Respondents were asked questions that elicited their personal information, such as sex, age, level of education and level of annual income from farming activities (cf. questions b1, b2 and c11 in Appendices 1 and 2). These biographical and economic data were solicited to describe the demographic profile of respondents who participated in the study. The demographic variables for farmers were used to inquire whether or not there is any correlation between these variables and the knowledge of farmers on climate change and variability and farmers’ adoption of farming innovation practices. The other categories of
126
respondents were the district agricultural extension officers and the programme manager of the CCAA project.
5.2.1 Gender of Respondents
There were more female 58 (69%) than male 26 (31%) respondents. This result reflected the composition of the groups of targeted farmers who received training and those who were not trained by the Climate Change and Adaptation in Africa (CCAA) project. Thus, in the training there were more women in the groups than men. The findings from semi-structured interviews showed that in Maluga village 20 (55.6%) respondents were female, while 16 (44.4%) respondents were male. In Chibelela village, 38 (79.1%) respondents were female and 10 (20.8%) respondents were male, as depicted in Table 5.1 and Figure 5.1. The greater number of women in Chibelela is explained by the presence of many women in farming groups engaged in agricultural activities in that village. The field observation showed that the district agricultural extension officers and the programme manager were all male.
Table 5.1: Gender of Farmers
Sex N=84 Frequency Percentage
Male 26 31
Female 58 69
Total 84 100
Figure 5.1: Distribution of Gender in Study Villages
16
10 20
38
0 5 10 15 20 25 30 35 40
Maluga Chibelela
Respondents
Villages
Male Female
127 5.2.2 Age of Respondents
Findings from the interviews show that most (26 or 31.0%) respondents were between the ages of 36 years and 45 years, followed by those above 60 years 20 (23.8%). The third group of respondents were between 51 and 60 years old (15 or 17.9%). The smallest group were between 15 and 25 years old (2 or 2.4%).
The age of both district agricultural officers involved in the study was between 36 years and 45 years while the programme manager’s age was between 46 and 50 years. Table 5.2 summarises the results on the age of the respondents.
Table 5.2: Age Profile of Respondents
Category N=84 Frequency Percentage
15-25 years 2 2.4
26-35 years 10 11.9
36-45 years 26 31.0
46-50 years 11 13.0
51-60 years 15 17.9
Over 60 years 20 23.8%
Total 84 100.0%
5.2.3 Respondents’ Levels of Education
Findings of the study indicate that most (63 or 75%) of the respondents were primary school leavers followed by those who were illiterate (12 or 14.3%). Eight (9.5%) of the respondents attained secondary education and only one (1.2%) attended college/university. The level of education of the respondents is shown in Figure 5.2.
128 Figure 3.2: Level of Education of Respondents
5.2.4 Income Level of Respondents Based on Annual Production
The study sought to determine the annual income of farmers from their agricultural production practices. Five categories of respondents’ annual income emerged. The categories were calculated based on wealth quintiles (Hoogeveen et al., 2009). The categorisation of wealth income groups is similar to the one used in the Tanzania Household Budget Survey of 2007, which shows the distribution of household monthly consumption (Poverty and Human Development Report PHDR, 2009c). Annual income level is calculated on the basis of monthly income, over 28 days in a month, and over a year of 13 months (Deaton 1988).
Those with an annual income of less than Tanzanian Shillings (Tsh) 50635 were grouped as the poorest and those with an annual income between Tsh 50636 and Tsh 86580 were grouped as poor. Respondents with an income between Tsh 86581 and Tsh 123370 per year were classified as average income earners, while respondents with income between Tsh 123371 and 177255 per year were categorised as better than average. Respondents with an income of between Tsh. 177256 and 361868 were grouped as least poor. Details are given in Table 5.3.
12; 14%
63; 75%
8; 10%
1; 1%
No formal education
Primary education
Secondary education
University/college education
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Table 5.3: Income Level of Respondents based on Annual Production Wealth Quintile
N=84
Level of Income per
Annum (USD)
Level of Income per Annum
(Tsh.)
