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grain filling are roasted and eaten, which is locally termed as „mashella eshet‟, „tibese‟ or
„lemete‟. These are the most common food types around September and October when sorghum reaches the soft dough stage. Depending on the maturity period farmers have access to “mashela eshet” until harvest.
Participatory rural appraisal is one of the most effective and popular way to gather information in rural areas. The basic concept of PRA is to learn from rural communities. It is a bottom-up approach developed in the early 1990s and stands on the principle that local communities are creative, capable and can do their own investigations, analysis and planning (Chambers, 1992).
Therefore, the objectives of this study were to determine the impact of drought on sorghum production and productivity over time and space, and to identify farmers‟ production constraints and coping strategies when dealing with drought in north eastern Ethiopia.
2.3 Materials and methods
39 Figure 2.1 Map of Ethiopia showing the study zones
Table 2.1 Major agro-ecological characteristics of the study zones Study zone Agro-
ecology
Altitude (masl)
Geographic position
Annual rainfall (mm)
Temperature (oC)
Min Max
North Wollo Semi-arid 1450-2400 11°49′50.49′′N 39°35′39.94′′E
700-1000 19 34
South Wollo Semi-arid 1600-2700 11°08′00.36′′N 39°37′58.32′′E
800-1250 16 31
Oromia Special
Semi-arid 1400-2100 10°42′58.64′′N 39°52′04.61′′E
750-1300 21 33
Key: masl= meters above sea level
The priority objective of farmers in the study areas is to secure an adequate family food supply throughout the year. Therefore, farmers in these areas practice mixed crop and livestock farming, which is the predominant source of farmers‟ livelihoods. Sorghum and tef are the major food
LEGEND
North Wollo South Wollo
Zone boundary Oromia Special
Surveyed villages
SUDAN
ERITREA
SOMALIA
KENYA
40
crops in terms of the area they are planted and volume of production obtained (CSA, 2016). The second priority is to earn cash incomes for household expenditures such as farm inputs, school fees, taxes and medical costs. This is also achieved through the production of cash crops such as sesame, noug, soybean, pepper, and in years of crop failure through the sale of livestock. The study sites are the major production and diversity belt for sorghum in the country. Sorghum, the main food source, is made into “injera”, which is the preferred dish in the area. Sometimes sorghum is prepared in the form of porridge, roasted “kolo”, cooked “nifro” or locally brewed
“tella”.
In the study site, tef is the preferred food crop. However, farmers give greater importance to sorghum and expect to harvest more grain and biomass than from tef. Sorghum is also harvested for its green-head as a food source in the immature stage, for roasted grains when tef is still in its vegetative stage, and the food supply is short.
2.3.2 Sampling method
Purposive sampling was employed to include the major sorghum growing agro-ecologies and zones for the study. According to the Ethiopian administrative classification a zone is a large administrative unit below region. From each administrative zone one woreda was selected. A zone is composed of a number of woredas, while a woreda is an administrative level that is equivalent to a district and composed of a number of kebeles. A kebele or neighbourhood association is the smallest unit of local government. From each woreda two kebeles known for experiencing recurrent droughts were purposely selected. The target woredas and kebeles were chosen on the basis of sorghum area coverage, production, consumption and prior information on the intensity, duration and spatial coverage of drought with the assistance of zone and woreda agriculture office. Overall, the survey was conducted in six kebeles selected from three woredas.
A total of 180 farmers that cultivated sorghum during 2014/15 cropping season participated in the study. In each kebele, 30 sorghum growing men and women farmers were selected and interviewed with the participation of kebele level developmental agents and three researchers (a Socio-Economist, an Agronomist and a Plant Breeder) drawn from Sirinka Agricultural Research Center. The survey was conducted between December 2014 and January 2015 when farmers were harvesting their sorghum.
41 2.3.3 Data collection and analysis
Data were collected through individual interviews, observations made by transect walks across selected kebeles, and focus group discussions with farmers. Semi-structured questionnaires were used to collect information on cropping systems, the impact of drought and other production constraints, drought coping mechanisms, farmer‟s varietal and trait preferences, sorghum utilization, seed sources and planting periods. Drought tolerant sorghum landraces widely used by farmers were identified and collected with their local names. In each kebele, discussions were held among selected elders, and their experiences and interests were recorded. Additional information was recorded through personal observations made during transect walks through each of the sampled kebeles. During the transect walks observations were made on crop lands where sorghum had been planted during the growing season. Observations were also made on the impact of a recent drought, maturity period, uses of sorghum, landrace diversity and cultural practices such as weeding and row planting.
Both qualitative and quantitative data were collected through questionnaires. Data were coded and subjected to analysis using the SPSS statistical package version 16.0 (SPSS, 2007). The processes of qualitative data analysis included identifying common observations, concepts, ideas, and issues related to cropping systems, as well as elements and indicators of drought.
Quantitative data that was collected from primary sources were subjected to statistical summaries such as means and chi-square analysis. Chi-square test was used for testing relationships between categorical variables included in this study. It is used to determine whether there is a significant association between the two variables. Sorghum productivity data was subjected to a one tailed t- test using the SAS statistical software package version 9.3 (SAS, 2011). A one tailed t-test was conducted using the mean grain yield of surveyed zones during the 2015 cropping season.
For t-test analysis used to test the significance of two means so that the surveyed sorghum productivity mean for each region was compared with its respective zonal mean sourced from CSA, 2015 data. In addition, the overall surveyed mean across the three zones was also compared with the mean of the country sorghum productivity sourced from CSA, 2015 data.
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