Hostname: page-component-cd9895bd7-mkpzs Total loading time: 0 Render date: 2024-12-18T15:37:59.678Z Has data issue: false hasContentIssue false

Lifetime productivity of dairy cows in smallholder farming systems of the Central highlands of Kenya

Published online by Cambridge University Press:  01 July 2009

M. C. Rufino*
Affiliation:
Plant Production Systems, Department of Plant Sciences, Wageningen University, PO Box 430, 6700 AK Wageningen, The Netherlands
M. Herrero
Affiliation:
International Livestock Research Institute, PO Box 30709, Nairobi, Kenya
M. T. Van Wijk
Affiliation:
Plant Production Systems, Department of Plant Sciences, Wageningen University, PO Box 430, 6700 AK Wageningen, The Netherlands
L. Hemerik
Affiliation:
Biometris, Wageningen University, PO Box 100, 6700 AC Wageningen, The Netherlands
N. De Ridder
Affiliation:
Plant Production Systems, Department of Plant Sciences, Wageningen University, PO Box 430, 6700 AK Wageningen, The Netherlands
K. E. Giller
Affiliation:
Plant Production Systems, Department of Plant Sciences, Wageningen University, PO Box 430, 6700 AK Wageningen, The Netherlands
Get access

Abstract

Evaluation of lifetime productivity is sensible to target interventions for improving productivity of smallholder dairy systems in the highlands of East Africa, because cows are normally not disposed of based on productive reasons. Feeding strategies and involuntary culling may have long-term effects on productive (and therefore economic) performance of dairy systems. Because of the temporal scale needed to evaluate lifetime productivity, experimentation with feedstuffs in single lactations is not enough to assess improvements in productivity. A dynamic modelling approach was used to explore the effect of feeding strategies on the lifetime productivity of dairy cattle. We used LIVSIM (LIVestock SIMulator), an individual-based, dynamic model in which performance depends on genetic potential of the breed and feeding. We tested the model for the highlands of Central Kenya, and simulated individual animals throughout their lifetime using scenarios with different diets based on common feedstuffs used in these systems (Napier grass, maize stover and dairy concentrates), with and without imposing random mortality on different age classes. The simulations showed that it is possible to maximise lifetime productivity by supplementing concentrates to meet the nutrient requirements of cattle during lactation, and during early development to reduce age at first calving and extend productive life. Avoiding undernutrition during the dry period by supplementing the diet with 0.5 kg of concentrates per day helped to increase productivity and productive life, but in practice farmers may not perceive the immediate economic benefits because the results of this practice are manifested through a cumulative, long-term effect. Survival analyses indicated that unsupplemented diets prolong calving intervals and therefore, reduce lifetime productivity. The simulations with imposed random mortality showed a reduction of 43% to 65% in all productivity indicators. Milk production may be increased on average by 1400 kg per lactation by supplementing the diet with 5 kg of concentrates during early lactation and 1 kg during late lactation, although the optimal supplementation may change according to milk and concentrate prices. Reducing involuntary culling must be included as a key goal when designing interventions to improve productivity and sustainability of smallholder dairy systems, because increasing lifetime productivity may have a larger impact on smallholders’ income than interventions targeted to only improving daily milk yields through feeding strategies.

