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Effects of Environment on Productive Performance of Holstein-Friesian Dairy Cows in Three Agro-Ecological Regions of Zimbabwe

Year 2022, , 172 - 179, 01.07.2022
https://doi.org/10.47115/bsagriculture.1031623

Abstract

The level of performance in any livestock production enterprise is a function of genetic and non-genetic factors and their interaction. For the purpose of agricultural production decisions, Zimbabwe was divided into five agro-ecological zones (AEZ) according to rainfall intensity, distribution and length of rainy season. Commercial dairy production, based on specialist dairy breeds such as Holstein, Holstein-Friesian and Jersey, is confined to AEZ I, II, III and IV. The performance of these breeds in contrasting AEZ has not been determined. In this study, farm level data of 7562 Holstein-Friesian cows calving in the period 2003-2011 was used to compare milk yield and milk components across three contrasting AEZ of Zimbabwe. A Generalized Linear Model (GLM) was fitted to investigate the fixed effects of year, season and AEZ and random effects of days in milk (DIM) on milk production and component traits. The factors herd, agro-ecological zone, year and season had significant (P<0.001) effects on all variables tested. The most favourable performance of Holstein-Friesian cows was observed in AEZ II and during the hot-dry season due to higher test-day milk yield, protein, butterfat and total solids, and lower somatic cell counts. However, season and agro-ecological region are not limiting factors for commercial dairy production in Zimbabwe. Where animal performance may be sub-optimal, opportunities do exist for using strategies and technologies that help adapt and cope with climate conditions.

References

  • Chirinda N, Murungweni C, Waniwa A, Nyamangara J, Tangi A, Peters M, Notenbaert A, Burkart S. 2021. Perspectives on reducing the national milk deficit and accelerating the transition to a sustainable dairy value chain in Zimbabwe. Front Sust Food Sys, 5: 726482.
  • Collier R, Zimbelman R, Rhoads R, Rhoads M, Baumgard L. 2011. A re-evaluation of the impact of temperature humidity index (THI) and black globe humidity index (BGHI) on milk production in high producing dairy cows. Western Dairy Management Conf. Reno, NV, USA, pp: 113-125.
  • Fontaneli RS, Sollenberger LE, Littell RC, Staples CR. 2005. Performance of lactating dairy cows managed on pasture–based or in free stall barn–feeding systems. J Dairy Sci, 88: 1264-1276.
  • Gororo E. 2016. Dairy farm business models and cost of doing dairy in Zimbabwe. Zimbabwe Association of Dairy Farmers (ZADF), Harare, Zimbabwe, pp: 56.
  • Gwatibaya S. 2012. Production and physiological responses of lactating Holstein dairy cows to the provision of shade in sub-tropical Zimbabwe. MSc thesis, University of Zimbabwe, pp: 43.
