Livestock Research for Rural Development 26 (3) 2014 Guide for preparation of papers LRRD Newsletter

Citation of this paper

Selecting indigenous cattle populations for improving dairy production in the Southern Highlands and Eastern Tanzania

P L Mwambene, A Chawala*, E Illatsia**, S M Das***, B Tungu* and R Loina****

Tanzania Livestock Research Institute (TALIRI) - Uyole, P.O. Box 6191, Mbeya Tanzania
piusmwambene@yahoo.co.uk
* Tanzania Livestock Research Institute (TALIRI) - Mpwapwa, P.O. Box 292, Mpwapwa Tanzania
** Kenya Agricultural Research Institute (KARI), P.O. Box 3840 Nakuru Kenya
*** Tanzania Veterinary Laboratory Agency (TVLA), P.O. Box 9254, Dar es Salaam Tanzania
**** Tanzania Livestock Research Institute (TALIRI) - Tanga, P.O. Box 5160 Tanga Tanzania

Abstract

A study to describe key dairy traits of selected indigenous cattle populations was conducted in the Southern Highlands and Eastern of Tanzania. Four districts, namely Njombe and Mufindi in the Southern Highlands, and Bagamoyo and Muheza in the Eastern zone were selected for data collection. A questionnaire was used to extract information from 122 farmers with respect to household characteristics of the respective farming communities and dairy attributes of their local cattle, as well as their production environments, production systems, production potentials, milk marketing and production challenges. Physical measurements on body weight, body length, heart girth and height at withers were also taken on 483 mature (> 4 years) animals, while their main body colours and colour patterns were appraised from 965 animals found in all the Southern Highlands’ selected cattle herds.

Most of the farmers were keeping indigenous cattle mainly for drought purpose, milk production and for socio-economic and cultural purposes. The majority of the farmers kept indigenous cattle, mainly the Tanzania Shorthorn Zebu (TSZ) and a few of them had some crosses of exotic and TSZ. All the farmers used natural bulls for breeding purposes. Mating practice was random among the majority of the farmsteads owing to grazing and watering on communal rangelands. Selection of breeding bulls was rarely rationally done. The average age at first calving was 50 ± 1.3 months, while the mean lactation length and calving interval were 148 ± 2.8 days and 16 ± 0.6 months, respectively. Mean daily milk yield at peak was about 3±0.15 litres. Kraals made of untreated thorny bushes were the predominant shelters used for cattle by all of the respondents. The majority of respondents mentioned diseases/parasites, shortages of breeding bulls of high vigour and feeds during the dry season as the main production challenges.  Both location and sex influenced all the body measurements, with bulls superseding cows. Most measurements were positively and highly correlated, with the body weight being predicted more accurately from the heart girth. The animals from Njombe and Mufindi districts had also variable body colour patterns, but being predominantly red, black, pied red and white, pied black and white and spotted red and white. Most animals had medium-sized teats and udders. Thus the cattle populations in the study can be classified as medium-sized strains with considerable variation in body size, morphological features and dairy production potential within and between districts. Variation in indigenous cattle in dairy traits can be capitalized for improvement of dairy production through selective breeding.

Key words: body measurements, breeding, dairy traits, disease


Introduction

There are about 23 million cattle in Tanzania (MLFD 2013) of which about 97% are indigenous. The indigenous cattle populations are diverse with unique genetic attributes such as adaptation to heat and drought, tolerance to diseases and utilization of low-quality forages (Mwambene et al 2012). However, despite this immense diversity, the country is a net importer of cattle products, especially milk and dairy products as the majority of the indigenous cattle are the local types considered to be of low genetic potential in terms of milk production. The indigenous cattle populations are generally a principal source of household income, meat, milk and many socio-cultural functions among pastoralists and agro-pastoralists (Anderson 2003). The current commercial production trends, which tend to focus on a few breeds is unsuitable for the future of the traditional sector as it limits farmers’ options to select and develop breeds adapted to existing diversity in production environments. The tendency to concentrate on a few high-yielding environmentally-less adapted breeds that are unsustainable often has led to collapse of livestock production levels (Kurwijila and Kifaro 2001; Tisdell 2003) since exposure of exotics and their crossbreds to less favourable production environments, risks of production increase and economic losses may occur (FAO 2006).

