Tree architecture, canopy shape, vegetation indices and canopy surface temperature related traits in response to soil drying in an apple tree core-collection
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3 janvier 2022
- doi: 10.15454/C8IPII
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Agricultural Sciences Malus domestica tree architecture core-collection T-LiDAR multispectral imaging thermal imagingSujets proches
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Aude Coupel-Ledru et al., « Tree architecture, canopy shape, vegetation indices and canopy surface temperature related traits in response to soil drying in an apple tree core-collection », Recherche Data Gouv, ID : 10.15454/C8IPII
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This dataset comes from a core-collection of 241 apple tree varieties mostly consisting of French local or old dessert apple varieties. The collection was assessed in 2017 in the field (4-years old trees), with four trees per variety. In July 2017, irrigation was withheld for two trees per variety, while the two other trees were maintained well-irrigated. Airborne imaging (thermal and multispectral) was deployed at four dates during the month of July (on 5th, 12th, 17th and 27th July). Vegetation indices (NDVI, GNDVI, MCARI2) were calculated from multispectral images. Mean canopy surface temperature (TS) was computed from thermal images, and differences between canopy surface and air temperature (TSTA) were then calculated to account for potential climate variations between dates. Two measurement campaigns were performed with a T-LiDAR scanner: one in October 2017 on leafy trees, and one in February 2018. Summer variables provided information on the canopy shape: alpha hull volume (a_volume), convex hull volume (c_volume) and plant height (height). c_volume represents the maximal space occupation of the tree, whereas a_volume represents the volume filled by leaves within this convex hull. For assessing light interception variables, we computed the STAR (Silhouette to Total Leaf Area Ratio). Finally, a convexity index (ci) correlated with STAR was computed as the ratio a_volume/c_volume. Winter scans were used to estimate tree architecture-related variables: the number of axes (nb_axes) and the total cumulative axis length (total_length) per tree. Along with genotypic data (https://doi.org/10.15454/F5XIVJ), this dataset was used to perform GWAS to detect SNPs associated with tree architecture, light interception and canopy surface temperature with the ultimate goal of assessing to which extent these architectural and functional traits do or do not share a common genetic origin (Coupel-Ledru et al., 2022). All methods regarding images and scans processing can be found in: Coupel-Ledru et al., 2019 Hort Res, DOI : 10.1038/s41438-019-0137-3 ; Pallas et al., 2020 Acta Hort, DOI: 10.17660/ActaHortic.2020.1281.82 ; Coupel-Ledru et al. 2022 New Phyt (in press).