Livestock Research for Rural Development 22 (5) 2010 Notes to Authors LRRD Newsletter

Citation of this paper

Determinants of cattle farmers’ perceived relevance of livestock technologies in Botswana

O I Oladele and K Rantseo

Department of Agricultural Economics, Education and Extension, Botswana College of Agriculture University of Botswana, Gaborone.
oladele20002001@yahoo.com

Abstract

This study examined the determinants of cattle farmers’ perceived relevance of livestock technologies in Botswana.  Simple random sampling technique was used to select 90 cattle farmers from three extension areas in Tonota sub-district. A structured questionnaire which had earlier been subjected to face validity, and with a reliability coefficient of 0.92 was used to collect data from the sampled cattle farmers.  Data was analysed using Statistical Package for Social Sciences (SPSS)  for frequency counts, percentages, means, standard deviation and multiple regression analysis. The significance of the relationship between the demographic characteristics of farmers and their perception of the relevance of livestock technologies was explored.

 

The results of the study showed that  majority of cattle farmers were male (73.4%), married (53.1%),  more than 50 years old (53.1%), had formal education (89.1%), had farming experience of at least 5 years (55%), had annual income of  more than P10 000 (88.9%) and obtained information from several sources(34.4%). The most prominent technologies among farmers were calf management (90.6%), use of multi-nutritive block- salt-licks (86.0%), use of Livestock Identification and Trace-back System  (LITS) (85.9%), hay from natural grass (82.8%), use of crop residues as feed resources (82.8%), calf weaning (82.8%) and use of Lab-lab hay (82.5%). However, technologies such as getting prices from  Botswana Meat Commission (BMC) by  short message service (SMS) (54.7%), stud breeding (51.6%) and weight determination by dentition (50%) recorded low awareness among farmers. The most relevant technologies as rated by farmers were vaccinations (78.2%), calf management and identification (76.6%), use of bolus insertion  (76.6%), use of crop residues as feed resources (75.0%), calf weaning (71.9%) and animal culling (70.3%). Conversely, technologies that were not considered relevant by farmers were use of composite breed (68.8%), use of cenchrus cilliaris for range land rehabilitation (67.2%)  and for ley-farming (64.1%), use of Napier grass      (62.5%) and feed formulation for milking cows (62.5%).  Significant determinants were educational level (t = 1.69), herd size (t = 1.88), income (t = 2.47) and distance to crushes (t = 2.20). It implies that the higher the educational level of farmers the higher the perceived relevance of livestock technologies. It is therefore important that these significant variables are factored into the technology development and dissemination process among cattle farmers in Botswana.

Keywords: Awareness, Botswana, cattle farmers’ livestock technologies, relevance


Introduction

Botswana is a landlocked southern African country, with an area of 566,000 square kilometres and a population of 1.5 million whose density is unusually low at 2.6  people per square km (World Bank 2001). The carrying capacity of soils is low and with semi-arid climatic conditions, with frequent droughts, the vast majority of the land is better suited to cattle ranching than arable agriculture. Beef exports (mainly to the European Union) were the major source of foreign exchange, but diamonds and tourism are now important. Although the discovery of diamonds has rescued Botswana from its former position as one of the poorest countries on earth, mining provides little employment, and  agriculture is  the main source of income for approximately half the population (Irz and Thirtle 2003). Livestock  are an important household asset because they are significant in maintaining livelihoods of their keepers by providing food, draught power, manure, skins, hides, cash, security, social and cultural identity as well as being a medium of exchange and means of savings (Mrema and Rannobe 1996; Chernichovsky et al 1985; MFDP 1991; World Bank 2001; Oladele and Monkhei 2008).  To improve agricultural production, some form of appropriate technology is necessary. Technology has been defined as all the methods of production which have been developed on the basis of existing  scientific knowledge and appropriate technologies in this context are defined as the latest scientific and technological development that have been adjusted to suit the local conditions to the highest possible degree (Oladele 2001). In this regard, farmers’ involvement in technology development has generated a lot of models through several studies.  The national and international research centres have reported significant yield increase in many crops, while insect pests and disease damage to  crops and animals  have been brought under substantial control (Oladele and Fawole 2007). At the same time Research institutions have developed technologies and disseminated them through the extension  services to farmers.

