Livestock Research for Rural Development 22 (2) 2010 Guide for preparation of papers LRRD News

Citation of this paper

Contribution of small scale dairy farming under zero-grazing in improving household welfare in Kayanga ward, Karagwe District, Tanzania

J Lwelamira, H K Binamungu* and F B Njau

Institute of rural development planning, P.O.Box 138, Dodoma, Tanzania
* Karagwe District council, P.O.Box,22, Kagera, Tanzania


This study was carried in Kayanga ward, Karagwe district in Tanzania with the aim of evaluating contribution of small scale dairy farming in improving household welfare. The specific objectives of the study were; firstly to compare annual profits from various enterprises including dairy cattle farming by smallholder dairy cattle farmers; secondly, to determine the role of manure from dairy cattle farming in improving crop productivity; and thirdly, to determine the role played by small scale dairy cattle farming in improving household income, possession of durable assets and food security status. The data for this study were collected through a cross- section survey which involved both dairy farming and non- dairy farming households. In-depth interviews with key- informants (i.e extension agents) were also carried out to gather some qualitative information. Data were analyzed using Statistical Package for Social Sciences (SPSS 11).


Results from this study indicated that small scale dairy farming contributed substantially to household welfare. Average annual profit per household from small scale dairy farming by small scale dairy farmers was on the same range as those from crop production and small scale business ( i.e. approximately 1 million Tsh.), meaning that it is equally profitable as with other main enterprises by dairy farmers. As a result of using manure in farms from dairy cattle, average food crop yields among small scale dairy farming households were significantly higher (P< 0.01) than those of non- dairy farming household, and hence more food secure.  Average household income, value of durable assets, and food security status (i.e. frequency of consumption of some nutritious food) were significantly higher (P < 0.01) in dairy farming households than in non- dairy farming households indicating dairy farming households to be better-off than their counterpart.


Due to the observed good outcomes of small scale dairy farming, more promotion of this undertaking in the area has been recommended.

Keywords: Livestock; poverty reduction; smallholder farmers


High incidences of poverty and poor living standard has been characterized many Sub-Saharan Africa countries including Tanzania. Among other reasons, low agricultural productivity, and high population growths not matching with the available resources to support them are associated with high incidences of poverty in these countries (Kelly 1998; Irz  et al  2001; Mwankemwa 2004; Mason and Lee 2005). Smallholder farmers predominates agricultural sector in Tanzania and other Sub- Saharan Africa countries. Smallholder farming has been characterized by low productivity. This situation is partly attributed to lack of capital and uses poor farming technologies by smallholder farmers, drought, and lack of market for the produce (Mwankemwa 2004). Lack of capital by smallholder farmers is linked to inaccessibility to formal credit institutions due to lack of collaterals by majority of smallholder farmers. In addressing the problem of lack of capital by smallholder farmers, the government of Tanzania has been encouraging farmers to start Serving and Credit Cooperative Society (SACCOS), encouraging financial institutions offering micro-credits to farmers under less tough conditions (i.e group landing schemes), as well as encouraging the Heifer in-Trust (HIT) credit schemes for the case of dairy cattle farming (Kashuliza et al 1998; Mohamed 2003; Mwakalile et al 2002; Mwankemwa 2004; Kyomo et al 2006; Ssendi and Anderson 2009). In HIT credit schemes some farmers are trained on dairy cattle management and thereafter are provided with one to two crossbred dairy cows (crossbred incalf heifer) for management under stall-feeding regime. Upon calving of the cows a farmer is suppose to pass on an equivalent animal from the offsprings to another farmer as a repayment for the credit. These HIT credit schemes have helped many poor farmers in the country who don’t have capital to buy dairy cattle to possess them. This type of scheme in the study area has been there over 20 years initially run by a project under Evangelical Lutheran Church of Tanzania (ELCT) and thereafter by Kagera Livestock Development Project (KALIDEP), in which both of the projects were donor funded. Donor support to the scheme ended up in 2001 and the scheme was left to be run by a trust i.e. Kagera Dairy Development Trust (KADADET) and farmers organizations (Kyomo et al 2006).