Type
Full Paper
Copyright
Copyright © The Animal Consortium 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abate, A, Abate, AN 1991. Wet season nutrient supply to lactating grade animals managed under different production systems. East African Agriculture and Forestry Journal 57, 3339.CrossRefGoogle Scholar
Abate, A, Dzowela, BH, Kategile, JA 1993. Intensive animal feeding practices for optimum feed utilisation. In Proceedings of a workshop on Future of livestock industries in East and Southern Africa (ed. JA Kategile and S Mubi), p. 227. ILCA, Addis Ababa, Ethiopia.Google Scholar
Adeyene, JA, Adebanjo, AK 1978. Lactational characteristics of imported British Friesian cows raised in Western Nigeria. Journal of Agricultural Science 91, 645651.CrossRefGoogle Scholar
Agricultural and Food Research Council (AFRC) 1993. Energy and protein requirements of ruminants. An advisory manual prepared by the AFRC Technical Committee on response to nutrients. CAB International, Wallingford, UK.Google Scholar
Agyemang, K, Nkhonjera, LP 1990. Productivity of crossbred cattle on smallholder farms in Southern Malawi. Tropical Animal Health and Production 22, 916.CrossRefGoogle ScholarPubMed
Bagley, CP 1993. Nutritional management of replacement beef heifers: a review. Journal of Animal Science 71, 31553163.CrossRefGoogle ScholarPubMed
Bebe, BO 2008. Dairy heifer rearing under increasing intensification of smallholder dairy systems in the Kenya highlands. Livestock Research for Rural Development 20Article # 22.Google Scholar
Bebe, BO, Udo, HMJ, Rowlands, GJ, Thorpe, W 2003a. Smallholder dairy systems in the Kenya highlands: breed preferences and breeding practices. Livestock Production Science 82, 117127.CrossRefGoogle Scholar
Bebe, BO, Udo, HMJ, Rowlands, GJ, Thorpe, W 2003b. Smallholder dairy systems in the Kenya highlands: cattle population dynamics under increasing intensification. Livestock Production Science 82, 211221.CrossRefGoogle Scholar
Bebe, BO, Udo, HMJ, Thorpe, W 2008. Characteristics of feeding and breeding practices for intensification of smallholder dairy systems in the Kenya highlands. Livestock Research for Rural Development 20Article # 23.Google Scholar
Conrad, HR 1966. Symposium on factors influencing voluntary intake of herbage by ruminants: physiological and physical factors limiting feed Intake. Journal of Animal Science 25, 227243.CrossRefGoogle ScholarPubMed
De Jong, R 1996. Dairy stock development and milk production with smallholders. PhD, Wageningen University.Google Scholar
Dijkhuizen, AA, Stelwagen, J, Renkema, JA 1986. A stochastic-model for the simulation of management decisions in dairy herds, with special reference to production, reproduction, culling and income. Preventive Veterinary Medicine 4, 273289.CrossRefGoogle Scholar
Gitau, GK, McDermott, JJ, Waltnertoews, D, Lissemore, KD, Osumo, JM, Muriuki, D 1994. Factors influencing calf morbidity and mortality in smallholder dairy farms in Kiambu district of Kenya. Preventive Veterinary Medicine 21, 167177.CrossRefGoogle Scholar
Haccou, P, Hemerik, L 1985. The Influence of larval dispersal in the cinnabar moth (Tyria jacobaeae) on predation by the red wood ant (Formica polyctena): an analysis based on the proportional hazards model. Journal of Animal Ecology 54, 755769.CrossRefGoogle Scholar
Jenet, A, Fernandez-Rivera, S, Tegegne, A, Yimegnuhal, A, Osuji, PO, Kreuzer, M 2004a. Growth and feed conversion of Boran (Bos indicus) and Holstein × Boran heifers during three physiological states receiving different levels of a tropical diet. Livestock Production Science 89, 159173.CrossRefGoogle Scholar
Jenet, A, Yimegnuhal, A, Fernandez-Rivera, S, Tegegne, A, Osuji, PO, McCrabb, G, Kreuzer, M 2004b. Long-term response to feeding level in lactational performance of Boran (Bos indicus) and Boran × Holstein cows. Animal Science 78, 331343.CrossRefGoogle Scholar
