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.

Background and Aims: Flowering and fruitset are principal determinants of grapevine yield. Poor fruitset is said to limit the yield of many varieties in most regions in Australia; however, there is a lack of knowledge of the reproductive performance of most varieties under Australian conditions. Methods and Results: The reproductive performance of Vitis vinifera winegrape varieties -Cabernet Sauvignon, Chardonnay, Merlot, Nebbiolo, Pinot Noir, Sangiovese, Sauvignon Blanc, Shiraz, Tempranillo, and Zinfandel -was studied in four consecutive growing seasons (commencing in 2004/05) across a range of climatic regions from cool (Adelaide Hills) to warm (Adelaide Plains). Measures of reproductive performance included flower number per inflorescence, fruitset (%), berry number per bunch, coulure index (CI), and millerandage index (MI). Principal component analysis and agglomerative hierarchical classification were used to group the varieties into three classes of reproductive performance. Conclusions: Certain varieties have a reputation of having 'poor fruitset' that has been inferred from relatively low berry number per bunch; however, for some of these varieties, it is 'low flower number per inflorescence' rather than 'poor fruitset' that is the cause of low berry number. Significance of the Study: An improved understanding of the reproductive performance of winegrape varieties has been achieved.

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Understanding how grapevines perceive and adapt to different environments will provide us with an insight into how to better manage crop quality. Mounting evidence suggests that epigenetic mechanisms are a key interface between the environment and the genotype that ultimately affect the plant’s phenotype. Moreover, it is now widely accepted that epigenetic mechanisms are a source of useful variability during crop varietal selection that could affect crop performance. While the contribution of DNA methylation to plant performance has been extensively studied in other major crops, very little work has been done in grapevine. To study the genetic and epigenetic diversity across 22 vineyards planted with the cultivar Shiraz in six wine sub-regions of the Barossa, South Australia. Methylation sensitive amplified polymorphisms (MSAPs) were used to obtain global patterns of DNA methylation. The observed epigenetic profiles showed a high level of differentiation that grouped vineyards by their area of provenance despite the low genetic differentiation between vineyards and sub-regions. Pairwise epigenetic distances between vineyards indicate that the main contributor (23–24%) to the detected variability is associated to the distribution of the vineyards on the N–S axis. Analysis of the methylation profiles of vineyards pruned with the same system increased the positive correlation observed between geographic distance and epigenetic distance suggesting that pruning system affects inter-vineyard epigenetic differentiation. Finally, methylation sensitive genotyping by sequencing identified 3,598 differentially methylated genes in grapevine leaves that were assigned to 1,144 unique gene ontology terms of which 8.6% were associated with response to environmental stimulus. Our results suggest that DNA methylation differences between vineyards and sub-regions within The Barossa are influenced both by the geographic location and, to a lesser extent, by pruning system. Finally, we discuss how epigenetic variability can be used as a tool to understand and potentially modulate terroir in grapevine.