In general, as with other agricultural development projects in Tanzania the main aim of the HIT schemes was to improve welfare of smallholder farmers and hence poverty reduction. As in many other parts in Tanzania, limited information is available on the performance of these schemes in improving household welfare of smallholder dairy farmers in the study area. Previous studies in the area and Kagera region as whole concentrated on evaluating   operational performance of the scheme as well as productive and reproductive performance of the animals. Similar apply to most other parts of Tanzania (Kyomo et al 2006; Asimwe and Kifaro 2007; Mwatawala and Kifaro 2007; Chenyambuga and Mseleko 2009). Based on this background, the main aim of this study was to evaluate the performance of the scheme in the study area in improving household welfare. Specific objectives of this study were threefold; 1) To compare annual profits from various enterprises including dairy cattle farming by smallholder dairy cattle farmers, 2) To determine the role of manure from dairy cattle farming in improving soil fertility and hence improved crop productivity, 3) To determine the role played by small scale dairy cattle farming in improving household income, possession durable assets and food security status. These information are important for policy makers and development agencies for making more informed decisions with regard to livestock and poverty reduction.



Study area


Karagwe district is one of the seven districts of Kagera region, Tanzania. The district is located on the North western corner of region. Annual rainfall in the district ranges from 800mmHg to 1000mmHg. Average annual temperature in the area is 26oC. Majority of households in the district rely on subsistence farming. Farmers in the area are engaged in both crop and livestock production. Major crops grown in the area include Banana, Beans, Maize and Coffee; and major livestock kept include local goat, chicken and cattle as well as dairy cattle. Dairy cattle in the District are mostly kept in Kayanga ward. Kayanga ward is located on north- eastern part of the district. About one-third of all small scale dairy farmers in the district are found in Kayanga ward and nearly a quarter of all rural households in the ward are involved dairy cattle farming. This was one of the major criteria for choosing Kayanga ward in the district as a study area.


Data collection


Data collection involved interviewing randomly selected dairy farming households involved in small scale dairy farming for at least three years as well as non-dairy farming households as control.  A total of 38 and 30 households were selected for dairy faming and non-dairy farming households, respectively. A face to face interview with household heads was carried out using a semi-structured questionnaire. With regard to households involved in dairy farming, a questionnaire was designed to capture information related to general characteristics of the household and the household head; farmland ownership and use pattern; production, inputs, costs and revenues/income from dairy farming and other non-diary farming activities; income from non-farm activities; expenditure of income from dairy farming; assets ownership; perceived benefits and constraints to dairy farming. On the other hand, a questionnaire for non-dairy faming households involved similar information with the exception to the information related to dairy farming. In-depth interviews with key-informants i.e. livestock extension officers were also carried out in order to have a further insight to issues pertaining to dairy cattle farming in the study area.


Data analysis


Data were analyzed for descriptive statistics (i.e. means, frequencies) using Statistical Package for Social Sciences (SPSS) computer program. The SPSS package was further used for performing Chi-square tests for ascertaining associations between categorical variables; t-test, One- Way Analysis of Variance (ANOVA I) and Duncan Multiple Range Test (DMRT) for comparing means.


Results and discussion 

Characteristics of the respondents


General characteristics of the interviewed respondents (i.e household heads) are indicated in Table 1. 

Table 1.  General information of the respondents


Dairy  farmers (n=38)

Non-dairy farmers (n=30)

All (n = 68)

















Age, years





< 35





35 -50










Marital status




















Education level





No formal education





Primary education





Secondary education





College and above





NS = Non significant at  (P>  0.05)

Results indicates distribution of household heads by sex, age, marital status and education level in the two types of households (i.e. Dairy farmers and Non-dairy farmers) were not significantly different (P> 0.05). Majority of respondents in both groups (i.e. more than 50%) were males, had age between 35 to 50 years, married and had primary education. These observations imply that there was no significant association between involvement in small scale dairy farming and these characteristics.


Means of livelihoods by the surveyed households


Results from Table 2 indicate that apart from small scale dairy farming, as with non- dairy farmers, all surveyed dairy farmers were also engaged in crop farming (i.e banana, beans, maize and coffee) with average land size for cropping per household being 2 acres. 

