Skip to main content
SpringerLink
Log in

Seasonal variations in the availability of fodder resources and practices of dairy cattle feeding among the smallholder farmers in Western Usambara Highlands, Tanzania

  • Regular Articles
  • Published:
Tropical Animal Health and Production Aims and scope Submit manuscript

Abstract

The aim of this study was to assess the seasonal effects on quantity and quality of fodder resources and associated utilization practices among smallholder dairy farmers in Western Usambara Highlands (WUHs) in Tanzania. The WUHs are among the major milk producing areas under smallholder dairy farming systems (SDFS) in Tanzania. Dry season fodder scarcity is a widespread problem affecting the East African SDFS and has been shown to contribute to over 40% reduction in milk yield. There is limited information with regard to seasonal fodder fluctuation and its effects on productivity of dairy cows in different landscape levels of Tanzania. Field and household surveys were conducted in 150 dairy cattle farming households from five villages in three wards located in WUHs. Survey data were analyzed using IBM SPSS version 21. In addition, remote sensing techniques were employed on gap-filled and smoothed Landsat data to generate land cover maps and bimonthly normalized difference vegetation index—time series for the 2009–2016. SDFS landscape was highly heterogeneous typified by crops, bushes, and forests. On average, the household landholding was 1.3 ha, while herd size was three cattle. About 87% of household land was devoted to crop growing with limited pasture along the farm margins and contour strips. Fodder scarcity was the major challenge during the dry season (July to October) as indicated by 87% of the respondents. On-farm fodder resources contributed most of the cattle diet (73%) while rangeland, forest, and purchased feed provided small amount. Natural pasture and napier grass (Pennisetum purpureum) were the most important feeds in wet season while maize stover was most significant during the dry season. Maize stover was profusely stored for dry season feeding and neither silage nor hay making was practiced. The nutritional values of the fibrous feeds declined during the dry season, whereby the metabolizable energy and crude protein contents were 6.0 MJ/kg and 10.1% dry matter, respectively, during wet season compared to 4.8 MJ/kg and 7.8% dry matter, respectively, during the dry season. Consequently, milk yield drops from 5.6 l per cow per day in the wet season to 3.0 l in the dry season. It is concluded that dry season fodder scarcity is a major problem in the WUHs and it hinders sustainable dairy production. It is therefore suggested that increase in fodder production as well as adoption of fodder conservation and feeding technologies are inevitable if sustainable dairy production is to be met in the Western Usambara Highlands and elsewhere with similar environments.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Angelsen, A., Larsen, H.O., C.S. Olsen., 2012. Measuring livelihoods and environmental dependence: Methods for research and fieldwork. Routledge. pp 55–59.

  • AOAC., 1990. Official Methods of Analysis. 15th ed. Association of Official Analytical Chemists, Washington, DC.

    Google Scholar 

  • Atzberger, C., Eilers, P.H.C., 2010. A smoothed 1km resolution NDVI time series (1998–2008) for vegetation studies in South America. International Journal of Digital Earth, 4(5), 365–386.

    Article  Google Scholar 

  • Breiman, L., 2001. Random forests. Machine learning, 45(1), 5–32.

    Article  Google Scholar 

  • Cadilhon, J. J., Pham, N. D., & Maass, B. L., 2016. The Tanga Dairy Platform: fostering innovations for more efficient dairy chain coordination in Tanzania. International Journal on Food System Dynamics, 7(2), 81–91.

    Google Scholar 

  • Crowder L.V. and Chheda H.R. (1982). Tropical Grassland Husbandry. Longman, London, U.K. Longman group Ltd.

    Google Scholar 

  • FAO., 2010. Status of and prospects for smallholder milk production: A Global Perspective. Edited by Hemme, T. and Otte, J., Food and Agriculture Organization of the United Nations, Rome, Italy (pp. 28–29).

  • Heemskerk, S. J., 2016. Bio-economic evaluation of forage cultivation scenarios in crop-dairy systems in Lushoto District, Tanzania. Farming Systems Ecology Thesis (MSc Thesis, Wageningen University).

