Production characteristics and gender roles in dairy farming in peri-urban areas of Eastern and Central Africa

D M G Njarui, J M Kabirizi*, J K Itabari, M Gatheru, A Nakiganda* and S Mugerwa*

Kenya Agricultural Research Institute - Katumani Research Centre, PO Box 340 – 90100, Machakos, Kenya
donaldnjarui@yahoo.com
* National Livestock Resources Research Institute, PO Box 96, Tororo, Uganda

Abstract

In the recent past, dairy farming has increasingly become an important source of livelihoods for urban and peri-urban dwellers in Eastern and Central Africa. A study was carried out on dairy cattle farming in peri-urban areas of Machakos and Wote towns in the semi-arid region of Kenya and in Masaka, a peri-urban area in the sub-humid region of central Uganda. The objective was to understand the functioning of the existing dairy production systems and division of labour among gender in the enterprise.

In peri-urban areas of Machakos and Masaka towns, 60 households at each site and 56 households in Wote were interviewed using structured questionnaires between February and July 2010. The study revealed that households in peri-urban areas of semi-arid Kenya had a relatively larger dairy herd size (5.3±3.7animals) than in peri-urban sub-humid Uganda (2.23±1.53 animals). Holstein-Friesian was the dominant breed (60% of breed) kept in Kenya while in Uganda crosses of local and exotic European breeds were dominant (80%).The semi-intensive system was the main production system in peri-urban semi-arid Kenya (54.8%) while in peri-urban Uganda, stall-feeding was the most preferred system (60%). Milk production per cow was generally low in both regions. In Kenya, it ranged from 3.4 litres/cow/day during the dry season to 9 litres/cow/day during the wet season. In Uganda, the average milk production was 3.5 litres/cow/day during the dry season and increased to 7.7 litres/cow/day during the wet season. Low rainfall was the major constraint in fodder and pasture establishment and was reported by over 70% of farmers in Kenya while in Uganda, high cost of seed (reported by 33% of farmers) was the most important constraint.

The labour contribution among gender for different activities in dairy production was variable. In peri-urban areas of Kenya, men contributed highest labour in spraying animals against ticks and planting fodder (20-29% of total labour requirement) while women contributed more labour in milking (32-34%) than in any other activity. On contrast, women contributed over 50% of total labour in all activities required for running the dairy unit in Uganda. Children contributed less than 10% of labour requirements in most of the activities in both countries.

Key words: Dairy cattle, production systems, semi-arid, smallholders’ farmers, sub-humid

Introduction

There are differences in development of dairy sub-sector between countries within the Eastern and Central Africa (ECA) region, with Kenya having a longer history in dairy farming than the other countries. Exotic dairy cattle were first introduced in Kenya from Europe by white settlers in 1920s, who established dairy farms in Central highlands and Rift Valley region. Although few farmers in the semi-arid region of eastern Kenya commenced dairy farming in 1960s, it was not until in 1980s and onwards when there was accelerated adoption of dairy farming (Njarui et al 2009). On the other hand, dairy farming is relatively young in Uganda with the first introduction of dairy cattle from Germany in 1980s. In the recent past, there has been a steady growth of dairy farming in the region and it has increasingly become an important source of livelihoods. For example, Kenya produced 3.8 billion litres of milk in 2007 (MoLD [Ministry of Livestock Development] 2008) and rose to 5 billion litres in 2011 of which some was consumed at household level and also sold to generate income. Thus the industry plays an important role in food security, employment creation, income generation, and enhancement of the livelihoods of dairy farmers, traders, processors and all participants engaged in the entire milk supply chain (Muia et al 2011). Studies by Njarui et al (2011a) showed that milk and milk products are an important dietary component for all social strata. In coastal lowlands of Kenya, Nicholson et al (2004) found that for each cow owned, mean household income increased by 53% compared with households without dairy cows.

The expanding dairy industry in the ECA region is fuelled by increased urbanization and improved income, resulting in high demand for milk and milk products. Consequently, many dairy farms have been established in peri-urban areas of major commercial urban centres with increased adoption of improved dairy cattle of European breed (Bos taurus); Holstein-Friesian, Aryshire, Guernsey, Jersey and their crosses with local zebu (Bos inducus). The production is mainly dominated by smallholders who own few dairy cattle. As smallholder farmers make major shift towards market-oriented dairy production, they are faced with several challenges.

