Yazar "Karabacak, Osman" seçeneğine göre listele

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    A comparison of management planning principles of wetland ecosystem (the Delta of Bendimahi) and mountain ecosystem (Mountain of Ispiriz) in the Van Lake Basin/Turkey
    (2013) Durmuş, Atilla; Alp, Şevket; Adizel, Özdemir; Ünal, Murat; Karabacak, Osman; Demirci, Emin Yaşar; Erman, Murat
    Van Lake Basin which is an important and different part of East Anatolia Region possesses important biological richness due to its geological, climatic, geographical and topographical varieties. In the region, Van Lake which is located between high mountains has led to the formation of a different climate which has resulted in different vegetation and formation of important wetlands. In the basin lies Ispiriz Mountain which is one of the important natural fields and Delta of Bendimahi which is an important part of the basin. Although the flora of Ispiriz Mountain has not been thoroughly studied, 35 of the plants which have been recorded from the area are classified as endemic, whilst 50 of them have been classified as rare plants. 15 of endemic plants have been collected from Ispriz Mountain and introduced to the world. 9 of these plants are endemic plants which have been recorded from a narrow area of Ispiriz Mountain. In the Delta of Bendimahi, there are 188 bird species. 68 of these birds are local, 80 of them migrant, 20 of them winter visitor, 15 of them transit migrant and 2 of them are determined to be coincidental. In this study, together with the socio-economic structure of Delta of Bendimahi which is wetland ecosystem and Mountain of Ispiriz which is mountain ecosystem, the existing relations and problems between natural resources have been determined. According to the gathered information, basic principles of management planning of both regions have been determined. In the presentation, the characteristics of both regions and similarities and differences between the two regions would be touched upon in terms of management of natural resources. It has been determined that the security and economical problems of the region have caused different difficulties in terms of studies which have aimed to determine natural resources in both ecosystems.
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    A Computer Vision System for Classification of Some Euphorbia (Euphorbiaceae) Seeds Based on Local Binary Patterns
    (IEEE, 2013) Kaya, Yilmaz; Karabacak, Osman; Caliskan, Abidin
    In this study, a computer vision system was proposed for the seed images classification. The classification process was performed using uniform local binary patterns obtained from digital seed images. In this study, 240 (120 training and 120 test) images of the seed were used. First, the average uniform histograms of each type of seed (seed type classes) was obtained for the training set. Then the uniform LBP histogram of each seed in the test set were produced and compared with histograms of classes by using nearest neighbor. The Euclidean distance, sum square error, histogram intersection and Chi-square statistics were used to calculate the distance between seed samples. 95.83%. of seed images has been diagnosed properly with the proposed. As a result, the surface shape of the seeds include important information patterns to determine the taxonomic relationships, it is is expected that the computer vision systems provide significant advantages to identify the type of seed.
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    An automatic identification method for the comparison of plant and honey pollen based on GLCM texture features and artificial neural network
    (Taylor & Francis As, 2013) Kaya, Yilmaz; Erez, Mehmet Emre; Karabacak, Osman; Kayci, Lokman; Fidan, Mehmet
    Pollen grains vary in colour and shape and can be detected in honey used as a way of identifying nectar sources. Accurate differentiation between pollen grains record is hampered by the combination of poor taxonomic resolution in pollen identification and the high species diversity of many families. Pollen identification determines the origin and the quality of the honey product, but this indefiniteness is also a big challenge for the beekeepers. This study aimed to develop effective, accurate, rapid and non-destructive analysis methods for pollen classification in honey. Ten different pollen grains of plant species were used for the estimation. GLCM (grey level co-occurrence matrix) texture features and ANN (artificial neural network) were used for the identification of pollen grains in honey by the reference of plant species pollen. GLCM has been calculated in four different angles and offsets for the pollen of the plant and the honey samples. Each angle and offset pair includes five features. At the final step, features were classified using the ANN method; the success of estimation with ANN was 88.00%. These findings suggest that the texture parameters can be useful in identification of the pollen types in honey products.
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    An Automatic Identification Method for the Comparison of Plant and Honey Pollens Based On GLCM Texture Features and Artificial Neural Network.Grana, (2013) 52(1): 71-77.
    (2013) Kaya, Yılmaz; Erez, Emre; Karabacak, Osman; Kaycı, Lokman; Fidan, Mehmet
    Pollen grains vary in colour and shape and can be detected in honey used as a way of identifying nectar sources. Accurate differentiation between pollen grains record is hampered by the combination of poor taxonomic resolution in pollen identification and the high species diversity of many families. Pollen identification determines the origin and the quality of the honey product, but this indefiniteness is also a big challenge for the beekeepers. This study aimed to develop effective, accurate, rapid and non-destructive analysis methods for pollen classification in honey. Ten different pollen grains of plant species were used for the estimation. GLCM (grey level co-occurrence matrix) texture features and ANN (artificial neural network) were used for the identification of pollen grains in honey by the reference of plant species pollen. GLCM has been calculated in four different angles and offsets for the pollen of the plant and the honey samples. Each angle and offset pair includes five features. At the final step, features were classified using the ANN method; the success of estimation with ANN was 88.00%. These findings suggest that the texture parameters can be useful in identification of the pollen types in honey products.
