Clone, Multi-dimensional decision-making technique, Pinus sylvestris, Root collar diameter, Seedling height.
 M. Cetin, F. Adiguzel, S. Gungor, E. Kaya, and M. C. Sancar, "Evaluation of thermal climatic region areas in terms of building density in urban management and planning for Burdur, Turkey," Air Quality, Atmosphere & Health, vol. 12, pp. 1103-1112, 2019. Available at: https://doi.org/10.1007/s11869-019-00727-3.
 M. Cetin, "The effect of urban planning on urban formations determining bioclimatic comfort area’s effect using satellitia imagines on air quality: A case study of Bursa city," Air Quality, Atmosphere & Health, vol. 12, pp. 1237-1249, 2019. Available at: https://doi.org/10.1007/s11869-019-00742-4.
 T. Yangin and N. Bilir, "Interaction of cone production and growth characters in Brutian pine (Pinus brutia Ten.) populations," Research and Reviews in Biotechnology and Science, vol. 9, pp. 6-10, 2014.
 M. Gunes and N. Umurusman, "A decision support tool fuzzy target programming tax optimization applications in local governments," Review of Social Economic & Business Studies, vol. 2, pp. 242- 255, 2003.
 A. F. Howard, "A critical look at multiple criteria decision making techniques with reference to forestry applications," Canadian Journal of Forest Research, vol. 21, pp. 1649-1659, 1991. Available at: https://doi.org/10.1139/x91-228.
 S. A. Hajkowicz and T. Prato, "Multiple objective decision analysis of farming systems in goodwater Creek Watershed, Missouri," Research Report No. 24, Centre for Agriculture, Resources and Environmental Systems, Columbia, Missouri1998.
 J. Ananda and G. Herath, "A critical review of multi-criteria decision making methods with special reference to forest management and planning," Ecological Economics, vol. 68, pp. 2535-2548, 2009. Available at: https://doi.org/10.1016/j.ecolecon.2009.05.010.
 P. Chatterjee and S. Chakraborty, "Material selection using preferential ranking methods," Materials & Design, vol. 35, pp. 384-393, 2012. Available at: https://doi.org/10.1016/j.matdes.2011.09.027.
 M. Karaatli, N. Omurbek, I. Budak, and O. Dag, "Ranking of liveable cities with multi criteria decision making methods," Selçuk University Journal of Institute of Social Sciences, vol. 33, pp. 215-228, 2015.
 H. Zhang, C.-l. Gu, L.-w. Gu, and Y. Zhang, "The evaluation of tourism destination competitiveness by TOPSIS & information entropy–a case in the Yangtze River Delta of China," Tourism Management, vol. 32, pp. 443-451, 2011. Available at: https://doi.org/10.1016/j.tourman.2010.02.007.
 A. Shemshadi, H. Shirazi, M. Toreihi, and M. J. Tarokh, "A fuzzy VIKOR method for supplier selection based on entropy measure for objective weighting," Expert Systems with Applications, vol. 38, pp. 12160-12167, 2011. Available at: https://doi.org/10.1016/j.eswa.2011.03.027.
 S. Cakir and S. Percin, "Measurement of R&D performance by integrated entropy weight-TOPSIS method in EU countries," Uludağ University, Journal of Faculty of Economics and Administrative Sciences, vol. 32, pp. 77-95, 2013.
 T. C. Wang and J. C. Hsu, "Evaluation of the business operation performance of the listing companies by applying TOPSIS method," 2004 IEEE International Conference on Systems, Man and Cybernetics, vol. 2, pp. 1286-1291, 2004.
 J. Wu, J. Sun, L. Liang, and Y. Zha, "Determination of weights for ultimate cross efficiency using Shannon entropy," Expert Systems with Applications, vol. 38, pp. 5162-5165, 2011. Available at: https://doi.org/10.1016/j.eswa.2010.10.046.
 X. Li, K. Wang, L. Liu, J. Xin, H. Yang, and C. Gao, "Application of the entropy weight and TOPSIS method in safety evaluation of coal mines," Procedia Engineering, vol. 26, pp. 2085-2091, 2011. Available at: https://doi.org/10.1016/j.proeng.2011.11.2410.
 M. Islamoglu, M. Apan, and A. Oztel, "An evaluation of the financial performance of REITs in Borsa Istanbul: A case study using the entropy-based TOPSIS method," International Journal of Financial Research, vol. 6, pp. 124-138, 2015. Available at: https://doi.org/10.5430/ijfr.v6n2p124.