However, there is an ever growing demand for livestock products in the country and a need for increased productivity. So far, about 90% of the traditional cattle in Tanzania are still non-descript and unimproved (Mwambene et al 2012). Inexistence of herd recording, lack of efficient breed improvement programmes and non availability of proven superior quality breeding animals are among the factors that contribute to the slow progress in improving the genetic merit of local cattle populations (Rege 1992). In the recent years, some crossbreeding programmes to upgrade the local cattle populations to 75% or more of exotic genotypes had been implemented in some parts of the country. However, the resultant short term increase in productivity from these exotic breeds and their crossbreds have often resulted in genetic erosion of adaptability traits that allow the very existence of these cattle in these harsh environments. This is largely due to lack of proper organization, non-recognition of farmers indigenous knowledge and participatory establishment and management of breeding schemes.

It is well acknowledged that the big differences between indigenous stocks with respect to production traits may to a large extent be of genetic and environmental origin. This is based on the ability of animals to respond optimally to prevailing environmental stimuli thereby maximizing on the expression of production and reproduction potential under the circumstances. This phenomenon, known as genotype x environment interaction, has been amply demonstrated in farm animals (Sorensen 1978). Thus, while in good environment, production would be influenced primarily by additive genetic potential for production traits, the adaptive quality of the animals would play a precedent role in stressful environments as emphasized in several studies (Cunningham 1981) and has special significance in developing countries where livestock improvement efforts through use of improved temperate germplasm have often been frustrated by inadequate economic capacity to sustain suitable conditions for animals.

The emphasis in the low inputs production systems needs, therefore, to be on the improvement of the productivity of indigenous livestock for dairy production through characterization and description of environments in which the indigenous cattle are found as a means for identifying and defining the environments in which the characterized groups are adapted for use in selective breeding programs. Characterization of the indigenous livestock serves as an important tool to identify and select potential individuals, breeds or breed types of livestock for improvement and conservation. Thus, preliminary identification and characterisation of suitable indigenous cattle populations that have high genetic potential for dairy production under farmers’ production environment was the basis of this study. It was envisaged that incomes and food security could be improved through selective breeding of indigenous traditional populations for dairy production in the targeted sites. This study was, therefore, undertaken to characterize and evaluate dairy production potential of selected indigenous cattle populations to ascertain diversity and ultimately improve genetic potential for future dairy production through selective breeding.


Materials and methods

Study area

The study was conducted in the Southern Highlands and Eastern of Tanzania. The altitude of the Southern Highlands ranges from 400 to 3000 meters above sea level while rainfall varies from 750mm in lower altitudes to 2600 in the mountains and along Lake Nyasa and it commences in November to April annually. The tropical and semi-temperate climate of the area favours livestock and crop production which are the main activities in the area. On the other hand, the altitude of the Eastern zone ranges from 0 to 1800 meters above sea level while rainfall varies from 750 in lower altitudes to 1200 mm along Usambara Mountains, starting in September to December and March to June annually. The tropical and coastal humid climatic conditions of the area also favour livestock and crop production which are the main socio-economic activities.

Data collection

Four districts - Njombe, Mufindi, Bagamoyo and Muheza - were selected for the study, one in each of the Njombe, Iringa, Coastal and Tanga regions, respectively, due to having large populations of indigenous cattle. The location and climatic conditions of each district covered in the present study hasve been described in the respective regional livestock profiles (URT 2010). Eight villages (Utiga, Lunguya, Kikombo, Mtambula, Tanganyika, Chang’ombe, Chamakweza and Kinzagu) were selected for the study (two villages per district). The villages were purposely selected based on the information provided by district livestock officers. Fifteen households were purposely selected per village from a list of households that had been keeping more than ten indigenous cattle for the last five years and their willingness to participate in the project, making a total of 120 study households. During the survey, all the selected villages and farmers were geo-referenced using GPS (Table 1).

Table 1: Sampling frame of the household herds and individual animals for morphometric measurements and observations

 

Districts

Villages

Elevation (masl)#

Number of   herds sampled

Number of animals measured and appraised

Animals observed for body colours

 

 

Bulls

Cows

Total

 

Njombe

Lunguya

1774

15

16

45

61

427

 

Utiga

1408

15

17

45

62

 

 

 

 

 

 

 

 

 

 

 

Mufindi

Kikombo

1702

9

15

45

60

538

 

Mtambula

1718

16

15

45

60

 

 

 

 

 

 

 

 

 

 

 

 

Muheza

Msakangoto

7

15

9

51

60

 N/A

 

Kigongomawe

102

15

7

53

60

 

 

Bagamoyo

 

 

 

 

 

 

 

 

Chamakweza

267

15

15

45

60

 N/A

 

Kinzagu

253

17

15

45

60

 

Overall

 

 

117

109

374

483

965

 

# masl = meter above sea level

 

Two approaches were employed to collect information in the study. The first approach involved application of a questionnaire where data on household characteristics, and productive and reproductive traits of indigenous cattle were collected from the selected households. The information collected included general household socio-economic characteristics; dairy production attributes (age at first calving, calving interval, number of calves per lifetime) as well as the current production environments, production systems, production potentials (milk yield, lactation length) and production challenges.

