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利用Airphen多光谱相机等多维度高通量研究苹果结构与功能表型

发表时间:2020-04-29 10:33:33点击:877

来源:北京博普特科技有限公司

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较近,来自法国农业科学院的科学家在Nature杂志上发表了题为Multi-scale high-throughput phenotyping of apple architectural and functional traits in orchard reveals genotypic variability under contrasted watering regimes文章,着重介绍了Airphen多光谱相机结合其它传感器进行苹果结构和功能表型研究的领域的应用。

Airphen多光谱相机是法国农业科学院与Hiphen公司开发的较先进的植物表型以及植被研究科研级物联网多光谱成像系统,代表野外植物表型研究的较高水准。北京博普特科技有限公司是法国Hiphen公司中国区总代理,全面负责其系列产品在中国市场的推广、销售和售后服务。

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Multi-scale high-throughput phenotyping of apple architectural and functional traits in orchard reveals genotypic variability under contrasted watering regimes

Despite previous reports on the genotypic variation of architectural and functional traits in fruit trees, phenotyping large populations in the field remains challenging. In this study, we used high-throughput  phenotyping methods on an apple tree core-collection  (1000 individuals) grown under contrasted watering regimes. First, architectural phenotyping  was achieved using T-LiDAR scans for estimating convex and alpha hull volumes and the silhouette to total leaf  area  ratio   (STAR). Second, a semi-empirical  index  (IPL) was computed from chlorophyll fluorescence measurements,  as a proxy for leaf photosynthesis. Last, thermal infrared and multispectral airborne imaging was used for computing  canopy temperature variations, water deficit, and vegetation indices. All traits estimated by these methods were compared to low-throughput in planta measurements. Vegetation indices and alpha hull volumes were significantly correlated with tree leaf area and trunk  cross sectional  area, while  IPL  values showed  strong  correlations with photosynthesis measurements collected on an independent  leaf dataset. By contrast, correlations between stomatal conductance and canopy temperature estimated from airborne images were lower, emphasizing discrepancies across measurement  scales. High heritability values were obtained for almost all the traits except leaf photosynthesis, likely due to large intra-tree variation. Genotypic means were used in a clustering  procedure  that defined  six classes of architectural and functional combinations. Differences between groups showed several combinations between architectural and functional traits, suggesting independent genetic controls. This study demonstrates the feasibility and relevance of combining multi-scale high-throughput  methods and paves the way to explore the genetic  bases of architectural and functional variations in woody crops in field conditions.


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