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Analysis of the role of milk yield in sustainable cattle breeding using geographically weighted regression

Yıl 2015, , 58 - 68, 31.01.2015
https://doi.org/10.29133/yyutbd.236275

Öz

The main aim of this paper is to address the question of why native cattle were shifted from native breeds to cultured and cross-breed cattle from 2000 to 2010 and to examine whether milk yield played role in those shifts. In this paper, how milk yield influences cattle production is characterized by taking into account the contribution of local geographical relationships and variations. This paper is motivated by the concern that total number of native cattle has decreased most alarmingly in Turkey. Sustainable dairy farm systems are inextricably linked with high milk yield culture cattle imported from European countries. High milk yield has become the indicator that possesses the spillover effect for the development of cattle production. The high milk yield that is abused by culture cattle systems has led to a general increase in cattle production, especially in the west and middle-south of Turkey where farmers are relatively richer.

Kaynakça

  • References
  • Barnwal P, Kotani K (2013). Climatic impacts across agricultural crop yield distributions: An application of quantile regression on rice crops in Andhra Pradesh, India. Ecological Economics, 87: 95-109.
  • Bernabucci U, Calamari L (1998). Effects of heat stress on bovine milk yield and composition. Nutrizione Animale. 24 (6): 247–257.
  • Bernués A, Ruiz R, Olaizola A, Villalba D, Casasús I (2011). Sustainability of pasture-based livestock farming systems in the European Mediterranean context: Synergies and trade-offs. Livestock Science. 139 (1/2): 44-57.
  • Blench R (2005). Conservation of indigenous livestock: sustaining biodiversity for current and future generations. In: Presentation in CGIAR annual general meeting 6th Dec 2005. Marrakech, Morocco.
  • BSB (2008). 2008 Kavşağında Türkiye siyaset iktisat ve toplum. Yordam, Istanbul.
  • Ediger VS, Huvaz O (2006). Examining the sectoral energy use in Turkish economy (1980–2000) with the help of decomposition analysis. Energy Conversion and Management 47 (6):732–745.
  • FAO (2007). The State of the World’s Animal Genetic Resources for Food and Agriculture -in brief. Rome.
  • Farrow A, Larrea C, Hyman G, Lema G (2005). Exploring the spatial variation of food poverty in Ecuador. Food Policy, 30(5): 510-531.
  • Fotheringham A S, Brunsdon C, Charlton M (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley, Chichester.
  • Gocer K. (2014). Analysis of changes in grain production on fruit and vegetable cultivation areas in Turkey through geographically weighted regression. Scientific Research and Essays. 9 (12): 540 - 547.
  • Hasanov M, Ayşen A, Telatar F (2010). Nonlinearity and structural stability in the Phillips curve: Evidence from Turkey. Economic Modelling 27 (5): 1103–1115.
  • Herrero M, Thornton PK, Notenbaert AM, Wood S, Msangi S, Freeman HA, Bossio D, Dixon J, Peters,M, van de Steeg J, Lynam J, Parthasrathy Rao P, Macmillan S, Gerard B, McDermott J, Seré C, Rosegrant M (2010). Smart investments in sustainable food production: revisiting mixed crop livestock systems. Science 327(5967): 822–825.
  • Huang J, Huang Y, Pontius R G, Zhang Z (2015). Geographically weighted regression to measure spatial variations in correlations between water pollution versus land use in a coastal watershed. Ocean and Coastal Management, 103: 14-24.
  • Kepenek Y, Yentürk N ( 2000). Türkiye ekonomisi. Remzi kitapevi, Isanbul.
  • Manca G, Attaway DF, Waters N (2014). Program assessment and the EU's agrienvironmental Measure 214: An investigation of the spatial dynamics of agrienvironmental policies in Sardinia, Italy. Applied Geography, 50: 24-30.
  • Nardone A, Ronchi B, Lacetera N, Ranieri MS, Bernabucci U (2010). Effects of climate changes on animal production and sustainability of livestock systems. Livestock Science. 130 (1-3): 57–69.
