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Çay Üretiminde Öncü Ülkelerin Çay Üretilen Bölgelerinin İklim Özellikleri Arasındaki İlişkilerin Analizi

Year 2022, Volume: 10 Issue: 1, 89 - 102, 30.06.2022

Abstract

Bu çalışmada Hiyerarşik sınıflandırma yöntemleri kullanılarak çay üretiminde önde gelen ülkelerin çay üretimi yapılan bölgelerinin aylık ortalama sıcaklık ve aylık ortalama toplam yağış miktarı arasındaki ilişki araştırıldı. Bu makalede en küçük örten ağaç yöntemi kullanmak, zor ve karmaşık ilişkiyi çok açık bir şekilde görselleştirmemizi sağlamıştır. Benzer ortalama sıcaklık ve yağış miktarı değişimleri gösteren ülkeler aynı grupta birbirlerine bağlanmaktadırlar. Çay üretimi yapılan ülkelerin genellikle sıcaklık değişimleri bakımından benzer karakteristikler gösterdiği ve aynı grupta yer aldığı görülmüştür. Elde edilen sonuçlara göre çay üretiminde aylık sıcaklık değişimi ve aylık ortalama yağış miktarının etkili olduğu anlaşılmaktadır.

References

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  • Badr, H. S., Zaitchik, B. F., & Dezfuli, A. K. (2015). A tool for hierarchical climate regionalization. Earth Science Informatics, 8(4), 949–958. https://doi.org/10.1007/s12145-015-0221-7
  • Bati M., & Yildiz M., (2017). "2002-2016 Tarihleri Arasindaki Milletvekilliği Genel Seçimlerinde Siyasi Partilerin Aldiklari Oylar Arasi İlişkilerin İstatistiksel Analizi", Memleket Siyaset Yönetim, 12: 135-150.
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  • Bonanno, G., Caldarelli, G., Lillo, F., & Mantegna, R. N. (2003). Topology of correlation-based minimal spanning trees in real and model markets. Physical Review E, 68(4). https://doi.org/10.1103/physreve.68.046130
  • Bonanno, G., Caldarelli, G., Lillo, F., Micciche, S., Vandewalle, N., & Mantegna, R. N. (2004). Networks of equities in financial markets. The European Physical Journal B - Condensed Matter, 38(2), 363–371. https://doi.org/10.1140/epjb/e2004-00129-6
  • Bonanno, G., Vandewalle, N., & Mantegna, R. N. (2000). Taxonomy of stock market indices. Physical Review E, 62(6), R7615–R7618. https://doi.org/10.1103/physreve.62.r7615
  • Brida, J. G., Esteban, L. P., Risso, W. A., & Such Devesa, M. J. (2010). The international hotel industry in Spain: Its hierarchical structure. Tourism Management, 31(1), 57–73. https://doi.org/10.1016/j.tourman.2009.02.003
  • Brida, J. G., Gómez, D. M., & Risso, W. A. (2009). Symbolic hierarchical analysis in currency markets: An application to contagion in currency crises. Expert Systems with Applications, 36(4), 7721–7728. https://doi.org/10.1016/j.eswa.2008.09.038
  • Brida, J.G., & Risso, W.A. (2007). Dynamics and structure of the main Italian companies. International , 18(11): 1783-1793. https://doi.org/10.1142/s0129183107011741
  • Brida, J. G., & Risso, W. A. (2009). Dynamics and Structure of the 30 Largest North American Companies. Computational Economics, 35(1), 85–99. https://doi.org/10.1007/s10614-009-9187-1
  • Brida, J.G., & Risso, W.A. (2009). Dynamic and Structure of the Italian stock market based on returns and volume trading, Economics Bulletin, 29 2417-2423. RePEc:ebl:ecbull:eb-09-00306
  • Buda, A., & Jarynowski, A. (2013). Network Structure of Phonographic Market with Characteristic Similarities between Artists. Acta Physica Polonica A, 123(3), 547–552. https://doi.org/10.12693/aphyspola.123.547