  • Küçük Resim
    Öğe
    Characterization of Multifloral Honeys of Pervari Region with Different Properties
    (2015) Erez, Mehmet Emre; Karabacak, Osman; Kayci, Lokman; Fidan, Mehmet; Kaya, Yılmaz
    The quality of honey from Pervari region was almost known by all over the country in Turkey. This study was undertaken to determine (i) physico-chemical parameters, (ii) antimicrobial analysis and (iii) pollen estimation method with expert computer system obtained from three different sites of Pervari region (Siirt/Turkey). For physico-chemical parameters; moisture, free acidity, diastase activity, hydroxyl methyl furfural (HMF), invert sugar, ash, commercial glucose and proline analysis were examined. For anti-microbial analysis disc dilution method were studied on six different bacteria species. For pollen analysis; different and new expert computer system was used for comparison of pollen of plants and honey samples. The aim of the study was to evaluate the properties of multi floral honey determined from three different locations in the same region and the way to understand to which plants were visited by the bees with comparing of pollen grains of flowers and honey by using the expert computer system. Honey samples of Pervari region were of acceptable quality based on recommended criteria of Turkish Food Codex and International Honey Commission.
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    Draba orientalis (Brassicaceae), a new species from Turkey
    (Finnish Zoological Botanical Publishing Board, 2009) Karabacak, Osman; Behcet, Luetfi
    Draba orientalis O. Karabacak & L. Behcet sp. nova (Brassicaceae) from Turkey is described and illustrated. Diagnostic characters of the species along with taxonomic notes are given. It is compared with the morphologically similar D. siliquosa, D. lanceolata and D. anatolica.
  • Küçük Resim
    Öğe
    First record of Psylliostachys spicata (Plumbaginaceae), confirmation of Salvia pratensis (Lamiaceae) from Turkey, and taxonomic status of Salvia ertekinii
    (2015) Celep, Ferhat; Karabacak, Osman; MALEKMOHAMMADI, Maryam; Fidan, Mehmet; Doğan, Musa
    Psylliostachys spicata (Plumbaginaceae) is reported as a new genus record for Turkey; an amended species description is given. Bossier’s record of Salvia pratensis (Lamiaceae) in Flora Orientalis is confirmed from Turkey. Additionally, the endemic Salvia ertekinii is reduced to a synonym of Salvia pinnata.
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    Öğe
    First record of Psylliostachys spicata (Plumbaginaceae), confirmation of Salvia pratensis(Lamiaceae) from Turkey, and taxonomic status of Salviaertekinii
    (2016) Celep, Ferhat; Karabacak, Osman; Malekmohammadı, Maryam; Fidan, Mehmet; Doğan, Musa
    Psylliostachys spicata (Plumbaginaceae) is reported as a new genus record for Turkey; an amended species description is given. Bossier s record of Salvia pratensis (Lamiaceae) in Flora Orientalis is confirmed from Turkey. Additionally, the endemic Salvia ertekiniiis reduced to a synonym of Salvia pinnata.
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    The flora of Kırmızı Tuzla (Karaçoban, Erzurum/Turkey) and Bahçe Tuzlası (Malazgirt, Mus/Turkey) and their environment
    (2009) Behçet, Lütfi; Özgökçe, Fevzi; Ünal, Murat; Karabacak, Osman
    Bu araştırma 2006-2007 yılları arasında, Kırmızı Tuzla (Karaçoban/Erzurum) ile Bahçe Tuzlası (Malazgirt/Muş) ve çevrelerinin florasını tespit etmek üzere yapılmıştır. Araştırma bölgesinde 75 familyaya bağlı 374 cins ve 1056 tür ve türaltı takson tespit edilmiştir. Bunlardan 70 takson B9 karesi için yeni kayıt, 4 takson kriptogam grubuna ve 1052 takson ise fanerogam grubuna aittir. Alandan toplam 101 (% 9. 56) endemik takson belirlenmiştir. Endemik ve nadir olan taksonların tehlike kategorilerine dağılımları: 2 takson kritik “CR”, 8 takson tehlikede “EN”, 30 takson zarar görebilir “VU”, 16 takson tehdit altına girebilir “NT”, 63 takson az endise verici “LC” ve 2 takson(Inula discoidea Boiss. ve Cicuta virosa L.) veri yetersiz “DD” şeklindedir. Inula discoidea Boiss. türü veri yetersiz kategorisinden (DD) çıkarılarak zarar görebilir (VU) kategorisine konuldu. En büyük üç familya; Asteraceae (170), Brassicaceae (97) ve Fabaceae (84)’dir. En büyük cinsler; Astragalus, Centaurea ve Silene’dir.