  • Herrero, M., Thornton, P. K., Notenbaert, A. M., Wood, S., Msangi, S., Freeman, H. A., … & Lynam, J., 2010. Smart investments in sustainable food production: revisiting mixed crop-livestock systems. Science, 327(5967), 822–825.

    Article  CAS  Google Scholar 

  • IBM Corp., 2013. IBM SPSS Statistics for Windows, Version 21.0. IBM 633 Corp., Armonk, New York.

  • Immitzer, M., Atzberger, C., Koukal, T., 2012. Tree Species Classification with Random Forest Using Very High Spatial Resolution 8-Band WorldView-2 Satellite Data. Remote Sensing, 4, 2661–2693. doi:https://doi.org/10.3390/rs4092661

    Article  Google Scholar 

  • Kawamura, K., Akiyama, T., Yokota, H.O., Tsutsumi, M., Yasuda, T., Watanabe, O., Wang, S., 2005. Quantifying grazing intensities using geographic information systems and satellite remote sensing in the Xilingol steppe region, Inner Mongolia, China. Agriculture, Ecosystems and Environment, 107, 83–93.

    Article  Google Scholar 

  • Kohavi, R., 1995. A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection. International Joint Conference on Artificial Intelligence 14, 1137–1143. doi:https://doi.org/10.1067/mod.2000.109031

    Article  Google Scholar 

  • Liaw, A., Wiener, M., 2002. Classification and Regression by random Forest. R news 2, 18–22. doi:https://doi.org/10.1177/154405910408300516

    Article  Google Scholar 

  • Lukuyu, B.A., Ravichandran, T., Maass, B., Laswai, G., Bwire, J. and Duncan, A.J., 2015. Enhancing livestock productivity through feed and feeding interventions in India and Tanzania. ILRI Project Report. Nairobi, Kenya: ILRI.

  • Lukuyu, M., Njehu, A., Mwilawa, A., Lukuyu, B.A., Omore, A.O. and Rao, J., 2016. A study to understand fodder markets and fodder trading patterns in MoreMilkiT sites and other selected regions in Tanzania.. ILRI Project Report. Nairobi, Kenya: ILRI.

  • MAFF., 1975. Energy allowances and feeding systems for ruminants. Ministry Of Agriculture, Fisheries and Food, Department Of Agriculture and Fisheries for Scotland and Department of Agriculture for Northern Ireland. 1975. Technical Bulletin 33: Her Majesty’s Stationery Office, London.

  • Meroni, M., Ng, W.-T., Rembold, F., Leonardi, U., Atzberger, C., Gadain, H., Shaiye, M., 2016. Mapping Prosopis juliflora in west Somaliland with Landsat 8 satellite imagery and ground information. Land Degradation & Development, 28(2), 494–506.

    Article  Google Scholar 

  • Mussa, H.M., 1998. Smallholder dairy production feed budgeting strategy in the Southern Highlands of Tanzania. A case study of Rungwe and Mbozi districts. M.Sc. Dissertation. Sokoine University of Agriculture.

  • Mwango, S. B., Msanya, B. M., Mtakwa, P. W., Kimaro, D. N., Deckers, J., Poesen, J., … & Bethuel, I., 2014. Root properties of plants used for soil erosion control in the Usambara Mountains, Tanzania. International Journal of Plant & Soil Science 3(12),1567–1580.

    Article  Google Scholar 

  • National Research Council., 2001 Nutrient Requirements of Dairy Cattle. National Academy Press, Washington: DC, USA.

  • Ng, W.-T., Immitzer, M., Floriansitz, M., Vuolo, F., Luminari, L., Adede, C., Wahome, R., Atzberger, C., 2016a. Mapping Prosopis spp. within the Tarach water basin, Turkana, Kenya using Sentinel-2 imagery 9998, 99980L. doi:https://doi.org/10.1117/12.2241279

  • Ng, W.-T., Meroni, M., Immitzer, M., Böck, S., Leonardi, U., Rembold, F., Gadain, H., Atzberger, C., 2016b. Mapping Prosopis spp. with Landsat 8 data in arid environments: evaluating effectiveness of different methods and temporal imagery selection for Hargeisa, Somaliland. International Journal of Applied Earth Observation and Geoinformation, 53(2016), 76–89.

