Understanding variability in winegrape production systems

Spatial variability in winegrape yield was studied over several vintages in blocks planted to Cabernet Sauvignon, Merlot and Ruby Cabernet in the Coonawarra, Clare Valley and Sunraysia regions of Australia using new yield monitoring technology, a differentially corrected global positioning system (GPS), a geographical information system and some simple methods of spatial analysis. In any given year, yield was highly variable and typically of the order of 10 fold (i.e. 2 to 20 t/ha). However, through the use of k‐means clustering and a method based on assessment of the probability of achieving yield targets relative to the mean annual block yield, temporal stability in the patterns of yield variation was demonstrated, even though there were substantial year to year differences in mean annual yield in these blocks. The methods used to demonstrate temporal stability in the patterns of yield variation also promote identification of zones of characteristic performance within variable vineyard blocks. Of significance in this work was the finding that, whilst k‐means clustering is the more statistically robust of the two methods used, the ability to incorporate expert knowledge into the yield target method enhances the ability of the manager to accommodate the effects of abnormal events (e.g. an unusually cold flowering period) in the zone identification process. Targeted harvesting of different zones, followed by comparison between commercial lots of wine, provided indication that wine characteristics vary from zone to zone. However, the ranking of wine scores for the various zones changed between seasons. Our results have important implications for the adoption of Precision Viticulture. In particular, they support the introduction of a system of zonal vineyard management. Thus, rather than being managed uniformly, individual blocks can be split into zones in which the management of both inputs to, and outputs from the production system can be applied differentially.     

Understanding variability in winegrape production systems 2. Within vineyard variation in quality over several vintages

Spatial variability in various indices of winegrape quality was studied over several vintages in blocks planted to Cabernet Sauvignon and Ruby Cabernet in the Coonawarra (1999–2002) and Sunraysia (2000–2002) regions of Australia. At both sites, inter‐annual variation was marked whilst intra‐annual variation was much greater for some indices (e.g. concentration of total phenolics) than others (e.g. Baumé). The magnitude of intra‐annual variation was readily identified in terms of the ‘spread’, defined as the difference between the maximum and minimum values, expressed as a % of the median value. Typical values of the spread were 20% for Baumé, but could be as high as 117% for phenolics, and better indicated the extent of variation facing the winemaker than the coefficient of variation (CV; typically 3% for Baumé and 14% for phenolics). For all attributes, variation in any given year showed marked spatial structure, with the patterns of variation being broadly consistent for each attribute in each year of the study, and with many attributes following similar patterns. The results therefore strongly support the idea of zonal vineyard management. However, fruit quality zone identification is dependent on a large sampling effort. Therefore, given the current availability of yield monitors, the finding that between‐zone differences in quality indices were generally significant (P < 0.05) for zones identified on the basis of yield alone, and, in the absence of an on‐the‐go sensing capability, it is suggested that zonal management should proceed on the basis of zones of characteristic yield productivity. Based on the present work, it is suggested that development of an on‐the‐go fruit quality sensing technology would enable the wine industry to maximise its opportunity to gain benefit from differential vineyard management such as selective harvesting. Indeed, the results of this work suggest that in the absence of zonal management, preferably supported by on‐the‐go quality sensing, winemaker demands for delivery of uniform parcels of fruit are unlikely to be satisfied.     

Analytic solutions to modelling exponential and harmonic functions using Chebyshev polynomials: fitting frequency-domain lifetime images with photobleaching

A novel approach is introduced for modelling linear dynamic systems composed of exponentials and harmonics. The method improves the speed of current numerical techniques up to 1000-fold for problems that have solutions of multiple exponentials plus harmonics and decaying components. Such signals are common in fluorescence microscopy experiments. Selective constraints of the parameters being fitted are allowed. This method, using discrete Chebyshev transforms, will correctly fit large volumes of data using a noniterative, single-pass routine that is fast enough to analyse images in real time. The method is applied to fluorescence lifetime imaging data in the frequency domain with varying degrees of photobleaching over the time of total data acquisition. The accuracy of the Chebyshev method is compared to a simple rapid discrete Fourier transform (equivalent to least-squares fitting) that does not take the photobleaching into account. The method can be extended to other linear systems composed of different functions. Simulations are performed and applications are described showing the utility of the method, in particular in the area of fluorescence microscopy.     

Vineyard variability in Marlborough,New Zealand: characterising spatial and temporal changes in fruit composition and juice quality in the vineyard

Background and Aims: Previous work has demonstrated that vineyards are spatially variable and that this variability can be understood in terms of the underlying characteristics of the land (soils, topography) supporting the vineyard. Selectively harvesting blocks in response to such variability may be highly profitable. While it has also been shown that crop maturation is spatially variable, there may also be temporal variations in the rate of maturation. Integrating knowledge of how spatial variation in fruit composition may be moderated in time has not previously been attempted and is the key objective in this work. Methods and Results: We used a proximal sensor to map vine vigour at high spatial resolution in a 5.9‐ha Marlborough vineyard planted with Sauvignon Blanc. Vigour measurements were also related to fruit‐soluble solids (SS), titratable acidity (TA) and pH – key indices of crop maturity. Knowledge of crop phenology and maturation was used to predict how these indices changed with time. The pooled opinions of over 50 Marlborough winemakers on the optimum juice SS, pH and TA at harvest to produce a ‘typical Marlborough Sauvignon Blanc’ were used to develop a juice index (JI), which in turn was mapped in space and time at the study site. The JI showed marked spatial and temporal variation. Conclusions: In addition to being spatially variable, grape quality in vineyards also changed with time. Thus, the optimisation of decisions about harvest timing requires knowledge of spatial variability. Conversely, strategies such as selective harvesting cannot be properly optimized without knowledge of crop phenology, the maturation of fruit and their implications for fruit quality – which are all also spatially variable. In this study, we have shown that, by integrating knowledge of crop phenology with an understanding of vineyard variability and winemaker objectives through the construction of a JI, it is possible for the optimum harvest decision to be made such that fruit destined for a particular end use are harvested at the right time and from the right place. Significance of the Study: This is the first study in which knowledge of both spatial and temporal vineyard variation has been integrated. It demonstrates that in order to be optimal, strategies such as selective harvesting need to incorporate knowledge of crop phenology rather than rely on knowledge of spatial variation alone.