Namık Kemal Sönmez

High level of copper application to soil and leaves reduce the growth and yield of tomato plants

Copper-containing fertilizers, fungicides and bactericides are extensively used in greenhouses in Turkey. Informations on effects of these applications to plants are scarce. The aim of the present study was to investigate effects of Cu application to a calcareous soil and to leaves on the yield and growth of tomato plants. Cu was first applied to soil as CuSO4.5H2O in three different levels (0, 1000, and 2000 mg Cu kg-1) and then to leaves in three different frequencies (no application, biweekly and weekly) using two cupric fungicides (Cu oxychloride, and Cu salts of fatty and rosin acids) in pot experiments carried out in a computer-controlled greenhouse. Total yield, fruit number, dry root weight and plant height decreased with increasing Cu application to soil. Increasing levels of Cu applied to soil and leaves resulted in decreasing final fruit number, dry root weight and plant height in 4th, 5th and 6th weeks. Combined applications of Cu to soil and leaves could be more deleterious to plants than when Cu is applied only to soil or leaves.

Seasonal changes of spatial variation of some groundwater quality variables in a large irrigated coastal Mediterranean region of Turkey

Soil and groundwater degradations have taken considerable attention, recently. We studied spatial and temporal variations of groundwater table depth and contours, and groundwater pH, electrical conductivity (EC), and nitrate (NO3) content in a large irrigated area in Western Mediterranean region of Turkey. These variables were monitored during 2009 and 2010 in previously constructed 220 monitoring wells. We analyzed the data by geostatistical techniques and GIS. Spatial variation of groundwater table depth (GTD) and groundwater table contours (GTC) remained similar across the four sampling campaigns. The values for groundwater NO3 content, EC, and pH values ranged from 0.01 to 454.1 gL(-1), 0.06 to 46.0 dS m(-1) and 6.53-9.91, respectively. Greatest geostatistical range (16,964 m) occurred for GTC and minimum (960 m) for groundwater EC. Groundwater NO3 concentrations varied both spatially and temporally. Temporal changes in spatial pattern of NO3 indicated that land use and farming practices influenced spatial and temporal variation of groundwater NO3. Several hot spots occurred for groundwater NO3 content and EC. These localities should be monitored more frequently and land management practices should be adjusted to avoid soil and groundwater degradation. The results may have important implications for areas with similar soil, land use, and climate conditions across the Mediterranean region.

Relationship between spectral reflectance and water stress conditions of Bermuda grass (Cynodon dactylon L.)

Abstract Remotely sensed data is an important tool for precision crop management. Satellite imaging systems and related‐hand held instruments are frequently proposed for detection of crop stress caused by water, soil compaction and lack of nutrients, etc. This study was conducted to investigate how Bermuda grass reflectance changes with the onset of water stress. Four different irrigation treatments were examined: 100% (I1), 75% (I2), 50% (I3) and 25% (I4) of the evaporation measured in the Class A Pan. A non‐irrigated plot was used as a control treatment (I5). Spectral reflectance data were collected using a hand‐held spectroradiometer which measured in the blue, green, red and near‐infrared. Soil water content was monitored by a neutron probe. Water‐stressed Bermuda grass (treatments I4 and I5) had lower spectral reflectance in near‐infrared and higher reflectance in red wavebands than the other treatments. The results were statistically tested using one‐way analysis of variance and Duncans multiple range test. Highly significant relationships were found between different irrigation treatments and near infrared wavelengths (P <0.01, R 2 =0.94) and between the irrigation treatments and the normalised difference vegetation index (NDVI) (P < 0.01, R 2 = 0.80). Results indicate that different water stress on Bermuda grass could be determined by using spectral reflectance, especially NDVI and near‐infrared reflectance regions. Analysis of experimental data indicated that it is possible to use remotely sensed data to develop maps of water stress conditions of Bermuda grass (Cynodon dactylon).

Determination of the ecological connectivity between landscape patches obtained using the knowledge engineer (expert) classification technique

Connection of similar landscape patches with ecological corridors supports habitat quality of these patches, increases urban ecological quality, and constitutes an important living and expansion area for wild life. Furthermore, habitat connectivity provided by urban green areas is supporting biodiversity in urban areas. In this study, possible ecological connections between landscape patches, which were achieved by using Expert classification technique and modeled with probabilistic connection index. Firstly, the reflection responses of plants to various bands are used as data in hypotheses. One of the important features of this method is being able to use more than one image at the same time in the formation of the hypothesis. For this reason, before starting the application of the Expert classification, the base images are prepared. In addition to the main image, the hypothesis conditions were also created for each class with the NDVI image which is commonly used in the vegetation researches. Besides, the results of the previously conducted supervised classification were taken into account. We applied this classification method by using the raster imagery with user-defined variables. Hereupon, to provide ecological connections of the tree cover which was achieved from the classification, we used Probabilistic Connection (PC) index. The probabilistic connection model which is used for landscape planning and conservation studies via detecting and prioritization critical areas for ecological connection characterizes the possibility of direct connection between habitats. As a result we obtained over % 90 total accuracy in accuracy assessment analysis. We provided ecological connections with PC index and we created inter-connected green spaces system. Thus, we offered and implicated green infrastructure system model takes place in the agenda of recent years.