Kabuga, JD, Agyemang, K 1984. Performance of Canadian Holstein-Friesian cattle in the humid forest zone of Ghana. II. Preweaning performance. Tropical Animal Health and Production 16, 174180.CrossRefGoogle ScholarPubMed
Kahi, AK, Thorpe, W, Nitter, G, Van Arendonk, JAM, Gall, CF 2000. Economic evaluation of crossbreeding for dairy production in a pasture based production system in Kenya. Livestock Production Science 65, 167184.CrossRefGoogle Scholar
Kaitho, RJ, Biwott, J, Tanner, JC, Gachuiri, CK, Wahome, RG 2001. Effect of allocation of fixed amounts of concentrates on milk yields and fertility of dairy cows. Retrieved June 20, 2006, from http://wwwfaoorg/DOCREP/ARTICLE/AGRIPPA/X9500E09HTM (Agrippa FAO Peer reviewed journal).Google Scholar
Kebreab, E, Smith, T, Tanner, JC, Osuji, PO 2005. Review of undernutrition in smallholder ruminant production systems in the tropics. In Coping with feed scarcity in smallholder livestock systems in developing countries (ed. AA Ayantunde, S Fernandez-Rivera and G McCrabb), pp. 3–94. Animal Sciences Group, Wageningen UR, Wageningen, The Netherlands; University of Reading, Reading, UK; ETH (Swiss Federal Institute of Technology), Zurich, Switzerland; and ILRI (International Livestock Research Institute), Nairobi, Kenya.Google Scholar
King, JM, Parsons, DJ, Turnpenny, JR, Nyangaga, J, Bakari, P, Wathes, CM 2006. Modelling energy metabolism of Friesians in Kenya smallholdings shows how heat stress and energy deficit constrain milk yield and cow replacement rate. Animal Science 82, 705716.CrossRefGoogle Scholar
Kleinbaum, DG, Klein, M 2005. Survival analysis: a self-learning text. Springer Science, Business Media, Inc., New York, USA.CrossRefGoogle Scholar
Knudsen, PB, Sohael, AS 1970. Vom Herd: a study of performance of a mixed Friesian/Zebu herd in a tropical environment. Tropical Agriculture 47, 189203.Google Scholar
Konandreas, PA, Anderson, FM 1982. Cattle herd dynamics: an integer and stochastic model for evaluating production alternatives ILCA Research report 2, ILCA Publications, Addis Ababa, Ethiopia.Google Scholar
Lanyasunya, TR, de Jong, R, Nyakira, BS, Mukisira, EA 2000. Impact of appropriate technologies on calf and heifer performance on-farm in Bahati Division, Nakuru District. In Testing of livestock technologies on smallholder mixed farms in Kenya (eds. R de Jong and EA Mukisira), p. 210. Signal press Ltd, Kenya Agricultural Research Institute and Royal Tropical Institute, Nairobi, Kenya and Amsterdam, The Netherlands.Google Scholar
Masama, E, Kusina, NT, Sibanda, S, Majoni, C 2003. Reproduction and lactational performance of cattle in a smallholder dairy system in Zimbabwe. Tropical Animal Health and Production 35, 117129.CrossRefGoogle Scholar
Methu, JN, Owen, E, Abate, AL, Tanner, JC 2001. Botanical and nutritional composition of maize stover, intakes and feed selection by dairy cattle. Livestock Production Science 71, 8796.CrossRefGoogle Scholar
Ministry of Agriculture Fisheries and Food (MAFF) 1987. Energy allowances and feeding systems for ruminants. ADAS Reference Book 433, 2nd edition. Her Majesty’s Stationery Office, London, UK.Google Scholar
Muia, JMK 2000. Use of Napier grass to improve smallholder milk production in Kenya. Phd, Wageningen University.Google Scholar
Mukasa-Mugerwa, E 1989. A review of reproductive performance of female Bos indicus (Zebu) cattle. ILCA, Addis Ababa, Ethiopia.Google Scholar
Ngategize, PK 1989. Economic evaluation of improved management for Zebu cattle in Northern Tanzania. Agricultural Systems 31, 305314.CrossRefGoogle Scholar
Ojango, JMK, Ducrocq, V, Pollott, GE 2005. Survival analysis of factors affecting culling early in the productive life of Holstein-Friesian cattle in Kenya. Livestock Production Science 92, 317322.CrossRefGoogle Scholar
