2024 Cilt 38 Sayı 1

Permanent URI for this collectionhttps://hdl.handle.net/11452/43454

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    Climate change impacts on precipitation dynamics in the Southern Marmara Region of Turkey
    (Bursa Uludağ Üniversitesi, 2024-04-05) Yetik, Ali Kaan; CANDOĞAN, BURAK NAZMİ; Bursa Uludağ Üniversitesi/Ziraat Fakültesi; 0000-0001-9898-5685
    Understanding the dynamics of precipitation patterns is crucial for effective water management strategies, especially in regions vulnerable to the impacts of climate change. This study investigates the projected changes in annual and seasonal precipitation across the Southern Marmara Region of Turkey by comparing the averages of the reference period (1971-2000) with those of the future period (2061-2090). Employing multiple climate models (GFDL, HADGEM, and MPI) and Representative Concentration Pathways (RCP4.5 and RCP8.5), the analysis includes Mann-Kendall trend tests and Sen's slope method to determine trends in precipitation patterns. Key findings reveal significant variability in precipitation projections among different models and scenarios, with implications for water resource management, agriculture, and ecosystem resilience in provinces such as Çanakkale, Balıkesir, Bursa, Bilecik, and Yalova. According to the annual rainfall change rates relative to the reference period, Balıkesir province stands out as the most resilient province against climate change with average rates of 8.81% and 7.09% under the HADGEM and MPI model simulations, respectively. Regarding seasonal variations, Bilecik province is expected to experience a significant decrease in rainfall, reaching up to -53.78% under the MPI RCP8.5 scenario. In terms of within-period changes in annual rainfall values, the strongest declining trend was identified with Z=-2.03 in Bilecik province under the MPI RCP8.5 scenario conditions by the Mann-Kendall test. On the other hand, for seasonal variations, Bursa province demonstrates the most robust decreasing trend under the GFDL RCP4.5 conditions (Z=-2.89). The study emphasizes the importance of considering spatially varying precipitation patterns and potential shifts in atmospheric circulation for sustainable water resource management amidst climate variability and change in the Southern Marmara region. These findings provide critical insights for policymakers and stakeholders involved in developing adaptive strategies to address the challenges posed by future climate scenarios.
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    Crop type classification using Sentinel 2A-derived Normalized Difference Red Edge Index (NDRE) and machine learning approach
    (Bursa Uludağ Üniversitesi, 2024-03-20) GÜNDOĞDU, KEMAL SULHİ; Bantchina, Benjamin Bere; Bursa Uludağ Üniversitesi/Fen Bilimleri Enstitüsü/Biyosistem Mühendisliği Bölümü; 0000-0002-2593-426X; 0000-0002-5591-4788
    Satellite remote sensing (RS) enables the extraction of vital information on land cover and crop type. Land cover and crop type classification using RS data and machine learning (ML) techniques have recently gained considerable attention in the scientific community. This study aimed to enhance remote sensing research using high-resolution satellite imagery and a ML approach. To achieve this objective, ML algorithms were employed to demonstrate whether it was possible to accurately classify various crop types within agricultural areas using the Sentinel 2A-derived Normalized Difference Red Edge Index (NDRE). Five ML classifiers, namely Support Vector Machines (SVM), Random Forest (RF), Decision Tree (DT), K-Nearest Neighbors (KNN), and Multi-Layer Perceptron (MLP), were implemented using Python programming on Google Colaboratory. The target land cover classes included cereals, fallow, forage, fruits, grassland-pasture, legumes, maize, sugar beet, onion-garlic, sunflower, and watermelon-melon. The classification models exhibited strong performance, evidenced by their robust overall accuracy (OA). The RF model outperformed, with an OA rate of 95% and a Kappa score of 92%. It was followed by DT (88%), KNN (87%), SVM (85%), and MLP (82%). These findings showed the possibility of achieving high classification accuracy using NDRE from a few Sentinel 2A images. This study demonstrated the potential enhancement of the application of high-resolution satellite RS data and ML for crop type classification in regions that have received less attention in previous studies.
