<p style="text-align: justify;"><strong>Aim</strong>: To evaluate the relationship between carbon isotope ratio (δ¹³C) and wine grape viticultural and oenological performance in organic farming.</p><p style="text-align: justify;"><strong>Methods and results</strong>: The study was carried out for four years in the Chianti Classico wine production district (Central Italy), on five non irrigated vineyards conducted in organic farming. The reference variety was Sangiovese. Eleven sites were chosen for vine monitoring and grape sampling. The performance parameters were alcohol and must sugar content, sugar accumulation rate, mean berry weight, and extractable polyphenols. δ¹³C, stem water potential, and soil water availability were also monitored. Finally, soil nitrogen as well as yeast available nitrogen in the must were measured. δ¹³C was directly related to stem water potential and soil water deficit, and indicated a range of water stress conditions from none and moderate to strong. However, its relationship with viticultural and oenological results was contrary to expectation, that is, performance linearly increased along with soil moisture. On the other hand, the worst performance was obtained where both water and nitrogen were more limiting.</p><p style="text-align: justify;"><strong>Conclusions</strong>: The unexpected relationship between δ¹³C and Sangiovese performance was caused by low nitrogen availability. The studied sites all had low-fertility soils with poor or very poor nitrogen content. Therefore, in the plots where soil humidity was relatively higher, nitrogen plant uptake was favoured, and Sangiovese performance improved. Macronutrient being the main limiting factor, the performance was not lower in the plots where soil water availability was relatively larger. Therefore, the best viticultural result was obtained with no water stress conditions, at low rather than at intermediate δ¹³C values.</p><p style="text-align: justify;"><strong>Significance and impact of the study</strong>: Water nutrition is crucial for wine grape performance. δ¹³C is a method used to assess vine water status during the growing season and to estimate vine performance. A good performance is expected at moderate stress and intermediate δ¹³C values. A better knowledge of the interaction between water and nutrient scarcity is needed, as it can affect the use of δ¹³C to predict vine performance.</p>

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A new rapid method to determine the total esterase enzymatic activity of yeast cells is proposed. In a sodium phosphate buffer a p-naphthol synthetic ester is hydrolized by cells, and the released pnaphthol Is coupled with a diazonium salt (Fast Garnet GBC) in the presence of sodium dodecyl sulfate. The whole procedure Is carried out in an aqueous buffer medium, and the resulting azo dye is directly evaluated by absorbance measurement at 524 nm. The analytical results from different assays were adjusted to a fixed cell concentration with a statistical procedure. The method shows good repeatability, reproducibility and detectability, and it requires simple equipment and instruments. It is therefore suitable both for routine analysis, as industrial yeast strain screening, and for yeast physiological studies, in order to improve the aromatic quality of fermented drinks.

NMR/IRMS techniques are now widely used to assess the geographical origin of wines. The sensory profile of a wine is also an interesting method of characterizing its origin. This study aimed at elaborating chemical, isotopic, and sensory parameters by means of statistical analysis. The data were determined in some Italian white wines—Verdicchio and Fiano—and red wines—Refosco dal Peduncolo Rosso and Nero d’Avola—produced from grapes grown in two different regions with different soil and climatic conditions during the years 2009–2010. The grapes were cultivated in Veneto (northwest Italy) and Marches (central Italy). The results show that the multivariate statistical analysis PCA (Principal Component Analysis) of all the data can be a useful tool to characterize the vintage and identify the origin of wines produced from different varieties. Moreover, it could discriminate wines of the same variety produced in regions with different soil and climatic conditions.