Nitrogen (N) is an essential element for vine development and yield; it is also involved in the winemaking process and significantly affects wine composition. It is therefore essential to control and optimise plant N use to ensure an adequate N composition of the grapes at harvest. An improved understanding of the impact of cultivation practices on plant N metabolism would allow a better orientation of technical choices with the objective of quality and sustainability (i.e., fewer inputs, more efficiency).Our trial focused on the impacts of fertilisation and crop thinning on grape N composition. A wide crop load gradient was set up in a homogeneous plot of Chasselas (Vitis vinifera L.) in an experimental vineyard in Switzerland. Foliar urea was applied at veraison in order to compare it with an unfertilised control. Vine development and grape composition were evaluated over two years, with particular attention to the carryover effects of both fertilisation and crop thinning.Foliar N fertilisation effectively increased the amount of N in grapes at harvest in the same year, but had no impact on grape ripeness or carryover effect on year n + 1. Conversely, crop thinning improved grape maturity by reducing fruit N and C demand. Interestingly, amino N proportions could be distinguished according to crop load, while the global grape N concentration at harvest remained unchanged. Some amino acids were more affected by crop thinning than others. The concentrations of alanine, γ-aminobutyric acid (GABA), serine and threonine were reduced by crop thinning. Crop thinning had a strong carryover effect on year n + 1. The carryover impact of crop thinning on grapes in terms of both maturation index and N composition could be observed at the onset of grape ripening on year n + 1.This experiment highlighted the influence of the previous year’s agricultural practices on grape C and N accumulation before and during the ripening phase. Consequently, the modulation of grape composition at harvest should be considered over two consecutive years. These results will contribute to the improvement of predictive models and sustainable agronomic practices in perennial crops.