Limited feed resource is a major constraint that hinders the growth of dairy farming in Uganda (Kabirizi 2006) and Kenya (Njarui et al 2011b). Inadequate quantity and quality of feeds has also been reported in Malawi (Banda et al 2011) and Ethiopia (Hassen et al 2010). In the semi-arid areas of Kenya, the amount of rainfall is low and drought occurrence is frequent, leading to poor growth of pastures, which result in inadequate quantity and quality of feeds. In the sub-humid region of Uganda, although the rainfall is much higher, frequent occurrence of drought has been reported in recent times (Kabirizi 2006). The situation is exacerbated by shrinking land holdings due to increased population and cultivation of food crops. Coupled with this, is limited labour available required to perform major activities in dairy units, such as planting forage, feeding, milking, cleaning the sheds and spraying against ticks. As dairy farming is labour intensive, family members across all gender are engaged in these activities for success of the dairy farming. Thus it is important to understand the socio-economic factors that influence management practices of the dairy unit in order to develop appropriate interventions. Furthermore, information on the functioning and status of the dairy farming in the peri-urban areas within the ECA region is not well understood. The objective of the study was, therefore, to understand the existing characteristics and gender involvement in dairy farming within selected areas in the ECA region.

Methodology

Description of the study areas

The study was carried out in the peri-urban areas of Machakos and Wote towns within Machakos and Makueni counties, respectively, of Kenya and in Masaka urban centre in Masaka district, Uganda. Machakos town (37^o27’E; 1^o52’S) is located at 1700 m above sea level and Wote town (37^o37’E; 1 ^o47’S) at an altitude of 1100 m. Masaka district lies between longitudes 31^o and 32’E and latitudes 1^o15’ and 0^o43’S at 1115 m above sea level. The rainfall in the study sites is bimodal. In Kenya, the long rains (LR) occurs from March to May and the short rains (SR) from October to December while in Uganda, the LR occurs between October and December and the SR from April to May. However, there are significant differences in terms of agricultural potential attributed to differences in amount of rainfall and geographical locations Machakos and Wote represent semi-arid type of climate with low (500 - 800 mm) and unreliable annual rainfall while Masaka represents sub-humid climate with annual rainfall of between 1000 - 1200 mm. In the semi-arid, annual evaporation exceeds the amount of rainfall and ranges from 1600-2300 mm (KARI 2001). Machakos is generally cooler than the other sites with average temperature ranging from 14-25^oC. In Wote and Masaka the average temperature ranges from 20 to 30^oC. The sites were purposively selected for the study since there are established dairy cattle farms.

Sampling and data collection

The survey covered 15 km radius around the urban centres. The target population for the study was defined as consisting of smallholder farmers having at least one grade dairy cow. Proportional stratified sampling method was employed and was based on geographical location of households within the urban centres. For this purpose each site was divided into four clusters relative to the town; north, south, east and west. From each direction, a list of farmers with at least a grade cow was compiled. A total of 60, 56 and 60 households in Machakos, Wote and Masaka, respectively, were selected using simple random sampling technique and interviewed. Information collected included household characteristics, type of feed resources, milk production, division of labour among gender and sources of information on dairy management. Farmers were asked to give information and their experiences using recall system. Structured questionnaires were used to gather the data. During the survey, the household head or the most senior member available was interviewed. Data collection technique included direct questioning, informal discussion and observations. The survey was conducted between February and July 2010

Data analysis and presentation

Data was coded and entered in a spreadsheet and analysed using the Statistical Procedures for Social Sciences (SPSS) version 12 for Windows (SPSS 2002). The results are presented using descriptive statistics, tables and graphical illustrations.

Results and Discussion

Social economic characteristics of households

It is important to understand the socio-economic characteristics of farming households as these influence farming decisions, choice and adoption of agricultural technologies (Omiti et al 1999). Across the household stratification, the majority of households were headed by males (Table 1). However, the proportion of the female-headed households was higher in Uganda (15%) than in Kenya, primarily because, an Non-Governmental Organization (NGO), “Send a Cow”, which was operating in the region prior to the survey had donated dairy cows to widows who had lost their husbands from HIV/AIDS, hence a relatively high proportion of women household heads who owned a dairy cattle. Surprisingly, despite high prevalence of HIV/AIDS in Uganda, households had larger families (6.3±3 persons) than in Kenya (4.5±2 persons). Typically, household members comprised of husband, wife and children. The size of household members could influence labour availability in dairy farming with Uganda having more labour available to perform dairy activities.

Literacy level was high in the region with majority of households’ heads having attained secondary education and above. This implies that adoption of any introduced dairy technology is likely to be high since level of education has been shown to be positively correlated to adoption of improved technology. Educated farmers are more able to interpret, make informed decisions and apply technical advice from research allowing them to accurately assess the relative benefits and risks from using alternative technologies (Omiti et al 1999). The universal free primary education in both countries has encouraged many households to acquire education at primary level.

