Smallholder Dairy Production Technology Transfer and Adoption Constraints in Mixed Farming System in Girar Jarso Woreda of North Shoa Zone Oromia Regional State
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2007-06
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Abstract
This study was carried out from September 2006 to April 2007 in four Kebeles’ of Girar-Jarso
Woreda, North Shoa zone of Oromia Regional State, Ethiopia to assess productive
performance of dairy cows and technology use in 200 randomly selected market-oriented
smallholder dairy farms. A structured questionnaire survey, farm visit, and PA discussion
were conducted during the study. The overall mean family size of respondents in this study
was 5.77+2.35 persons. The average number of economically active family members (greater
than 15 years old) was 2.44 persons (1.20 ± 1.25 male and 1.24 ± 1.33 female). The average
number of livestock owned by the respondent farmers was 16.65 ± 7.11animals or 9.47 TLU.
Dairy cows constituted the highest proportion of the herd followed by draft oxen. Crossbred
dairy cows represented the highest proportion of the cattle herd composition with the mean
value of 1.83 (22.7%). There was statistically significant difference between crossbred and
indigenous cattle in all production and reproduction performance parameters assessed
(p<0.05). The respondent farmers pointed-out that scarcity of feeds, mainly during dry season,
is the major limiting factor which affected the development of livestock sub-sector in general
and the rearing of crossbred dairy cows in particular. Land allotted for livestock grazing was
only 0.71 hectares. From a total of 21 dairy technologies identified in the study area
crossbreeding and mastitis inspection had highest adoption rates, 91.5% and 95%
respectively. The average numbers of dairy technology up take was 9.89 +2.16 with a range
from 5-16. Sex, age, level of education and farming experience were found important
characteristics that influence demand for dairy technologies in the study area. The results
showed that the female groups were less users of dairy technology averaged 9.26 +1.90
compared to the male group (average 9.95+2.20); thus gender differences seem to have a
significance influence on likelihood of technology uptake. Education was another important
factor that favored the likelihood of technology uptakes. This suggests the important role of
education in stimulating demand for technology use. Farm experiences also determine the use
of dairy technology in the study area. Accordingly the t-values of the variables were
computed and out of these variable the age, farm experience, and level of education were
found to differ significantly (p > 0.05) probability level. As expected, sex is positively and is
statistically significant (p < 0.05) for all technologies identified and adopted in the area.
According to the survey result characteristics of the household head (84%) and source of
information (68.5%) were the most frequent factors that influence the decisions of the
household to choice new technologies.