Modelling the Effects of Soil Conditions on Olive Productivity in Mediterranean Hilly Areas

The majority of olive (Olea europaea L.) production in Mediterranean environments is characterized by low external inputs and is practiced in hilly areas with shallow soils. This study aimed to study the yield and nutritional status for olive (cv. “Zeiti”) trees in northwestern Syria and establish c...

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Main Authors: Ashraf Tubeileh, Francis Turkelboom, Anwar Al-Ibrahem, Richard Thomas, Kholoud Sultan-Tubeileh
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:International Journal of Agronomy
Online Access:http://dx.doi.org/10.1155/2014/672123
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author Ashraf Tubeileh
Francis Turkelboom
Anwar Al-Ibrahem
Richard Thomas
Kholoud Sultan-Tubeileh
author_facet Ashraf Tubeileh
Francis Turkelboom
Anwar Al-Ibrahem
Richard Thomas
Kholoud Sultan-Tubeileh
author_sort Ashraf Tubeileh
collection DOAJ
description The majority of olive (Olea europaea L.) production in Mediterranean environments is characterized by low external inputs and is practiced in hilly areas with shallow soils. This study aimed to study the yield and nutritional status for olive (cv. “Zeiti”) trees in northwestern Syria and establish correlations between yield, on the one hand, and soil/land factors and tree nutrition, on the other hand, to determine the most yield-affecting factors. Land and soil fertility parameters (field slope, soil depth, and soil nutrients) and concentrations of leaf minerals were determined. As olive roots can go deep in the soil profile to extract nutrients, the total available nutrients per tree (over the whole profile) were estimated. Multiple regression analyses were performed to determine the model that best accounts for yield variability. Total available soil potassium amount (R2=0.68), soil total N amount (R2=0.59), and soil depth (R2=0.56) had the highest correlations with olive fruit yields. Available soil potassium amount and soil depth explained together 77% of the yield variability observed. In addition to these two factors, adding leaf B and Fe concentrations to the model increased the variability explained to 83%.
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publishDate 2014-01-01
publisher Wiley
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series International Journal of Agronomy
spelling doaj-art-888da21969d24dfbac1eec1397b0f00f2025-08-20T03:38:06ZengWileyInternational Journal of Agronomy1687-81591687-81672014-01-01201410.1155/2014/672123672123Modelling the Effects of Soil Conditions on Olive Productivity in Mediterranean Hilly AreasAshraf Tubeileh0Francis Turkelboom1Anwar Al-Ibrahem2Richard Thomas3Kholoud Sultan-Tubeileh4International Center for Agricultural Research in the Dry Areas, P.O. Box 5466, Aleppo, SyriaInternational Center for Agricultural Research in the Dry Areas, P.O. Box 5466, Aleppo, SyriaGeneral Commission for Scientific Agricultural Research, Department of Olive Research, Idleb, SyriaInternational Center for Agricultural Research in the Dry Areas, P.O. Box 5466, Aleppo, SyriaUniversity of Guelph, Kemptville Campus, P.O. Box 2003, Kemptville, ON, K0G 1J0, CanadaThe majority of olive (Olea europaea L.) production in Mediterranean environments is characterized by low external inputs and is practiced in hilly areas with shallow soils. This study aimed to study the yield and nutritional status for olive (cv. “Zeiti”) trees in northwestern Syria and establish correlations between yield, on the one hand, and soil/land factors and tree nutrition, on the other hand, to determine the most yield-affecting factors. Land and soil fertility parameters (field slope, soil depth, and soil nutrients) and concentrations of leaf minerals were determined. As olive roots can go deep in the soil profile to extract nutrients, the total available nutrients per tree (over the whole profile) were estimated. Multiple regression analyses were performed to determine the model that best accounts for yield variability. Total available soil potassium amount (R2=0.68), soil total N amount (R2=0.59), and soil depth (R2=0.56) had the highest correlations with olive fruit yields. Available soil potassium amount and soil depth explained together 77% of the yield variability observed. In addition to these two factors, adding leaf B and Fe concentrations to the model increased the variability explained to 83%.http://dx.doi.org/10.1155/2014/672123
spellingShingle Ashraf Tubeileh
Francis Turkelboom
Anwar Al-Ibrahem
Richard Thomas
Kholoud Sultan-Tubeileh
Modelling the Effects of Soil Conditions on Olive Productivity in Mediterranean Hilly Areas
International Journal of Agronomy
title Modelling the Effects of Soil Conditions on Olive Productivity in Mediterranean Hilly Areas
title_full Modelling the Effects of Soil Conditions on Olive Productivity in Mediterranean Hilly Areas
title_fullStr Modelling the Effects of Soil Conditions on Olive Productivity in Mediterranean Hilly Areas
title_full_unstemmed Modelling the Effects of Soil Conditions on Olive Productivity in Mediterranean Hilly Areas
title_short Modelling the Effects of Soil Conditions on Olive Productivity in Mediterranean Hilly Areas
title_sort modelling the effects of soil conditions on olive productivity in mediterranean hilly areas
url http://dx.doi.org/10.1155/2014/672123
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