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  • Eom, C., Oh, G., & Kim, S. (2007). Topological Properties of a Minimal Spanning Tree in the Korean and the American Stock Markets. Journal of the Korean Physical Society, 51(4), 1432. https://doi.org/10.3938/jkps.51.1432
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  • Garas, A., & Argyrakis, P. (2008). A network approach for the scientific collaboration in the European Framework Programs. EPL (Europhysics Letters), 84(6), 68005. https://doi.org/10.1209/0295-5075/84/68005
  • Górski, A. Z., Drożdż, S., & Kwapień, J. (2008). Scale free effects in world currency exchange network. The European Physical Journal B, 66(1), 91–96. https://doi.org/10.1140/epjb/e2008-00376-5
  • Graham, R., & Hell, P. (1985). On the History of the Minimum Spanning Tree Problem. IEEE Annals of the History of Computing, 7(1), 43–57. https://doi.org/10.1109/mahc.1985.10011
  • Kantar, E., Aslan, A., Deviren, B., & Keskin, M. (2016). Hierarchical structure of the countries based on electricity consumption and economic growth. Physica A: Statistical Mechanics and Its Applications, 454, 1–10. https://doi.org/10.1016/j.physa.2016.01.075
  • Kantar, E., Deviren, B., & Keskin, M. (2011). Hierarchical structure of Turkey’s foreign trade. Physica A: Statistical Mechanics and Its Applications, 390(20), 3454–3476. https://doi.org/10.1016/j.physa.2011.05.004
  • Kantar, E., Deviren, B., & Keskin, M. (2014). Hierarchical structure of the European countries based on debts as a percentage of GDP during the 2000–2011 period. Physica A: Statistical Mechanics and Its Applications, 414, 95–107. https://doi.org/10.1016/j.physa.2014.07.001
  • Kantar, E., & Keskin, M. (2013). The relationships between electricity consumption and GDP in Asian countries, using hierarchical structure methods. Physica A: Statistical Mechanics and Its Applications, 392(22), 5678–5684. https://doi.org/10.1016/j.physa.2013.07.029
  • Keskin, M., Deviren, B., & Kocakaplan, Y. (2011). Topology of the correlation networks among major currencies using hierarchical structure methods. Physica A: Statistical Mechanics and Its Applications, 390(4), 719–730. https://doi.org/10.1016/j.physa.2010.10.041
  • Kocakaplan, Y., Deviren, B., & Keskin, M. (2012). Hierarchical structures of correlations networks among Turkey’s exports and imports by currencies. Physica A: Statistical Mechanics and Its Applications, 391(24), 6509–6518. https://doi.org/10.1016/j.physa.2012.07.021
  • Kruskal, J. B. (1956). On the shortest spanning subtree of a graph and the traveling salesman problem. Proceedings of the American Mathematical Society, 7(1), 48–50. https://doi.org/10.1090/s0002-9939-1956-0078686-7
  • Mantegna, R. (1999). Information and hierarchical structure in financial markets. Computer Physics Communications, 121–122, 153–156. https://doi.org/10.1016/s0010-4655(99)00302-1
  • Mantegna, R. N., & H Eugene Stanley. (2016). An introduction to econophysics : correlations and complexity in finance. Cambridge University Press ; Beijing Shi.
  • Marx, W., Haunschild, R., & Bornmann, L. (2017). Global Warming and Tea Production—The Bibliometric View on a Newly Emerging Research Topic. Climate, 5(3), 46. https://doi.org/10.3390/cli5030046
  • Matesanz, D., & Ortega, G. J. (2013). Network analysis of exchange data: interdependence drives crisis contagion. Quality & Quantity, 48(4), 1835–1851. https://doi.org/10.1007/s11135-013-9855-z
  • McDonald, M., Suleman, O., Williams, S., Howison, S., & Johnson, N. F. (2005). Detecting a currency’s dominance or dependence using foreign exchange network trees. Physical Review E, 72(4). https://doi.org/10.1103/physreve.72.046106
