Environment friendly nutrition supplying and soil cultivation methods applicable in the upper zone of hillside vineyards

Implementing artificial intelligence (AI) in viticulture and enology is a rapidly growing field of research with an essential number of potential practical applications.

Within the DOCa Rioja three main production areas are differentiated: Rioja Alta (RA), Rioja Alavesa (RAv) and Rioja Oriental (RO). They are three diverse territories with particular characteristics that are claimed to give rise to differentiated profiles. The present work aims at evaluating the sensory diversity of young commercial red wines in these three subregions. Therefore 30 young red wines (mainly Tempranillo and vintage 2021), ten from each subregion, were sensory described following a non-verbal free sorting task and a verbal free comment task by 32 well-established Rioja winemakers.

At CREA – Centro di Ricerca di Viticoltura ed Enologia, based in Velletri (RM), an experimental vineyard including 10 downy mildew resistent/tolerant grape varieties and two susceptible varieties was set up with the principal goal to evaluate the behavoir of these varieties in term of resistance to downy mildew (Plasmopara viticola). This evaluation, together to oenological studies, are necessary to register them also in Regional Register (in Lazio region). Monitoring of behavior towards Plasmopara viticulture of resistant vines were done in 2020 and 2021 at different times (phenological stages) and until harvesting, according to an international standard code BBCH a centesimal phenological scale, based on coding system.

Making high quality but affordable Pinot noir (PN) wine is challenging in most terroirs and New Zealand’s (NZ) situation is no exception. To increase the probability of making highly typical PN wines producers choose to grow grapes in cool climates on lower fertility soils while adopting labour intensive practices. Stringent yield targets and higher input costs necessarily mean that PN wine cost is high, and profitability lower, in line-priced varietal wine ranges. To understand the reasons why higher yielding vines are perceived to produce wines of lower quality we have undertaken an extensive study of PN in NZ. Since 2018, we established a network of twelve trial sites in three NZ regions to find individual vines that produced acceptable commercial yields (above 2.5kg per vine) and wines of composition comparable to “Icon” labels. Approximately 20% of 660 grape lots (N = 135) were selected from within a narrow juice Total Soluble Solids (TSS) range and made into single vine wines under controlled conditions. Principal Component Analysis of the vine, berry, juice and wine parameters from three vintages found grape berry mass to be most effective clustering variable. As berry mass category decreased there was a systematic increase in the probability of higher berry red colour and total phenolics with a parallel increase in wine phenolics, changed aroma fraction and decreased juice amino acids. The influence of berry size on wine composition would appear stronger than the individual effects of vintage, region, vineyard or vine yield. Our observations support the hypothesis that it is possible to produce PN wines that fall within an “Icon” benchmark composition range at yields above 2.5kg per vine provided that the Leaf Area:Fruit Weight ratio is above 12cm2 per g, mean berry mass is below 1.2g and juice TSS is above 22°Brix.

Validation of the phloroglucinolysis and RP-HPLC method showed selectivity and repeatability within acceptable limits for all investigated matrices. Recovery of polymeric phenols by SPE was also acceptable.