  • Naskar S, Gopal GR, Chopra A, Chandan C, Prince LLL (2012). Genetic Adaptability of Livestock to Environmental Stresses, pp. 335-337, In: Environmental Stress and Amelioration in Livestock Production, Sejian V, Naqvi SM K, Ezeji T, Lakritz J, Lal R ( eds), Springer-Verlag Berlin Heidelberg.
  • Nienaber JA, Hahn GL, Eigenberg RA (1999). Quantifying livestock responses for heat stress management: a review. International Journal of Biometeorology. 42 (4): 183-188.
  • Passel SV, Mathijs E, Van Huylenbroeck G (2006). Explaining Differences in Farm Sustainability: Evidence from Flemish Dairy farms. In: Contributed paper prepared for presentation at the International Association of Agricultural Economists Conference. Gold Coast, Australia, August 12-18, 2006. Scottish Agricultural College, 2006. The Farm Management Handbook 2006/07. SAC. Edinburgh.
  • Rhone A (2008). Factors Affecting Milk Yield, Milk Fat, Milk Quality, And Economic Performance of Dairy Farms in The Central Region of Thailand University of Florida. Doctorate topics, pp. 26- 29.
  • Sage JL, Goldberger JR (2012). Decisions to direct market: Geographic influences on conventions in organic production. Applied Geography, 34: 57-65.
  • Sang N, Dramstad WE, Bryn A (2014). Regionality in Norwegian farmland abandonment: Inferences from production data. Applied Geography 55: 238-247.
  • Schiere J, Ibrahim MNM, Keulen H (2002). The role of livestock for sustainability in mixed farming: criteria and scenario studies under varying resource allocation. Agriculture Ecosystems and Environment. 90 (2): 139–153.
  • Sejian V, Naqvi S M K, Ezeji T Lakritz J & Lal R (2012). Introduction. Sejian V Naqvi S M K Ezeji T, Lakritz J & Lal R (eds.), Environmental Stress and Amelioration in Livestock Production, Springer-Verlag Berlin Heidelberg. pp. 1-12.
  • Sturaro E, Marchiori E, Cocca G, Penasa M, Ramanzin M, Bittante G (2013). Dairy systems in mountainous areas: Farm animal biodiversity, milk production and destination, and land use. Livestock Science. 158 (1): 157-168.
  • Su S, Xiao R, Zhang Y (2012). Multi-scale analysis of spatially varying relationships between agricultural landscape patterns and urbanization using geographically weighted regression. Applied Geography, 32 (2): 360-375.
  • SUTBIRLIK (2013 ). Türkiye süt üreticileri merkez birliği. Avaliable on the internet: http://www.sutbirlik.com/ .Accessed 15 January 2014.
  • Tu and J, Xia ZG (2008). Examining spatially varying relationships between land use and water quality using geographically weighted regression I: model design and evaluation. Science of the Total Environment 407 (1): 358 -378.
  • Tu J (2011). Spatially varying relationships between land use and water quality across an urbanization gradient explored by geographically weighted regression. Applied Geography, 31(1): 376-392.
  • TUIK (2001). Agricultural census village information. Turkish Statistical Institute . Ankara.
  • TUIK (2013). Livestock statistics. Turkish Statistical Institute, Ankara. Available on the internet: http://tuikapp.tuik.gov.tr/hayvancilikapp/hayvancilik.zul. Accessed 10 October 2012.
  • TZOB (2008). Türkiye Süt Sektörünün Değerlendirilmesi 2008 Yılı ve Sonrası Beklentiler. Türkiye Ziraat Odaları Birliği. ANKARA.p. 25-26
  • Wang Q, Ni J, Tenhunen J (2005). Application of a geographically‐weighted regression analysis to estimate net primary production of Chinese forest ecosystems. Global Ecology and Biogeography, 14(4): 379-393.
  • Wolfenson D, Roth Z Meidan R (2000). Impaired reproduction in heat stressed cattle: basic and applied aspects, Animal Reproduction Science, 60–61: 535–547.
  • Yang Y, Tong X, Zhu J. (2013). A geographically weighted model of the regression between grain production and typical factors for the Yellow River Delta. Mathematical and Computer Modelling, 58(3): 582-587.

