Brazil is the largest producer of oranges (Citrus sinensis) in the world. The nutrient management of tree orchards is designed from experiments with a limited number of varieties. This knowledge is transferred to other varieties by diagnosing tissue nutrient composition and tree demand. Compositional data analysis, has been first applied to tissue analysis of agricultural crops using centered log ratios Compositional Nutrient Diagnosis (CND-clr). The isometric log ratio (ilr) transformation is a new approach based on binary nutrient ratios and the principle of orthogonality (CND-ilr). We analyzed 11 nutrients azote nitrogen (N), sulphur (S), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), boron (B), copper (Cu), zinc (Zn), manganese (Mn), and iron (Fe) in leaf tissue samples across 108 commercial plots, i.e. 31 ‘Valencia’, 22 ‘Hamlim’, 20 ‘Pêra’, and 35 ‘Natal’. Nutrients were partitioned between macro and micronutrients as well as anionic and cationic species. The effect size of varieties over ‘Valencia’ was quantified by the mean and standard deviation of ilr values across ilr coordinates. Specific varietal nutrient profiles and ilr norms were defined. The nutrient profile of orange varieties could be classified into homogeneous groups to take advantage of fertilizer trials conducted on varieties of the same group. The Aitchison distance and a perturbation vector could be instrumental for diagnostic purposes and nutrient management.