Variability in Monthly Rainfall and Temperature Has an Influence on Daily Milk Production in Sahiwal Cows in Kenya
[1]
MacDonald Gichuru Githinji, Kenya Agriculture and Livestock Research Organization, Naivasha, Kenya; Department of Animal Sciences, Egerton University, Egerton, Kenya.
[2]
Evans Deyie Ilatsia, Kenya Agriculture and Livestock Research Organization, Naivasha, Kenya.
[3]
Thomas Kainga Muasya, Department of Animal Sciences, Egerton University, Egerton, Kenya.
[4]
Bockline Omedo Bebe, Department of Animal Sciences, Egerton University, Egerton, Kenya.
Climate change leads to alteration of environmental conditions directly or indirectly through anthropogenic activities. The consequences include fluctuations in the mean as well as variability of recognizable environmental variables with the changes persisting for longer than normal periods. Climate change poses numerous serious threats to livestock production through increased temperature, changes and shifts in rainfall distribution and increased frequency of extreme weather events. Grazing systems that are dependent on the natural cycle of climatic conditions are expected to be more seriously impacted by climate change. The consequences of climate change include increased heat stress, reduced water and feed quality and availability, increased cases of diseases and pests and or emergence of new ones. As livestock farmers in the tropics continue to bear the brunt of climate change, there is need to understand how the variability of identifiable environmental variables influence livestock performance. The objective of this study was to determine the influence of rainfall and temperature of milk yield in Sahiwal cattle in Kenya. Monthly milk yield records of Sahiwal cows and meteorological data for monthly minimum and maximum temperature and rainfall for a period of 32 years were extracted from records at the national Sahiwal stud, Naivasha, Kenya. The relationship between the variables was studied by multiple regression analysis. Minimum and maximum temperature and monthly rainfall significantly (P < 0.05) affected monthly milk yield. The proportion of total variation accounted for by climatic variables was small (0.5%) but significant. Each individual weather variable accounted for a small proportion of total variation. Minimum and maximum temperature had a negative effect on monthly milk yield. For every 1°C increase temperature, in monthly milk yield decreased by -1.58kg and -1.17kg, respectively. A 1 mm increase in monthly rainfall of monthly caused monthly milk yield to increase by 0.07kg. Mitigating strategies are required to alleviate the negative effects of temperature on monthly milk yield. Sound grazing management and feed conservation could harness the advantage of the positive effect of rainfall on milk yield.
Climate Change, Heat Stress, Mitigation, Rainfall Variability
[1]
United Nations Framework Convention on Climate Change (UNFCC) 2008 Challenges and opportunities for mitigation in the agricultural sector. http://unfccc.int/resource/docs/2008/tp/08.pdf
[2]
Intergovernmental Panel on Climate Change (IPCC) 2007 Climate Change 2007: impacts, adaptation and vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the IPCC, M. L. Parry, O. F. Canziani, J. P. Palutikof, P. J. van der Linden and C. E. Hanson, eds. Cambridge, UK, Cambridge University Press. 976 pp. http://www.eea.europa.eu
[3]
Rojas-Downing M M, Nejadhashemi A P, Harrigan T and Woznicki S A 2017 Climate change and livestock: impacts, adaptation, and mitigation. Climate Risk Management 16, 145–163.
[4]
Chapman S C, Chakraborty S, Dreccer M F and Howden S M 2012 Plant adaptation to climate change: opportunities and priorities in breeding. Crop Pasture Science 63, 251–268. https://bioone.org/journals
[5]
Nardone A, Ronchi B, Lacetera N, Ranieri M S, Bernabucci U 2010 Effects of climate change on animal production and sustainability of livestock systems. Livestock Science 130, 57–69.
[6]
Thornton P K, Van de Steeg J, Notenbaert A and Herrrero M 2009 The impacts of climate change on livestock and livestock systems in developing countries: A review of what we know and what we need to know. Agricultural Systems 101, 113–127. http://www.fao.org/tempref/AG/Reserved
[7]
Karl T R, Melillo J M and Peterson T C 2009 Global Climate Change Impacts in the United States. U.S. Global Change Research Programme. Cambridge University Press. http://www.iooc.us.
[8]
UNDP 2014 Sustaining Human Progress: Reducing Vulnerabilities and Building Resilience; Human Development Report 2014. United Nations Development Programme (UNDP), New York, USA. http://www. hdr.undp.org/
[9]
Aydinalp C and Cresser M S 2008 The effects of global climate change on agriculture. American-Eurasian Journal of Agricultural and Environmental Science, 3: 672-676.
[10]
Hoffman M T and Vogel C 2008 Climate change impacts on African rangelands. Rangelands, 30: 12-17. https://bioone.org/
[11]
FAO 2009 State of food and agriculture - livestock in the balance. Rome. http://www.fao.org
[12]
Thornton P K and Gerber P J 2010 Climate change and the growth of the livestock sector in developing countries. Mitig. Adapt. Strategies Global Change 15, 169–184.
[13]
Nouaceur Z, Murărescu O and Murătoreanu G 2017 Rainfall variability and trend analysis of multiannual rainfall in Romanian plain. Annals of Valahia University of Targoviste. Geographical Series, 17(2): 124-144 DOI: 10.1515/avutgs-2017-0012. https://content.sciendo.com/.