 K. Karakuş, D. Aydemir, A. Öztel, G. Gunduz, and F. Mengeloglu, "Nanoboron nitride-filled heat-treated wood polymer nanocomposites: Comparison of different multicriteria decision-making models to predict optimum properties of the nanocomposites," Journal of Composite Materials, vol. 51, pp. 4205-4218, 2017. Available at: https://doi.org/10.1177/0021998317699984.
 H. Gumus, D. Aydemir, E. Altuntas, R. Kurt, and E. Imren, "Cellulose nanofibrils and nano-scaled titanium dioxide-reinforced biopolymer nanocomposites: Selecting the best nanocomposites with multicriteria decision-making methods," Journal of Composite Materials, vol. 54, pp. 923-935, 2020. Available at: https://doi.org/10.1177/0021998319870842.
 M. Madić, V. Gecevska, M. Radovanović, and D. Petković, "Multi-criteria economic analysis of machining processes using the WASPAS method," Journal of Production Engineering, vol. 17, pp. 1-6, 2014.
 E. K. Zavadskas, Z. Turskis, J. Antucheviciene, and A. Zakarevicius, "Optimization of weighted aggregated sum product assessment," Electronics and Electrical Engineering, vol. 122, pp. 3-6, 2012. Available at: https://doi.org/10.5755/j01.eee.122.6.1810.
 E. K. Zavadskas, J. Antucheviciene, J. Šaparauskas, and Z. Turskis, "Multi-criteria assessment of facades’ alternatives: Peculiarities of ranking methodology," Procedia Engineering, vol. 57, pp. 107-112, 2013. Available at: https://doi.org/10.1016/j.proeng.2013.04.016.
 J. Saparauskas, E. K. Zavadskas, and Z. Turskis, "Evaluation of alternative building designes according to the three criteria of optimality," Proceedings of the 10th International Conference on Modern Building, Structures and Techniques, May 19-21, Vilnius, Lithuania, 2010.
 G. Stojić, Z. Stević, J. Antuchevičienė, D. Pamučar, and M. Vasiljević, "A novel rough WASPAS Approach for supplier selection in a company manufacturing PVC carpentry products," Information, vol. 9, pp. 1-16, 2018. Available at: https://doi.org/10.3390/info9050121.
 E. Triantaphyllou and S. H. Mann, "An examination of the effectiveness of multi-dimensional decision-making methods: A decision-making paradox," Decision Support Systems, vol. 5, pp. 303-312, 1989. Available at: https://doi.org/10.1016/0167-9236(89)90037-7.
 K. Pazek, C. Rozman, V. Pavlovic, A. Cerenak, and M. Pavlovic, "The multi-criteria decision model aid for assessment of the hop cultivars (Humulus lupulus L.), Genetics, plant breeding and seed production," presented at the 44th Croatian & 4th International Symposium on Agriculture, 2009.
 N. Bilir and A. Sofu, "Estimation of productions for reproductive characters in seed orchards of Pinus sylvestris by fuzzy logic model approaches," presented at the Seed Orchard Conference. Jeju, Korea, 2009.
 M. Pavlovic, A. Cerenak, V. Pavlovic, C. Rozman, K. Pazek, and M. Bohanec, "Development of DEX-HOP multi-attribute decision model for preliminary hop hybrids assessment," Computers and Electronics in Agriculture, vol. 75, pp. 181-189, 2011. Available at: https://doi.org/10.1016/j.compag.2010.11.002.
 A. E. Idris, K. A. Mohamed, and H. I. Mohammed, "Using regression indices and multiple criteria analysis for study of some rice genotypes under interaction of variable environmental conditions," American Journal of Experimental Agriculture, vol. 2, pp. 407-425, 2012. Available at: https://doi.org/10.9734/ajea/2012/1193.
 K. A. Mohamed, A. E. Idris, H. I. Mohammed, and K. A. O. Adam, "Ranking rice (Oryza sativa L.) Genotypes using multi-criteria decision making, correlation and path coefficient analysis," British Biotechnology Journal, vol. 2, pp. 211-228, 2012. Available at: https://doi.org/10.9734/bbj/2012/1821.
 H. Küçükönder, S. Boyaci, and A. Akyüz, "A modeling study with an artificial neural network: Developing estimationmodels for the tomato plant leaf area," Turkish Journal of Agriculture and Forestry, vol. 40, pp. 203-212, 2016. Available at: https://doi.org/10.3906/tar-1408-28.
 E. Gemici, C. Yücedağ, H. B. Ozel, and E. Imren, "Predicting cone production in clonal seed orchard of Anatolian black pine with artificial neural network," Applied Ecology and Environmental Research, vol. 17, pp. 2267-2273, 2019. Available at: https://doi.org/10.15666/aeer/1702_22672273.