Evaluación de la respuesta del cerezo al déficit hídrico para la optimización del manejo del riego"

Dirigée par:
  1. Rafael Domingo Miguel Directeur
  2. Roque Torres Sánchez Directeur

Université de défendre: Universidad Politécnica de Cartagena

Fecha de defensa: 30 juin 2022

  1. Gregorio Egea Cegarra President
  2. Fulgencio Soto Vallés Secrétaire
  3. Alejandra Juana Navarro García Rapporteur

Type: Thèses


Resumen de la tesis: This thesis evaluates the sweet cherry trees responses to different water stress intensities, durations, and time of water stress onset, which could help us understand the physiological, agronomic, and morphological responses to water stress and environmental conditions in semi-arid zones, where water is a limiting factor and evaporative demand is high. Based on this objective, several experiments were conducted to assess the sweet cherry’s response to water stress and the suitability of different technologies to estimate plant water status and crop yield. Thus, three lines of research were carried out: (i) adaptive mechanisms to water deficit in cherry trees; (ii) remote sensing to estimate plant water status and fruit yield; and (iii) effects of water deficit and environmental conditions on the reproductive response of sweet cherry. The main conclusions drawn from this thesis are: i) drought-adaptive mechanisms developed by cherry trees are aimed to postpone water deficit rather than increase the tree's tolerance to water deficit conditions, ii) deficit irrigation applied during the post-harvest stage did not increase the occurrence of double fruits the following season, however, high air temperature during the 30 days after the harvest date did, iii) the fruit size, one of the most important quality characteristics of sweet cherries, was affected by the crop load as well as by the tree's leaf area, which is the main source for exporting assimilates to sinks (fruits), iv) remote sensing provides useful information about the water and agronomic status of the trees, which is crucial for the optimization of regulated deficit irrigation, and v). the information derived from prediction models based on vegetation indices allows growers to predict the expected yield and plan a labor schedule. http://repositorio.bib.upct.es/dspace/