[14]
Rustum R, Adeloye A J and Mwale F 2017 Spatial and temporal Trend Analysis of Long Term rainfall records in data-poor catchments with missing data, a case study of Lower Shire floodplain in Malawi for the Period 1953-2010. Hydrology and Earth Systems Sciences Discuss., https://doi.org/10.5194/hess-2017-601
[15]
Pedersen L, Jensen N E, Christensen L E, Madsen H 2010 Quantification of the spatial variability of rainfall based on a dense network of rain gauges. Atmospheric Research 95, 441–454. https://orbit.dtu.dk/.
[16]
Kumar N, Panchal C C, Chandrawanshi S K and Thanki J D 2017 Analysis of rainfall by using Mann-Kendall trend, Sen’s slope and variability at five districts of south Gujarat, India. Mausam, 68(2), 205-222. www.indiaenvironmentportal.org.in
[17]
Thornton P K 2010 Livestock production: recent trends, future prospects. Philosophical Transactions of the Royal Society B, 365: 2853-2867. https://royalsocietypublishing.org/doi/10.1098/rstb.2010.0134
[18]
Lacetera N 2019 Impact of climate change on animal health and welfare. doi: 10.1093/af/vfy030. https://academic.oup.com/af/article/9/1/26/5168813
[19]
Santos R, Cachapa A, Carvalho G P, Silva C B, Hernández L, Preira L S, Minas M amd Vala H 2019 Mortality and Morbidity of Beef Calves in Free-Range Farms in Alentejo, Portugal—A Preliminary Study. Veterinary Medicine International Volume 2019, Article ID 3616284, 8 pages https://doi.org/10.1155/2019/3616284.
[20]
Waghorn G C and Hegarty R S 2011 Lowering ruminant methane emissions through improved feed conversion efficiency. Animal Feed Science Technology, 166-167: 291-301.
[21]
Ilatsia E D, Roessler R, Kahi A K, Piepho H-P and Valle Zárate A 2011 Production objectives and breeding goals of Sahiwal cattle keepers in Kenya. Implications for a breeding programme. Tropical Animal Health and Production (Online first article; doi: 10.1007/s11250-011-9928-8s). https://pdfs.semanticscholar.org/
[22]
Muhuyi W B, Lokwaleput I and Ole Sinkeet S N 1999 Conservation and utilization of the sahiwal cattle in kenya. AGRI 26, 35-44. https://pdfs.semanticscholar.org
[23]
Msechu J K K, Mgheni I M and Syrstad O 1995 Influence of various climatic factors on milk production in cattle in Tanzania Tropical Animal Health and Production 27, 121-126
[24]
Asfaw A, Simane B, Hassen A and Bantider A 2018 Variability and time series trend analysis of rainfall and temperature in northcentral Ethiopia: A case study in Woleka sub-basin. Weather and Climate Extremes 19, 29-41.
[25]
Rhoads R P, Baumgradt l H and Saugee-Bedore J 2013 Metabolic proiroties during heat stress with emphasis on skeletal muscle. Journal of Animal Science, 91(6) doi:10.2527/jas.2012-6120.
[26]
Brown-Brandl, T. M., R. A. Eigenberg, J. A. Nienaber, and G. L. Hahn. 2005a. Dynamic response indicators of heat Stress in shaded and non-shaded feedlot cattle, Part 1: analyses of indicators. Biosystems Engineering 90: 451-462.
[27]
Berman A J 2005 Estimates of heat stress relief needs for Holstein dairy cows. Journal of Animal Science 83, 1377–1384. https://europepmc.org/article/med/15890815
[28]
Javari M 2017 Assessment of temperature and elevation controls on spatial variability of rainfall in Iran. Atmosphere 8, 45; doi:10.3390/atmos8030045. https://www.mdpi.com/2073-4433/8/3/45
[29]
IFAD [International Fund for Agricultural Development) 2010 Livestock and climate change. http://www.ifad.org/lrkm/events/cops/papers/climate.pdf
[30]
USDA (United States Department of Agriculture) 2013 Climate Change and Agriculture in the United States: Effects and Adaptation. USDA technical bulletin, Washington, DC. http://www.usda.gov/oce/climate_change/effects_2012/CC%20and%20Agriculture%20Report%20%2802-04-2013%29b.pdf.
[31]
Renaudeau, D., Collin, A., Yahav, S., De Basilio, V., Gourdine, J. L., Collier, R. J., 2012. Adaptation to hot climate and strategies to alleviate heat stress in livestock production. Animal 6 (05), 707–728.
[32]
Thornton P K and Herrero M 2010 The Inter-linkages between rapid growth in livestock production, climate change, and the impacts on water resources, land use, and deforestation. World Bank Policy Research Working Paper, WPS 5178. World Bank, Washington, DC. http://citeseerx.ist.psu.edu/
[33]
Lakew H 2017 Economic impact of climate change on milk production: a case study of selected areas in the Free State. MSc thesis, University of the Free State, Bloemfontein, South Africa.
[34]
Sejian V, Maurya V P, Kumar K and Naqvi S M K 2013 Effect of multiple stresses (thermal, nutritional, and walkingstress) on growth, physiological response, blood biochemical and endocrine responses in Malpura ewes under semi-arid tropical environment. Tropical Animal Health and Production 45:107–116. doi:10.1007/s11250-012-0180-7.
