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Analysis of trend changes in degree-day values of heating and cooling: broiler breeding case

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
An ideal broiler house should be designed to minimize the effects of weather changes and to keep indoor conditions at the comfort temperature of the animals. In this case, this should be done with minimum cost and possible lowest operating costs. Degree-day methods are used in order to have knowledge of the energy need of any structure. With this method, the measured values or meteorological data can be used to give information about the heating and cooling energy quantities of structures. Depending on the climate change in recent years, the changes need to be examined that have taken place in order to provide optimum comfort in animal barn. Isparta province and districts were selected as the study area. The longterm average daily temperature values are used from meteorological stations of the selected region. The heating and cooling degree day values were calculated for selected balance temperatures in broiler breeding. Linear Regression Analysis and Spearman Rank Correlation Test were conducted to determine the changes of these values due to climate change. In conclusion, it was determined that there were statistically significant trends at 5% significance level in Egirdir (21°C), Isparta (31-29-25 and 23°C), Kasimlar (18°C), Senirkent (31-29-25-23 and 21°C), Sutculer (all selected balance temperature values) and Yalvac (31-29-25-23 and 21°C) in terms of heating degree-day values, and in Atabey (29-25-23-21 and 18°C), Barla (25-23 and 21°C), Isparta (23-21 and 18°C), Senirkent (29- 25-23-21 and 18°C), Sutculer (29-25-23-21 and 18°C), Sarkikaraagac (25-23-21 and 18°C), Uluborlu (25-23-21 and 18°C) and Yalvac (25-23-21 and 18°C) in terms of cooling degree-day values. As a result, it has been concluded that more energy consumption will be a concern for heating and cooling of the broiler house that will be built in the province of Isparta.
Rocznik
Tom
Strony
645--660
Opis fizyczny
Bibliogr. 33 poz., tab., wykr.
Twórcy
autor
  • Osmaniye Korkut Ata University, Osmaniye Vocational School, Osmaniye, Turkey
autor
  • Suleyman Demirel University Agriculture Faculty Agricultural Structure and Irrigation Department 32260 Isparta, Turkey
autor
  • Osmaniye Korkut Ata University, Osmaniye Vocational School, Osmaniye, Turkey
autor
  • Suleyman Demirel University Agriculture Faculty Agricultural Structure and Irrigation Department 32260 Isparta, Turkey
Bibliografia
  • Anonymous, (2015). Broiler Production, (online) (15.12.2016) Available at: http://www. tarim. gov.tr (In Turkish).
  • Atilgan A., Yucel A., Oz, H. (2012). Determination of heating and cooling day data for broiler housing: Isparta case, Journal of Food, Agriculture & Environment 10(3&4):353-356.
  • Aydin D., Kavak A.F., Toros H. (2015). Impact on electricity consumption of heating and cooling degree days VII. Atmospheric Science Symposium, April 28-30, Istanbul, pp.29-39.
  • Bagdatli, M.C., Istanbulluoglu, A., Alturk, B., Arslan, C. (2014). Uzun Yıllık Sıcaklık Verilerindeki Değişim Trendinin Tarımsal Kuraklık Açısından Değerlendirilmesi: Çorlu Örneği, Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 2:100-107. (In Turkish).
  • Bulut, H., Yesilata, B., Yesilnacar, M. I. (2006). Atatürk Baraj Gölünün Bölge İklimi Üzerine Etkisinin Trend Analizi İle Tespiti, GAP V. Mühendislik Kongresi Bildiriler Kitabı, 26-28 Nisan 2006, 79-86, Şanlıurfa. (In Turkish).
  • Buyukalaca O., Bulut H., Yilmaz T. (2001). Analysis of variable-base heating and cooling degree-days for Turkey, Applied Energy, 69:269-283.
  • Dahmen, E. R., Hall, M. J. (1990). Screening of Hydrological Data: Tests for Stationary and Relative Consistency, 58 p., Netherlands.
  • Demir, D.A., Sahin, U., Demir, Y. (2016). Murat Nehri Su kalite Parametrelerinin Trend Analizi ve Tarımsal Açıdan Kullanılabilirliği, YYÜ Tar. Bil. Derg., 26(3): 414-420. (In Turkish).