    Article  Google Scholar 

  • R Core Team, 2015. R: A Language and Environment for Statistical Computing. R Found. Stat. Comput. Vienna. doi:https://doi.org/10.1038/sj.hdy.6800737

    Book  Google Scholar 

  • Rouse, J.W., Haas, R.H., Schell, J.A., Deering, D.W., 1974. Monitoring vegetation systems in the Great Plains with ERTS. Third ERTS-1 Symp. 309–317.

  • Rubel, F., and M. Kottek, 2010. Observed and projected climate shifts 1901-2100 depicted by world maps of the Köppen-Geiger climate classification. Meteorologische Zeitschrift, 19(2), 135–141.

    Article  Google Scholar 

  • Tilley J.M.A. and Terry R.A., 1963. A two stage technique for the in vitro digestion of forage crops. Journal of British Grasslands Society 18, 104–111.

    Article  CAS  Google Scholar 

  • Van Soest P.J., Robertson, J.B. and Lewis, B.A., 1991. Methods for Dietary Fibre and Non-Starch Polysaccharides in Relation to Animal Nutrition. Dairy Science, (74) 3583–3597.

    Article  Google Scholar 

  • Vuolo, F., Ng, W., Atzberger, C., 2017. Smoothing and gap-filling of high resolution multi-spectral time series: Example of Landsat data. International Journal of Applied Earth Observation and Geoinformation, 57, 202–213.

    Article  Google Scholar 

  • Waithaka, M.M., Thornton, P.K., Herrero, M., Shepherd, K.D., 2006. Bio-economic evaluation of farmers’ perceptions of viable farms in western Kenya. Agricultural Systems. 90, 243–271.

    Article  Google Scholar 

  • Wulder, M.A., White, J.C., Loveland, T.R., Woodcock, C.E., Belward, A.S., Cohen, W.B., Fosnight, E.A.,Shaw, J., Masek, J.G., Roy, D.P., 2016. The global Landsat archive: Status, consolidation, and direction. Remote Sensing of Environment, 185, 271–283.

    Article  Google Scholar 

Download references

Acknowledgments

We thank the management and staff of the livestock division at Lushoto and Bumbuli District Councils for logistics and assistance during data collection. We heartfelt acknowledge the willingness of the farmers to be involved in the study, responding to our questions and for allowing us to visit their farms.

Funding

This study received funding from the Regional Universities Forum for Capacity Building in Agriculture (RUFORUM) through the competitive grant number RU 2015 CARP 06.

Author information

Authors and Affiliations

  1. Department of Sustainable Agriculture, Biodiversity and Ecosystems Management, The Nelson Mandela African Institution of Science and Technology, PO Box 447, Arusha, Tanzania

    David Maleko

  2. Institute for Surveying, Remote Sensing and Land Information, University of Natural Resources and Life Sciences, Vienna (BOKU), Peter Jordan Str. 82, A-1190, Vienna, Austria

    Wai-Tim Ng

  3. Department of Animal, Aquaculture and Range Sciences, Sokoine University of Agriculture, PO Box 3004, Morogoro, Tanzania

    David Maleko & George Msalya

  4. Tanzania Livestock Research Institute, Mabuki Research Centre, PO Box 352, Mabuki, Mwanza, Tanzania

    Angello Mwilawa

  5. Department of Business Administration and Management, Nelson Mandela African Institution of Science and Technology, PO Box 447, Arusha, Tanzania

    Liliane Pasape

  6. Department of Water Resources, Environmental Science and Engineering, Nelson Mandela African Institution of Science and Technology, PO Box 447, Arusha, Tanzania

    Kelvin Mtei

Authors
  1. David Maleko
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wai-Tim Ng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. George Msalya
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Angello Mwilawa
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Liliane Pasape
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Kelvin Mtei
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to David Maleko.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Maleko, D., Ng, WT., Msalya, G. et al. Seasonal variations in the availability of fodder resources and practices of dairy cattle feeding among the smallholder farmers in Western Usambara Highlands, Tanzania. Trop Anim Health Prod 50, 1653–1664 (2018). https://doi.org/10.1007/s11250-018-1609-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11250-018-1609-4

Keywords

Search

Navigation