There were similarities in the level of experience in livestock farming. Farmers in Machakos and Masaka regions had almost equal number of years in livestock farming. As Table 1 shows, in Wote peri-urban farmers had marginally more years (13±11 years) in livestock farming than the others sites. Many years in dairy farming implies that farmers are experienced to manage their dairy cattle better for improved productivity. There was also variation in occupation of household heads between the two regions. Highest percentages of household heads in Masaka were full time farmers (89.5%) compared with two sites in Kenya where a good proportion of household’s heads were engaged in both farming and business. Farming in semi-arid Kenya is more risky than in sub-humid Uganda due to low and unreliable rainfall, thus people seek other alternative means for their livelihoods. 

Dairy herd size and structure

Dairy cattle are important for supplying milk to meet demand from the increased high population in urban centres within the ECA region. Households in peri-urban areas of semi-arid Kenya had a relatively larger dairy herd size (average 5.3±3.7 animals) than in peri-urban areas of sub-humid Uganda (2.23±1.53 animals) (Table 2). Cows constituted the highest proportion (45%) of the herd in Kenya followed by heifers (21%). The herd size in peri-urban areas of semi-arid Kenya was similar to that found in Nyandarua, Central Kenya.  Muia et al (2011) found that on average farmers kept 5.3 heads of cattle with 40% being cows. In Uganda, heifers and bulls comprised the largest proportion of the herd. The bulls were mainly kept for breeding purposes as artificial insemination services are not well developed.

Dairy production systems

Three distinct dairy management systems were identified in the peri-urban regions of Kenya and Uganda (Figure 1). However, there was variation in the proportion of farmers practicing each system. The semi-intensive was the preferred system (54.8%) in peri-urban areas of semi-arid Kenya and this agrees with the findings of Njarui et al (2009) in a rural area within the same agro-ecological zone. Stall-feeding, commonly known as zero grazing was preferred (60%) in Uganda. The difference is attributed to size of land. On average, land sizes were larger in peri-urban areas of semi-arid Kenya than in Masaka, Uganda, thus animals had relatively more pasture to move around and graze. The average land holding was 2.66±18 ha in Machakos, 9.83±7.81 ha in Wote and 1.2±0.08 ha in Masaka. Farmers mostly prefer stall-feeding as the land sizes become small (Mburu et al 2007). However, in stall-feeding, a high number of animals can be kept in a relatively small area and this allows easier control of diseases. In Kenya, Holstein-Friesian was the most widely kept breed (60%), while in Uganda, crosses between the exotic European breeds and local zebu were dominant (80%).

Feed resources

Feed availability is key to productivity of dairy animals. Feed resources can be grouped into four main categories, namely, natural grasslands, established pastures, crop residues, and agricultural by-products. In Kenya, between 23-40% (0.2±0.17 to 0.8 ±0.7 ha) of total land per household was devoted to feed production with only about 8% planted with improved forages and the rest under natural pastures or fallow. Napier and Rhodes grass were the major cultivated forages with the former being more widely grown. Crop residues, particularly maize stovers were the major feed during the dry seasons. The stovers are usually high in roughage, but low in nutritive value (Njarui et al 2011b). Around Masaka town, planted forages, mainly Napier grass, was the most important feed resource and accounted for 62% of the total feed for livestock. The area allocated to Napier grass was generally small with majority cultivating about 0.1 ha. Although legumes such as lablab, desmodium, calliandra and leucaena have been promoted widely, less than 10% of farmers interviewed cultivated them.

Farmers faced several challenges in feed production. High cost of seed was the most widely experienced problem and was reported by about 42% of farmers in Uganda. In Kenya, low rainfall was the biggest constraint (Table 3). In Uganda, seed production was largely mainly informal and there was no regulatory mechanism to ensure production of good quality seed. As a result there was limited seed in the market, which was normally expensive for the low income smallholder farmers. In the semi-arid, the annual rainfall is low (500-800 mm) and erratic with coefficient of variation of between 45 and 58% (KARI-NDFRC 1995). Thus it is quite clear that there is need to intervene to increase seed availability for farmers in Uganda and develop interventions to increase water availability for forage production in Kenya. 