 

Agricultural research in Botswana was initiated in 1963 at the Morale Pasture Research Station with emphasis on animal production and range research. In the 1970’s researchers and policy makers  observed that despite the impressive results of agricultural research programmes, agricultural production was not increasing. A concern was also shown on the large gap that existed between on-station research yields and those from farmers’ fields even when the same technologies were used (Acquah and Macala 1998) It was realized  then that either the various technologies were not reaching farmers or that the technologies were not being accepted.   To address the problems identified in technology transfer and the high yield gap,  a decision was made to initiate technology testing on farmers’ fields. Two projects came into existence in the mid-1970s, namely Evaluation of Farming System and Agricultural Implements Project (EFSAIP) and the Integrated Farming Pilot Project (IFPP). The IFPP later on became known as the Farming System Southern Region (FSSR) (Acquah and Macala 1998).

 

Anecdotal evidence suggests that farmers’ perception of the relevance of technologies developed and disseminated in Botswana affected their adoption of these technologies. This study was designed to determine the cattle farmers’ perception of the relevance of livestock technologies.  The broad objective  was to analyze the perception of farmers on the relevance of livestock technologies in Botswana. Specific objectives include the identification of demographic characteristics of the farmers and determination of their awareness of the relevance of livestock technologies. 

 

Methodology

A descriptive research design was employed in conducting this study.  The target population of the study was cattle farmers in Tonota sub-district. There are 1624 cattle farmers distributed within four extension areas namely Tonota East (345), Tonota West (371), Mabesekwa (377) and Borolong (531). Simple random selection was done for three extension areas and 30 cattle farmers from each of the extension areas to give a total sample size of 90. A structured questionnaire was used to collect data from the sampled cattle farmers.  The questionnaire was designed based on review of related literature and objectives of the study. The questionnaire consisted of personal characteristics, awareness and perception of cattle farmers on the relevance of livestock technologies. The questionnaire was face validated and  pre-tested with a similar sample group in Mochudi extension area. Data was analysed using Statistical Package for Social Sciences (SPSS) for frequency counts, percentages, means, standard deviation and multiple regression analysis.

 

Results and discussion

The   household characteristics of respondents examined in the study were summarized in table 1.

Table 1.  Household  characteristics of cattle farmers in Tonota

Variables

Percentage

Age

 

Less than 30

23.3

30-40

31.3

41-50

17.2

Above 50

28.2

Education

 

Primary

12.5

JSS

7.8

SSS

14.1

College

20.3

University

34.4

Non response

10.9

Gender

 

Male

73.4

Female

26.6

Marital Status

 

Single

42.2

Married

53.1

Divorced

3.1

Widowed

1.6

Family Size

 

Less than 5

43.8

5-9

42.2

Above 10

4.7

Non response

9.4

Income

 

Less than 10000

11.1

10000 - 15000

15.6

15000 - 20000

9.4

Above 20000

18.9

Non response

45.3

Farming experience

 

1-5

42.3

6-10

26.7

Above 10

28.3

Non response

3.1

Out of the total number of respondents, 73.4% were male and this indicates their dominance in farming activities   which may be due to their access to farmland and their position as head of family. The lower proportion of female farmers could be due to their inability to get their own farmland and the fact that they preferred to engage in trade instead. This result agrees with the work of Nsoso et al (2005) who concluded that farming is a male-dominated profession. The results further showed that 53.1% of the respondents were married and were more than 50years old. About 34% of the respondents had formal education, reflecting high literacy levels among respondents.  Many of the cattle farmers (44%) had annual income of at least P10 000  and 55% had been farming for not less than 6 years.

 

In Table 2, the description of Herd size, composition,  sources of information and organisation membership among cattle farmers  were presented.

Table 2.  Herd size, composition,  sources of information and
organisation membership among cattle farmers

Variables

Percentage

Herd Size

 

Non response

14.1

Less than 20

31.5

20-50

33

51-100

12.7

Above 100

9.6

Herd Composition

 

Brahman

9.4

Simmental

1.6

Tswana

48.5

Friesian

28.1

Mixed

12.5

Sources of information

 

Radio

12.5

Newspapers

3.1

Veterinary Officers

32.8

Television

6.2

Friends and Relatives

9.3

Posters

1.6

All

34.4

Non response

45.3

Membership  of organization

 

Yes

15.6

No

82.8

Non response

1.6

About 55% of the farmers had at least 20 cattle. This shows the degree of subsistence among the farmers. It also stress the need to ensure that technologies are relevant to their need in order for the framer to sustain their livelihoods.  Tswana cattle breed was the most common among farmers. This may be due to the adaptability to the arid environment in Botswana by the breed as compared to other breeds. In this study, almost 83% of the respondents did not belong to any farmers’ organization. A combination of sources on information was explored by farmers in the study area. This may be due to the fact that information dissemination now uses multimedia strategy where information was provided through several media.

