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Assessing grapevine phenological models under Chinese climatic conditions

Abstract : The objective of this work was to carry out a 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 utilised 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 using the different phenological models. The simulation dates and the actual dates were compared and the performance of the models was assessed for the 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 the limited Chinese observations. The impact of soil-burying management on budburst simulation was also discussed. These results highlight the strengths of some phenological models for use in China. This study also reiterates the strong need for the establishment of a grapevine phenology observation network in China to obtain more comprehensive data.
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https://hal.inrae.fr/hal-03150362
Contributor : Virginie Lelièvre <>
Submitted on : Tuesday, February 23, 2021 - 5:00:23 PM
Last modification on : Wednesday, February 24, 2021 - 3:07:26 AM

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Xueqiu Wang, Hua Li, I. García de Cortázar-Atauri. Assessing grapevine phenological models under Chinese climatic conditions. OENO One, Institut des Sciences de la Vigne et du Vin (Université de Bordeaux), 2020, ⟨10.20870/oeno-one.2020.54.3.3195⟩. ⟨hal-03150362⟩

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