Table 2.  Sources of income by the surveyed households*


Dairy  farmers  (n = 38)

Non-Dairy farmers (n = 30)


38 (100.0%)


Crop farming

38 (100.0%)

30 (100%)

Small scale businesses (i.e. off-farm activities)

8 (21.0%)

10 (33.3%)

Other type of livestock

12 (31.6%)

14 (46.7%)

Data set was based on multiple response*

Small scale businesses were practiced by 20% and about one-third (33.3%) of the surveyed households for dairy farmers and non- dairy farmers, respectively. Substantial proportion of household in both groups (31.6% for dairy farmers and 46.7% for non- dairy farmers) were also involved in keeping other type of livestock  specifically local chickens and to a lesser extent local goat and cattle.  These results show a high degree of livelihood diversification by surveyed households in the study area. Livelihood diversification by most of rural households has also been reported elsewhere in Africa (Brown et al 2006; Degrande et al 2007; Roetter et al 2007) as a way of coping with uncertainties i.e crop production and market failures, a situation which is very common in these countries.


Information related to dairy farming


Dairy cattle farming in the area is practiced under zero grazing using mostly Friesian x Boran (F1) crosses.  Forages for dairy animals are usually established pastures (Napier grass) from own plots and farm edges; natural pastures from communal lands, river banks and road sides; and crop residues i.e banana tops. Animal are also supplemented with concentrates such as maize bran, cotton seed cakes and minerals block (mineral lick). These concentrates are usually bought from local suppliers in the area.  Majority of farmers (82%) owns between 2 to 3 dairy cattle of mixed age (Table 3).

Table 3.  Distribution of households by number of dairy animals owned (mixed age)

No. of dairy cattle

Frequency (n =38)











More than 3



Since most farmers avoid keeping male calves/bulls due to economical reasons and hence tend to cull or sell them, therefore, most of dairy animals by these farmers are females. Source of bull for breeding by majority of farmers (more than 90%) is through Artificial insemination (AI) usually done by livestock field officers in the area.


Annual profit from dairy farming relative to other enterprises


Annual profit i.e. Total Annual Revenue less Total Annual Variable Costs for various enterprises by the surveyed dairy farming households in the study area is presented in Table 4.

Table 4.  Annual profit for different enterprises by dairy farming households


No. of household in the enterprise

Annual profit  per household per annum, Tsh. (Means ± S.D)



1,000,150 ± 388,770a

Crop farming


1,032,432 ± 489,277a

Small scale businesses (i.e. off-farm activities)


950,000 ± 542,481a

Other type of livestock


131,833 ± 114,290b

a,bMeans with different superscript letters are significantly different (P<0.05)

S.D = Standard deviation

Results indicate that dairy farming, crop farming and small scale businesses had high profit compared to profit obtained from keeping other type of livestock. Results from the Table further shows that average profit per annum per household from each of the first three enterprises was around 1 million Tsh, and the differences between them were not significant (P< 0.05), indicating dairy farming contributes substantially to household income and it is as well equally important as with crop farming and small scale businesses as means of livelihood. This call for promotion of small scale dairy farming in the area to encourage more farmers to join it. Significant contribution of small scale dairy farming to household income has also been reported elsewhere (Muriuki et al 2001; Urassa and Raphael 2002), and hence its potential for poverty alleviation.


Food crop production by dairy farmers compared to non- dairy farmers


Decline in crop productivity as result declining soil fertility has been a major problem in Kagera region with Karagwe district not exceptional (Rugalema et al 1994; Baijukya 2004). Manure produced from cattle bans were found to be used by dairy farmers in crop farms and pasture plots for fertilizing the land for boosting production. Food crop production was compared between dairy farming and non-dairy farming households to determine whether the use of manures by dairy farmers has benefited them in improving productivity and hence food security. Results from Table 5 indicate that yield per acre for all major food crops in the area was significantly higher (P<0.01) for dairy farming households compared to non- dairy farming households.