 

Awareness of technologies

 

The respondents awareness of agricultural technologies is shown in Table 3.

Table 3.  Farmers’ awareness and perceived relevance of livestock technologies

Technologies

Awareness %

Relevance%

Yes

Mean

SD

Yes

Mean

SD

Feed formulation for milking cows

56.3

1.56

0.50

37.5

1.34

0.51

Breed selection for beef production

78.1

1.78

0.42

45.3

1.45

0.50

Use of composite breed

71.9

1.69

0.50

31.3

1.31

0.47

Lab-lab hay

82.5

1.84

0.41

51.6

1.50

0.53

Lab-lab silage

64.1

1.64

0.48

37.5

1.34

0.51

Hay from planted grass

79.7

1.80

0.41

45.3

1.45

0.50

Hay from natural grass

82.8

1.83

0.38

57.8

1.56

0.53

Use of Napier grass

51.6

1.48

0.56

37.5

1.34

0.51

Use of cenchrus cilliaris for Ley-farming

53.2

1.52

0.50

34.4

1.52

1.41

Use of cenchrus cilliaris for Range land rehabilitation

50.0

1.48

0.53

32.8

1.33

0.47

Breed selection for dairy production

60.9

1.61

0.49

50.0

1.66

1.42

Use of multi-nutritive block- Salt-licks

86.0

1.83

0.42

62.5

1.63

0.49

Use of multi-nutritive block - Molasses block

81.3

1.81

0.39

68.8

1.66

0.51

Use of multi-nutritive block - Winter-lick block

81.3

1.81

0.39

62.5

1.63

0.49

Calf weaning

82.8

1.83

0.38

71.9

1.72

0.45

Calf management and identification

90.6

1.91

0.29

76.6

1.77

0.43

Use of  Livestock Identification and Trace-back System (LITS)

85.9

1.86

0.35

76.6

1.77

0.43

Calf feeding

73.4

1.73

0.45

62.5

1.63

0.49

Maintaining calf pans

75.0

1.75

0.44

53.1

1.53

0.50

Feeding dairy calves

62.5

1.63

0.49

45.3

1.45

0.50

Establishment of personal grazing lands

65.7

1.63

0.52

51.6

1.83

2.49

Weaner production scheme

64.1

1.64

0.48

50.0

1.50

0.50

Beef finisher

64.1

1.64

0.48

54.7

1.55

0.50

Animal culling

78.1

1.95

1.34

70.3

1.70

0.46

Botswana Meat Commission  Grading

78.1

1.78

1.42

59.4

1.58

0.53

Use of crop residues as feed resources

82.8

1.81

0.43

75.0

1.75

0.44

Vaccinations

81.5

1.78

0.45

78.2

1.75

0.47

Stud breeding

48.4

1.47

0.53

39.1

1.36

0.55

Botswana Meat Commission   Premium Payment Scheme

59.4

1.59

0.50

51.5

1.63

1.43

Feedlot purchasing

71.9

1.72

0.45

45.3

1.45

0.50

Botswana Meat Commission  prices by short message service

45.3

1.45

0.50

45.3

1.45

0.50

Weight determination by dentition

50.0

1.47

0.53

37.5

1.36

0.52

All the technologies recorded high awareness among the respondents. The most prominent technologies among farmers were calf management (90.6%, use of multi-nutritive block- salt-licks (86.0%), use of Livestock Identification and Trace-back System  (LITS) (85.9%), hay from natural grass (82.8%), use of crop residues as feed resources (82.8%), calf weaning (82.8%) and use of Lab-lab hay (82.5%). These may be due to the fact that these technologies were important in determining the profitability of beef ranching among farmers. The prevalent semi arid and arid conditions stress the importance of feed resource availability to cattle production, so farmers will have to be aware and adopt technologies that would enhance feed supply to the animals. Also, the use of Bolus was introduced in order to enhance the tracking of animals by the Botswana Meat Commission (BMC) which is the major marketing outlet for cattle farmers, without which cattle cannot be sold.  Other plausible reasons for this high awareness could be traced to the high intensity of extension services provided by the Department of Extension Coordinating Services. This is coupled with the involvement of the Department of Agricultural Research Institutes in the preparation of extension materials such as posters, bulletins and radio programmes,. Also it may be due to the fact that farmers saw these technologies as a means of enhancing their incomes and increasing their sources of protein. People will adopt a technology that will sustain their means of livelihood. On the other hand technologies such as getting prices from BMC by short message service (54.7%), stud breeding (51.6%) and weight determination by dentition (50%) recorded low awareness among farmers.