  • Mizuno, T., Takayasu, H., & Takayasu, M. (2006). Correlation networks among currencies. Physica A: Statistical Mechanics and Its Applications, 364, 336–342. https://doi.org/10.1016/j.physa.2005.08.079
  • Naylor, M. J., Rose, L. C., & Moyle, B. J. (2007). Topology of foreign exchange markets using hierarchical structure methods. Physica A: Statistical Mechanics and Its Applications, 382(1), 199–208. https://doi.org/10.1016/j.physa.2007.02.019
  • Nojarov, P. (2016). Genetic climatic regionalization of the Balkan Peninsula using cluster analysis. Journal of Geographical Sciences, 27(1), 43–61. https://doi.org/10.1007/s11442-017-1363-y
  • Ortega, G. J., & Matesanz, D. (2006). Cross-country hierarchical structure and currency crises. International Journal of Modern Physics C, 17(03), 333–341. https://doi.org/10.1142/s012918310600856x
  • Park, K., & Yılmaz A. (2010). A Social Network Analysis Approach to Analyze Road Networks. Paper presented at the ASPRS Annual Conference, San Diego, CA.
  • Prim, R. C. (1957). Shortest Connection Networks and Some Generalizations. Bell System Technical Journal, 36(6), 1389–1401. https://doi.org/10.1002/j.1538-7305.1957.tb01515.x
  • Sen, B., Topcu, S., Türkeș, M., Sen, B., & Warner, J. (2012). Projecting climate change, drought conditions and crop productivity in Turkey. Climate Research, 52, 175–191. https://doi.org/10.3354/cr01074
  • Sensoy, A., & Tabak, B. M. (2014). Dynamic spanning trees in stock market networks: The case of Asia-Pacific. Physica A: Statistical Mechanics and Its Applications, 414, 387–402. https://doi.org/10.1016/j.physa.2014.07.067
  • Sollin, G. (1965). “M. Le tracé de canalisation”. Programming, Games, and Transportation Networks (in French) Spada, E., Sagliocca, L., Sourdis, J., Garbuglia, A. R., Poggi, V., de Fusco, C., & Mele, A. (2004). Use of the Minimum Spanning Tree Model for Molecular Epidemiological Investigation of a Nosocomial Outbreak of Hepatitis C Virus Infection. Journal of Clinical Microbiology, 42(9), 4230–4236. https://doi.org/10.1128/jcm.42.9.4230-4236.2004
  • Stooksbury, D. E., & Michaels, P. J. (1991). Cluster analysis of Southeastern U.S. climate stations. Theoretical and Applied Climatology, 44(3–4), 143–150. https://doi.org/10.1007/bf00868169
  • Tabak, B. M., Serra, T. R., & Cajueiro, D. O. (2009). The expectation hypothesis of interest rates and network theory: The case of Brazil. Physica A: Statistical Mechanics and Its Applications, 388(7), 1137–1149. https://doi.org/10.1016/j.physa.2008.12.036
  • TopicTea Team, 10 Major Tea Producers - Know Where Your Favorite Tea Comes From.Free Worldwide Shipping. Available online: https://topictea.com/blogs/tea-blog/major-tea-producers (accessed on 22 June 2020).
  • Türkeş, M., Koç, T., & Sariş, F. (2008). Spatiotemporal variability of precipitation total series over Turkey. International Journal of Climatology, 29(8), 1056–1074. https://doi.org/10.1002/joc.1768
  • Ulusoy, T., Keskin, M., Shirvani, A., Deviren, B., Kantar, E., & Çaǧrı Dönmez, C. (2012). Complexity of major UK companies between 2006 and 2010: Hierarchical structure method approach. Physica A: Statistical Mechanics and Its Applications, 391(21), 5121–5131. https://doi.org/10.1016/j.physa.2012.01.026
  • Vandewalle, N., Brisbois, F., & Tordoir, X. (2001). Non-random topology of stock markets. Quantitative Finance, 1(3), 372–374. https://doi.org/10.1088/1469-7688/1/3/308.

