Water stress assessment on grapevines by using classification and regression trees

New Labeling Rules for Wine: Wine Alcohol-Derived Calories and Polyphenol Consumption on Health

Alcohol content, proanthocyanins and anthocyanins influence wine quality. The composition of wine depends on the type of cultivar, location, environmental conditions, and management practices. Phenolic compounds have attracted considerable research interest due to their antioxidant properties and potential beneficial effects on human health. However, the low bioavailability of anthocyanins creates a major bottleneck in their ability to exert beneficial effects. Despite extensive research on the effects of wine on human health, no clear evidence has been obtained on the benefits of wine quality or geographic area of production on health conditions, such as metabolic syndrome. Five climatically and geologically distinct wines were evaluated. Based on recent studies, meta-analyses, and pooled analyses of wine composition, along with the predicted low bioavailability of polyphenol compounds, we estimated the efficacy of five geographically distinct wines according to gastrointestinal absorption and the effects of alcohol intake on both men and women, with a view to ascertaining whether geographical origin influences the antioxidant serum composition of wine. Data on the estimated consumption of wine suggest that the polyphenol contents are similar regardless of choice of wine/area, while different alcohol compositions affect the level of alcohol and calorie intake. Thus, moderate wine drinkers should be advised to control the habit, but without exceeding the dose considered a healthy threshold (up to 30-40 g of alcohol/day in men and 10-20 g of alcohol/day in women), given no medical contraindications are present. These results will add value to the framework of the last reform of the Common Agricultural Policy (CAP) adopted in December 2021, where the European Parliament and the Council introduced new labeling rules for the wine sector and aromatized wine products.

CART model to classify the drought status of diverse tomato genotypes by VPD, air temperature, and leaf-air temperature difference

Regular water management is crucial for the cultivation of tomato (Solanum lycopersicum L.). Inadequate irrigation leads to water stress and a reduction in tomato yield and quality. Therefore, it is important to develop an efficient classification method of the drought status of tomato for the timely application of irrigation. In this study, a simple classification and regression tree (CART) model that includes air temperature, vapor pressure deficit, and leaf-air temperature difference was established to classify the drought status of three tomato genotypes (i.e., cherry type 'Tainan ASVEG No. 19', large fruits breeding line '108290', and wild accession 'LA2093'). The results indicate that the proposed CART model exhibited a higher predictive sensitivity, specificity, geometric mean, and accuracy performance compared to the logistic model. In addition, the CART model was applicable not only to three tomato genotypes but across vegetative and reproductive stages. Furthermore, while the drought status was divided into low, medium, and high, the CART model provided a higher predictive performance than that of the logistic model. The results suggest that the drought status of tomato can be accurately classified by the proposed CART model. These results will provide a useful tool of the regular water management for tomato cultivation.

Leaf Area Calculation Models for Vines Based on Foliar Descriptors

In the case of foliar area studies on vines, with a large number of determinations, a simple, fast, sufficiently accurate and low-cost method is very useful. The typology of leaves on the vine is complex, characterized by several descriptive parameters: median rib; secondary venations of the first and second order; angles between the median rib and the secondary venations; sinuses; length and width of the leaf. The present study aimed to evaluate models for calculating the leaf area based on descriptive parameters and KA (KA as the surface constant used to calculate the leaf area) for six vine cultivars, ‘Cabernet Sauvignon’ (CS), ‘Muscat Iantarnîi’ (MI), ‘Muscat Ottonel’ (MO), ‘Chasselas’ (Ch), ‘Victoria’ (Vi) and ‘Muscat Hamburg’ (MH). The determined KA surface constants had subunit values (0.91 to 0.97), except for the cultivars ‘Muscat Iantarnîi’ and ‘Muscat Ottonel’ where the surface constant KA₂ (in relation to the second-order secondary venations) had supraunitary values (1.07 and 1.08, respectively). The determination of the leaf area was possible under different conditions of statistical accuracy (R² = 0.477, p = 0.0119, up to R² = 0.988, p < 0.001) in relation to the variety and parametric descriptors considered. The models obtained from the regression analysis facilitated a more reliable prediction of the leaf area based on the elements on the left side of the leaf, in relation to the median rib, compared to those on the right. The accuracy of the results was checked on the basis of minimum error (ME) and confirmed by parameters R², p and RMSE.