  • Hagnestam-Nielsen C, Emanuelson U, Berglund B, Strandberg E. 2009. Relationship between somatic cell count and milk yield in different stages of lactation. J Dairy Sci, 92: 3124-3133.
  • Hammami H, Boulbaba R, Gengler N. 2009. Genotype by environment interaction in dairy cattle. Soc Environ, 13(1): 155-164.
  • Kunaka K, Makuza SM. 2005. Genetic and environmental trends for milk traits for Zimbabwean Holstein-Friesian population, Pakistan J Biol Sci, 8(7): 1011-1015.
  • Makuza SM, McDaniel BT. 1997. Genetic and phenotypic trends for Holstein herds in Zimbabwe. J Zimbabwe Soc Anim Prod, 8: 111-114.
  • Matekenya DT. 2016. Large scale dairy value chain in Zimbabwe. URL: http://www.drss.gov.zw/ (access date: September 17, 2021).
  • Mhlanga I, Ndaimani H, Mpakairi K, Mujere N. 2018. Climate change: An uncertain future for dairy farming in Zimbabwe. Transact Royal Soc South Africa, 73(3): 237-242.
  • Minitab. 2014. Minitab release 17: Statistical software for windows. USA: Minitab Inc.
  • Missanjo EM, Imbayarwo-Chikosi VE, Halimani TE. 2010. Environmental factors affecting milk, fat and protein yields in Jersey cattle in Zimbabwe. Tropical Anim Health Prod, 43: 665-667.
  • Muchenje V, Mhlanga FN, Makuza SM, Banga C. 1997. Effects of some environmental factors on lactation milk yield. J Zimbabwe Soc Anim Prod, 8: 115-118.
  • Mugandani R, Wuta M, Makarau A, Chipindu B. 2012. Re-Classification of agro-ecological regions of Zimbabwe in conformity with climate variability and change. African Crop Sci J, 20(s2): 361-369.
  • Nyamushamba GB, Tavirimirwa B, Banana NYD. 2012. Non-genetic factors affecting milk yield and composition of Holstein-Friesian cows nested within natural ecological regions of Zimbabwe. Sci J Anim Sci, 2(5): 102-108.
  • Oliver J. 1987. Dairy farmers handbook. National Association of Dairy Farmers of Zimbabwe (NADF), Harare, Zimbabwe.
  • Rodriguez LA, Mokkonen G, Wilcox CJ, Martin T, Crooned WA. 1985. Effect of relative humidity, maximum and minimum temperature, pregnancy and stage of lactation on milk yield and composition in dairy cows. J Dairy Sci, 68: 973-978.
  • Valencia M, Montaldo HH, Ruíz, F. 2007. Interaction between genotype and geographic region for milk production in Mexican Holstein cattle. Arch Zootec, 57(220): 457-463.
  • Vincent V, Thomas R, Staples R. 1960. An agricultural survey of Southern Rhodesia. Part 1. Agro-ecological survey. Government Printer, Salisbury, Southern Rhodesia.
  • Wongpom B, Koonawootrittriron S, Elzo MA, Suwanasopee T. 2017. Milk yield, fat yield and fat percentage associations in Thai multi-breed dairy population. Argi Nat Res, 51: 218-222.
  • Zvinorova IP, Halimani TE, Mano RT, Ngongoni NT. 2013. Viability of smallholder dairying in Wedza Zimbabwe. Trop Anim Health Prod, 45: 1007-1015.
Year 2022, , 172 - 179, 01.07.2022
https://doi.org/10.47115/bsagriculture.1031623

