Performance of several models for predicting budburst date of grapevine (Vitis vinifera L.)

Abstract

The budburst stage is a key phenological stage for grapevine (Vitis vinifera L.), with large site and cultivar variability. The objective of the present work was to provide a reliable agro-meteorological model for simulating grapevine budburst occurrence all over France. The study was conducted using data from ten cultivars of grapevine (Cabernet Sauvignon, Chasselas, Chardonnay, Grenache, Merlot, Pinot Noir, Riesling, Sauvignon, Syrah, Ugni Blanc) and five locations (Bordeaux, Colmar, Angers, Montpellier, Epernay). First, we tested two commonly used models that do not take into account dormancy: growing degree days with a base temperature of 10 degrees C (GDD(10)), and Riou's model (RIOU). The errors of predictions of these models ranged between 9 and 21 days. Second, a new model (BRIN) was studied relying on well-known formalisms for orchard trees and taking into account the dormancy period. The BRIN model showed better performance in predicting budburst date than previous grapevine models. Analysis of the components of BRIN formalisms (calculation of dormancy, use of hourly temperatures, base temperature) explained the better performances obtained with the BRIN model. Base temperature was the main driver, while dormancy period was not significant in simulating budburst date. For each cultivar, we provide the parameter estimates that showed the best performance for both the BRIN model and the GDD model with a base temperature of 5 degrees C.

Modelling the timing of Betula pubescens budburst. II. Integrating complex effects of photoperiod into process-based models

“…Yet, the experiments conducted by Myking & Heide (1995) and Heide (1993) have shown an intermediate behaviour in partially chilled plants, with growth occurring at a lower rate. Fitting a realistic response to chilling temperatures remains a difficult task, as noted in previous studies (Linkosalo et al 2008, Garcia de Cortazar Atauri et al 2009), since dormancy release is difficult to measure and very few observations of this phenophase exist. However, phenological models have to take the dormancy phase into account in order to ensure accurate predictions of budburst dates for the future.…”

Resistance and resilience to changing climate of Tuscany and Valpolicella wine grape growing regions in Italy

“…the ability to adapt to different climates [1,2]. Although heat requirements are specific to each variety [3][4][5], the same variety grown in different regions is able to show differences of up to 300…”

Application of crop modelling to portuguese viticulture: implementation and added-values for strategic planning

“…For the Lisbon region, Malheiro et al (2013) and Fraga et al (2014a) applied a linear regression models to show that phenological timings are deeply tied to air temperatures and remote sensing indices. Many other studies assessing relationships between air temperature, remote sensing indices and grapevine phenology have been conducted worldwide (Williams et al, 1985;Chuine et al, 2003;de Cortazar-Atauri et al, 2009;Caffarra and Eccel, 2010;Bock et al, 2011;Cunha and Richter, 2012;Fila et al, 2012;Parker et al, 2013;Rodrigues et al, 2013).…”