Thibaut Scholasch
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View article: Review of plant-based methods for assessing vine water status
Review of plant-based methods for assessing vine water status Open
Assessing vine water status is crucial to optimising cultural practices, including irrigation strategies, to guarantee environmentally and economically sustainable viticulture in a context of increasing water shortages and global warming. …
View article: Local influence of climate on grapevine: an analytical process involving a functional and Bayesian exploration of farm data time series synchronised with an eGDD thermal index
Local influence of climate on grapevine: an analytical process involving a functional and Bayesian exploration of farm data time series synchronised with an eGDD thermal index Open
Climate influence on grapevine physiology is prevalent and this influence is expected to increase with climate change. Climate influence on grapevine physiology can vary depending on the terroir. A better understanding of these local terro…
View article: State-of-the-art of tools and methods to assess vine water status
State-of-the-art of tools and methods to assess vine water status Open
Rising global air temperatures will lead to an increased evapotranspiration and altered precipitation pattern. In many regions this may result in a negative water balance during the vegetative cycle, which can augment the risk of drought a…
View article: Review of water deficit mediated changes in vine and berry physiology; Consequences for the optimization of irrigation strategies
Review of water deficit mediated changes in vine and berry physiology; Consequences for the optimization of irrigation strategies Open
The increasing risk of water deficit stress due to global warming subjects winegrowers of traditional rain fed viticulture regions to new challenges regarding vine water status assessment and possible drought mitigation strategies, such as…
View article: Evaluation of a functional Bayesian method to analyse time series data in precision viticulture
Evaluation of a functional Bayesian method to analyse time series data in precision viticulture Open
[Departement_IRSTEA]Ecotechnologies [TR1_IRSTEA]INSPIRE