Ongadi, PM, Wakhungu, JW, Wahome, RG, Okitoi, LO 2007. Characterization of grade dairy cattle owning households in mixed small scale farming systems of Vihiga, Kenya. Livestock Research for Rural Development 19Article #43.Google Scholar
Osuji, PO, Saarisalo, EM, Tegegne, A, Umunna, NN 2005. Undernutrition of dairy cattle in smallholder production systems in East Africa. In Coping with feed scarcity in smallholder livestock systems in developing countries (ed. AA Ayantunde, S Fernandez-Rivera and G McCrabb), pp. 97–120. Animal Sciences Group, Wageningen UR, Wageningen, The Netherlands; University of Reading, Reading, UK; ETH (Swiss Federal Institute of Technology), Zurich, Switzerland; and ILRI (International Livestock Research Institute), Nairobi, Kenya.Google Scholar
Perry, BD, Randolph, TF, McDermott, JJ, Sones, KR, Thornton, PK 2002. Investing in animal health research to alleviate poverty. International Livestock Research Institute (ILRI), Nairobi, Kenya Available at http://www.ilri.org/Infoserv/webpub/Fulldocs/InvestAnim/index.htmGoogle Scholar
Powell, JM, Williams, TO 1993. Livestock, nutrient cycling and sustainable agriculture in the West African Sahel. International Institute for Environment and Development, London, UK.Google Scholar
Romney, DL, Thorne, P, Lukuyu, B, Thornton, PK 2003. Maize as food and feed in intensive smallholder systems: management options for improved integration in mixed farming systems of east and southern Africa. Field Crops Research 84, 159168.CrossRefGoogle Scholar
Romney, D, Utiger, C, Kaitho, R, Thorne, P, Wokabi, A, Njoroge, L, Chege, L, Kirui, J, Kamotho, D, Staal, S 2004. Effect of intensification on feed management of dairy cows in the Central Highlands of Kenya. In Responding to the livestock revolution: the role of globalization and implications for poverty alleviation (ed. E Owen, T Smith, MA Steele, S Anderson, AJ Duncan, M Herrero, JD Leaver, CK Reynolds, JI Richards and JC Ku-Vera), pp. 167178. British Society of Animal Science Publication 33, Nottingham University Press, Nottingham, UK.Google Scholar
Rufino, MC, Herrero, M, Van Wijk, MT, Dury, J, De Ridder, N, Giller, KE 2008. NUANCES – LIVSIM: The Livestock Simulator, version 08.08. Plant Production Systems Group, Wageningen University, Wageningen, The Netherlands Available at http://www.africanuances.nlGoogle Scholar
Staal, S, Owango, M, Muriuki, H, Kenyanjui, M, Lukuyu, B, Njoroge, L, Njubi, D, Baltenweck, I, Musembi, F, Bwana, O, Muriuki, K, Gichungu, G, Omore, A, Thorpe, W 2001. Dairy systems characterisation of the greater Nairobi milk shed. MoARD, KARI, ILRI, DFID, Nairobi, Kenya, p. 73.Google Scholar
Tolkamp, BJ, Ketelaars, JJMH 1994. Efficiency of energy utilisation in cattle given food ad libitum: predictions according to the ARC system and practical consequences. Animal Production 59, 4347.Google Scholar
Trail, JCM, Marples, HJS 1968. Friesian cattle in Uganda. Tropical Agriculture 45, 173178.Google Scholar
Van Arendonk, JAM 1985. A model to estimate the performance, revenues and costs of dairy cows under different production and price situations. Agricultural Systems 16, 157189.CrossRefGoogle Scholar
Van de Ven, GWJ, De Ridder, N, Van Keulen, H, Van Ittersum, MK 2003. Concepts in production ecology for analysis and design of animal and plant–animal production systems. Agricultural Systems 76, 507525.CrossRefGoogle Scholar
Van Schaik, G, Perry, BD, Mukhebi, AW, Gitau, GK, Dijkhuizen, AA 1996. An economic study of smallholder dairy farms in Murang’a district, Kenya. Preventive Veterinary Medicine 29, 2136.CrossRefGoogle Scholar
Vargas, B, Herrero, M, Van Arendonk, JAM 2001. Interactions between optimal replacement policies and feeding strategies in dairy herds. Livestock Production Science 69, 1731.CrossRefGoogle Scholar