Document Detail

Increasing the robustness of phenological models for Vitis vinifera cv. Chardonnay.
MedLine Citation:
PMID:  19937456     Owner:  NLM     Status:  In-Process    
Phenological models are important tools for planning viticultural practices in the short term and for projecting the impact of climate change on grapevine (Vitis vinifera) in the long term. However, the difficulties in obtaining phenological models which provide accurate predictions on a regional scale prevent them from being exploited to their full potential. The aim of this work was to obtain a robust phenological model for V. vinifera cv. Chardonnay. During calibration of the sub-models for budburst, flowering and veraison we implemented a series of measures to prevent overfitting and to give greater physiological meaning to the models. Among these were the use of experimental information on the response of Chardonnay to forcing temperatures, restriction of parameter space into physiologically meaningful limits prior to calibration, and simplification of the previously selected sub-models. The resulting process-based model had good internal validity and a good level of accuracy in predicting phenological events from external datasets. Model performance was especially high for the prediction of flowering and veraison, and comparison with other models confirmed it as a better predictor of phenology, even in extremely warm years. The modelling study highlighted a different phenological behaviour at the only mountain station, Cembra. We hypothesised that phenotypical plasticity could lead to growth rates adapting to a lower mean temperature, a mechanism not usually accounted for by phenological models.
Amelia Caffarra; Emanuele Eccel
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2009-11-25
Journal Detail:
Title:  International journal of biometeorology     Volume:  54     ISSN:  1432-1254     ISO Abbreviation:  Int J Biometeorol     Publication Date:  2010 May 
Date Detail:
Created Date:  2010-04-28     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0374716     Medline TA:  Int J Biometeorol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  255-67     Citation Subset:  IM    
IASMA Research and Innovation Centre - Fondazione Edmund Mach, Environment and Natural Resources Area, Via E. Mach, 38010 San Michele all'Adige, Trento, Italy.
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