 

Perception of technologies

 

From Table 3, farmers’ perception of the relevance of agricultural technologies shows a high degree of variation. The technologies rated as most relevant by farmers were vaccinations (78.2%), calf management and identification (76.6%), use of Livestock Identification and Trace-back System (LITS)  (76.6%), use of crop residues as feed resources (75.0%), calf weaning (71.9%) and animal culling (70.3%). This rating has the potential to affect the eventual adoption of these technologies.  Technologies on management and improvement of livestock are perceived to be relevant by the farmers. This may be attributed to the fact that all these technologies feature prominently in the farming systems in the study area.

     

On the other hand, technologies that were not considered relevant by farmers were use of composite breed (68.8%), use of Cenchrus cilliaris for range land rehabilitation (67.2%), use of Cenchrus cilliaris for ley-farming (64.1%), use of Napier grass    (62.5%) and feed formulation for milking cows (62.5%). Also, the fact that some of the technologies are not in the current interest and needs of the farmers could be responsible for their perception as at the time of this study. The perception of farmers on these technologies, therefore, emphasizes the need for a demand-driven technology generation rather than supply-driven. 

 

The result of multiple regression analysis of relationships between farmers’ characteristics and perceived relevance of livestock technologies by cattle farmers is presented in Table 4. 

Table 4.  Determinants of cattle farmers’ perception of livestock technologies relevance

 

Regression coefficients

SE

Reg. Coeff/SE

(Constant)

62.0

9.45

6.56**

Age

6.9-02

0.10

0.68

Educational level

1.33

0.79

1.68*

Gender

-0.29

2.42

-0.12

Marital status

-0.99

1.86

-0.53

Herd size

.844

0.45

1.88*

Family size

3.1-02

0.02

1.23

Herd composition

-0.53

0.66

-0.80

Number of dependants

-0.10

0.45

-.221

Ownership status

-4.56

3.30

-1.37

Farming experience

-0.19

0.12

-1.56

 Information sources

-2.8-02

0.34

-0.08

Group membership

-1.91

2.34

-0.81

Income

7.7-05

0.00

2.46**

Time spent on farm

0.18

0.88

0.21

Distance to crushes

-3.8-02

0.01

-2.20**

Time taken to crushes

0.12

0.25

0.46

R

0.61

 

 

R square

0.37

 

 

F

1.71

 

 

p

0.007

 

 

The independent variables were significantly related to perceived relevance of livestock technologies with F value of 1.71, p < 0.05.  Also, R value of 0.61 showed that there was a strong correlation between independent variables and perceived relevance of livestock technologies. The result further predicted 37 percent of the variation in perceived relevance of livestock technologies by farmers. Significant determinants were educational level (t = 1.68), herd size (t = 1.88), income (t = 2.46) and distance to crushes (t = 2.20). It implies that the higher the educational level of farmers, and the more the herd size kept, and the higher the derived income the higher the perceived relevance of livestock technologies.  However, as the distance to crushes increases, their perceived relevance of livestock technologies decreases.

 

Anim (2008) reported that, in South Africa, cattle farmers’ age and herd size determines their willingness to pay for extension services.   The trend of these results may be attributed to the fact that adoption of livestock technologies had been reported by several studies to be influenced by education, income and herd size.  Farmers’ educational level would enhance their understanding of new technologies and remove the traditional stereotype practices. Herd size and income are directly related to how much investments and benefits farmers would make from their farms. These factors would influence their choice of practices and activities to enhance profit maximization. The inverse relationship between distance to crushes and perceived relevance of livestock technologies was due to the fact that bolus were inserted to cattle in designated crushes by veterinary  officers. This use of bolus by farmers would ensure their conformity to the required standards by the Botswana Meat Commission, an agency through which farmers market their cattle.

 

Conclusion

The study has clearly shown that:

 

References

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Received 13 March 2010; Accepted 18 March 2010; Published 1 May 2010

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