Analysis of the Relationship Between the Climate Characteristics of the Tea Producing Regions of the Leading Countries in Tea Production

Year 2022, Volume: 10 Issue: 1, 89 - 102, 30.06.2022

Abstract

Using hierarchical classification methods, the relationship between temperature and precipitation amount of the tea producing regions of the leading countries in tea production was investigated. Using the minimum spanning tree method in this article has allowed us to very clearly visualize the difficult and complex relationship. Countries that show similar average temperature and precipitation changes are linked in the same group. According to the results, it is understood that monthly temperature change and monthly precipitation rates is effective in tea production.

References

  • Adamatzky, A. (2012). Bioevaluation Of World Transport Networks. Wspc.
  • Badr, H. S., Zaitchik, B. F., & Dezfuli, A. K. (2015). A tool for hierarchical climate regionalization. Earth Science Informatics, 8(4), 949–958. https://doi.org/10.1007/s12145-015-0221-7
  • Bati M., & Yildiz M., (2017). "2002-2016 Tarihleri Arasindaki Milletvekilliği Genel Seçimlerinde Siyasi Partilerin Aldiklari Oylar Arasi İlişkilerin İstatistiksel Analizi", Memleket Siyaset Yönetim, 12: 135-150.
  • Bivona, S., Bonanno, G., Burlon, R., Gurrera, D., & Leone, C. (2008). Taxonomy of correlations of wind velocity — an application to the Sicilian area. Physica A: Statistical Mechanics and Its Applications, 387(23), 5910–5915. https://doi.org/10.1016/j.physa.2008.06.026
  • Bonanno, G., Caldarelli, G., Lillo, F., & Mantegna, R. N. (2003). Topology of correlation-based minimal spanning trees in real and model markets. Physical Review E, 68(4). https://doi.org/10.1103/physreve.68.046130
  • Bonanno, G., Caldarelli, G., Lillo, F., Micciche, S., Vandewalle, N., & Mantegna, R. N. (2004). Networks of equities in financial markets. The European Physical Journal B - Condensed Matter, 38(2), 363–371. https://doi.org/10.1140/epjb/e2004-00129-6
  • Bonanno, G., Vandewalle, N., & Mantegna, R. N. (2000). Taxonomy of stock market indices. Physical Review E, 62(6), R7615–R7618. https://doi.org/10.1103/physreve.62.r7615
  • Brida, J. G., Esteban, L. P., Risso, W. A., & Such Devesa, M. J. (2010). The international hotel industry in Spain: Its hierarchical structure. Tourism Management, 31(1), 57–73. https://doi.org/10.1016/j.tourman.2009.02.003
  • Brida, J. G., Gómez, D. M., & Risso, W. A. (2009). Symbolic hierarchical analysis in currency markets: An application to contagion in currency crises. Expert Systems with Applications, 36(4), 7721–7728. https://doi.org/10.1016/j.eswa.2008.09.038
  • Brida, J.G., & Risso, W.A. (2007). Dynamics and structure of the main Italian companies. International , 18(11): 1783-1793. https://doi.org/10.1142/s0129183107011741
  • Brida, J. G., & Risso, W. A. (2009). Dynamics and Structure of the 30 Largest North American Companies. Computational Economics, 35(1), 85–99. https://doi.org/10.1007/s10614-009-9187-1
  • Brida, J.G., & Risso, W.A. (2009). Dynamic and Structure of the Italian stock market based on returns and volume trading, Economics Bulletin, 29 2417-2423. RePEc:ebl:ecbull:eb-09-00306
  • Buda, A., & Jarynowski, A. (2013). Network Structure of Phonographic Market with Characteristic Similarities between Artists. Acta Physica Polonica A, 123(3), 547–552. https://doi.org/10.12693/aphyspola.123.547
  • Chakrabarti, B. K., Chakraborti, A., & Chatterjee, A. (2006). Econophysics and Sociophysics: Trends and Perspectives (1st ed.). Wiley-VCH.
  • Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische Mathematik, 1(1), 269–271. https://doi.org/10.1007/bf01386390
  • Eom, C., Oh, G., & Kim, S. (2007). Topological Properties of a Minimal Spanning Tree in the Korean and the American Stock Markets. Journal of the Korean Physical Society, 51(4), 1432. https://doi.org/10.3938/jkps.51.1432
