Résumé
Training in fruit trees is aimed at improving light distribution within the tree canopy, because this is expected to improve fruit quality, namely homogenise the distribution of fruit quality parameters. Adult apple trees trained with one, two or three main axes (central leader, Ycare and Drilling, respectively) were 3D-digitised at the leafy shoot scale in 2004 and 2005 in Valais, Switzerland. Fruiting and vegetative shoots were distinguished. The digitising datasets were combined with information at the leaf scale in order to make 3D computer plants. Images of the 3D plants were used to compute the light distribution at the fruiting shoot scale within the tree. Fruit quality parameters like diameter and sugar content were measured on a sample of fruits at harvest. Light and fruit quality distribution did not show significant differences between training systems, but large differences between the two years of growth due to low blooming-return in 2005 favouring vegetative growth. All training systems showed a large range of shoot leaf irradiance and fruit quality, and fruit quality distribution was generally related to light distribution within the crown. Several spectral indices developed from the near infra-red (NIR) and shortwave infra-red (SWIR) liquid water absorption bands and two biophysical indices (REIP and [(R750-800)/(R695-740)]-1) were correlated with measures of near-surface moisture. Each species of Sphagnum exhibited a clear and well-defined spectral response to reductions in volumetric moisture content (VMC); reflecting the general water tolerance of each species, and its location in relation to the water table. Airborne imagery were also collected during 2002 for a raised bog located in W. Wales. Details regarding the integration of laboratory and airborne remote sensing data for mapping near surface hydrological conditions using the spectral reflectance characteristics of Sphagnum will also be presented