Bilal Cemek

Response of lettuce (Lactuca sativa var. crispa) to salinity of irrigation water

Abstract This study was conducted in a greenhouse to assess the response of lettuce (Lactuca sativa var. crispa) to increasing salinity of irrigation water (0.75, 1.5, 2.5, 3.5, 5.0, and 7.0 dS m−1). Soil salinity increased linearly with increasing salinity of irrigation water. The threshold value was determined as 1.1 dS m−1 and the relative yield decrease in slope after this threshold as 9.3%. The results showed that L. sativa var. crispa was moderately sensitive to salinity. In contrast to yield, plant dry matter content increased with increasing salinity for the salinity range studied. The taste of lettuce was not affected by salinity. The results further showed that the variables of leaf number per plant, plant height, water use efficiency, and accumulation of calcium (Ca) and iron (Fe) in the leaves decreased with salinity, whereas accumulation of potassium (K), nitrogen (N), copper (Cu), manganese (Mn), and zinc (Zn) in plant leaves was unaffected.

Spatial variability of depth and salinity of groundwater under irrigated ustifluvents in the Middle Black Sea Region of Turkey

Information on the potential risk for soil salinity buildup can be very helpful for soil salinity management in irrigated areas. We evaluated the spatial and temporal variability of groundwater salinity (GWS) and groundwater depth (GWD), which are two of the most important indicators of soil salinity, by indicator kriging technique in a large irrigated area in northern Turkey. GWS and GWD were measured on a monthly basis from irrigation season (August 2003) to rainy season (April 2004) at 60 observation wells in the 8,187-ha irrigated area. Five indicator thresholds were used for GWS and GWD. The semivariogram for each of the thresholds for both variables was analyzed then used together with experimental data to interpolate and map the corresponding conditional cumulative distribution functions (CCDF). Risk for soil salinity buildup was greater in the irrigation season compared to that in the rainy season. The greatest risk for soil salinity buildup occurred in the eastern part of the study area, suffering from poor drainage problem due to malfunctioning drainage infrastructure, as indicated by the CCDF of GWS and GWD obtained in both seasons. It was concluded that a combination of mechanical and cultural measures should be taken in high-risk locations to avoid further salinity problems.

Salinity and drought affect yield response of bell pepper similarly

Abstract There is a growing realization that an increasing number of countries are approaching full utilization of their conventional water resources and that the quantity of good-quality water supplies available to agriculture is diminishing. Effects of irrigation regime and irrigation water salinity on bell pepper including yield, fruit number and quality, vegetative and root growth, evapotranspiration and water use efficiency were investigated in this study by conducting two different experiments. Six different salinity levels of irrigation water and four different irrigation regimes were used as treatments. Considering the results from irrigation water salinity experiment, it can be concluded that as soil salinity increases, water consumption, water use efficiency, yield and other vegetative growth parameters of bell pepper were decreased. A polynomial relationship between soil salinity and water consumption was observed. It was found that bell pepper is moderately sensitive to salinity with a 1.2 dS m−1 threshold and a 10.9% slope value. In the irrigation regime experiment, limited irrigation caused decreases in water consumption, yield and vegetative growth of bell pepper. Yield response factors were close in the cases of irrigation regime (1.50) and irrigation water salinity (1.40). Total soluble solids of bell pepper were increased due to both irrigation water salinity and water application rate but not dry matter ratio. Considerable water consumption decreases because of salinity were determined. Therefore, the effect of irrigation water salinity should be considered in irrigation management to prevent excess saline water application and to protect the environment.

Determination of Seawater Intrusion via Hydrochemicals and Isotopes in Bafra Plain, Turkey

AbstactThis study was carried out between October 2007 and September 2008 to determine seawater intrusion in the right bank of the Bafra Plain, Turkey. Monthly water samples were taken from 28 groundwater wells used for irrigation water supply, and EC, pH, Na+, Ca2+, K+, Mg2+, CO32−, HCO3−, Cl− and SO42− levels were measured. 18O, D and T analysis were performed using water samples taken in August 2008. TDS, EC, Cl− and Na+ levels of some wells were extremely high, and correlations between Cl− and TDS, EC and Na+ values were also very high. A Piper diagram constructed from average annual data indicated various levels of seawater intrusion, and a correlation was observed between seawater intrusion rates and water table heights, with intrusion rates decreasing in line with increases in water table heights above sea level (asl). Graphs of 18O and D values indicated all wells to be close to the seawater-freshwater mixture line. A linear relationship was observed between 18O and Cl−, EC and SO42−.

