Vegetative growth and fruit set of olive (Olea europaea L. cv. ‘Zard’) in response to some soil and plant factors

Vegetative growth and fruit set of olive (Olea europaea
L. cv. ‘Zard’) in response to some soil and plant
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NOORI, O., ARZANI, K., MOAMENI, A., TAHERI, M.VEGETATIVE GROWTH AND FRUIT SET OF OLIVE (OLEA EUROPAEA L. CV. €ZARD€) IN RESPONSE TO SOME SOIL AND PLANT FACTORS

2015, 16(3), p.319 - 329, DOI: http://dx.doi.org/10.5513/JCEA01/16.3.1627

Abstract

This experiment was conducted to explore the reasons of difference between ‘Zard’olive orchard with the poor vegetative growth rate and fruit set and orchard with suitablevegetative growth rate and fruit set in relation to some soil and plant factors during twoseasons. Note that assumptions were based on the overall canopy greenness of theolive trees, so experimental orchards in which the planted trees showed optimum leafgreenness were considered good situations for optimum vegetative growth andproductivity. Remote sensing technologies based on normalized difference vegetationindex (NDVI) were employed on olive orchards, and two orchards meeting the criteria ofhighest amount of greenness and lowest amount of greenness were selected. Length ofcurrent-year shoot (LCYS) and fruit set were considered indicators of tree vegetativegrowth and productivity, respectively. Results clearly indicated a significant differencebetween the two selected orchards in terms of canopy volume (CV), leaf nitrogencontent (N), leaf potassium content (K), silt, sand, Sodium adsorption rate (SAR),available phosphorous (Pavi), total neutralizing value (TNV), electrical conductivity (EC),chloride (Cl), and Fe variables. A stepwise regression method was used to evaluate theeffects of soil and plant variables on fruit set and LCYS. According to the obtainedresults, the main reasons for differences between two orchards in fruit set andvegetative growth was N and K deficiencies, soil salinity, and a high percentage of silt inthe soil.

Keywords:
fruit setnitrogenolea europaea l.potassiumremote sensingsalinity