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首页> 外文期刊>American journal of enology & viticulture >Performance of a Chill Overlap Model for Predicting Budbreak in Chardonnay Grapevines over a Broad Range of Growing Conditions
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Performance of a Chill Overlap Model for Predicting Budbreak in Chardonnay Grapevines over a Broad Range of Growing Conditions

机译:在广泛的生长条件下使用冷重叠模型预测霞多丽葡萄萌芽的性能

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Predicting phenological stages through modeling has significant implications for planning viticultural practices and for predicting the impact of climate change on phenology. The Chill Overlap Model is based on an exponentially declining curve that integrates the demonstrated compensatory relationship between chill and heat accumulation. It also incorporates recent research-based knowledge of physiological changes during dormancy. The aim of this work was to develop parameters for a Chill Overlap Model to predict budbreak in Vitis vinifera cv. Chardonnay grapevines. We also wanted to determine if using a Chill Overlap Model could be better at predicting budbreak than previously developed phenology models. The Chill Overlap Model incorporated the use of the Dynamic chill accumulation model to quantify accumulation of chill exposure in a cultivar with a relatively low chill requirement. Budbreak timing determined in Californian and Spanish winegrape-growing regions, which have a wide range of climates, was used to establish parameters for a Chill Overlap Model for Chardonnay. The newly developed Chardonnay Chill Overlap Model did not predict budbreak better than previous models, but did highlight significant differences between the dynamics of chilling in grapevines and that in other species for which a Chill Overlap Model has been developed. Further research is needed to understand the environmental and vineyard management factors that influence the timing of budbreak to improve the model and better understand factors that influence the completion of dormancy in grapevines.
机译:通过建模预测物候阶段对规划葡萄栽培实践以及预测气候变化对物候的影响具有重要意义。 Chill Overlap模型基于指数下降的曲线,该曲线整合了已证明的冷却和蓄热之间的补偿关系。它还结合了基于研究的休眠期间生理变化的最新知识。这项工作的目的是为低温重叠模型开发参数,以预测葡萄(Vitis vinifera cv)的芽裂。霞多丽葡萄。我们还想确定使用Chill Overlap模型是否可以比以前开发的物候模型更好地预测萌芽。低温重叠模型结合了动态冷蓄积模型的使用,以量化寒冷需求相对较低的品种中冷暴露的累积。在加利福尼亚和西班牙葡萄种植区域确定的芽裂时间,这些区域气候范围广泛,用于为霞多丽的寒意重叠模型建立参数。新开发的霞多丽寒意重叠模型并没有比以前的模型更好地预测芽裂,但是确实突出了葡萄藤与其他已经开发了寒意重叠模型的物种之间的低温动态差异。需要进一步研究以了解影响芽萌发时间的环境和葡萄园管理因素,以改善模型,并更好地了解影响葡萄树休眠完成的因素。

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