Predicting field capacity, wilting point, and the other physical properties of soils using hyperspectral reflectance spectroscopy: two different statistical approaches

In this study, we examined the ability of reflectance spectroscopy to predict some of the most important soil parameters for irrigation such as field capacity (FC), wilting point (WP), clay, sand, and silt content. FC and WP were determined for 305 soil samples. In addition to these soil analyses, clay, silt, and sand contents of 145 soil samples were detected. Raw spectral reflectance (raw) of these soil samples, between 350 and 2,500-nm wavelengths, was measured. In addition, first order derivatives of the reflectance (first) were calculated. Two different statistical approaches were used in detecting soil properties from hyperspectral data. Models were evaluated using the correlation of coefficient (r), coefficient of determination (R2), root mean square error (RMSE), and residual prediction deviation (RPD). In the first method, two appropriate wavelengths were selected for raw reflectance and first derivative separately for each soil property. Selection of wavelengths was carried out based on the highest positive and negative correlations between soil property and raw reflectance or first order derivatives. By means of detected wavelengths, new combinations for each soil property were calculated using rationing, differencing, normalized differencing, and multiple regression techniques. Of these techniques, multiple regression provided the best correlation (P < 0.01) for selected wavelengths and all soil properties. To estimate FC, WP, clay, sand, and silt, multiple regression equations based on first(2,310)-first(2,360), first(2,310)-first(2,360), first(2,240)-first(1,320), first(2,240)-first(1,330), and raw(2,260)-raw(360) were used. Partial least square regression (PLSR) was performed as the second method. Raw reflectance was a better predictor of WP and FC, whereas first order derivative was a better predictor of clay, sand, and silt content. According to RPD values, statistically excellent predictions were obtained for FC (2.18), and estimations for WP (2.0), clay (1.8), and silt (1.63) were acceptable. However, sand values were poorly predicted (RDP = 0.63). In conclusion, both of the methods examined here offer quick and inexpensive means of predicting soil properties using spectral reflectance data.

Nondestructive leaf-area estimation and validation for green pepper (Capsicum annuum L.) grown under different stress conditions

Leaf area of a plant is essential to understand the interaction between plant growth and environment. This useful variable can be determined by using direct (some expensive instruments) and indirect (prediction models) methods. Leaf area of a plant can be predicted by accurate and simple leaf area models without damaging the plant, thus, provide researchers with many advantages in horticultural experiments. Several leaf-area prediction models have been produced for some plant species in optimum conditions, but not for a plant grown under stress conditions. This study was conducted to develop leaf area estimation models by using linear measurements such as lamina length and width by multiple regression analysis for green pepper grown under different stress conditions. For this purpose, two experiments were conducted in a greenhouse. The first experiment focused to determine leaf area of green pepper grown under six different levels of irrigation water salinity (0.65, 2.0, 3.0, 4.0, 5.0, and 7.0 dS m−1) and the other under four different irrigation regime (amount of applied water was 1.43, 1.0, 0.75, and 0.50 times of required water). In addition to general models for each experiment, prediction models of green pepper for each treatment of irrigation water salinity and of irrigation regime experiments were obtained. Validations of the models for both experiments were realized by using the measurements belong to leaf samples allocated for validation purposes. As a result, the determined equations can simply and readily be used in prediction of leaf area of green pepper grown under salinity and water stress conditions. The use of such models enable researchers to measure leaf area on the same plants during the plant growth period and, at the same time, may reduce variability in experiments.

Estimation of daily reference evapotranspiration by neuro computing techniques using limited data in a semi-arid environment

