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2018
DOI: 10.5344/ajev.2018.18008
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Performance of a Chill Overlap Model for Predicting Budbreak in Chardonnay Grapevines over a Broad Range of Growing Conditions

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Cited by 5 publications
(1 citation statement)
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“…The function predicts phenology using a user-defined starting date and forcing heat data (GDD or GDH), and a dataframe for starting dates and heat requirements. Although the thermal models are highly unrealistic in a biological sense, and not recommended for most species, so far is still the best approach to estimate phenology in grapevine, as more realistic models have not demonstrated superior efficacy (Parker et al, 2011;Prats-llinàs et al, 2018), in contrast to other species like apple (Darbyshire et al, 2017), cherry (Darbyshire et al, 2020) or almond (Diez-Palet et al, 2019).…”
Section: Fruclimadapt Package Featuresmentioning
confidence: 99%
“…The function predicts phenology using a user-defined starting date and forcing heat data (GDD or GDH), and a dataframe for starting dates and heat requirements. Although the thermal models are highly unrealistic in a biological sense, and not recommended for most species, so far is still the best approach to estimate phenology in grapevine, as more realistic models have not demonstrated superior efficacy (Parker et al, 2011;Prats-llinàs et al, 2018), in contrast to other species like apple (Darbyshire et al, 2017), cherry (Darbyshire et al, 2020) or almond (Diez-Palet et al, 2019).…”
Section: Fruclimadapt Package Featuresmentioning
confidence: 99%