Effect of commercial amino acids on iron nutrition of tomato plants grown under lime-induced iron deficiency

The objective of this work was to study the effect of root and foliar application of two commercial products containing amino acids from plant and animal origin on iron (Fe) nutrition of tomato seedlings cultivated in two nutrient media: lime and normal nutrient solutions. In the foliar-application experiment, each product was sprayed with 0.5 and 0.7 mL L–1 2, 7, 12, and 17 d after transplanting. In the root application experiment, 0.1 and 0.2 mL L–1 of amino acids products were added to the nutrient solutions. In both experiments, untreated control plants were included as well. Foliar and root application of the product containing amino acids from animal origin caused severe plant-growth depression and nonpositive effects on Fe nutrition were found. In contrast, the application of the product from plant origin stimulated plant growth. Furthermore, significantly enhanced root and leaf FeIII-chelate reductase activity, chlorophyll concentration, leaf Fe concentration, and FeII : Fe ratio were found in tomato seedlings treated with the product from plant origin, especially when the amino acids were directly applied to the roots. These effects were more evident in plants developed under lime-induced Fe deficiency. The positive results on Fe uptake may be related to the action of glutamic acid, the most abundant amino acid in the formulation of the product from plant origin.

Causal Maps and Indirect Influences Analysis in the Diagnosis of Second-Home Tourism Impacts

This paper proposes a method for diagnosing the impacts of second-home tourism and illustrates it for a Mediterranean Spanish destination. This method proposes the application of network analysis software to the analysis of causal maps in order to create a causal network model based on stakeholder-identified impacts. The main innovation is the analysis of indirect relations in causal maps for the identification of the most influential nodes in the model. The results show that the most influential nodes are of a political nature, which contradicts previous diagnoses identifying technical planning as the ultimate cause of problems.