ABSTRACT In this paper, the daily reference evapotranspiration (ET0) for Bulawayo Goetz was estimated from climatic data using neuro computing techniques. The region lacks reliable weather data and experiences inconsistencies in the measuring process due to inadequate and obsolete measuring equipment. This paper aims to propose neuro computing techniques as an alternative methodology to estimating evapotranspiration. Firstly, ET0 was calculated using FAO-56 Penman-Monteith (PM) equation from available climatic data. Data was divided into training, testing and validation for neuro computing purposes. The study also investigated the effect of different normalisation techniques on neuro computing ET0 estimation accuracy. In another application, neuro-computing ET0 estimates were compared against those obtained using empirical methods and their calibrated versions. The Z-score normalisation technique for all data sets gave best results with a Multi-layer perceptron (5–5-1) model having RMSE, MAE and R2 values in the range 0.12–0.25 mm day−1, 0.08–0.15 mm day−1 and 0.94–0.99 respectively. There were no significant differences in ET0 estimation accuracy by neuro computing techniques due to normalisation technique. The Neuro computing techniques were superior to empirical methods in ET0 estimation for Bulawayo Goetz. The Neuro computing techniques are recommended for use in cases of limited climatic data at Bulawayo Goetz.

Assessment of spatial and seasonal changes in groundwater nitrate pollution of agricultural lands through ordinary and indicator kriging techniques

ABSTRACT Geostatistical approaches (ordinary kriging (OK) and indicator kriging (IK)) were used in this study to investigate the spatial and temporal variations in groundwater nitrate concentrations in Çarşamba plain of Turkey. Groundwater samples were taken in April 2012, July 2012, September 2012 and March 2013 from 78 groundwater wells. The experimental semivariograms were often fitted well by a Gauss model for April 2012 and September 2012, whereas a spherical model was fitted to experimental semivariograms for July 2012 and March 2013. Spatial distribution maps revealed that groundwater nitrate concentrations were above the threshold value of 50 mg L−1 specified for drinking water in 4.3% of the study area in April 2012, 40.8% in July 2012, 32.8% in September 2012 and 19.1% in March 2013. Probability maps created with IK showed that 3.1% and 3.2% of the total area had very strong probability (0.8–1.0) of exceeding the threshold nitrate concentration in July 2012 and September 2012, respectively. Current findings revealed that groundwater nitrate concentrations changed seasonally and increased much more in summer. It was concluded that OK and IK may yield significant outcomes for groundwater management, identification of risky sites for potential pollution and identification of the sites with excessive fertilizer uses.

Determination of Indoor Climate Requirements of Greenhouses in Samsun Provinces with –GIS assisted / Samsun İl Ve İlçelerinde Seraların İklimsel İhtiyaçlarının Cografi Bilgi Sistemleri İle Belirlenmesi

ABSTRACT: In this study, the most suitable growing period was explored in order to continue production economically in greenhouses. Based on the climatic data gathered from 9 different district of Samsun provinces the time periods for cooling, heating and natural ventilation were determined and compared with each other. Spatially distributions of mean daily outside temperature in region of Samsun determined using DEM (Digital Elevaluation Model) and spatial distributions of heating requirements of greenhouses determined using IDW(Inverse Distance Weight), with support of GIS (Geographic Information system). Research results showed that the central district of Samsun had more advantages in aspects of greenhouse production compared to other districts and Carsamba, Bafra, Kolay, Taflan and Vezirkopru followed it. Unlikely Ladik, Havza and Kavak had several disadvantages for production in greenhouses. Key words: Greenhouses, climatologic requirements, ventilation, heating, cooling, GIS Samsun Il Ve Ilcelerinde Seralarin Iklimsel Ihtiyaclarinin Cografi Bilgi Sistemleri Ile Belirlenmesi OZET: Bu calismada, Samsun il ve ilcelerinde ekonomik olarak seracilik yapilmasi icin iklim parametreleri goz onune alinarak en uygun yetistirme periyotlari belirlenmistir. Calismada, 9 ilcenin iklim verileri kullanilmis, isitma, dogal havalandirma, sogutma gerektiren aylar belirlenmis ve Samsun merkez ilce ile karsilastirilmistir. Samsun il ve ilcelerinin seracilik acisindan gunluk ortalama sicaklik degerlerin uzaysal dagilimi Sayisal Yukseklik Modeli (DEM) kullanilarak, isi gereksinimleri ise Ters Mesafe Agirlikli Enterpolasyon Teknigi (IDW) ile belirlenmistir. Seracilik acisindan en avantajli ilce merkez ilce olup bunu, Carsamba, Bafra, Kolay, Taflan ve Vezirkopru izlerken seracilik acisindan digerlerine gore dezavantajli Ladik, Havza ve Kavak ilceleri bulunmustur Anahtar Kelimeler: Seralar, iklimlendirme istekleri, havalandirma, isitma, sogutma, CBS