  • Fovell, R.G., & Fovell, M.C. (1993). Climate zones of the conterminous United States defined using cluster analysis. Journal of Climate 6: 2103-2135. https://doi.org/10.1175/1520-0442(1993)006<2103:CZOTCU>2.0.CO;2
  • Galam, S. (2008). Sociophysics: a review of Galam models. International Journal of Modern Physics C, 19(03), 409–440. https://doi.org/10.1142/s0129183108012297
  • Galam, S. (2012). Sociophysics: A Physicist’s Modeling of Psycho-political Phenomena (Understanding Complex Systems) (2012th ed.). Springer.
  • Garas, A., & Argyrakis, P. (2007). Correlation study of the Athens Stock Exchange. Physica A: Statistical Mechanics and Its Applications, 380, 399–410. https://doi.org/10.1016/j.physa.2007.02.097
  • Garas, A., & Argyrakis, P. (2008). A network approach for the scientific collaboration in the European Framework Programs. EPL (Europhysics Letters), 84(6), 68005. https://doi.org/10.1209/0295-5075/84/68005
  • Górski, A. Z., Drożdż, S., & Kwapień, J. (2008). Scale free effects in world currency exchange network. The European Physical Journal B, 66(1), 91–96. https://doi.org/10.1140/epjb/e2008-00376-5
  • Graham, R., & Hell, P. (1985). On the History of the Minimum Spanning Tree Problem. IEEE Annals of the History of Computing, 7(1), 43–57. https://doi.org/10.1109/mahc.1985.10011
  • Kantar, E., Aslan, A., Deviren, B., & Keskin, M. (2016). Hierarchical structure of the countries based on electricity consumption and economic growth. Physica A: Statistical Mechanics and Its Applications, 454, 1–10. https://doi.org/10.1016/j.physa.2016.01.075
  • Kantar, E., Deviren, B., & Keskin, M. (2011). Hierarchical structure of Turkey’s foreign trade. Physica A: Statistical Mechanics and Its Applications, 390(20), 3454–3476. https://doi.org/10.1016/j.physa.2011.05.004
  • Kantar, E., Deviren, B., & Keskin, M. (2014). Hierarchical structure of the European countries based on debts as a percentage of GDP during the 2000–2011 period. Physica A: Statistical Mechanics and Its Applications, 414, 95–107. https://doi.org/10.1016/j.physa.2014.07.001
  • Kantar, E., & Keskin, M. (2013). The relationships between electricity consumption and GDP in Asian countries, using hierarchical structure methods. Physica A: Statistical Mechanics and Its Applications, 392(22), 5678–5684. https://doi.org/10.1016/j.physa.2013.07.029
  • Keskin, M., Deviren, B., & Kocakaplan, Y. (2011). Topology of the correlation networks among major currencies using hierarchical structure methods. Physica A: Statistical Mechanics and Its Applications, 390(4), 719–730. https://doi.org/10.1016/j.physa.2010.10.041
  • Kocakaplan, Y., Deviren, B., & Keskin, M. (2012). Hierarchical structures of correlations networks among Turkey’s exports and imports by currencies. Physica A: Statistical Mechanics and Its Applications, 391(24), 6509–6518. https://doi.org/10.1016/j.physa.2012.07.021
  • Kruskal, J. B. (1956). On the shortest spanning subtree of a graph and the traveling salesman problem. Proceedings of the American Mathematical Society, 7(1), 48–50. https://doi.org/10.1090/s0002-9939-1956-0078686-7
  • Mantegna, R. (1999). Information and hierarchical structure in financial markets. Computer Physics Communications, 121–122, 153–156. https://doi.org/10.1016/s0010-4655(99)00302-1
  • Mantegna, R. N., & H Eugene Stanley. (2016). An introduction to econophysics : correlations and complexity in finance. Cambridge University Press ; Beijing Shi.
  • Marx, W., Haunschild, R., & Bornmann, L. (2017). Global Warming and Tea Production—The Bibliometric View on a Newly Emerging Research Topic. Climate, 5(3), 46. https://doi.org/10.3390/cli5030046
  • Matesanz, D., & Ortega, G. J. (2013). Network analysis of exchange data: interdependence drives crisis contagion. Quality & Quantity, 48(4), 1835–1851. https://doi.org/10.1007/s11135-013-9855-z
  • McDonald, M., Suleman, O., Williams, S., Howison, S., & Johnson, N. F. (2005). Detecting a currency’s dominance or dependence using foreign exchange network trees. Physical Review E, 72(4). https://doi.org/10.1103/physreve.72.046106
