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Aim: Shoot thinning is a common canopy management practice used to obtain a desired shoot density and to improve canopy microclimate. Since thinning is often carried out manually, the cost can be high. In this study the effect of severe shoot thinning (50 % of shoots removed) applied at EL 15 was investigated by comparing yield components, canopy size, berry and wine chemistry, and sensory attributes to a non-thinned control for the variety Semillon. The objective was to determine whether shoot thinning could change canopy architecture and lead to improved fruit and wine chemistry and sensory characteristics. Methods and results: The trial was carried out over four consecutive growing seasons (starting in 2014-15) in the Semillon block of the Coombe vineyard (Waite Campus, the University of Adelaide). Canopy architecture was monitored at key phenological stages in each season and yield components were assessed at harvest. The harvested fruit was used for chemical and sensory analysis of the berries. Wines were made and their chemistry and sensorial attributes assessed. Shoot thinning reduced the total leaf area in only two of the four seasons, but single shoot leaf area and cane weight were higher in shoot-thinned vines in all seasons. Shoot thinning did not reduce yield, despite a large reduction in bunch number, because of increased bunch weight. Shoot thinning did not change berry and wine chemistry. Similarly, little differences were observed in the sensory profile of berries and wines, and the assessors preferred the wines obtained from shoot thinned vines in the last season only. Conclusions: In this study, shoot thinning increased the leaf area per shoot and the cane weight, but yield and grape and wine chemistry were unaffected. The vine balance indices leaf area/yield and yield/pruning weight were also unaffected by the treatment, despite its intensity (50 % of shoots removed). Significance and impact of the study: The practice of shoot thinning when applie

Bushfires are becoming more frequent and intensive due to changing climate. Those that occur close to vineyards can cause smoke contamination of grapevines and grapes, which can affect wines, producing smoke-taint. At present, there are no available practical in-field tools available for detection of smoke contamination or taint in berries. This research proposes a non-invasive/in-field detection system for smoke contamination in grapevine canopies based on predictable changes in stomatal conductance patterns based on infrared thermal image analysis and machine learning modeling based on pattern recognition. A second model was also proposed to quantify levels of smoke-taint related compounds as targets in berries and wines using near-infrared spectroscopy (NIR) as inputs for machine learning fitting modeling. Results showed that the pattern recognition model to detect smoke contamination from canopies had 96% accuracy. The second model to predict smoke taint compounds in berries and wine fit the NIR data with a correlation coefficient (R) of 0.97 and with no indication of overfitting. These methods can offer grape growers quick, affordable, accurate, non-destructive in-field screening tools to assist in vineyard management practices to minimize smoke taint in wines with in-field applications using smartphones and unmanned aerial systems (UAS).

Leaf area index (LAI) and plant area index (PAI) are common and important biophysical parameters used to estimate agronomical variables such as canopy growth, light interception and water requirements of plants and trees. LAI can be either measured directly using destructive methods or indirectly using dedicated and expensive instrumentation, both of which require a high level of know-how to operate equipment, handle data and interpret results. Recently, a novel smartphone and tablet PC application, VitiCanopy, has been developed by a group of researchers from the University of Adelaide and the University of Melbourne, to estimate grapevine canopy size (LAI and PAI), canopy porosity, canopy cover and clumping index. VitiCanopy uses the front in-built camera and GPS capabilities of smartphones and tablet PCs to automatically implement image analysis algorithms on upward-looking digital images of canopies and calculates relevant canopy architecture parameters. Results from the use of VitiCanopy on grapevines correlated well with traditional methods to measure/estimate LAI and PAI. Like other indirect methods, VitiCanopy does not distinguish between leaf and non-leaf material but it was demonstrated that the non-leaf material could be extracted from the results, if needed, to increase accuracy. VitiCanopy is an accurate, user-friendly and free alternative to current techniques used by scientists and viticultural practitioners to assess the dynamics of LAI, PAI and canopy architecture in vineyards, and has the potential to be adapted for use on other plants.

The wine industry worldwide is under considerable long-term pressure because of climate change, resulting in increased water scarcity and rising operational costs. The Vineyard of The Future (V oF) is an intemational and multidisciplinary initiative to establish fully instrumented vineyards for clirnate change research. One of the strategies proposed is the use of hyperspectral irnaging as a tool to assist in the estirnation of vine water status of grapevines. In th is study, outdoors hyperspectral irnages of the whole canopy were taken from 18 fi ve-year old Sangiovese ( Vitis vinifera L.) grapevines. The vines were grown outside in 70L pots near Piacenza (Italy). Images were taken over four dates during August 2011. Images After the Chilean wine crisis in the 1980s decade, in 1994 the vineyard plantations resumed. These plantations were done under an old technological paradigm, i.e., mass selection and the obtainment of plant material from renowned vineyards, without a prior sanitary and varietal selection-making. These vineyards normal! y present a mixture of cultivars and sorne pathological problerns, such as trunk canker, virus diseases and nematodes. A grapevine cultivar found mixed within other cultivars (including Cabernet-Sauvignon, Merlot and Cót rouge), inside a vineyard cv. Carmem!re at Palmilla (Colchagua Valley, Chile), were identified by classical ampelographic description and by molecular genetic markers (RAPD and AFLP). The agronomic traits of the unidentified and problematic cultivar, which presented an inflorescence necrosis phenomena, were characterized by pheno1ogica1 tracking (in re1ation to cv. Carmenere), detailed description of flowering phenomena, flower microscope slides and assessing the effect of cane girdling on inflorescence necrosis and fruit set.