Table 5.   Agricultural productivity for food crops in the season 2007/2008



Dairy farmers

(Mean ± S.D)

Non- dairy farmers

(Mean ± S.D)



Yield per acre

Banana, bunches

314 ± 80

200 ± 40




Beans, kg

231± 68

118 ± 32




Maize, kg

152 ± 70

63 ± 11



Land size per H/Hold, acres


2.30 ±  0.86

2.25  ± 0.87



H/Hold = Household ; S.D = Standard deviation

NS, ** , *** = Non-significant, significant at (P<0.01), and significant at (P<0.001), respectively

Increase in crop productivity as results of using manure from cattle bans was noted as one of the major motives for small scale farmers engaging in dairy farming (From a key informant, Kayanga ward).   These findings are in agreement with studies by Utiger et al (2000) in Kenya Highlands, and Bayer and Kapunda (2006) in Southern Highlands of Tanzania. These observations demonstrate the role played by dairy cattle farming in improving crop productivity and hence improved household foods security and welfare.


Household income, value of assets owned and food security status by Dairy and Non- dairy farmers


Household income, current value of durable assets and food security status of a household are among of the measures of household welfare (Mwankemwa 2004). To assess whether dairy cattle farmers were better-off than non- dairy farmers and hence positive impact of the scheme these two groups were compared on these variables. Results from Table 6 reveal that dairy farming households had significantly higher average annual income (P< 0.001) and were relatively more better off  in terms value of assets owned (P< 0.001) compared to their counterpart . This observation further indicates the role played by small scale dairy farming in improving household welfare.

Table 6.  Average annual household income, value of house (s) owned and other durable assets in Tsh.


Dairy  farmers

(Mean ± S.D)

Non- dairy farmers

(Mean ± S.D)



Household income per year

2,585,263 ± 648,210

1,398,333 ± 475,700



Value of house (s)

3,457,895 ± 1,996,704

1,338,333 ± 1,083,339



Value of other durable assets

1,368,812 ± 1,006,335

625,000 ± 291,359



S.D = Standard deviation ; *** = Significant at (P<0.001)

In their study in southern highlands of Tanzania Bayer and Kapunda (2006) observed that   Income from milk sales helped some smallholder families acquire additional land, improve their houses (and cattle sheds) ,finance small-scale businesses, send their children to secondary school, and expand the dairy business.


Animal protein intake (i.e. meat, eggs, milk) is a major problem in Developing countries including Tanzania and hence malnutrition in these countries is widespread (Mulangila et al 2002; Nielsen et al 2003). Low animal protein intake is partly been linked to its unavailability and being relatively expensive.  In human, animal protein are source of precursors of body compounds e.g. enzymes, blood protein, antibodies, hormones and several amino acids required for protein synthesis (Lehninger 1982). In this study it was hypothesized that by keeping dairy cattle a household will access milk easily and hence consumes milk more frequently than non- dairy farming households, and further that additional income from small scale dairy farming will increase the ability of a household to buy other animal based protein rich food i.e. Fish, Meat (which in most cases are expensive) for home consumption and hence improved nutrition. In the current study a trend on number of meals per day in a household were observed to be similar in both groups, in which more than 90% of households in both groups consumed almost two meals per day. However, frequency of intake of some nutritious food stuffs (animal protein) differed significantly between the two groups. (Table, 7).  

Table 7.  Distribution of households by frequency of eating valuable foods in a month

Food type


Frequency per month


< 5 times

5-10 times

> 10 times


Dairy farmers






Non-dairy farmers






Dairy farmers






Non-dairy farmers






Dairy farmers






Non-dairy farmers





NS, * , *** = Non-significant, significant at (P<0.05), and significant at (P<0.001), respectively

Dairy farming households tended to consume meat/fish and milk more frequently than non- dairy farming households and the differences were significant at (P< 0.05) and (P< 0.001), respectively.  Majority of dairy farming households (78%) consumes milk more than ten times a month compared to only 19% for non- dairy farming households.  A substantial proportion of  non- dairy farming households (54.8%) consumes milk less than five times a month (Table 7). While more than 80% of dairy farming households indicated to consume meat/fish for at least five times a month, only 56.7% do so for non- dairy farming households. Results further show that almost a quarter of dairy farming households consume meat/fish more than ten times a month as opposed to only 10% for non- dairy farming households. This observation indicates that apart from household income and values of durable assets, dairy farming households were also better-off nutritionally compared to non- dairy farmers and hence relatively more food secure. These findings underscore the potential role played by small scale dairy farming in reducing malnutrition. Both groups tended to consume egg less frequently in which majority of households in both groups consumed it less than 5 times a month. Taboos against egg consumption by some rural households in Kagera region (Lupiya 2007) could partly be responsible for the observed trend.


