4.7 Article

Discrimination ability of leaf and stem water potential at different times of the day through a meta-analysis in grapevine (Vitis vinifera L.)

期刊

AGRICULTURAL WATER MANAGEMENT
卷 221, 期 -, 页码 202-210

出版社

ELSEVIER
DOI: 10.1016/j.agwat.2019.04.020

关键词

Collaborative research; Methods; Pressure chamber; Water status

资金

  1. Spanish Ministry of Economy and Competitiveness [AGL2015-70931-REDT, AGL2017-90759-REDT]
  2. [AGL 2001-1285-C03]
  3. [AGL2011-30408-C04]
  4. [RTA2011-00041-C02]
  5. [RTA2012-00105-00]
  6. [AGL2014-54201]
  7. [RTA2014-00049-005]
  8. [RTA2015-00091-00]
  9. [AGL2017-83738-C3-1-R]

向作者/读者索取更多资源

Water potential is considered to be the gold-standard measure for plant water status determination. However, there are some discrepancies on how and at what time of the day water potential measurements should be performed in order to obtain meaningful information. The aim of this work is to evaluate the discrimination ability of water potential measurements in grapevines depending on the time of the day and of the measurement procedure (leaf vs. stem). To do so, a meta-analysis was performed using > 78,000 measurements of water potential data obtained in field irrigation experiments, provided by 13 research teams working in this subject in Spain. For each measurement day and experiment, Discrimination Ratio (DR) was calculated and used to determine the discrimination ability of each method, and then pooled for comparison. The measurement procedure with the greatest DR can be hypothesised to be the most suitable under the average working conditions. Leaf water potential showed lower DR mean values than predawn or stem water potential. The climatic conditions and the cultivar may affect to the discrimination ability, although the abovementioned trend was always maintained. Leaf water potential in vineyards should therefore be replaced, as a general rule, by either stem or predawn water potential readings, without a clear pre-eminence of the performance of predawn and stem water potential measurements. Building a common dataset and its subsequent meta-analysis has been proved to be an efficient and robust tool to compare plant measurements, and should be implemented for other species and/or measurement procedures.

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