Phonological and pomological characteristics of some important apricot cultivars grown in Turkey

The study was conducted to contribute to the phenological, pomological characteristics and fruit quality specification of 28 apricot genotypes grown under similar practices in Adana province belonging to the Mediterranean region. In the present study authors wanted to determine the differences of local and foreign apricot genotypes based on their yield and fruit quality. Flowering was observed in February and March, and fruits were harvested in May and June. Generally, maturation duration ranged from 62 (‘Aurora’) to 95 (‘Fracasso’) days. Authors could not suggest a suitable genotype for Adana conditions at the all aspects among the investigated genotypes. However, the best cultivar is ‘Harcot’ in terms of fruit quality and size aspect. While the genotype of 7X89 which was taken from the local genotypes group was noticed the best in terms of yield, fruit weight and, TSS content. Among the foreign cultivars, ‘Precoce de Tyrinthe’ was pointed out for the aspects of earliness and fruit weight. © 2019 International Society for Horticultural Science. All rights reserved

Leaf iron concentration of ‘Kabarla’ strawberry under various irrigation levels and a biostimulant application

The investigation was conducted in the Adana province with a Mediterranean climate during the 2015-2016 season on the ‘Kabarla’ strawberry. The aim of the study was to determine the Fe (iron) concentration of the leaves as it is important for chlorophyll syntheses under different irrigation levels (IR50, IR75, IR100, and IR125) during the intense harvest period (March, April and May). The effect of the biostimulant (sea weed extract) application on the Fe concentration of the leaves was also evaluated. The trial layout was a factorial design with a split plot, carried out over months. The main factors were the application (Biostimulant), subplot, and irrigation levels. The biostimulant treatment did not affect the iron concentration of strawberry leaves. The months significantly influenced the leaf iron concentration. The highest iron concentration was found in April. Also, irrigation levels significantly affected the iron concentration which decreased with increased irrigation until IR100. However, the highest iron concentration was found in the IR125 treatment, in the contrast with visual observations, chlorosis was more severe with increased irrigation. The interaction between irrigation level and application was significant (p<0.01). The biostimulant application positively affected the leaf iron concentration at different irrigation levels except in the IR125 treatment. The highest leaf iron concentration was found in the control of the IR125 treatment. © 2018 International Society for Horticultural Science. All rights reserved

Health and taste related compounds in strawberries under various irrigation regimes and bio-stimulant application

PubMedID: 29784329Strawberry has a unique status within the fruit species in terms of health and taste related compounds. This experimental study concerned the application of a bio-stimulant at various drip irrigation levels (IR125, IR100, IR75 and IR50). The effects of the bio-stimulant (seaweed extract) on the eating quality, i.e., the taste-related (TSS, fructose, glucose, sucrose and citric, malic, L-ascorbic acid), and health-related (antioxidant activity, total phenol, myricetin and quercetin) compounds were studied in two strawberry cultivars. The ‘Rubygem’ with its higher sugar and lower acid content has been more preferable than the ‘Kabarla’ cultivar. The bio-stimulant contributes to taste by improving the TSS, fructose, sucrose and also to health by increasing the quercetin content of the fruit which is associated to the cardiovascular properties and cancer reducing agents. The experiment conducted revealed significant increases only in the TSS contents and antioxidant activity under the IR50 and IR75 deficit irrigation treatments. © 2018 Elsevier LtdFirat University Scientific Research Projects Management Unit: FDK-2016-5886This work was financially supported by the Coordination Unit of the Scientific Research Projects of the Çukurova University via the project FDK-2016-5886. S. Kapur (Ph. D, Aberdeen University, UK), retired faculty of Çukurova and Maryland Universities (European Division) is acknowledged for the language editing of the text

Determination of rainfall-runoff relationship in Yenicegoruce Basin with

The goal of this study is to model rainfall-runoff process using HEC-HMS developed by U.S. Army Corps of Engineers for the 10,508 km(2) catchment that has E01A012-Yenicegoruce stream gage at its outlet which is located just at the upstream of the point where Meric and Ergene Rivers meet. This study is conducted as a part of 115Y064 numbered "Development of a geographical information systems based decision-making tool for water quality management of Ergene watershed using pollutant fingerprints" project funded by TUBITAK. First, meteorological parameters such as daily precipitation and temperature, and daily streamflow data that are observed in and around the study catchment are collected. Then land use, hydrologic soil groups and digital elevation data of the catchment are collected and integrated into Geographic Information System (GIS) environment. Digital maps compiled in GIS environment were transferred into WMS for the calculation of basin parameters, and then the hydrological model for the basin is developed in HEC-HMS using these data. The model is calibrated using daily streamflow values of 1997-2002 and validated for 2003-2005 data. The model results obtained at the Yenicegoruce stream gage has Nash-Sutcliffe Efficiency (NSE) values of 0.8 and 0.75 for calibration and validation, respectively. Hydrological models for Hayrabolu, Luleburgaz and Inanli sub-catchments represented by stream gages D01A008, E01A006 and E01A012, respectively are developed and calibrated as well. Model performances are evaluated using statistical measures such as NSE values and correlations.C1 [Mesta, Buket] Orta Dogu Tekn Univ, Fen Bilimleri Enstitusu, Yer Sistem Bilimleri, Ankara, Turkey.[Kargi, Pinar Gokce; Ayvaz, M. Tamer] Pamukkale Univ, Muhendislik Fak, Insaat Muhendisligi Bolumu, Denizli, Turkey.[Tezyapar, Ipek; Goktas, Recep Kaya] Kocaeli Univ, Muhendislik Fak, Cevre Muhendisligi Bolumu, Kocaeli, Turkey.[Kentel, Elcin] Orta Dogu Tekn Univ Univ, Muhendislik Fak, Insaat Muhendisligi Bolumu, Ankara, Turkey.[Tezel, Ulas] Bogazici Univ, Cevre Muhendisligi Bolumu, Cevre Bilimleri Enstitusu, Istanbul, Turkey

Determination of rainfall-runoff relationship in Yenicegoruce Basin with

The goal of this study is to model rainfall-runoff process using HEC-HMS developed by U.S. Army Corps of Engineers for the 10,508 km(2) catchment that has E01A012-Yenicegoruce stream gage at its outlet which is located just at the upstream of the point where Meric and Ergene Rivers meet. This study is conducted as a part of 115Y064 numbered "Development of a geographical information systems based decision-making tool for water quality management of Ergene watershed using pollutant fingerprints" project funded by TUBITAK. First, meteorological parameters such as daily precipitation and temperature, and daily streamflow data that are observed in and around the study catchment are collected. Then land use, hydrologic soil groups and digital elevation data of the catchment are collected and integrated into Geographic Information System (GIS) environment. Digital maps compiled in GIS environment were transferred into WMS for the calculation of basin parameters, and then the hydrological model for the basin is developed in HEC-HMS using these data. The model is calibrated using daily streamflow values of 1997-2002 and validated for 2003-2005 data. The model results obtained at the Yenicegoruce stream gage has Nash-Sutcliffe Efficiency (NSE) values of 0.8 and 0.75 for calibration and validation, respectively. Hydrological models for Hayrabolu, Luleburgaz and Inanli sub-catchments represented by stream gages D01A008, E01A006 and E01A012, respectively are developed and calibrated as well. Model performances are evaluated using statistical measures such as NSE values and correlations