The second approach involved collection of physical body measurements which were taken on 483 mature (> 4 years) animals (372 cows and 110 bulls) in all the study districts; body colours and colour patterns were appraised on all 965 animals from all selected herds in Njombe and Mufindi districts. These data were taken to complement the information on dairy attributes that were taken from the farmers. The key body measurements were taken on randomly selected mature male and female animals once, as described by Mason (1996). Measurements were taken on four major traits as described by Francis et al (2002), Adeyinka and Mohammed (2006) and FAO (2012). The key measurements that were taken included body weights (BW), body lengths (BL), heart girths (HG) and height at withers (HW). BW and HG were estimated and measured, respectively, using a weigh band calibrated both in kilograms and centimetres, on different sides of the band. The bands (RondoR) used have been calibrated from some East African indigenous cattle breeds (Shirima et al 2005). Before the actual estimation of BW of the 483 animals was established, the correctness of the calibration was validated by comparing the actual weights and estimated weights of 30 mature bulls and cows. The BW was estimated and HG measured as the perimeter of the body immediately behind the shoulder blades in a vertical plane, perpendicular to the long-axis of the body. A mason’s measuring tape was used to determine the body length (BL), as the distance from the shoulder point to the pin bone and height at withers (HW), as the distance from the hoof base to the withers. On the other hand, coat colours and colour patterns were scored using a standard colour descriptor manual (SADC/ILRI Animal Genetic Resources Survey Colour Chart SADC 2001).

Data processing and analysis

Qualitative data from the farmers were coded and analysed using the Statistical Package for Social Sciences (SPSS 2008) computer software in order to generate descriptive statistics such as means and frequencies or percentages. All quantitative data (body measurements) were analysed using the General Linear Models Procedure of the Statistical Analysis Systems, Ver. 9.1.3 (SAS 2004), with the MANOVA option for calculating partial correlation coefficients among the body measurement variables. Location (districts) and sex were used as fixed effects and villages within location as nested effects.


Results and discussion

Household characteristics

 The majority of the households were male-headed while only a few (7%) of them headed by females (Table 2 ). Most of the respondents were the heads of the households. The gender of headship of the households is an important factor in decision making and rate of adoption of technologies. They also tend to give the knowledge of the general behaviour and attitude of the people in the study area. The  age range of most of the farmers is within the common labour force group in Tanzania. The people in this group tend to be active, creative and participate in many social and economic activities (URT 2006). The majority of respondents had primary education while only a few (7%) had secondary education. However, a considerable (17%) number of farmers were illiterate. Even though the majority of farmers were able to read and write, it was revealed from the study that education level varied between districts with the highest level (100%) of literacy in Mufindi and the lowest (56%) in Bagamoyo district (Table 2).

Table 2: Socio-economic characteristics of the households in the study area

Characteristics

Districts

Overall
(N = 123)

Muheza
(n = 28)

Bagamoyo
(n = 34)

Mufindi
(n = 31)

Njombe
(n = 30)

Gender of respondents (%)

 

 

 

Male

96

91

93

90

93

Female

4

9

7

10

7

Educational levels of respondents (%)

 

 

None

14

44

0

7

17

Primary

82

41

97

87

76

Secondary

4

15

3

7

7

Age of respondents (%)

 

 

 

 

21-40 years

25

15

13

17

17

41-60 years

54

71

77

73

69

Over 61 years

21

15

10

10

14

Is respondent head of household? (%)

 

 

 

Yes

93

100

97

93

96

No

7

0

3

7

4

Land used for grazing (%)

 

 

 

Communal

92

98

90

87

92

Private

5

2

3

3

3

Communal and Private

3

0

7

17

5

Main sources of household income (%)

 

 

 

Livestock product sales

58

71

39

37

51

Crop and livestock sales

57

41

76

75

62

Purposes of keeping cattle (%)

 

 

 

Draft power

38

25

43

43

37

Milk

37

33

15

17

25

Socio-economic

25

30

48

46

37

Production challenges (%)

 

 

 

Diseases/parasites

90

94

97

96

94

Bulls shortages

86

81

84

81

83

Feed shortages

67

61

57

62

62

Note: N = number of respondents

Land ownership, source of income and purpose of keeping selected indigenous cattle

The majority of the farmers depended on communally owned land for socio-economic activities while only a few farmers had their own land or private land or utilised both communal and private lands (Table 2). The major sources of income were livestock products and both crops and livestock. The majority of the farmers ranked livestock as their major sources of income while crops and small enterprises were ranked second and third sources of income, respectively. The main purposes for keeping cattle were mentioned as provision of draught power and milk with many farmers nd the remaining farmers (38%) keeping cattle as source of income, meat and for socio-cultural purposes.

