Irrigation Science

, Volume 22, Issue 1, pp 39–46 | Cite as

Comparison of water status indicators for young peach trees

  • Damiano Remorini
  • Rossano Massai
Original Paper


We measured a series of physiological and physical indicators and compared them to xylem sap flow, to identify the most sensitive and reliable plant water status indicator. In the growing season of 1998, 4-year-old peach trees (Prunus persica Batsch cv. 'Suncrest', grafted on 'GF 677' rootstock) were studied under two irrigation treatments, 25 l day−1 and no irrigation, and during recovery. Trials were conducted near Pisa (Italy) in a peach orchard situated on a medium clay loam soil and equipped with a drip-irrigation system (four 4 l h−1 drippers per tree). Measurements of leaf water potential (Ψ W ), stem water potential (Ψ S ), and leaf temperature (T l) were taken over 5 days (from dawn to sunset) and analyzed in conjunction with climatic data, sap flow (SF), trunk diameter fluctuation (TDF) and soil water content (SWC). Physiological indicators showed substantial differences in sensitivity. The first indication of changes in water status was the decrease of stem radial growth. TDF and SF revealed significant differences between the two irrigation treatments even in the absence of differences in pre-dawn leaf water potential (pdΨW), up until now widely accepted as the benchmark of water status indicators. Irrigated trees showed a typical trend in SF rate during the day, while in non-irrigated plants the maximum peak of transpiration was anticipated. Measurements of water potential showed ΨS to be a better indicator of tree water status than ΨW. T l was found to have poor sensitivity. In conclusion, we found the sensitivity of the indicators from the most to the least was: TDF >SF rate >SF cumulated = pdΨWS>mdΨW>T l.


Soil Water Content Vapor Pressure Deficit Leaf Water Potential Irrigate Tree Plant Water Status 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Research work was supported by the European Community under Project FAIR1-CT95-0030 (Innovative biological indicators to improve water and nitrogen use and fruit quality in tree crops). We thank Dr. Edi Cecchini and Enrico Barone for revising the English and for their useful comments.


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Copyright information

© Springer-Verlag 2003

Authors and Affiliations

  1. 1.Dipartimento di Coltivazione e Difesa Specie LegnoseUniversità di PisaPisaItaly

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