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    Assessment of resistance of wheat genotypes (T. aestivum and T. durum) to copper toxicity
    (WFL PUBL, 2013) Karaman, M. Rustu; Tusat, Ekrem; Er, Fatih; Turan, Metin; Dizman, Mumin
    Copper (Cu) availability to plants depends on a large number of factors and their interactive relationships. Especially, localized excess soil Cu is often a great risk for plant growth on the agricultural lands. Development of resistant varieties to Cu toxicity is a high priority on these regions, where the soils have high levels of Cu. Thus, this study aimed to assess the resistance of wheat genotypes to Cu toxicity using the agronomic and physiologic parameters. For this aim, a pot experiment, based on a completely randomized design with three replications, was conducted using the soil of calcareous usthochrepts. In the study, twenty different wheat genotypes of T. aestivum and T. durum were used. Copper fertilizer at the levels of 0 (-Cu) and 20 mg Cu kg(-1) (+Cu) as CuSO4 center dot 5H(2)O was applied to the pots. After harvest, plant dry matter yield was recorded, and total Cu concentrations in tops of wheat plants were determined. The results indicated the existence of a large genotypic variation among wheat genotypes to their physiologic and agronomic susceptibility to Cu toxicity. Resistance of bread wheat cultivars of T. aestivum to Cu toxicity were higher than that of wheat cultivars of T. durum under the Cu toxicity condition. Thus, evaluation of assessment of new wheat cultivars to Cu toxicity could also be used in breeding programs in order to develop more Cu-tolerant cultivars.
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    COMPARISON OF GIS BASED INTERPOLATION METHODS IN ASSESSING OF SITE SPECIFIC PHOSPHORUS VARIABILITY ON THE APPLE ORCHARD
    (PARLAR SCIENTIFIC PUBLICATIONS (P S P), 2013) Karaman, M. Rustu; Horuz, Ayhan; Susam, Tekin; Er, Fatih; Tusat, Ekrem
    Evaluating of geostatistical approaches in monitoring of spatial variability of some chemical contaminants such as agricultural phosphorus (P) will provide valuable data for large agricultural areas. In this study, performance of varied GIS based geostatistical interpolation methods were tested in assessing of site specific P variability on the apple orchard. For this aim, soil samples were systematically collected from the agricultural apple area using the grid sampling system. The samples were taken at two depths (025 cm and 25-50 cm), the distance on the Y direction is 10 m and in the X direction is 20 m. The soil samples were prepared for analysis, and some physical and chemical analyses were made in the samples by routine methods. The data concerning with soil P levels were analyzed comparatively according to GIS based interpolation methods of Ordinary Kriging (OK), Simple Kriging (SK) and Universal Kriging (UK). The interpolation methods were also tested with varied semivariogram models of Spherical, Exponential and Gaussian. As a result of cross validations, the best optimal method was found to be interpolation method of UK (Universal RMSE, +/- 0.472) with semivariogram model of guassian for topsoil, whereas it was found to be interpolation method of SK (Simple RMSE, +/-0.323) with semivariogram model of exponential for topsoil. Predicted P values were significantly (p< 0.01) correlated with measured values for both topsoil (r = 0.993) and subsoil (r = 0.980), respectively. Soil P distribution maps were adequately performed by using selected kriging interpolation methods and suitable sernivariogram models. The results indicated that monitoring of site specific P variability on the apple orchard using these GIS based interpolation methods will help to create the effective schemes for agricultural chemical managements such as P fertilization resulting in optimal yield and quality with reduced environmental pollution.