Traditional management practices

The majority of farmers practiced extensive and continuous grazing system, whereby the cattle were herded during the dry and wet season on communal grazing land and harvested grain crop fields. Rotational grazing was practised by a very few farmers. The predominant source of forage was communal lands with natural pasture species. However, 17% of the farmers also utilized crop residues from their own and/or neighbour’s farms for feeding their cattle during the dry season. Maize stovers were the commonest crop residues used during the dry season in all the study districts. All the respondents used kraals as their animal house.

Dairy breeds and breeding practices

The majority of the farmers kept indigenous cattle, mainly the Tanzania shorthorn zebu (TSZ) and a few (7%) of them kept some crosses of exotic x TSZ. All (100%) the farmers used natural bulls for breeding purposes, whereby mating practices were often uncontrolled. Sources of breeding bulls among the farmers included own herds, neighbours and a few of them purchased breeding bulls from other farmers. A considerable number of the farmers had at least one, if not several, bulls for breeding purposes.

Production characteristics

The mean age at first calving and calving interval were about 50±1.3 months and 16±0.6 months, respectively. The average milk yield was 3±0.15 litres per cow per day (ranging from 1 to 7). The majority of the farmers reported the lactation length of their indigenous cattle varied from 110 to 200 days. The average age at first calving is normally related to the type of management, genetic potential and generation interval and could therefore influence cow's productive life.

Production challenges

The majority of respondents mentioned diseases/parasites, lack of breeding bulls of high vigour and shortage of animal feeds during the dry season as the main production challenges (Table 2). However, various methods were employed for disease control, such as vaccination, dipping and deworming. Dipping was practiced by most of the farmers in all the study districts to control mainly tick-borne diseases. However, there were no well organised vaccination and deworming programmes against viral/bacterial diseases and endoparasites. Thus, farmers need to have well organised and coordinated diseases control programmes.

Marketing of dairy products

The amount of milk sold ranged between 1 and 5 litres in Njombe and Mufindi districts (Table 3). However, most farmers in Muheza and Bagamoyo sold more than 10 litres per household per day. Most of the farmers sold their milk to the local market, at the farm gate and to the neighbouring countries. However, farmers mentioned low milk prices, problem in setting prices, lack of marketing information and poor milk cooling facilities as major constraints in milk production both in the Southern Highlands and Eastern zones. The majority of the farmers were within 1 - 5 km of the milk marketing places, especially in Njombe, Muheza and Bagamoyo districts.

Table 3: Quantities of milk sold, type of market and distance to the milk markets (data are percentages of households)

 

Districts

 

Overall

Muheza

Bagamoyo

Mufindi

Njombe

Fresh milk sold, liters/d

 

 

 

 

 

Nil

7.4

17.6

0

0

10.4

 1-5

25.9

14.7

100

57.1

32.5

6-10

11.1

20.6

0

28.6

15.6

> 10

55.6

47.1

0

14.3

41.6

Where milk sold?

 

 

 

 

 

Farm gate

40

53.6

77.8

40

50.7

Local market

44

46.4

22.2

40

41.8

Cross border

16

0

0

20

7.5

Distance to the market

 

 

 

 

 

Less than 1 km

6.3

0

60

0

10.5

1-5 km

50

66.7

0

50

50

6-10 km

43.8

6.7

0

0

21.1

> 10 km

0

6.7

0

50

5.3

Unknown

0

6.7

0

0

2.6

Nil

0

13.3

40

0

10.5

Body measurements

Location influenced all the body measurements of the study cattle populations, with animals from Njombe and Mufindi districts being superior in most of the body measurements to those from Bagamoyo and Muheza districts (Table 4). This discrepancy in body measurements among the study cattle populations could be attributed to differences in production environments, availability of feed resources, breeding goals, traditional management practices or inherent genetic differences among the study cattle populations.

Table 4: Least square means (±SE) for body measurements of selected cattle populations, summarised by districts  

Traits

Bagamoyo
(n = 120)

Mufindi
(n = 120)

Muheza
(n = 109)

Njombe
(n = 123)

Height at withers (cm)

93.0±3.04a

109±3.00ab

98.5±4.42a

110±3.00ab

Body weights (kg)

285±5.54b

287±5.47b

233±8.06a

284±5.47b

Body length (cm)

97.6±0.88b

121±0.86c

91.7±1.27a

122±0.86c

Heart girth (cm)

146±1.10b

147±1.08b

137±1.60a

148±1.08b

Note: n = number of animals measured; Least square means with different superscripts within a row are significantly different at P 0.05.

