SPIDER delta: an empirical method to extrapolate grapevine (vitis vinifera l.) water status at the whole denomination scale using delta C-13 as ancillary data
2014
Martinez-Vergara, A. | Payan, J.C. | Salançon, E. | Tisseyre, Bruno
Aims: The aim of this study is to test a method to extrapolate vine water status (estimated by the water potential; Psi) 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 (delta C-13) 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. Psi 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. delta C-13 measurements were made at harvest in 2010 on the 24 sites. The spatial model (SPIDER delta) was calibrated using Psi data from 2009 and 2010 and delta C-13 data from 2010. The quality of prediction was tested on the 2008 data, considered as an independent data set. The results show that SPIDER delta was relevant in estimating Psi at the whole appellation scale. The extrapolation model significantly improves the prediction (R-2 = 0.88) compared to a conventional method based on Psi averages across the appellation (R-2 = 0.66). Conclusion: Based on a single measurement taken at time "t" on a reference site, SPIDER delta makes it possible to estimate Psi on all sites where a delta C-13 value is available. The use of AD like delta C-13 makes it possible to consider the spatial extrapolation of Psi 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 delta C-13 to assess Psi 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.
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Эту запись предоставил National Institute for Agricultural Research