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The Effects of Global Warming to the Agricultural Yield

The Effects of Global Warming to the Agricultural Yield. DURUCASU, Hasan LEZKİ, Şenay ÇOŞKUN, Duygu. Global Warming. Climate Change. Agricultural Map of Turkey. Agricultural Products. Wheat is commonly cultivated plant with a frequency of 7 regions T omato cultivated in 5 regions

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The Effects of Global Warming to the Agricultural Yield

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  1. The Effects of Global Warming to the Agricultural Yield DURUCASU, Hasan LEZKİ, Şenay ÇOŞKUN, Duygu

  2. Global Warming

  3. Climate Change

  4. Agricultural Map of Turkey

  5. Agricultural Products • Wheat is commonly cultivated plant with a frequency of 7 regions • Tomato cultivated in 5 regions • Sugar beet cultivated in 4 regions • Hazelnutcultivated in 1 region

  6. Climate Features • Rainfall (mm)

  7. Climate Features • Rainfall (mm) • Snow cover (cm)

  8. Climate Features • Rainfall (mm) • Snow cover (cm) • Humidity (%)

  9. Climate Features • Rainfall (mm) • Snow cover (cm) • Humidity (%) • Air temperature (°C)

  10. Climate Features • Rainfall (mm) • Snow cover (cm) • Humidity (%) • Air temperature (°C) • Soil temperature (°C)

  11. Selected Meteorological Variables

  12. Rainfall

  13. Snow cover

  14. Humidity

  15. Air Temperature

  16. Soil Temperature

  17. Meteorological Variables For each product, Annual Averages of meteorological variables are considered just for the stations located in the determined agricultural regions

  18. Selected Agricultural Products

  19. Annual Wheat Production (MT)

  20. Annual Tomato Production (MT)

  21. Annual Sugar Beet Production (MT)

  22. Annual Hazelnut Production (MT)

  23. Database

  24. Correlations Between Chosen Meteorological Variables

  25. Regression Analysis Regression coefficients Error  Explanatory variables  Explained variable

  26. Statistical Model for Wheat Production • The regression model is, Wheat =56315793 –100511 Rainfall + 487304 Snow Cover – 265082 Humidity +6441109 Air Temperature –6701124 Soil Temperature R2=35.3% Anova p=0.042

  27. Statistical Model for Sugar Beet Production • The regression model is, Sugar Beet = 123095987 - 124367 Rainfall + 331934 Snow Cover -80709 Humidity +18066146 Air Temperature - 19211292 Soil Temperature R2= 68% Anova p=0.000

  28. Statistical Model for Tomato Production • The regression model is, Tomato = - 75406988 - 49456 Rainfall + 196884 Snow Cover + 493640 Humidity - 3255145 Air Temperature + 5929358 Soil Temperature R2 = 39.7% Anova p=0.020

  29. Statistical Model for Hazelnut Production • The regression model is, Hazelnut = - 1637064 + 981 Rainfall - 10371 Snow Cover + 4429 Humidity + 155448 Air Temperature - 29431 Soil Temperature R2= 36.3% Anova p= 0.036

  30. Conclusion • Meteorological factors • Soil quality • Seed quality • Fertilization

  31. Thanks for your interest e-mail adresses: hdurucasu@anadolu.edu.tr slezki@anadolu.edu.tr dcoskun@anadolu.edu.tr

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