Likewise, sex influenced all the body measurements except the height at withers, with bulls superseding the cows (Table 5). Marked differences between bulls and cows in many body measurements have also been reported by several other scholars (Mwacharo et al 2006; Kugonza et al 2011). In the present study sexual dimorphism was evident in the study cattle populations, with bulls having significantly greater measurements than the cows for the traits studied. The sex-related differences are most probably the result of the usual between-sex differential hormonal effects on growth.

Table 5: Least square means (±SEM) for body measurements of cows and bulls

Traits

Bulls (n = 110)

Cows (n = 372)

p - value

Height at withers (cm)

105±3.05

101±0.78

0.3067

Body weights (kg)

299±5.56

246±2.80

0.0011

Body length (cm)

110±0.88

106±0.44

0.0210

Heart girth (cm)

148±1.10

142±0.55

0.0058

Note: n = number of animals measured; SEM = Standard Error of the Mean

The phenotypic partial correlation coefficients between the morphometric measurements were positive and the majority highly significant (Table 6). Body weight was highly and positively correlated with heart girth (0.59), height at withers (0.47) and body length (0.37); hence, the latter traits can reliably be used as a proxy (either singly or in combination with other linear traits) for estimating body weights for the studied cattle populations.

Table 6: Partial correlation coefficients among various body measurements of selected indigenous cattle

Traits

Height at withers

Body lengths

Heart girth

Body weight

0.47***

0.37***

0.59***

Height at withers

 

0.30***

0.41***

Body length

 

 

0.30***

Note:  ***P < 0.001

Physical characteristics

The indigenous cattle populations in Njombe and Mufindi districts had variable body colour patterns with some community colour preferences across the two study districts. The predominant colours were red, black, pied (red and white), pied (black and white) and spotted (red and white). Other colours were found in small proportions in the herds (Table 7). The majority of farmers preferred animals with black or red or mixture of either red or black and white. The solely white colour was reported to be not preferred by many farmers due to being associated with high risks of tick infestations.

 Table 7: Frequency (%) of body coat colour patterns in selected indigenous cattle populations, summarised by districts

Colour patterns

Njombe

Mufindi

Overall

n

%

n

%

N

%

Red

164

38

194

36

358

37

Black

105

25

127

24

232

24

Pied (black and white)

35

8

47

9

82

9

Pied (brown and white)

0

0

2

0.37

2

0.21

Spotted (black and white)

21

5

27

5

48

5

Brown

1

0.23

1

0.19

2

0.21

Pied (red and white)

45

11

61

11

106

11

Dun

0

0

1

0.19

1

0.10

Gray

12

2.81

21

4

33

3

Pied (red and black)

0

0

1

0.19

1

0.10

Pied (brindle and white)

0

0

2

0.37

2

0.21

Pied (gray and white)

0

0

1

0.19

1

0.10

Brindle

6

1

8

1

14

1

White

0

0

1

0.19

1

0.10

Spotted (red and white)

38

9

44

8

82

9

Total (observed animals)

427

100

538

100

965

100

Note: n = number of observed animals; % = percentage

 The udders and teats were mostly medium-sized (Table 8). These observations are consistent with those observed for Baggara cattle in Sudan (Alsiddig et al 2010) and Tarime cattle in Tanzania (Chenyambuga et al 2008).

Table 8: Frequency (%) of udder and teat sizes of selected cows, summarised by districts

 


Quality

Njombe              (n = 90)

Mufindi
(n = 86)

Muheza
(n = 103)

Bagamoyo (n = 90)

Overall
 
(N = 369)

Udder size

Large

2

0

1

0

1

Medium

46

37

64

77

56

Small

52

63

35

23

43


Teat size

           

Large

1

0

1

0

0

Medium

60

41

64

77

61

Small

39

59

35

23

39

Note: n = number of respondents


Conclusion


Acknowledgements

The financial support from the World Bank through ASARECA in East and Central Africa (ECA) is highly appreciated. Gratitude is extended to researchers and assistant researchers of Tanzania Livestock Research Institute (TALIRI) for their tireless involvement in data collection. Appreciation is also extended to District Livestock officers and farmers for accepting us to be interviewed and for providing their cattle herds for phenotypic appraisal.


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Received 31 January 2014; Accepted 17 February 2014; Published 1 March 2014

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