而，培育抗干旱的优良杨树仍然是一项重大挑战。全球范围内的育种计划主要集中在种内/种间杂交，其中L.是一个基本的亲本库。虽然高通量基因分型带来了前所未有的能力，可以快速解码植物抗逆性的复杂遗传结构，但将基因组学与表型组学联系起来却受到技术上具有挑战性的表型分析的阻碍。高通量田间表型分析（HTFP）依靠基于无人机（UAV）的遥感和成像技术，旨在对大群体中的基因型表现进行高精度、高效、无损的筛选。为了有效地支持林木育种计划，地面实况观测应该用标准化的HTFP进行补充。在本研究中，我们开发了一种高分辨率（叶水平）的HTFP方法，以研究一个全同胞F部分自交群体（这里称为“POP6”）对干旱的响应，其F是通过具有高度不同表型的基因型之间的种内控制杂交获得的。我们通过使用航空无人机进行低海拔（25米）飞行并拍摄7836张热红外（TIR）图像，评估了两种水分处理（充分浇水和中度干旱）对两个相邻实验地块（1.67公顷）中4603棵树（503个基因型）群体的影响。对TIR图像进行去畸变、地理参考和正射校正，以获得辐射镶嵌图。使用两种独立的半自动分割技术（基于eCognition和Matlab）提取冠层温度（），以避免混合像元问题。总体而言，结果表明基于无人机平台的热成像能够有效地评估干旱胁迫条件下的基因型变异性。在两种分割技术中，从航空热成像中得出的与地面实况气孔导度（）都呈现出良好的相关性。有趣的是，HTFP方法有助于在25%的群体中检测到耐旱响应。本研究展示了基于无人机的热成像在杨树和其他树种田间表型组学中的潜力。预计这将对加速林木抗非生物胁迫的遗传改良产生巨大影响。
