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几种预测葡萄(欧亚种葡萄)萌芽日期模型的性能。

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

作者信息

García de Cortázar-Atauri Iñaki, Brisson Nadine, Gaudillere Jean Pierre

机构信息

Unité AGROCLIM, INRA, Site Agroparc, Domaine Saint Paul, Avignon cedex 9, 84914, France.

出版信息

Int J Biometeorol. 2009 Jul;53(4):317-26. doi: 10.1007/s00484-009-0217-4. Epub 2009 Mar 12.

DOI:10.1007/s00484-009-0217-4
PMID:19280231
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.

摘要

萌芽期是葡萄(欧亚种葡萄)的一个关键物候期,其在不同地点和品种间差异很大。本研究的目的是提供一个可靠的农业气象模型,用于模拟法国各地葡萄的萌芽情况。该研究使用了来自十个葡萄品种(赤霞珠、夏瑟拉、霞多丽、歌海娜、美乐、黑皮诺、雷司令、长相思、西拉、白玉霓)和五个地点(波尔多、科尔马、昂热、蒙彼利埃、埃佩尔奈)的数据。首先,我们测试了两种常用的未考虑休眠因素的模型:基础温度为10摄氏度的生长度日(GDD(10))和里奥模型(RIOU)。这些模型的预测误差在9至21天之间。其次,研究了一种新模型(BRIN),该模型基于果树的知名公式并考虑了休眠期。BRIN模型在预测萌芽日期方面比之前的葡萄模型表现更好。对BRIN公式的组成部分(休眠计算、每小时温度的使用、基础温度)的分析解释了BRIN模型取得更好性能的原因。基础温度是主要驱动因素,而休眠期在模拟萌芽日期时并不显著。对于每个品种,我们提供了参数估计值,这些估计值在基础温度为5摄氏度时,对BRIN模型和GDD模型都表现出最佳性能。

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Towards a Stochastic Model to Simulate Grapevine Architecture: A Case Study on Digitized Riesling Vines Considering Effects of Elevated CO.建立用于模拟葡萄树结构的随机模型:以考虑高浓度二氧化碳影响的数字化雷司令葡萄树为例
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Climate Change Impacts on Plant Phenology: Grapevine () Bud Break in Wintertime in Southern Italy.气候变化对植物物候的影响:意大利南部冬季葡萄树()的芽萌动
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