Challenges to small scale dairy farming in the area


In the present study small scale dairy farmers were also asked to rank problems they perceive to constrain them in small scale dairy farming in their area. Results from Table 8 reveal that unreliable milk market was the most important problem followed by high prices of drugs and concentrates. Unreliable milk market and high prices of concentrates were also revealed in a study by Urassa and Raphael (2002) in Morogoro urban district, Tanzania.

Table 8.  Constraints to small scale dairy farming in the area as perceived by small scale dairy farmers



Total frequency

Total weighted scorea





Unreliable milk market

18 (72)

13 (39)

2 (4)

0 (0)



High prices of drugs

11 (44)

9 (27)

7 (14)

1 (1)



High prices of concentrates

5 (20)

5 (15)

12 (24)

0 (0)



Limited extension services

1 (4)

5 (15)

1 (2)

2 (2)



Lack of AI services2

1 (4)

1 (3)

4 (8)

5 (5)



Lack of breeding bulls

2 (8)

1 (3)

3 (6)

2 (2)



Figures in brackets are frequencies and those out of brackets are weighted scores1.

1Weighted scores were obtained by multiplying frequencies by a weight of a respective rank with a 1st , 2nd, 3rd and 4th ranks given a weight of 4, 3, 2 and 1, respectively.

aTotal weighted score for each problem was obtained by summing up individual weighted scores from different ranks (indicated in brackets) in a problem.

2AI = Artificial insemination.

Finding external market for excess milk produced in the area could reduce the problem of milk market. However, this would require encouraging private individuals or farmers groups to establish small scale milk processing plants for increasing shelf life of milk in which farmers could sell their milk there. In turn, processed milk from these plants could be sold to external markets. High prices of drugs and concentrates in the area have mainly been attributed to few veterinary shops in the area. Again encouraging private individuals to initiate more veterinary shop could help reducing prices of these inputs.


Conclusion and recommendations 



Asimwe L and Kifaro, G C 2007 Effect of breed, season, year and parity on reproductive performance of dairy cattle under smallholder production system in Bukoba District, Tanzania. Livestock Research for Rural Development 19 (10). Site visited on 16/5/2008


Baijukya  F P 2004 Adapting to change in banana- based farming systems of northwest Tanzania. Msc. Dissertation, Wageningen University. 161pp.


Bayer W and Kapunda L B 2006 Dairy cattle for poverty alleviation in Southern  Tanzania. In: Proceeding of the conference on International Agricultural Research For Development. 11-13 October 2006, Bonn, Germany.  Site visited on 19/5/2008.


Brown D R, Stephens E C, Ouma J O Murithi  F M and Barrett C B 2006  Livelihood strategies in the rural Kenyan highlands. African Journal of Agriculture and Resource Economics 1 (1): 21-36.


Chenyambuga  S W and Mseleko K F 2009 Reproductive and lactation performances of Ayrshire and Boran crossbred cattle kept in smallholder farms in Mufindi district, Tanzania. Livestock Research for Rural Development, 21(7): Site visited on 30/11/2009.


Degrande A, Schreckenberg K, Mbosso C and Mfoumou C  2007 Farmer livelihoods in the Humid Forest and Moist Savannah zones of Cameroon. Working Paper no. 47 Yaoundé, ICRAF-WCA/HT. 61pp


Irz X, Lin L, Thirtle C and Wiggins S 2001 Agricultural productivity growth and poverty alleviation. Development policy review 19(4): 449-466.


Kashuliza A K, Hella J P, Magayane F T and Mvena Z S K 1998 The role of informal and semi-formal finance in poverty alleviation in Tanzania: Results of  field study in two regions. Research on Poverty Alleviation (REPOA)- Tanzania. Research Report No. 98.1.


Kelly A C 1998 The impacts of rapid population growth on poverty, food production, and the environment. Duke Economic working paper No. 98. Duke University .Site accessed on 13/5/2008.


