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Airphen多光譜表型系統在高通量研究蘋果的結構與功能表型的應用

瀏覽次數:1201 發布日期:2020-2-17  來源:本站 僅供參考,謝絕轉載,否則責任自負

最近,來自法國農業科學院的科學家在Nature雜志上發表了題為Multi-scale high-throughput phenotyping of apple architectural and functional traits in orchard reveals genotypic variability under contrasted watering regimes文章,著重介紹了Airphen多光譜相機結合其它傳感器進行蘋果結構和功能表型研究的領域的應用。
 

Airphen多光譜相機是法國農業科學院與Hiphen公司開發的較先進的植物表型以及植被研究科研級物聯網多光譜成像系統,代表野外植物表型研究的較高水準。北京博普特科技有限公司是法國Hiphen公司中國區總代理,全面負責其系列產品在中國市場的推廣、銷售和售后服務。
 

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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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