Frequency Percentage
Poorest (1st) 0-32.67 Less than 0-50635 4 4.8
Poor (2nd) 32.68-55.86 50636-86580 7 8.3
Average (3rd) 55.87-79.59 86581-123370 4 4.8
Better than Average (4th)
70.60-114.36 123371-177255 13 15.5
Least Poor (5th) 114.37-233.46 177256-361868 56 66.6
Total 84 100.0
(PHDR 2009c)
Note: 1USD~1550 Tshs.
Cross tabulation of farmers' income in the study villages indicated more poor in Chibelela village than in Maluga village. Findings indicate that in Maluga village there are few respondents in the 1st and 2nd wealth quintiles. These were one (14.3%) compared to 10 (90.5%) in Chibelela village. Findings indicate the 3rd wealth quintile had two (2.4%) respondents in each village. The 4th wealth category had seven (53.8%) respondents in Maluga village as compared to six (46.2%) in Chibelela village. The last wealth quintile group had 26 (46.3%) respondents in Maluga and 30 (53.6%) in Chibelela village. Table 5.4 shows the results in detail.
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Table 2.4: Poverty Distribution across Study Villages Income
Categories
Maluga Village Chibelela Village
Total Frequency Percentage Frequency Percentage
Poorest 0 0.0 4 4.8 100
Poor 1 14.3 6 85.7 100
Average 2 2.4 2 2.4 100
Better than Average
7 53.8 6 46.2 100
Least Poor 26 46.4 30 53.6 100
Total 36 48 84
5.2.5 Farm Sizes
The respondents were asked the size of their farms (cf. research question c10 in Appendices 1 and 2). Findings from the interviews show that most (50 or 59.6%) respondents possess farms of sizes above five acres. Another 27 (32.1%) respondents own farms of between 2.5 and 5.0 acres. The last category of respondents has farms of between 1.0 and 2.0 acres. Table 5.5 summarises the areas of the farms.
Table 5.5: Acreage of Farms Owned
Farm sizes (acres) N=84 Frequency Percentage
1.0-2.0 7 8.3
2.1-5.0 27 32.1
Above 5 50 59.6
Total 84 100.0
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The findings indicated that farmers in Chibelela village had larger farms compared to those in Maluga village. Results showed 6 (85.7%) farmers in Chibelela village with farm sizes between 1.0-2.0 acres, compared to 1 (14.3%) in Maluga village. Farmers with farm sizes between 2.5 and 5.0 acres were 11 (40.7%) in Maluga village and 16 (59.3%) in Chibelela village. More farmers in Chibelela had farms above 5 acres (26 or 52%), compared with 24 (48%) in Maluga village. The results are given in Figure 5.3.
Figure 5.3: Respondents’ Farm Sizes 5.2.6 Respondents’ Occupations
Table 5 shows that most, that is 78 (92.8%) respondents, indicated their primary occupation as farming and a few (6 or 7.2%) stated that their primary occupation was non-farming. The study found that those respondents who are not primarily dependent on farming, but are salaried, were 4 (4.8%). Another 2 (2.4%) depended primarily on petty trading.
Findings indicate that the majority (28 or 33.2%) had livestock keeping as their secondary occupation. Twenty-three (27%) respondents engaged in petty trading. The results showed 4 (4.8%) had their secondary occupation as farming, while another 4 (4.8%) respondents stated their secondary occupation was government employment. Twenty four, 24 (28.6%) respondents did not indicate having any secondary occupation and were designated as not having a secondary occupation. Only 1 (1.2%) respondent’s secondary occupation was beekeeping. The results are given in Tables 5.6 and 5.7.
1
11
24
6
16
26
0 5 10 15 20 25 30
1.0-2.0 2.1-5.0 Above 5
Number of Respondents
Farm Sizes (acres)
Maluga Chibelela
132 Table 5.6: Respondents’ Primary Occupation
Primary Occupation N=84 Frequency Percentage
Farming 78 92.8
Salaried job 4 4.8
Petty trading 2 2.4
Total 84 100.0
Table 5.7: Respondents’ Secondary Occupation Secondary Occupation
N=84
Frequency Percentage
Livestock keeping 28 33.2
Salaried jobs 4 4.8
Petty trading 23 27.4
No secondary activity 24 28.6
Beekeeping 1 1.2
Farming 4 4.8
Total 84 100 .0
5.3 Farming Practices and Farmers’ Source of Water in Chibelela and Maluga