Facilitating mapping and understanding of within-vineyard variation in fruit composition using data pooled from multiple vineyards

Background and Aims A large number of fruit samples is required for adequate variogram estimation, making the development of prescriptive maps for vineyard management cost prohibitive for most growers. The project assessed the efficacy of aggregating samples from multiple vineyards, over multiple years, to estimate a 'common' variogram that could be generated and applied more efficiently. Methods and Results Fifteen hundred berry samples were collected over 3 years (2017-2019) in four vineyards in California for analysis of fruit composition and spatial variability. Maps were produced for anthocyanins, malic acid and beta-damascenone in each vineyard using four separate aggregations of samples and showed only subtle changes in patterns of spatial variability in any of the three analytes assessed. A common variogram generated without points from the vineyard to be mapped indicated lower kriging variances over 100 simulations and was able to correctly classify up to 70% of sample values. Conclusions The use of a common variogram in describing spatial variability in vineyards adds important statistical support to the generation of robust maps that could be used for targeted vineyard management. Grower collaboration across multiple regional vineyards could therefore improve mapping support for all involved. Though high-density sampling may still be required in some cases, once stable zones of fruit quality have been characterised, the sample size could potentially be reduced in subsequent years. Significance of the Study Maps produced from combined datasets collected from multiple vineyards and years could provide growers and wineries more confidence in zonal management by showing the temporal stability of the spatial variability of several aspects of fruit quality.