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    Effect of age, live weight and body condition score on fertility in estrous synchronization of kıvırcık sheep
    (Bursa Uludağ Üniversitesi, 2024-03-11) Nageye, Farida İbrahim; KOYUNCU, MEHMET; Bursa Uludağ Üniversitesi/Ziraat Fakültesi/Zootekni Bölümü; Bursa Uludağ Üniversitesi/Ziraat Fakültesi/Zootekni Bölümü; 0000-0003-0379-7492; 0000-0003-0379-7492
    Kızgınlığı senkronize edilen Kıvırcık koyunlarında yaş, canlı ağırlık ve vücut kondisyon skorunun koyunların üreme parametreleri ve kuzuların gelişimi üzerindeki etkisi araştırılmıştır. Bu kapsamda yaş, vücut kondisyonu ve canlı ağırlığı farklı olan toplam 85 baş koyun değerlendirmeye alınmıştır. Ana yaşı, vücut kondisyon skoru (koç katım-doğum) ve canlı ağırlık (koç katım-doğum) ortalamaları sırasıyla 2.98, (3.04-3.22) ve (57.05-62.99) bulunmuştur. Ana yaşı ve vücut kondisyon skorunun kuzulama oranı, çoğuz doğum oranı ve yaşama gücü üzerine etkisi önemli bulunmuştur (P<0.05). Koç katım ve doğum dönemindeki canlı ağırlıkların çoğuz doğum oranı üzerine etkisi önemli bulunurken, yaşama gücü üzerine sadece doğum dönemindeki canlı ağırlık değerinin etkisi önemlidir (P<0.05). Ana yaşının doğum ağırlığı üzerine önemsiz, sütten kesim ağırlığı ve günlük canlı ağırlık artışı üzerine etkileri ise önemlidir (P<0.05). Anaların doğum dönemindeki canlı ağırlığının, kuzuların sütten kesim ve günlük canlı ağırlık artışı üzerindeki regresyon katsayısı önemlidir (P<0.05). Koyunların yaş, farklı dönemlerdeki canlı ağırlık ve vücut kondisyonun kendi aralarındaki korelasyon katsayısı değerlerinin (0.220-0.874) önemli olduğu saptanmıştır (P<0.05; P<0.01).
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    Water-yield relationships of green pepper (Capsicum annuum) cultivated at different ırrigation levels
    (Bursa Uludağ Üniversitesi, 2024-05-08) KUŞÇU, HAYRETTİN; Yılmaz, Sinem; Bursa Uludağ Üniversitesi/Ziraat Fakültesi/Biyosistem Mühendisliği Bölümü; 0000-0003-0150-7834; 0000-0001-9600-7685
    A field experiment was carried out in Bursa ecological conditions to determine the effects of different irrigation strategies on water-yield relationships of green pepper cultivation. In the study, where the amount of water evaporated from the class A pan (E) was taken as reference, different pan-crop coefficients (kpc: 0.25, 0.50, 0.75, and 1.00) were used for four irrigation treatments (S25: E×0.25, S50: E×0.50, S75: E×0.75, and S100: E×1.00) was created. While statistically significant (p<0.05) higher yields were obtained from S100 and S75 treatments, the yield decreased significantly from S50 and S25 treatments. The decrease in irrigation levels also caused a decrease in the size and diameter of the fruit. The highest water productivity was achieved from the S75 irrigation treatment. According to the results obtained, S75 irrigation treatment can be recommended in Bursa ecological conditions to obtain higher fruit yield both per unit area and per unit volume of water. Regarding S75, seasonally applied irrigation water was found to be 368.4 mm, evapotranspiration was 516.6 mm, fruit yield was 3629 kg da-1 and water productivity was 7.02 kg m-3