Spiderδ: an empirical method to extrapolate grapevine ( Vitis vinifera L.) water status at the whole denomination scale using δ 13 C as ancillary data

摘要

Aims: The aim of this study is to test a method to extrapolate vine water status (estimated by the water potential; Ψ) over a whole appellation (protected geographical indication). The spatial extrapolation is based on an empirical approach that combines a reference site (baseline measurements) and carbon isotope discrimination (δ13C) values as ancillary data (AD).Methods and results: Experiments were conducted on the whole Tavel appellation (Gard, France). The study focused on the dominant variety: Grenache. Ψ was measured as predawn leaf water potential and was monitored over three consecutive years, 2008, 2009 and 2010, on 10, 24 and 24 sites, respectively. δ13C measurements were made at harvest in 2010 on the 24 sites. The spatial model (SPIDERδ) was calibrated using Ydata from 2009 and 2010 and δ13C data from 2010. The quality of prediction was tested on the 2008 data, considered as an independent data set. The results show that SPIDERδ was relevant in estimating Ψ at the whole appellation scale. The extrapolation model significantly improves the prediction (R2 = 0.88) compared to a conventional method based on Ψ averages across the appellation (R2 = 0.66).Conclusion: Based on a single measurement taken at time ?t? on a reference site, SPIDERδ makes it possible to estimate Ψ on all sites where a δ13C value is available. The use of AD like δ13C makes it possible to consider the spatial extrapolation of Ψ with higher spatial resolution than when only direct measurements are used to calibrate the model.Significance and impact of the study: This work demonstrates the value of using an AD like δ13C to assess Ψ at a scale larger than the single field. This significant result opens the door to the practical use of spatial extrapolation models with higher spatial resolution. IntroductionVine water status can be highly variable at the within-field level (van Leeuwen et al. 2006), at the vineyard level (Taylor et al. 2010) and, of course, at the whole appellation level (Baralon et al. 2012). Variability in vine water status induces a great variability of vine response in terms of vigour, yield, precocity and grape composition (Tisseyre et al. 2008). Hence, characterizing the spatial variability of the vine water status is a key issue for terroir study (Seguin 1983, van Leeuwen et al. 2009), as it provides important information to manage and/or assess grape quality (van Leeuwen et al. 2009, Hakimi Rezaei and Reynolds 2010).In a review paper, Acevedo-Opazo et al. (2008) discussed the importance of methods for spatial monitoring of vine water status. Furthermore, the same authors proposed an empirical spatial model (Equation 1) to predict the vine water status (estimated with the water potential; Ψ) across a given domain (vineyard block, vineyard, region, etc.).Ψ(s,t) = as.Ψ(sre,t) [eq.1]The principle of the model is to extrapolate a reference Ψ value Ψ(sre,t) measured at a reference site sre and time t. The extrapolation is based on a linear relationship defined by the coefficients as whose values are specific to site s. The model provides an estimate Ψ(s,t) of Ψ values at any site s where a coefficient as is available. This spatial model has been successfully tested at the within-field level (Acevedo-Opazo et al. 2010a) and at a vineyard level constituted of several blocks (Taylor et al. 2011). More recently, the model has been successfully tested at the whole denomination scale by Baralon et al. (2012). At this scale, the approach was called SPIDER (SPatial extrapolation of the vIne water status at the whole DEnomination scale from a Reference site). Note that in Baralon et al. (2012), the term denomination refers to an appellation (a legally defined and protected geographical indication). The scale at which these authors have actually tested the approach is a small appellation of the south of France (Tavel) where climatic conditions where assumed homogeneous. For consistency, the term denomination was kept in this paper.At the denomination scale, SPIDER proved to be more accurate in estimating Ψ values than a classical approach based on the average of Ψ values sampled over the domain. At this scale, SPIDER may be of particular interest as a decision support tool for field selection based on the water restriction experienced by the vines (Reynard et al. 2011) or for identifying zones where irrigation is most needed. However, as outlined by Baralon et al. (2012), applying SPIDER at a large scale raised some practical limitations, of which the most important is the spatial resolution that is possible with such an approach. Indeed, the spatial resolution of the model is limited by the number of sites where as coefficients are known. The determination of as values needs Ψ to be monitored over several dates on each site s. Considering Ψ measurements are cumbersome and cost prohibitive, this practical constraint necessarily limits the number of measurements and the resulting spatial resolution of the model. One possi