Service tree (Sorbus domestica L.) belongs to a large genus of plants, that in the past characterized the agricultural landscape of large areas of Europe. In the light of recent acquisitions regarding nutraceutical and functional properties of service fruits in allied Sorbus species, our work aimed at the morphological description, evaluation of fruit quality and functionalnutraceutical properties of the same accessions selected for timber, in order to identify double aptitude plants. Morphological and chemical differences among plant selections were found particularly for titratable acidity and red colour of the skin: bletting contributed to mitigate such differences. Chromatograms obtained by reversed-phase HPLC analysis indicated that the phenolic compounds present in the matrix may be assimilated to three main classes of compounds: gallic acid, its derivative and polymeric tannins. Acids and flavonols were present in much lower quantities this indicating that the main phenolic compounds nature of our service fruit selections were hydrolysable tannins. A linear and positive correlation was found between the two methods, DPPH-EPR and CAB, used to assay antioxidant capacity this indicating that easy to manage DPPH-EPR assay may be used for substrates that are high in phenols as the case of service fruits. Our original hypothesis of wide variability among trees was finally confirmed by discriminant analysis which admitted most of the recorded variables, and showed each plant selection as a case in itself.

SUMMARYA reliable evaluation of crop nutritional status is crucial for supporting fertilization aiming at maximizing qualitative and quantitative aspects of production and reducing the environmental impact of cropping systems. Most of the available simulation models evaluate crop nutritional status according to the nitrogen (N) dilution law, which derives critical N concentration as a function of above-ground biomass. An alternative approach, developed during a project carried out with students of the Cropping Systems Masters course at the University of Milan, was tested and compared with existing models (N dilution law and approaches implemented in EPIC and DAISY models). The new model (MAZINGA) reproduces the effect of leaf self-shading in lowering plant N concentration (PNC) through an inverse of the fraction of radiation intercepted by the canopy. The models were tested using data collected in four rice (Oryza sativaL.) experiments carried out in Northern Italy under potential and N-limited conditions. MAZINGA was the most accurate in identifying the critical N concentration, and therefore in discriminating PNC of plants growing under N-limited and non-limited conditions, respectively. In addition, the present work proved the effectiveness of crop models when used as tools for supporting education.