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Table_7_Comparative Aerial and Ground Based High Throughput Phenotyping for the Genetic Dissection of NDVI as a Proxy for Drought Adaptive Traits in Durum Wheat.XLSX

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NIAID Data Ecosystem2026-03-10 收录
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https://figshare.com/articles/dataset/Table_7_Comparative_Aerial_and_Ground_Based_High_Throughput_Phenotyping_for_the_Genetic_Dissection_of_NDVI_as_a_Proxy_for_Drought_Adaptive_Traits_in_Durum_Wheat_XLSX/7505084
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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.

高通量表型平台(High-throughput phenotyping platforms, HTPPs)为更高效解析干旱适应性性状的遗传基础提供了全新机遇。本研究依托全基因组关联分析(Genome-wide Association Study, GWAS),对比了两套无人机(Unmanned Aerial Vehicles, UAVs)与一套地面平台,在248份优良硬粒小麦(Triticum turgidum L. ssp. durum Desf.)种质材料中,于不同生育阶段及水分调控条件下测得的归一化差异植被指数(Normalized Difference Vegetation Index, NDVI)结果。 研究结果表明,空中平台检测NDVI相关数量性状位点(Quantitative Trait Loci, QTL)的能力优于地面平台,尤其在终端干旱胁迫环境下:前者共检测到22个单QTL,基于多QTL模型解释的表型方差达89.6%;后者仅检测到16个单QTL,对应表型方差解释率为64.7%。 此外,本研究还针对终端干旱胁迫下的叶片叶绿素含量(SPAD)、叶片卷曲度及干生物量开展了检测分析。最终共获得46个可跨平台影响NDVI的显著QTL,其中22个同时对叶片绿度产生影响、2个影响叶片卷曲、10个影响干生物量。 在1A、1B、2B、4B、5B、6B及7B染色体上的9个同时调控NDVI与其他干旱适应性性状的QTL热点区域中,有8个的遗传效应本身与物候期无关。
创建时间:
2018-12-24
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