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This study was focussed on a comprehensive investigation on the state of pollution of the Danube and Sava Rivers in the region of Belgrade. Different complementary analytical approaches were employed covering both i) organic contaminants in the river water by target analyses of hormones and neonicotinoids as well as non-target screening analyses and ii) heavy metals in the sediments. Finally, some common water quality parameters were analysed. The overall state of pollution is on a moderate level. Bulk parameters did not reveal any unusual observations. Moreover, quantification of preselected organic contaminants did not indicate to elevated pollution. More significant contaminations were registered for chromium, nickel, zinc and partially copper in sediments with values above the target values according to Serbian regulations. Lastly, non-target screening analysis revealed a wider spectrum of organic contaminants comprising pharmaceuticals, technical additives, personal care products and pesticides. The study presented a comprehensive view on the state of pollution of the Sava and Danube Rivers and is the base for setting up further monitoring programs. As a superior outcome, it was illustrated how different chemical analyses can result in different assessments of the river quality. A

The inbred maize lines Polj 17 and F-2 have previously been shown to differ by up to three-fold in leaf abscisic acid (ABA) concentration in the field. Lines from the cross Poljl7 x F-2 differing in leaf ABA concentrations, and the parents, were studied in the field to characterize the differences amongst the lines in ABA concentrations during the season, during the day and in different parts of the plants. The water status of the plants was measured and leaves were heat girdled to get information on possible causes for the genetic variation amongst the lines in ABA concentration.Leaf ABA concentrations of the high-ABA lines increased markedly and consistently from flowering time onwards, whereas leaf ABA concentrations of the low-ABA lines gradually fell after flowering. Leaf water potentials of high-ABA and low-ABA lines were similar during this time. Leaf ABA concentrations varied little during the day, and heat girdling caused a rise in ABA concentrations, which was similar in both high-ABA and low-ABA lines, only after girdling for at least 4 h. ABA concentrations were highest in the leaves and it was only in the leaves and developing kerneIs that substantial differences in ABA concentrations were found between the high-ABA and low-ABA c1asses. Although aerial brace roots also had high ABA concentrations, other roots and stern internodes had ABA concentrations which were consistently low and the same for both ABA c1asses.Differences between the ABA c1asses were unlikely to be due to differences in leaf water status or in ABA export from the leaves. Other possible explanations for the genotypic differences in leaf ABA concentrations are discussed.

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The synthetic maize population 316PO2 was subjected to genetic correlation analyses between grain yield, yield components and morphological traits. The purpose was to enable estimates to be made of the advantage of using selection indices compared with selection based on grain yield only, and if that advantage was present, to choose enough simple selection indices for practical use. Selection indices were constructed out of four traits highly significantly correlated with grain yield, in addition to yield itself.Grain yield exhibited a highly significant additive genetic correlation with ear diameter (r a =0.588**), kernels row -1 (r a =0.643**), ears plant -1 (r a =0.871**) and ear height (r a =0.427**). The most efficient index was Index No. 14 (R.E.I 12345 = 108.83%), which included all four traits and grain yield. Index No. 3, one of the simplest forms of index, including only ears plant -1 and grain yield, showed slightly less relative efficiency (R.E.I 35 =107.24%) than Index No. 14. Using this simple form of index with two characters (Index No. 3) could improve the efficiency of selection for grain yield. The estimated advantage from its use is 179.6 kg/selection cycle for grain yield over selection based only on grain yield.

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Due to the interaction and noise in the experiments, yield trails for studying varieties are carried out in numerous locations and in the course of several years. Data of such trials have three principle tasks: to evaluate precisely and to predict the yield on the basis of limited experimental data; to determine stability and explain variability in the response of genotypes across locations; and to be a good guide for the selection of the best genotype for sowing under new agroecological conditions. The yield prediction without the inclusion of the interaction with the environments is incomplete and imprecise. Therefore, a great deal of breeding and agronomic studies are devoted to observing of the interaction via multilocation trials with replicates with the aim to use the interaction to obtain the maximum yield in any environment. Fifteen maize hybrids were analyzed in 24 environments. As the interaction participates in the total sum of squares with 6%, and genotypes with 2%, the interaction deserves observations more detailed than the classical analysis of variance (ANOVA) provides it. With a view to observe the interaction effect in detail in order to prove better understanding of genotypes, environments and their interactions AMMI (Additive Main Effect and Multiplicative Interaction) and the cluster analysis were applied. The partition of the interaction into the principal components by the PCA analysis (Principal Components Analysis) revealed a part of systematic variations in the interaction. These variations are attributed to the length of the growing season in genotypes and to the precipitation sum during the growing season in environments. Results of grouping by the cluster analysis are in high accordance with grouping observed in the biplot of the AMMI1 model