Kyomo M L, Maiseli N G and Haule A 2006 Production of adequate dairy cows in Tanzania and examples of dairy breeding models in Tanga and Kagera milkshed areas, Tanzania. In: Proceedings of the 6th National Dairy Development Conference. 2nd June 2006, Morogoro, Tanzania, pp 52 -67


Lehninger  A L 1982 Principles of Biochemistry. Worth Publishers Inc. 1011pp.


Lupilya G S 2007 Assessment of social support projects for vulnerable groups towards poverty reduction: A case study of TASAF  in Bukoba district. M.A Dissertation, Sokoine University of Agriculture, Morogoro, Tanzania. 112pp.


Mason A and Lee S 2005 The demographic dividend and poverty reduction. In Proceedings of the United Nations Seminar on the Relevance of Population Aspects for the Achievement of the Millennium Development Goals. 17-19 November 2004, New York, USA


Mohamed K 2003  Access to formal and quasi-formal credit by smallholder farmers and artisanal fishermen: A case of Zanzibar. Research on Poverty Alleviation (REPOA)- Tanzania. Research Report No. 03.6


Mulangila R C T, Salum M R, Masangya G, Budeba S, Turingwa A P and Mleche C W H 2002 A study of intake profiles of vegetables and animal products: Their implication on prevalence of poverty and food insecurity in rural farmers of south-east Tanzania. In. Proceedings of the joint Scientific Conference of the 17th Scientific Conference of Tanzania Society of Animal Production and the 20th Scientific  Conference of Tanzania Veterinary Association, 3 – 5,  December 2002, Arusha, Tanzania, pp 231- 247


Muriuki  H G,  Mwangi D M and Thorpe W 2001 How smallholder dairy systems in Kenya contribute to food security and poverty alleviation: results of recent collaborative studies. In: Proceedings of the 28th scientific conference of Tanzania Society of Animal Production. 7 - 9 August  2001, Morogoro, Tanzania.


Mwakalile  I F N, Bachmann F, Mshana Y and Mgittu V F 2002 Improved livestock  management and rural livelihood: Twenty years of experience of southern highlands dairy development project in Mbeya and Iringa region, Tanzania. In: Proceedings of the joint Scientific Conference of the 17th Scientific Conference of Tanzania Society of Animal Production and the 20th Scientific  Conference of Tanzania Veterinary Association, 3 – 5,  December 2002, Arusha, Tanzania, pp 35-51


Mwankemwa A S A 2004 Performance of saving and credit co-operative societies and their impact on rural livelihoods: A case study of Morogoro rural and Mvomero districts, Tanzania. Msc. Dissertation, Sokoine University of Agriculture, Morogoro, Tanzania. 132pp.


Mwatawaha  H and Kifaro G C 2007 First lactation performance and crossbreeding effects of Friesian x Boran Crosses in Tanzania. Bulletin of Animal Health and Production in Africa  55 (2): pp 127 – 137


Nielsen H, Roos N and Thilsted S H 2003 The impact of semi-scavenging poultry production on the consumption of animal source food by women and girls in Bangladesh. Journal of Nutrition 133: 4027-4030


Roetter R P, Van Keulen H, Kuiper M, Verlag J and Van Laar H H 2007 Rural livelihood: Interplay between farm activities, non- farm activities and the resource base. In: Science for Agriculture and Rural Development in Low- Income Countries. Springer, The Netherlands, Pp 77 -95


Rugalema G H, Johnsen F H, Okting’ati A and Minjas A 1994 The homegarden agroforestry system of Bukoba district, North- Western Tanzania. An economical appraisal of possible solutions to falling productivity. Agroforestry Systems 28 (3): 227- 236


Ssendi L and Anderson A R 2009 Tanzanian micro enterprises and micro finance. Journal of Entrepreneurship 18 (1): 1-19


Urassa J K and Raphael E 2002 The contribution of small scale dairy farming to community welfare: a case study of Morogoro Municipality.  Site visited on 12/5/2008


Utiger C, Romney D, Njoroge L, Staal S, Lukuyu B and Chege  L 2000 Nutrient flows and balances in intensive crop-dairy production systems in the Kenya highlands. In Proceedings of the 3rd All Africa Conference on Animal Agriculture and 11thConference of the Egyptian Society of Animal Production. 6-9 November 2000, Alexandria, Egypt.

Received 2 December 2009; Accepted 5 January 2010; Published 7 February 2010

Go to top