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Combining mechanistic models of plant rsponse to water stress and plant-based sensors in irrigation scheduling: a bet for a present and future

AutorDíaz-Espejo, Antonio ; Álvarez Garrido, Rafael; Hernández Santana, V.
Fecha de publicación8-jun-2015
EditorInternational Society for Horticultural Science
CitaciónVIII International Symposium on Irrigation of Horticultural Crops (2015)
ResumenThe improvement in the optimization of water use in agriculture goes through two key master pillars: first, our knowledge enhancement on the mechanisms of plant response to waterstress,which will help us to put into physiologlcal context the degree of stress that environmental and cultural practices impose on crops; second, manner to remote sensing data at the farm level, is not straight forward and the introduction of baselines or threshold values add a strong empirical component which weaken their wide use. On the other hand, although in the last decades many experiences have conducted in the most important agronomical species to identify water stress indicators, like threshold values of stem water poten ti al, their real meaning in the context of water stress and their consequences in yield and crop performance is not fully understood yet. Process-based models with a strong physiological basis are essential tools to achieve this, since they can integrate many aspects simultaneously, often studied independently. In the last decade we have achieved remarkable improvements in the comprehension of the response of plants to water stress and on how to quantify it. In this way, process-based models of stomatal conductance, quantitative analysis of limitation to photosynthesis and quantitative analysis of limitation to stomatal conductance by hydraulic and non-hydraulic factors are the monitoring of whole farms or orchards, as well as single plants, either with remote sensing techniques or plant-based sensors, or both. currently, the use of only one of these options has been shown to produce unsatisfactory results. The interpretation of plant-based sensors like sap flow, dendrometers or leaf turgor, m like available, which allow us not only to understand the current stress level of the plant, but also to predict in advance its evolution as a function of the weather forecast or irrigation scheduled. In this work we have applied these process-based models in commercial agronomical systems: a vineyard in Ribera del Duero, a tomato plantation in a greenhouse in Almeria and a hedgerow olive orchard in Seville. The three systems were highly monitored with sap flow sensors, dendrometers and physiological measurements. Our goal was to integrate all the information using process-based models, plant monitoring and weather forescast, and to simplify it, so it can be easily used to manage and to take decisions on irrigation scheduling. This is a first step forward to satisfy the demand of farm managers who, despite of recognizing the potential in the on-line monitoring of plant performance, claim for a simplification of overwhelming multivariable screens offered in these applications by companies.
DescripciónPoster presentado en el VIII International Symposium on Irrigation of Horticultural Crops Junio 8-11 Lérida (España) (2015)
URIhttp://hdl.handle.net/10261/132787
Aparece en las colecciones: (IRNAS) Comunicaciones congresos
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