Using stem water potential derived from continuous reading sensors for irrigation scheduling: nectarine as a test case

Eyal Nevo, Nativ Rotbart*, Alexander Slutsky, Rony Wallach, Yoni Gal, Amos Naor, Shabtai Cohen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

We investigated on-site soil and plant based sensors translated to stem water potential for nectarine orchard irrigation control on heavy clay soil. Irrigation targeted predetermined stem water potential (SWP) thresholds for each phenological stage. Sensors were compared to SWP in six trees in a drying and wetting plot where irrigation was withheld periodically, allowing SWP to reach moderate water stress. Other sensor readings were regressed on SWP for those times, and the regressions were used for irrigation scheduling. The latter kept stage I and III SWP at ~ − 0.9 MPa, and moderate water stress in stage II (SWP ~ − 1.5 MPa). Weekly adjustments were made according to the thresholds. Results showed that tensiometers could be used for stages I and III, as they were very sensitive. However, when stress was applied soil water tension exceeded tensiometer range at 30 cm depth.Soil water content sensors had slower responses than the others, so they might be difficult to use for precise irrigation in heavy soils. Dendrometers responded quickly and therefore might be more useful for management even in moderate water stress, even with their sensitivity to climatic conditions. Analysis showed to maintain SWP within ± 0.1 MPa, 2 tensiometers, 10 soil water content sensors and 7 dendrometers stations are needed. Signal-to-noise (SNR) ranks were SWP > 30 cm tensiometers > 60 cm tensiometers > dendrometers > 30 cm soil water content > 60 cm soil water content sensors for the full season. Nonetheless, in some stages tensiometer SNR was greater than that of SWP.

Original languageEnglish
JournalIrrigation Science
DOIs
StateAccepted/In press - 2024

Bibliographical note

Publisher Copyright:
© The Author(s) 2024.

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