Back to Search Start Over

Assessing grapevine phenological models under Chinese climatic conditions

Authors :
Inaki Garcia de Cortazar Atauri
Xueqiu Wang
Hua Li
Northwest A and F University
Agroclim (AGROCLIM)
Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Source :
OENO One, OENO One, Institut des Sciences de la Vigne et du Vin (Université de Bordeaux), 2020, ⟨10.20870/oeno-one.2020.54.3.3195⟩, OENO One (2020)
Publication Year :
2020
Publisher :
Universite de Bordeaux, 2020.

Abstract

The objective of this work was to perform preliminary assessment of the performance of different models for the simulation of three main phenology stages (budburst, flowering, and veraison) of grapevine in China. This work utilized observations from five representative wine regions (Changli, Laixi, Shangri-La, Xiaxian, and Yanqi) and four widely cultivated grape cultivars (Cabernet Sauvignon, Cabernet Franc, Merlot, and Chardonnay) in China. The corresponding daily temperature data were used to simulate the timing of grape phenology stages based on the different phenological models. The dates based on the simulation and the actual dates were compared and the performance of these models were assessed for different cultivars and wine regions. The GDD10 model exhibited the best performance for budburst simulation in soil-burying regions, irrespective of the cultivar and location. For flowering and veraison, the optimal model varied in performance between cultivars and locations, and non-linear models exhibited better performance than linear models. In general, the performance of these models was better for the latter two stages than for budburst. The models with relatively good performance were selected for further calibration using these limited Chinese observations. The impact of soil-burying management on budburst simulation was also estimated. These results highlight the strengths of some phenological models for use in China. This study also reiterates the strong need for establishment of a grapevine phenology observation network in China to obtain more comprehensive data.

Details

ISSN :
24941271
Database :
OpenAIRE
Journal :
OENO One
Accession number :
edsair.doi.dedup.....12a99309b4f8ff637df6254a54e53050
Full Text :
https://doi.org/10.20870/oeno-one.2020.54.3.3195