Poster by Isabelle Baltenweck, Emmanuel Kinuthia, Bernard Lukuyu, Dominic Menjo, Susan Atyang and Elisée Kamanzi presented at the 13th Biennial Scientific Conference of the Kenya Agricultural Research Institute (KARI), Nairobi, Kenya, 22-26 October 2012.

1. Cost of milk production in East Africa
Isabelle Baltenweck, Emmanuel Kinuthia, Bernard Lukuyu, Dominic Menjo, Susan Atyang and Elisée Kamanzi
International Livestock Research Institute (ILRI), Nairobi, Kenya
Presented at the 13th KARI Biennial Scientific Conference, 22-26 October 2012, Nairobi, Kenya
Introduction Results
In East Africa, millions of smallholder farmers live below the poverty Table 1: Comparison of costs and profits by production system Table 2: Comparison of costs and profits by scale of operation
line despite the potential to earn well-above subsistence income of USD Item Kenya Rwanda Uganda Item Kenya Rwanda Uganda
2 a day. In this region, keeping dairy cattle and selling milk is common, Extensive Semi Sign Intensive Extensive Sign Intensive Extensive Sign Small Medium Sign Small Medium Sign Small Medium Sign
though not always profitable. Many development partners, including extensive scale scale scale
the East Africa Dairy Development (EADD) project, are intervening in Milk revenue 0.27 0.28 ns 0.31 0.3 ns 0.25 0.24 *** Milk revenue 0.29 0.27 ** 0.3 0.3 ns 0.21 0.17 **
Cattle revenue 0.12 0.04 * 0.05 0.08 ns 0.08 0.33 ** Cattle revenue 0.12 0.04 * 0.03 0.18 ** 0.17 0.35 *
the dairy sector to support producers to enhance the profitability of
Total revenue 0.4 0.32 ns 0.35 0.38 ns 0.33 0.57 * Total revenue 0.4 0.31 ** 0.33 0.48 * 0.38 0.52 ns
smallholder dairy production. However, there is inadequate information
Total cost 0.16 0.12 ns 0.31 0.13 *** 0.21 0.73 ** Total cost 0.13 0.16 ns 0.24 0.19 ns 0.19 0.52 **
regarding profitability of the dairy enterprise.
Milk profit only 0.12 0.17 ns -0.01 0.17 *** 0.04 -0.21 *** Milk profit only 0.15 0.11 ns 0.06 0.11 ns 0.03 -0.35 ***
Total profit 0.24 0.21 ns 0.04 0.25 *** 0.12 0.13 ns Total profit 0.22 0.15 ** 0.09 0.3 ** 0.2 -0.002 *
***, ** and * significant at 1%, 5% and 10%, respectively; costs in USD ***, ** and * significant at 1%, 5% and 10%, respectively; costs in USD
Objectives
 To compute the cost of producing one litre of milk in Kenya, Rwanda  Farmers in extensive systems in Kenya realised higher revenue from cattle sales  In Kenya, small-scale farmers earned higher revenue from milk and cattle sales
and Uganda and compare the costs according to scale of operation than those in semi-extensive production systems. than medium-scale farmers and thus higher profits.
and production system  Intensive systems in Rwanda incurred higher production costs and made lower  In Rwanda, medium-scale farmers earned higher revenue from cattle sales than
profits than extensive production systems. small-scale farmers and thus higher total profit.
 To identify the cost components that should be targeted to enhance
 Intensive systems in Uganda earned higher revenue from milk sales while  In Uganda, small-scale farmers earned higher revenue from milk sales while
profitability extensive systems earned higher revenues from cattle sales and overall revenue. medium-scale farmers earned higher revenue from cattle sales.
 Extensive systems in Uganda incurred higher production costs than intensive  Total production cost was high among medium-scale farmers in Uganda resulting
systems (mostly due to cattle deaths) and made lower profits from milk sales. in lower profits. This was mainly driven by high incidences of cattle deaths.
Methods
 Data were collected from a random sample of 148 farmers drawn
from the EADD project sites.
 In Rwanda and Uganda, three hubs in each country were selected
from intensive and extensive systems.
 In Kenya, three hubs each were selected from extensive and semi- Cost distribution by scale of operation in Kenya Cost distribution by scale of operation in Rwanda Cost distribution by scale of operation in Uganda
extensive systems.
 An estimate of total milk production in the last three months
preceding the survey was obtained by regression analysis
 Partial budget analysis was used to compute revenue, costs and
profits and the comparison made using t-test
 Two approaches were considered
• Revenues from milk only
• Revenues from milk and cattle sales Cost distribution by production system in Uganda
Cost distribution by production system in Kenya Cost distribution by production system in Rwanda
 Selected small-scale farmers owned at most three cows in intensive
systems while those in the extensive systems owned 8 to 15 cows.  Important costs among smallholders and medium-scale farmers  Significant costs among small- and medium-scale farmers  Significant costs among small-scale were include feeds, mortalities and calf
in Kenya were feeds, cattle deaths and calf milk include feeds, transport and hired labour although animal milk while among medium scale was mortalities
 Important costs among extensive and semi-extensive farmers health was also high among medium-scale farmers  Calf milk, purchased feeds, hired labour, mortalities and animal health were
were cattle deaths, feeds and calf milk  Purchased feeds, hired labour and transport were significant significant among farmers practicing intensive system
among farmers practising intensive system  Mortalities and purchased feeds were the highest cost components among
Conclusions  Purchased feeds, hired labour, and animal health were highest
cost components among in the extensive system
farmers practising extensive system
 Uganda had the highest cost of milk per litre followed by Rwanda
then Kenya.
 The most significant costs of production in Uganda were cattle
deaths, hired labour, calf milk and purchased feeds. In Rwanda, these
were purchased feeds, hired labour, animal health and transport,
while in Kenya these were cattle deaths, purchased feeds and calf
milk.
 In all countries, interventions should focus on reducing feed costs. In
Kenya and Uganda, focus should be on reducing cattle deaths and
cost of feeding calves. In Rwanda, focus should be on reducing
transport costs.