Abstract

References

  • Chirinda N, Murungweni C, Waniwa A, Nyamangara J, Tangi A, Peters M, Notenbaert A, Burkart S. 2021. Perspectives on reducing the national milk deficit and accelerating the transition to a sustainable dairy value chain in Zimbabwe. Front Sust Food Sys, 5: 726482.
  • Collier R, Zimbelman R, Rhoads R, Rhoads M, Baumgard L. 2011. A re-evaluation of the impact of temperature humidity index (THI) and black globe humidity index (BGHI) on milk production in high producing dairy cows. Western Dairy Management Conf. Reno, NV, USA, pp: 113-125.
  • Fontaneli RS, Sollenberger LE, Littell RC, Staples CR. 2005. Performance of lactating dairy cows managed on pasture–based or in free stall barn–feeding systems. J Dairy Sci, 88: 1264-1276.
  • Gororo E. 2016. Dairy farm business models and cost of doing dairy in Zimbabwe. Zimbabwe Association of Dairy Farmers (ZADF), Harare, Zimbabwe, pp: 56.
  • Gwatibaya S. 2012. Production and physiological responses of lactating Holstein dairy cows to the provision of shade in sub-tropical Zimbabwe. MSc thesis, University of Zimbabwe, pp: 43.
  • Hagnestam-Nielsen C, Emanuelson U, Berglund B, Strandberg E. 2009. Relationship between somatic cell count and milk yield in different stages of lactation. J Dairy Sci, 92: 3124-3133.
  • Hammami H, Boulbaba R, Gengler N. 2009. Genotype by environment interaction in dairy cattle. Soc Environ, 13(1): 155-164.
  • Kunaka K, Makuza SM. 2005. Genetic and environmental trends for milk traits for Zimbabwean Holstein-Friesian population, Pakistan J Biol Sci, 8(7): 1011-1015.
  • Makuza SM, McDaniel BT. 1997. Genetic and phenotypic trends for Holstein herds in Zimbabwe. J Zimbabwe Soc Anim Prod, 8: 111-114.
  • Matekenya DT. 2016. Large scale dairy value chain in Zimbabwe. URL: http://www.drss.gov.zw/ (access date: September 17, 2021).
  • Mhlanga I, Ndaimani H, Mpakairi K, Mujere N. 2018. Climate change: An uncertain future for dairy farming in Zimbabwe. Transact Royal Soc South Africa, 73(3): 237-242.
  • Minitab. 2014. Minitab release 17: Statistical software for windows. USA: Minitab Inc.
  • Missanjo EM, Imbayarwo-Chikosi VE, Halimani TE. 2010. Environmental factors affecting milk, fat and protein yields in Jersey cattle in Zimbabwe. Tropical Anim Health Prod, 43: 665-667.
  • Muchenje V, Mhlanga FN, Makuza SM, Banga C. 1997. Effects of some environmental factors on lactation milk yield. J Zimbabwe Soc Anim Prod, 8: 115-118.
  • Mugandani R, Wuta M, Makarau A, Chipindu B. 2012. Re-Classification of agro-ecological regions of Zimbabwe in conformity with climate variability and change. African Crop Sci J, 20(s2): 361-369.
  • Nyamushamba GB, Tavirimirwa B, Banana NYD. 2012. Non-genetic factors affecting milk yield and composition of Holstein-Friesian cows nested within natural ecological regions of Zimbabwe. Sci J Anim Sci, 2(5): 102-108.
  • Oliver J. 1987. Dairy farmers handbook. National Association of Dairy Farmers of Zimbabwe (NADF), Harare, Zimbabwe.
  • Rodriguez LA, Mokkonen G, Wilcox CJ, Martin T, Crooned WA. 1985. Effect of relative humidity, maximum and minimum temperature, pregnancy and stage of lactation on milk yield and composition in dairy cows. J Dairy Sci, 68: 973-978.
  • Valencia M, Montaldo HH, Ruíz, F. 2007. Interaction between genotype and geographic region for milk production in Mexican Holstein cattle. Arch Zootec, 57(220): 457-463.
  • Vincent V, Thomas R, Staples R. 1960. An agricultural survey of Southern Rhodesia. Part 1. Agro-ecological survey. Government Printer, Salisbury, Southern Rhodesia.
  • Wongpom B, Koonawootrittriron S, Elzo MA, Suwanasopee T. 2017. Milk yield, fat yield and fat percentage associations in Thai multi-breed dairy population. Argi Nat Res, 51: 218-222.
  • Zvinorova IP, Halimani TE, Mano RT, Ngongoni NT. 2013. Viability of smallholder dairying in Wedza Zimbabwe. Trop Anim Health Prod, 45: 1007-1015.
There are 22 citations in total.

Details

Primary Language English
Subjects Zootechny (Other)
Journal Section Research Articles
Authors

Tafara Kundai Mavunga 0000-0002-9534-9154

Eddington Gororo This is me 0000-0003-2125-8919

Obert Tada This is me 0000-0003-4330-164X

Publication Date July 1, 2022
Submission Date December 3, 2021
Acceptance Date March 28, 2022
Published in Issue Year 2022

Cite

APA Mavunga, T. K., Gororo, E., & Tada, O. (2022). Effects of Environment on Productive Performance of Holstein-Friesian Dairy Cows in Three Agro-Ecological Regions of Zimbabwe. Black Sea Journal of Agriculture, 5(3), 172-179. https://doi.org/10.47115/bsagriculture.1031623

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