The living conditions of living beings are becoming ever more difficult due to the climate change caused by industrialization. Forests, which have a great importance in terms of natural resources, are one of the main elements which prevent this situation. Therefore, it is important to ensure the sustainability of forests and to increase their genetic and structural quality. Appropriate farms and clonal seed orchards should be established with the purpose of achieving this genetic diversity. This way, quantitative traits of clones, which are located in these seed orchards, depending on their growth performance, the cone yield can be determined. In this study, the best clones in terms of cone yield were determined through MAUT and WASPAS methods, which are some of the multiple criteria decision-making techniques. This was done by using the height and diameter measurements of 30 Scots pine (Pinus sylvestris L.) clones selected according to random sampling method in 3 different blocks in Erzurum region. Based on the sum product assessment and multi-attribute utility theory model results, clones 22 and 29 were determined as superior and prospective for further breeding procedures in terms of seedling height and root collar diameter. According to the entropy method, the maximum weights for seedling height and root collar diameter were obtained in Block-3 with 0.580175 and in Block-1 with 0.590017, respectively. Contribution/Originality:This study plays important role in selecting the best clones in terms of cone yield through MAUT and WASPAS methods, which are some of the multiple criteria decision-making techniques.

The aim of the paper is to determine the effects of nano fillers such as cellulose nanofibrils and nano-scaled titanium dioxide on some properties of polyhydroxybutyrate and polylactic acid biopolymers; it also determined the selection of biopolymer nanocomposites with the optimum properties by using multicriteria decision-making methods such as multi-attribute utility theory, simple additive weighting, and weighted aggregated sum product assessment. Test results showed that the mechanical properties of the biopolymer nanocomposites generally increased with the addition of the cellulose nanofibrils and nano-scaled titanium dioxide. However, the addition of nano-scaled titanium dioxide decreased the tensile modulus. The addition of the cellulose nanofibrils had a higher effect on the tensile and flexure modulus of elasticity than the addition of the nano-scaled titanium dioxide. Thermal properties were generally found to improve with the addition of the cellulose nanofibrils and nano-scaled titanium dioxide. Melting temperature (Tm) generally decreased with the addition of the nano fillers. The scanning electron microscopic images showed that the nano fillers were dispersed as white dots in the biopolymer matrix. After accelerated weathering and decay test, outdoor performance of the biopolymer nanocomposites was found to be improved with the addition of the nano fillers. Multicriteria decision-making methods were conducted to determine the biopolymer nanocomposites having the optimum properties, and all the methods showed that the best biopolymer nanocomposites was polylactic acid with 1% cellulose nanofibrils.

Seed orchards are an important seed source because they have the most important link between tree breeding and plantation forestry. The aim of this study is to evaluate the potential of Adaptive Neuro-Fuzzy Inference Systems of artificial neural networks to predict the amount of cone in clonal seed orchards of Anatolian black pine. It was found that the coefficient of determination (R 2 ), the mean absolute error (MAE) and the root mean square error (RMSE) of the artificial neural network model were 0.85, 14.83 and 18.85, respectively. The amount of cone in clonal seed orchards of Anatolian black pine was predicted with high efficiency through artificial neural networks. Considering the lack of forestry studies based on the artificial neural network, this study will enable further researches to provide a new perspective.

ÖZETTürkiye ormanlarındaki zengin biyolojik çeşitlilik, ülkenin değişik yörelerinde yayılış gösteren ormanlar içinde zengin ODOÜ (Odun Dışı Orman Ürünleri) kaynaklarının yer almasına imkan sağlamaktadır. Bu kaynaklardan sağlanan ODOÜ'lerden gerek yerel, gerekse ülke bazında çok çeşitli ihtiyaçların karşılanmasında yararlanılmakta ve ihraç yoluyla da önemli sayılabilecek gelirler elde edilmektedir. Bu çalışmada Türkiye'nin dış ticaretinde önemli bir yere sahip olan defne, kekik, çam fıstığı, adaçayı, kimyon, anason, ıhlamur ve kestane bitkilerinin 1995-2015 yılları arasındaki 21 yıllık ihracat durumu incelenmiş ve elde edilen bu veriler tasnif edildikten sonra grafik halinde sunularak yıllar itibariyle meydana gelen değişmeler yüzdesel hesaplamalarla ortaya konulmuştur. Anahtar kelimeler: ODOÜ, Dış Ticaret, İhracat Gelir, İhracat Miktar NON-WOOD FOREST PRODUCTS IN TURKEY FORESTRY SECTOR: EXPORT ANALYSİS ABSTRACTRich biological diversity of the forests in Turkey offers rich NWFP (Non-Wood Forest Products) sources in the forests in different parts of the country. These NWFP are utilized to meet a range of needs both locally and nationwide. And also significant income is generated through export. In this study, the export of bay leaves, thyme, pine nuts, sage, cumin, anise, linden and chestnut which have a significant places in Turkey export, for 21 years (between 1995 and 2015) were investigated. And the collected data were classified and presented in graphics. Thus, the changes by years are shown with percent calculations.

Bu çalışmada, Türkiye kâğıt ürünleri, orman ürünleri ve mobilya sektörlerinde yer alan on beş işletmenin finansal performansını belirlemek için Entropi temelli PROMETHEE yöntemiyle bir değerlendirme sistemi oluşturulmuş, değerlendirme göstergelerine göre işletmelerin Borsa İstanbul (BIST) hisselerinin pandemi dönemi ve öncesi mevcut gelişmelere gösterdikleri tepki yansıtılmaya çalışılmıştır. Finansal performans oranlarını kapsayan on bir kriter, 2018-2019 yılları pandemi öncesi ve 2020 yılı pandemi dönemi temel alınarak değerlendirilmiş t ir. Ağırlıklandırılmış kriterlere göre hisselerin tercih sıralaması oluşturulmuştur. Bu sıralamada ALKA (K1) ve SUMAS (OM4) hissesinin pandemi ve öncesi dönemde en iyi performansı gösterdiği görülmüştür. Genel olarak orman endüstri sektöründe faaliyet gösteren firmaların pandemiden minimum etkilendiği tespit edilmiştir.