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Open Access Publications from the University of California

Diagnosing Mn deficiency in barley genotypes differing in Mn efficiency using analysis of fast fluorescence inductions kinetics and state transitions

  • Author(s): Husted, Søren
  • et al.

Manganese (Mn) deficiency is a major plant nutritional problem in many parts of the world. Most frequently Mn deficiency occurs as a hidden nutritional disorder without displaying any visual leaf symptoms and there is an urgent need for fast and specific method to diagnose the disorder. In this study two barley genotypes displaying a marked difference in their ability to tolerate growth at low Mn concentrations, a phenomenon designated as differential Mn efficiency, were used. Induction of Mn deficiency in the genotypes led to a decline in the quantum yield efficiency of PSII for both, however, faster in the Mn-inefficient genotype. Leaf tissue and thylakoid Mn concentrations were reduced under Mn deficiency, but no difference between genotypes was observed and no visual Mn deficiency symptoms were developed during the experiment. However, analysis of the fast fluorescence induction kinetics (FIK) revealed that in addition to the usual O-J-I-P steps, clear K- and D-steps were developed in the Mn-inefficient genotype under Mn deficiency. These marked changes indicated damages to photosystem II (PSII). This was further substantiated by state transition measurements, indicating that the ability of plants to redistribute excitation energy was reduced. The percent change in state transitions for control plants with normal Mn supply of both genotypes were 9-11%. However, in Mn deficient leaves of the Mn inefficient genotypes, state transitions were reduced to less than 1%, whereas no change was observed for the Mn-efficient genotypes. Comparison of plants with deficiencies of other relevant nutrients (Mg, S, Fe, Cu and Mn) revealed that fluorescence spectroscopy based leaf measurements constitute a highly specific and promising tool to accurately diagnose Mn deficiency in cereals. These data will be presented at the conference.

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