Sürdürülebilir Sığır Islahında Coğrafik Ağırlıklı Regresyon Kullanılarak Süt Verimi Rolü Analizi

Yıl 2015, , 58 - 68, 31.01.2015
https://doi.org/10.29133/yyutbd.236275

Öz

Bu makalenin temel amacı 2000-2010 arasındaki dönemde, yerli sığır yetiştiriciliğinden kültür ve melez sığırlara geçişin nedenlerinin ve geçişte süt verimliliğinin rolünün olup olmadığının saptanmasıdır. Bu çalışmada süt verimliliğinin sığır üretimini nasıl etkilediği yerel coğrafi ilişkiler ve varyasyonlar dikkate alınarak karakterize edilmiştir. Türkiye’de yerli sığırların sayılarındaki belirleyici azalma, çalışmanın temel motivasyonu olmuştur. Sürdürülebilir süt çiftlik sistemleri Avrupa ülkelerinden ithal edilen ve yüksek süt verimliliği olan kültür sığırları ile sıkı ilişki içindedir. Yüksek süt verimliliği sığır üretiminin gelişmesinde ayırdedici bir yayılma etkisine sahiptir. Türkiye’nin doğusu ve batısı süt verimliliği açısından oldukça farklılık göstermiştir.  Kültür sığır yetiştiriciliği tarafından suiistimal edilmiş olan yüksek süt verimi, özelikle çiftçilerin oransal olarak daha zengin olduğu Batı ve Orta-Güney Türkiye’de sığır üretiminde genel bir artışa neden olmuştur. 