  • Mizuno, T., Takayasu, H., & Takayasu, M. (2006). Correlation networks among currencies. Physica A: Statistical Mechanics and Its Applications, 364, 336–342. https://doi.org/10.1016/j.physa.2005.08.079
  • Naylor, M. J., Rose, L. C., & Moyle, B. J. (2007). Topology of foreign exchange markets using hierarchical structure methods. Physica A: Statistical Mechanics and Its Applications, 382(1), 199–208. https://doi.org/10.1016/j.physa.2007.02.019
  • Nojarov, P. (2016). Genetic climatic regionalization of the Balkan Peninsula using cluster analysis. Journal of Geographical Sciences, 27(1), 43–61. https://doi.org/10.1007/s11442-017-1363-y
  • Ortega, G. J., & Matesanz, D. (2006). Cross-country hierarchical structure and currency crises. International Journal of Modern Physics C, 17(03), 333–341. https://doi.org/10.1142/s012918310600856x
  • Park, K., & Yılmaz A. (2010). A Social Network Analysis Approach to Analyze Road Networks. Paper presented at the ASPRS Annual Conference, San Diego, CA.
  • Prim, R. C. (1957). Shortest Connection Networks and Some Generalizations. Bell System Technical Journal, 36(6), 1389–1401. https://doi.org/10.1002/j.1538-7305.1957.tb01515.x
  • Sen, B., Topcu, S., Türkeș, M., Sen, B., & Warner, J. (2012). Projecting climate change, drought conditions and crop productivity in Turkey. Climate Research, 52, 175–191. https://doi.org/10.3354/cr01074
  • Sensoy, A., & Tabak, B. M. (2014). Dynamic spanning trees in stock market networks: The case of Asia-Pacific. Physica A: Statistical Mechanics and Its Applications, 414, 387–402. https://doi.org/10.1016/j.physa.2014.07.067
  • Sollin, G. (1965). “M. Le tracé de canalisation”. Programming, Games, and Transportation Networks (in French) Spada, E., Sagliocca, L., Sourdis, J., Garbuglia, A. R., Poggi, V., de Fusco, C., & Mele, A. (2004). Use of the Minimum Spanning Tree Model for Molecular Epidemiological Investigation of a Nosocomial Outbreak of Hepatitis C Virus Infection. Journal of Clinical Microbiology, 42(9), 4230–4236. https://doi.org/10.1128/jcm.42.9.4230-4236.2004
  • Stooksbury, D. E., & Michaels, P. J. (1991). Cluster analysis of Southeastern U.S. climate stations. Theoretical and Applied Climatology, 44(3–4), 143–150. https://doi.org/10.1007/bf00868169
  • Tabak, B. M., Serra, T. R., & Cajueiro, D. O. (2009). The expectation hypothesis of interest rates and network theory: The case of Brazil. Physica A: Statistical Mechanics and Its Applications, 388(7), 1137–1149. https://doi.org/10.1016/j.physa.2008.12.036
  • TopicTea Team, 10 Major Tea Producers - Know Where Your Favorite Tea Comes From.Free Worldwide Shipping. Available online: https://topictea.com/blogs/tea-blog/major-tea-producers (accessed on 22 June 2020).
  • Türkeş, M., Koç, T., & Sariş, F. (2008). Spatiotemporal variability of precipitation total series over Turkey. International Journal of Climatology, 29(8), 1056–1074. https://doi.org/10.1002/joc.1768
  • Ulusoy, T., Keskin, M., Shirvani, A., Deviren, B., Kantar, E., & Çaǧrı Dönmez, C. (2012). Complexity of major UK companies between 2006 and 2010: Hierarchical structure method approach. Physica A: Statistical Mechanics and Its Applications, 391(21), 5121–5131. https://doi.org/10.1016/j.physa.2012.01.026
  • Vandewalle, N., Brisbois, F., & Tordoir, X. (2001). Non-random topology of stock markets. Quantitative Finance, 1(3), 372–374. https://doi.org/10.1088/1469-7688/1/3/308.
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Details

Primary Language English
Subjects Environment and Culture
Journal Section Research Article
Authors

Mehmet Batı

Mehmet Şahin

Publication Date June 30, 2022
Submission Date March 18, 2022
Published in Issue Year 2022 Volume: 10 Issue: 1

Cite

APA Batı, M., & Şahin, M. (2022). Analysis of the Relationship Between the Climate Characteristics of the Tea Producing Regions of the Leading Countries in Tea Production. Takvim-I Vekayi, 10(1), 89-102.

Takvim-i Vekayi (تقويم وقايع)