  • Erturk, M., Kurt, H.A., Kilic, A., Kaya, S. (2015). Relations of investigation for heating & cooling degree time calculator in latitude, longitude, altitude in the Marmara Region, 12. National Installation Engineering Congress, April 8-11, Izmir, pp1575-1594.
  • Gultekin, L., Kadioglu, M. (1996). Marmara Bölgesinde Isıtma ve Soğutma DereceGünlerinin Dağılımı, Tesisat Mühendisliği, Temmuz-Ağustos 1996, 3(31):33-41. (In Turkish).
  • Haan, C. T. (1977). Statistical Methods in Hydrology, Iowa State University Press, Ames, USA.
  • Hamdi, M. R., Abu-Allaban. M., Al-Shayeb, A., Jaber, M., Momani, N. M. (2009). Climate Change in Jordan: A Comprehensive Examination Approach, American Journal of Environmental Sciences, 5(1), 58-68.
  • Helsel, D. R., Hirsch, R. M. (1993). Statistical Methods in Water Resources, Studies in Environmental Sciences: 49, Elsevier, USA.
  • Kadioglu, M. (1997). Trends in Surface Air Temperature Data over Turkey, Int. J.Climatol., 17:511-520.
  • Kadioglu, M., Sen, Z., Gultekin, L. (2001). Variation and Trends in Turkish Seasonal Heating and Cooling Degree-Days, Climatic Change, 49: 209-223.
  • Kalayci, S., Kahya, E. (1998). Susurluk Havzası nehirlerinde su kalitesi trendlerinin belirlenmesi. Journal of Engineering and Environmental Science, 22: 503-514. (In Turkish).
  • Kanji, G. K. (2006). 100 Statistical Tests, 3rd Edition, SAGE Publications, 242 p., New Delhi.
  • Kendall, M., Gibbons, J. D. (1990). Rank Correlation Methods, Fifth Edition, 260 p., USA.
  • Kottegoda, N. T. (1980). Stochastic Water Resources Technology, The McMillan Press Ltd., 384 p., London.
  • Krese G., Prek M., Butala V. (2012). Analysis of building electric energy consumption data using an improved cooling degree day method. Journal of Mechanical Engineering, 58(2): 107-114.
  • Kuehn, T.H., Ramsey, J.W., Threlkeld, J.L. (1998). Thermal Environmental Engineering, 3th Edition, Prentice Hall, New Jersey, 740 pp.
  • Lindley J.A., Whitaker J.H. (1996). Agricultural buildings and structures, 2nd edition. Technical Books Information Publishing Group, USA, 605 p.
  • Onoz, B., Bayazit, M. (2003). The Power of Statistical Tests for Trend Detection, Turkish Journal of Engineering and Environmental Sciences, 27:247-251.
  • Satman A., Yalcinkaya N. (1999) Heating and cooling degree-hours for Turkey, Energy, 24:833-840.
  • Shammugasundram, S. (2012). Statistical Analysis to Detect Climate Change And Its Implication on Water Resources, School of Engineering And Science, Faculty of Health, Engineering And Science, Victoria University, Australia.
  • Singh, D., Gupta, R. D., Jain, S. K. (2015). Study of Daily Temperature Indices Over Sutlej Basin, N-W Himalayan Region, India, Global NEST Journal, 17(2):301-311.
  • Sneyers, R. (1990). On The Statistical Analysis of Series of Observations, WMO Technical Note 143, WMO No: 415, TP-103, Genva, World Meteorological Organization, pp192.
  • Sen, Z. (2002). Hidrolojide Veri İşleme, Yorumlama ve Tasarım, Seminer Notları, 28 Ocak - 2 Şubat, Su Vakfı Yayınları, İstanbul. (In Turkish).
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  • Yildiz, I., Sosaoglu B. (2007). Spatial distributions of heating, cooling, and industrial degree-days in Turkey. Theoretical and Applied Climatology, 90 (3-4): 249-261.
  • Yucel, A., Atilgan, A., Oz, H., Saltuk, B. (2014). The determination of heating and cooling day values using degree-day method: Tomato plant example. Infrastructure and Ecology of Rural Areas, VI(I):1049-1061.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-26ed42bd-8038-436f-9022-b32c2e3e9a69
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