Person: DEMİR, ALİ OSMAN
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DEMİR
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ALİ OSMAN
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Publication Comparative analysis of the pysebal model and lysimeter for estimating actual evapotranspiration of soybean crop in Adana, Turkey(Selçuk Üniversitesi Yayınları, 2020-06-01) Sawadogo, Alidou; Tim, Hessels; Gündoğdu, Kemal Sulhi; Demir, Ali Osman; Ünlü, Mustafa; Zwart, Sander Jaap; Sawadogo, Alidou; GÜNDOĞDU, KEMAL SULHİ; DEMİR, ALİ OSMAN; Ziraat Fakültesi; Biyosistem Mühendisliği Bölümü; 0000-0002-5591-4788; 0000-0002-5091-1801; JLX-2232-2023; DXY-6494-2022; ABI-4047-2020Accurate estimation of evapotranspiration (ET) is an important factor in water management, especially in irrigated agriculture. Accurate irrigation scheduling requires accurate estimation of ET. The objective of this study was to estimate the actual evapotranspiration (ETa) by the pySEBAL model and to compare it with the actual evapotranspiration measured by the lysimeter method of soybean crop in Adana, Turkey. Five Landsat 5 Thematic Mapper (TM) images and weather data were used for this study to estimate actual evapotranspiration by the pySEBAL model. The results showed a good relationship between ETa estimated by the pySEBAL model and ETa measured by the lysimeter method, with an R-2 of 0.73, an RMSE of 0.51 mm.day(-1), an MBE of 0.04 mm.day(-1) and a Willmott's index of agreement (d) of 0.90. Based on this study, there is a good relationship between the actual evapotranspiration estimated by the pySEBAL model and the actual evapotranspiration measured by the lysimeter method. Consequently, ETa of soybean crop can be estimated with high accuracy by the pySEBAL model in Adana, Turkey.Publication Determination of diurnal leaf gas exchange for drip-irrigated kenaf plant in sub-humid climatic conditions(Hard, 2022-01-01) Candoğan, Burak Nazmi; Yetik, Ali Kaan; Sincik, Mehmet; Demir, Ali Osman; Büyükcangaz, Hakan; CANDOĞAN, BURAK NAZMİ; SİNCİK, MEHMET; DEMİR, ALİ OSMAN; BÜYÜKCANGAZ, HAKAN; Ziraat Fakültesi; Tarla Bitkileri Bölümü; AAH-1811-2021; AAH-3102-2021; JLX-2232-2023; HHX-4880-2022Kenaf stands out as an important fiber source in the industry with its 4000-year history. Physiological properties have a great effect on the development process of kenaf. Physiological properties are significantly affected by seasonal air temperature changes and precipitation, as well as fluctuations during the day. The main reason for these fluctuations is seen as instant changes in environmental factors. In this study, it was aimed to determine the hourly changes of leaf gas exchange parameters of drip-irrigated kenaf plant and to examine the relationships between these parameters. Field experiment was conducted in Bursa, Turkey, which has sub-humid climatic conditions. For this purpose, net photosynthesis rate (A), stomatal conductivity (gs), intercellular CO2 concentration (Ci) and transpiration rate ( E) measurements were carried out on 18th September 2019 and 26th September 2020, between 08:00 h and 18:00 h. As a result of the study, while it was determined that A, gs, Ci and E parameters varied between 14.75-23.67 mu mol CO2 m(-2) s(-1), 0.23- 0.74 mol H (2) O m(-2) s(-1), 243-331 mu mol CO2 mol air(-1) and 2.67-7.37 mmol H (2) O m(-2) s(-1), respectively in 2019, they varied between 13.97-22.30 mu mol CO2 m(-2) s(-1), 0.29-0.58 mol H2O m(-2) s(-1), 217-278 mu mol CO2 mol air(-1) and 6.3-14.7 mmol H2O m(-2) s(-1), respectively in 2020. Different measurement times had significant effects on all parameters at the p<0.01 level for both years. As a result of the evaluation of the relationships between gas exchange parameters, it was determined that the gs-A and E-A relationships were statistically significant at the p<0.01 level for both years. On the other hand, in 2019 and 2020, Ci-A relationships were significant at p<0.05 and p< 0.01 probability levels, respectively. Information on the responses of leaf gas exchange parameters to weather changes occurring during the day in kenaf plant in sub-humid climate conditionsPublication Determination of pipe diameters for pressurized irrigation systems using linear programming and artificial neural networks(Ankara Üniversitesi, 2023-01-01) Kurtulmuş, Ezgi; Kurtulmuş, Ferhat; Kuşcu, Hayrettin; Arslan, Bilge; Demir, Ali Osman; KURTULMUŞ, EZGİ; KURTULMUŞ, FERHAT; KUŞÇU, HAYRETTİN; ARSLAN, BİLGE; DEMİR, ALİ OSMAN; Ziraat Fakültesi; Biyosistem Mühendisliği Bölümü; 0000-0001-9600-7685; AAH-4682-2021; AAH-2936-2021; R-8053-2016; JOP-8553-2023; JLX-2232-2023Pressurized irrigation systems are widespread among other alternatives in Mediterranean countries. Since the initial investment costs of pressurized irrigation systems are quite high, it is crucial to determine design parameters such as pipe diameter. Most of the current optimization techniques for pipe diameter selection are based on linear, non-linear, and dynamic programming models. The ultimate aim of these techniques is to produce solutions to problems with less cost and computation time. In this study, a novel approach for determining pipe diameter was proposed using Artificial Neural Networks (ANN) as an alternative to existing models. For this purpose, three pressurized irrigation systems were investigated. Different ANN architectures were created and tested using hydrant level parameters of the irrigation systems, such as irrigated area per hydrant, hydrant discharge, pipe length, and hydrant elevation. Different training algorithms, transfer functions, and hidden neuron numbers were tried to determine the best ANN model for each irrigation system. Using multilayer feed-forward ANN architecture, the highest coefficients of determination were found to be 0.97, 0.93, and 0.83 for irrigation systems investigated. It was concluded that pipe diameters could be determined by using artificial neural networks in the planning of pressurized irrigation systems.