East Africa Dairy Development in Tanzania—Cost of milk production

Baltazary, C., Kinuthia, E., Baltenweck, I. and Omondi, I. (ILRI)

6th Tanzania Dairy Development Forum Meeting, Njombe, Tanzania, 29 May 2016

Presentation Outline

1. EADD Overview

2. Introduction

3. Methodology

4. Variables for computation of cost of milk production

5. Findings/results

6. Conclusion and recommendations

Milk Production in Tz

SOUTHERN HIGHLANDS SOUTHERN HIGHLANDS MILK SHEDMILK SHED

• Total cattle = 1.35 mil (6%)– Dairy herd = 86,982 (12%)– Local herd = 1.26 mil (6%)

• Opportunity for breed improvement

• Annual milk production = 538 mil L/year (27%)

• Households keeping livestock = 295,547 (13%)– Critical mass

EADD Project Area

Introduction cont’d

• Since the inception EADD II , there is inadequate information regarding costs of milk production and profitability of smallholder dairy enterprise in the project sites

Survey Objectivesi. Assessing the cost of milk production and

profitability of dairy enterprise in the study areasii.Identifying cost components EADD II should

target in order to enhance profitability of the dairy farms in EADD II project sites

Methodology

• From the project’s baseline sample, a random sample of 20 households per hub was drawn with additional of 10 households as replacement to cater for non-response

• A total of 217 households keeping cattle (irrespective of the breed and scale of production) were surveyed in three Clusters

Clusters POs/Hubs

Mbeya Kyimo (Faraja), Vwawa (Mviwambo), Ilembo (ISAIMA) and Isange (Busokelo)

Njombe Igima (Mshikamano), Kichiwa (WAWAHANJO) and Uwemba (Lukamo)

Iringa Igowole (MUDCO), Ifunda (Iringa) and Mtitu (Dabaga)

Variables for computation of Cost of Production

  Revenues included in calculations

Costs included in calculations

Scenario 1

1. Milk sales2. Milk consumed by

households3. Milk given to calves

and laborers4. Sale of animals5. Manure sales

Variable costsFixed costsMilk given to calves and laborersMilk spoilage (defined as the volume of milk rejected by the buyer)

Scenario 2

1. Milk sales2. Milk consumed by

households3. Milk given to calves

and laborers

Variable costsFixed costsMilk given to calves and laborersMilk spoilage

Analytical Procedure

Cattle production systems and Breeds

Cluster Prod system

Dom Breed

Av milk prod (L/d/HH)

Mbeya Intensive Improved (88%)

9.2*

Njombe Extensive Zebu (58%) 2.3*Iringa Extensive Zebu (65%) 2.3*

* The average milk production volumes are figures from the annual survey conducted between Nov – Dec 2015

Results/findings

Profit per liter (Tsh/L) from milk, cattle and manure revenues combined across Clusters

Cluster

Av Pr/LTsh

TR/L(MaR+CR+MR)

TVC/L TFC/L Total Prod cost/L

Profit/L

Mbeya 598 702 146 18 164 538Njombe 657 747 390 52 442 305

Iringa 996 822 634 72 706 116Overall (SH)

750 757 390 47 437 320

MR=Milk Revenue, CR= Cattle sales revenue, MaR=Manure sales revenue and SH = Southern Highlands

Profit per litre from milk revenue only (Tsh)

Cluster Milk Rev/L Total Cost/L

Profit/L

Mbeya 571 164 407Njombe 654 442 212Iringa 772 706 66Overall (SH) 666 437 229

• There is a significant drop in average profit per litre across all clusters when revenue was calculated from milk sales only.

• This shows the contribution of other dairy components (manure and sales of live animals) on the profitability of dairy enterprise

Comparison of revenue, costs and profits by systems of production

• Farmers in intensive system generated significantly higher milk profit than those in extensive system (P>0.1)

• Farmers practicing extensive system were incurring significantly higher cost per litre on milk given out, milk consumed, variable costs, total costs and fixed costs (P>0.01) than the farmers practicing intensive system of production.

• Contrary to expectations the cost of hired labor, animal health and extension costs per litre were higher in extensive system than in intensive system.  

    

Distribution of Variable Costs by Clusters

Break Even Volumes (BEV)

• Mbeya cluster had the highest (4.8 litres) break even volume of milk production per household per day as a result of low average milk price per litre

• Similarly farmers under the intensive system have to produce higher (4.5 litres) volume per day compared to their counterparts who practice extensive system (2.6 litres) to  cover for the low average price per litre that farmers in intensive system receive.

Conclusion

• Generally farmers in SH generate on average a profit of 320 Tsh per litre

• Hired labour, purchased feeds and animal health were the major cost drivers of milk production in both the extensive and intensive systems.

• In addition, milk spoilage contributed to revenue loss across the three clusters.

• Farmers in intensive system have to produce more milk for them to generate revenue enough to cover their production costs.

Recommendations

• In order to increase production efficiency, EADD II will continue facilitating farmers in the adoption of good animal husbandry practices to reduce the major cost drivers.

• To realize bigger impact, EADD II is calling upon development partners to invest on improvement of dairy farming through facilitating market access, access to improved breeds and linkages of POs with service providers (financial institutions)