Kaynakça

  • References
  • Barnwal P, Kotani K (2013). Climatic impacts across agricultural crop yield distributions: An application of quantile regression on rice crops in Andhra Pradesh, India. Ecological Economics, 87: 95-109.
  • Bernabucci U, Calamari L (1998). Effects of heat stress on bovine milk yield and composition. Nutrizione Animale. 24 (6): 247–257.
  • Bernués A, Ruiz R, Olaizola A, Villalba D, Casasús I (2011). Sustainability of pasture-based livestock farming systems in the European Mediterranean context: Synergies and trade-offs. Livestock Science. 139 (1/2): 44-57.
  • Blench R (2005). Conservation of indigenous livestock: sustaining biodiversity for current and future generations. In: Presentation in CGIAR annual general meeting 6th Dec 2005. Marrakech, Morocco.
  • BSB (2008). 2008 Kavşağında Türkiye siyaset iktisat ve toplum. Yordam, Istanbul.
  • Ediger VS, Huvaz O (2006). Examining the sectoral energy use in Turkish economy (1980–2000) with the help of decomposition analysis. Energy Conversion and Management 47 (6):732–745.
  • FAO (2007). The State of the World’s Animal Genetic Resources for Food and Agriculture -in brief. Rome.
  • Farrow A, Larrea C, Hyman G, Lema G (2005). Exploring the spatial variation of food poverty in Ecuador. Food Policy, 30(5): 510-531.
  • Fotheringham A S, Brunsdon C, Charlton M (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley, Chichester.
  • Gocer K. (2014). Analysis of changes in grain production on fruit and vegetable cultivation areas in Turkey through geographically weighted regression. Scientific Research and Essays. 9 (12): 540 - 547.
  • Hasanov M, Ayşen A, Telatar F (2010). Nonlinearity and structural stability in the Phillips curve: Evidence from Turkey. Economic Modelling 27 (5): 1103–1115.
  • Herrero M, Thornton PK, Notenbaert AM, Wood S, Msangi S, Freeman HA, Bossio D, Dixon J, Peters,M, van de Steeg J, Lynam J, Parthasrathy Rao P, Macmillan S, Gerard B, McDermott J, Seré C, Rosegrant M (2010). Smart investments in sustainable food production: revisiting mixed crop livestock systems. Science 327(5967): 822–825.
  • Huang J, Huang Y, Pontius R G, Zhang Z (2015). Geographically weighted regression to measure spatial variations in correlations between water pollution versus land use in a coastal watershed. Ocean and Coastal Management, 103: 14-24.
  • Kepenek Y, Yentürk N ( 2000). Türkiye ekonomisi. Remzi kitapevi, Isanbul.
  • Manca G, Attaway DF, Waters N (2014). Program assessment and the EU's agrienvironmental Measure 214: An investigation of the spatial dynamics of agrienvironmental policies in Sardinia, Italy. Applied Geography, 50: 24-30.
  • Nardone A, Ronchi B, Lacetera N, Ranieri MS, Bernabucci U (2010). Effects of climate changes on animal production and sustainability of livestock systems. Livestock Science. 130 (1-3): 57–69.
  • Naskar S, Gopal GR, Chopra A, Chandan C, Prince LLL (2012). Genetic Adaptability of Livestock to Environmental Stresses, pp. 335-337, In: Environmental Stress and Amelioration in Livestock Production, Sejian V, Naqvi SM K, Ezeji T, Lakritz J, Lal R ( eds), Springer-Verlag Berlin Heidelberg.
  • Nienaber JA, Hahn GL, Eigenberg RA (1999). Quantifying livestock responses for heat stress management: a review. International Journal of Biometeorology. 42 (4): 183-188.
  • Passel SV, Mathijs E, Van Huylenbroeck G (2006). Explaining Differences in Farm Sustainability: Evidence from Flemish Dairy farms. In: Contributed paper prepared for presentation at the International Association of Agricultural Economists Conference. Gold Coast, Australia, August 12-18, 2006. Scottish Agricultural College, 2006. The Farm Management Handbook 2006/07. SAC. Edinburgh.
  • Rhone A (2008). Factors Affecting Milk Yield, Milk Fat, Milk Quality, And Economic Performance of Dairy Farms in The Central Region of Thailand University of Florida. Doctorate topics, pp. 26- 29.
  • Sage JL, Goldberger JR (2012). Decisions to direct market: Geographic influences on conventions in organic production. Applied Geography, 34: 57-65.
  • Sang N, Dramstad WE, Bryn A (2014). Regionality in Norwegian farmland abandonment: Inferences from production data. Applied Geography 55: 238-247.
  • Schiere J, Ibrahim MNM, Keulen H (2002). The role of livestock for sustainability in mixed farming: criteria and scenario studies under varying resource allocation. Agriculture Ecosystems and Environment. 90 (2): 139–153.
  • Sejian V, Naqvi S M K, Ezeji T Lakritz J & Lal R (2012). Introduction. Sejian V Naqvi S M K Ezeji T, Lakritz J & Lal R (eds.), Environmental Stress and Amelioration in Livestock Production, Springer-Verlag Berlin Heidelberg. pp. 1-12.
  • Sturaro E, Marchiori E, Cocca G, Penasa M, Ramanzin M, Bittante G (2013). Dairy systems in mountainous areas: Farm animal biodiversity, milk production and destination, and land use. Livestock Science. 158 (1): 157-168.
  • Su S, Xiao R, Zhang Y (2012). Multi-scale analysis of spatially varying relationships between agricultural landscape patterns and urbanization using geographically weighted regression. Applied Geography, 32 (2): 360-375.
  • SUTBIRLIK (2013 ). Türkiye süt üreticileri merkez birliği. Avaliable on the internet: http://www.sutbirlik.com/ .Accessed 15 January 2014.
  • Tu and J, Xia ZG (2008). Examining spatially varying relationships between land use and water quality using geographically weighted regression I: model design and evaluation. Science of the Total Environment 407 (1): 358 -378.
  • Tu J (2011). Spatially varying relationships between land use and water quality across an urbanization gradient explored by geographically weighted regression. Applied Geography, 31(1): 376-392.
  • TUIK (2001). Agricultural census village information. Turkish Statistical Institute . Ankara.
  • TUIK (2013). Livestock statistics. Turkish Statistical Institute, Ankara. Available on the internet: http://tuikapp.tuik.gov.tr/hayvancilikapp/hayvancilik.zul. Accessed 10 October 2012.
  • TZOB (2008). Türkiye Süt Sektörünün Değerlendirilmesi 2008 Yılı ve Sonrası Beklentiler. Türkiye Ziraat Odaları Birliği. ANKARA.p. 25-26
  • Wang Q, Ni J, Tenhunen J (2005). Application of a geographically‐weighted regression analysis to estimate net primary production of Chinese forest ecosystems. Global Ecology and Biogeography, 14(4): 379-393.
  • Wolfenson D, Roth Z Meidan R (2000). Impaired reproduction in heat stressed cattle: basic and applied aspects, Animal Reproduction Science, 60–61: 535–547.
  • Yang Y, Tong X, Zhu J. (2013). A geographically weighted model of the regression between grain production and typical factors for the Yellow River Delta. Mathematical and Computer Modelling, 58(3): 582-587.
Toplam 36 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Su Kaynakları ve Su Yapıları
Bölüm Makaleler
Yazarlar

Kenan Göçer

Yayımlanma Tarihi 31 Ocak 2015
Yayımlandığı Sayı Yıl 2015

Kaynak Göster

APA Göçer, K. (2015). Analysis of the role of milk yield in sustainable cattle breeding using geographically weighted regression. Yuzuncu Yıl University Journal of Agricultural Sciences, 25(1), 58-68. https://doi.org/10.29133/yyutbd.236275

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