A multielement analysis of Cu induced changes in the mineral profilesof Cu sensitive and tolerant populations of Silene paradoxa L.Sara Pignattelli
, Ilaria Colzi
, Antonella Buccianti
, Ilenia Cattani
, Gian Maria Beone
, Henk Schat
, Cristina Gonnelli
, 2013, original scientific article
Abstract: tThis work investigates the Cu induced changes in element profiles in contrasting ecotypes of Silene para-doxa L. A metallicolous copper tolerant population and a non-metallicolous sensitive population weregrown in hydroponics and exposed to different CuSO4treatments. Shoot and root concentrations of Ca,Cu, Fe, K, Mg, Mn, Mo, Na, P, S and Zn were evaluated through ICP-OES.Results indicated that increasing the environmental Cu concentration had a population dependenteffect on element profiles, shoot-to-root ratios and correlations among the elements. Generally, in thetolerant population Cu treatment induced a higher element accumulation in roots and had minimaleffects on the shoot element profile, thus resulting in a progressively decreasing shoot-to-root ratio foreach element. In the sensitive population element concentrations in root and shoot were much moreaffected and without a consistent trend. Copper treatment also affected the correlations between theelements, both in roots and shoots of the two populations, but more so in the sensitive population thanin the tolerant one. Thus, Cu exposure strongly disturbed element homeostasis in the sensitive population,but barely or not in the tolerant one, probably mainly due to a higher capacity to maintain proper rootfunctioning under Cu exposure in the latter. Differences in element profiles were also observed in theabsence of toxic Cu exposure. These differences may reflect divergent population-specific adaptations todifferential nutrient availability levels prevailing in the populations’ natural environments. There is noevidence of inherent side-effects of the Cu tolerance mechanism operating in the tolerant population.
Keywords: Mineral profile, Copper tolerance, Silene paradoxa, Compositional data analysis
Published in RUNG: 20.04.2020; Views: 2194; Downloads: 0
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