Irrigation Science

, Volume 32, Issue 4, pp 283–294 | Cite as

Effects of irrigation using treated wastewater on table grape vineyards: dynamics of sodium accumulation in soil and plant

  • Yishai Netzer
  • Moshe Shenker
  • Amnon SchwartzEmail author
Original Paper


The effect of using treated wastewater for irrigation of table grapes (Vitis vinifera cv. Superior Seedless) was studied for six seasons. The experimental vineyard was grown on clay loam soil in a semi-arid area. Treated wastewater (5.83 meq L−1 Na+) with (TWW + F) and without (TWW) fertilizer, and fresh water with fertilizer (FW + F, 2.97 meq L−1 Na+), were each applied at three irrigation levels (80, 60 and 40 % of crop evapotranspiration before harvest). Root zone (0–60 cm soil depth) soil saturated paste extract Na+ concentrations and sodium adsorption ratio (SAR) values fluctuated over the years, but generally decreased in the order TWW > TWW + F > FW + F for each irrigation level. Both Na+ concentrations and SAR values developed faster and to a greater extent at higher irrigation. Adding fertilizer to TWW decreased Na+ and SAR only at the high irrigation level. Na+ concentrations in the trunk wood, bark and xylem sap of the TWW and TWW + F irrigated vines were significantly higher than those in the FW + F-irrigated vines. Leaf petiole Na+ content increased with time and its maximum value in TWW and TWW + F irrigated vines exceeded 6,500 mg kg−1, threefold higher than in FW + F irrigated vines. We conclude that in clay soils under relatively high irrigation, Na+ may pose a greater potential risk to plants and soil rather than Cl or salinity per se. However, significant effects on yield were not recorded during this six-year study probably due to the high salinity tolerance of the ‘Paulsen’ rootstock used in the experiment.


Irrigation Water Irrigation Treatment Sodium Adsorption Ratio Table Grape Irrigation Season 
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.



This research was supported by a grant from the Israeli Ministry of Agriculture (Project No. 826-47-02). The authors would like to thank Amram Hazan, Yosi Cohen, Carmit Lifshitz, Idith Dembak, Shiri Naftalyahu, and Tamar Weinberg for their assistance in field and laboratory work.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.The Robert H. Smith Institute for Plant Science and Genetics in Agriculture, Faculty of Agriculture, Food and EnvironmentThe Hebrew University of JerusalemRehovotIsrael
  2. 2.The Department of Soil and Water Sciences, The Robert H. Smith Faculty of Agriculture, Food and EnvironmentThe Hebrew University of JerusalemRehovotIsrael
  3. 3.Samaria and Jordan Rift Research and Development CenterArielIsrael

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