Milk production and marketing

Milk production per cow was variable between seasons and was generally low. Farmers reported that milk production was high during the wet seasons and declined by over 50% during the dry seasons, largely due to inadequate and low quality feeds and water. It ranged from 3.4 litres/cow/day during the dry season and increased to 9 litres/cow/day during wet seasons, in peri-urban areas of Kenya. In Masaka, Uganda, average milk production was 3.5 litres/cow/day during the dry season and increased to 7.7 litres/cow/day during the wet season. Muia et al (2011) reported average milk yield of 8.4 litres/cow/day in Central highlands of Kenya. Households consumed from 1 to 3 litres per day and the extra milk that was not consumed by households was normally sold to individuals including neighbours who did not have a dairy cow. Middlemen and catering services were also important customers. In peri-urban areas of Wote town, some of the farmers delivered their milk to the dairy co-operative society. The price for milk ranged from US $ 0.37 per litre in the wet season to US $ 0.75 per litre in the dry season in Kenya. Milk was relatively cheaper in Uganda and ranged from US $ 0.14 to US $ 0.28 per litre in wet and dry season, respectively. Where milk was sold to catering services and milk bars, it was mainly transported by bicycles and on foot. Most of the milk was sold raw since there was limited processing. However, during the milk glut period, the extra milk was fermented to extend the shelf life and either consumed by household or sold to neighbours.

There were challenges facing raw milk marketing in the region. Slightly over 50% of the farmers reported that low price of milk was the major constraint in both countries. A similar constraint was also reported by Njarui et al (2009) in other part of semi-arid region of eastern Kenya. Nevertheless, the price offered was normally higher than that offered in traditionally dairy region of central highlands and Rift Valley region of Kenya for the same quantity and quality of milk. Unstable price was the second major constraint and this was brought about by variation in milk output which was dependent on weather. Generally during the wet season, there is improved feed availability leading to increased milk output per household and low prices while in the dry season milk output was low resulting in increased prices. The other problems were competition, delayed payments and long distance to market.

Gender roles in dairy cattle farming

The activities performed in the dairy enterprise are shown in Table 4. Most of these are performed daily, implying that dairy farming is a labour intensive enterprise. There was no distinct age and sex division of labour, but all gender contributed in all activities. However, there were disparity in level of labour contribution between men, women and children for dairy production activities. In peri-urban Machakos, on average, men contributed more labour (17%) in the dairy unit than women (12%), but in peri-urban Wote, women contributed marginally more labour than men. Women contributed highest labour in milking (32-34%) than in any other activity while men contributed highest in spraying against ticks and planting of forages (20 - 29%). In general, women tended to contribute highest labour to tasks that are performed daily while for men it was mainly in tasks performed weekly or seasonally. For example, planting of forage is carried out during the wet season while spraying is on weekly basis while milking is carried out daily. In Uganda, labour contribution to the dairy unit was skewed towards women who contributed over 50% of labour requirement in all dairy production activities. The contribution of children to running of dairy unit was low and was less than 10% of total labour for most of the activities. Notably, in Uganda, children did not participate in cutting forages, feeding and watering the animals. The low contribution of children was primarily because they attended school during week days and they were only available during week-ends. It is important to note that husbands are largely the decision maker on how the dairy unit should be managed.

Nonetheless, the family labour was not sufficient to run the dairy unit and significant labour was sourced from outside particularly in Kenya. As Table 4 shows, in Kenya, overall hired labour contributed about two thirds of total labour required in running of the dairy enterprises. This implies that external labour is important for the success of dairy farming in the peri-urban areas of semi-arid. This scenario was also reported by Njarui et al (2009) who found out that hired employees contributed about 50% of the entire labour requirement of the dairy unit in the rural areas of semi-arid Kenya. In Uganda, hired labour made lower contribution (average 24%) in running the dairy compared with Kenya. 

Agencies and channels of information dissemination

Information is important as it make farmers aware of new agricultural technologies. In Kenya, the three major sources of information were farmer-to-farmer, government extension service and electronic media (Table 5). In Uganda, the main sources of information were NGOs and electronic media. Research institutions and universities were lowly rated as agents of agricultural information as both are involved mainly in research and training, respectively. 

Conclusions

• There were differences in dairy management in the peri-urban areas of semi-arid Kenya and sub-humid region of Uganda. The semi-intensive system was the preferred production system in semi-arid Kenya while stall-feeding was preferred in Uganda.
  
  
• Milk production was generally low particularly during the dry season primarily due to inadequate feed.
  
  
• The gender division of labour and participation varied between regions. Women contributed greatly more labour in all dairy production activities in Uganda while in Kenya men contributed higher labour in planting of forages and spraying while women contributed more labour in milking.

Acknowledgements

The authors are grateful to household members who participated in the study and assistance of extension offices from both countries. Our gratitude is extended to the Directors, Kenya Agricultural Research Institute (KARI) and National Livestock Resources Research Institute (NaLIRRI) for the support. We thank the staffs of KARI and NaLIRRI for administering the questionnaires. This study was funded by the Association for Strengthening Agriculture in Eastern and Central Africa (ASARECA). The views expressed in this report are not necessarily those of ASARECA. 

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Received 10 May 2012; Accepted 5 June 2012; Published 1 July 2012

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