DOCSLIB.ORG

The Challenges and Opportunities of Honey Production Systems in Jimma Horro District Kellem Wollega Zone, Oromia, Ethiopia

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
The Challenges and Opportunities of Honey Production Systems in Jimma Horro District Kellem Wollega Zone, Oromia, Ethiopia Research Article ISSN: 2574 -1241 DOI: 10.26717/BJSTR.2020.29.004779 The Challenges and Opportunities of Honey Production Systems in Jimma Horro District Kellem Wollega Zone, Oromia, Ethiopia Soresa Shuma1* and Negasu Gamachu Dinsa2 1Dambi Dollo University, Department of Animal and Range Sciences, Ethiopia 2Oromia Agricultural Research Institute (IQQO), Haro Sabu Agricultural Research Centre, Ethiopia *Corresponding author: Soresa Shuma, Dambi Dollo University Ethiopia, Department of Animal and Range Sciences, Ethiopia ARTICLE INFO AbsTRACT Received: July 25, 2020 The study was designed to identify the challenges and opportunities of honey production systems in the study area. Three peasant associations (PAs), namely Gile, Published: August 04, 2020 Tibe and Kaba Sayo of Jimma Horro District PAs was selected based on variations in agro-ecology (high land, mid land and low land).Beekeepers in the study are challenged by several honey production Constraints. Such constraints are Honeybee Citation: Soresa Shuma, Negasu Gamachu pest and predators, misuse of pesticides and herbicides, honeybee diseases, colony Dinsa. The Challenges and Opportunities of absconding and shortage of bee forages. Some of the opportunities associated with Honey Production Systems in Jimma Horro District Kellem Wollega Zone, Oromia, resource, increasing hive products’ demand and Increasing attention and focus from Ethiopia. Biomed J Sci & Tech Res 29(2)- the government.study area are Availability of honeybee floral resources, Availability of honeybee 2020. BJSTR. MS.ID.004779. Keywords: Honey Production; Bee Forage; Challenges; Diseases Introduction the most important intervention areas for sustainable development Beekeeping or apiculture entails the rearing or keeping of among poor countries like Ethiopia [4]. bees with the aim of exploiting its products (such as honey, pollen grain, propolis, and brood) (Onwumere et al). Whereas, Belets Based on the level of technological advancements, three types Gebremich and Berhanu Gebremedhin reported that apiculture is of beehives (traditional, intermediate and frame hives) are used a promising off farm enterprise, directly and indirectly contributes for honey production in Ethiopia. Despite the long beekeeping to smallholders’ income in particular and nation’s economy tradition in Ethiopia, the highest bee density, being the leading in general. In addition, Takele Gina [1] reports indicated that honey producer and one of the largest beeswax exporting countries Ethiopia is one of the countries in the continent that has the largest in Africa, the share of the sub-sector to the Gross Domestic Product honeybee population and owns a big honey production potential (GDP) of the country has never been commensurate with the huge resources and the country’s potential for beekeeping. Productivity the largest and leading honey producer in Africa and tenth largest has always been low, leading to higher domestic hive products in its varied ecological and climatic zones. Specifically, Ethiopia is honey producer in the world. Unlike many other commodities utilization and relatively low export earnings. With this, even if such as crop and livestock, honey products generate multiple efforts are still on-going, most of the on-station based adaptive market opportunities, and are also nutritious foods. In addition, research works which were carried out for the last few decades the production process is not in competition with another form of couldn’t improve hive productivity and honey production so far. agriculture and it can be integrated positively (Aravindakshan et al) [2].The same to that, honey production is also considered as a vegetation, cultivated crops composition and considered as However, even if Jimma Horro District is believed to have diversified natural resource conserving and environmentally friendly activity beekeeping potential, a detailed and comprehensive research data [3] through its plant pollination services. Thus, it should be one of on honey production systems, challenges and opportunities in the Copyright@ Soresa Shuma | Biomed J Sci & Tech Res | BJSTR. MS.ID.004778. 22314 Volume 29- Issue 2 DOI: 10.26717/BJSTR.2020.29.004779 area is not available so far [5] .Therefore, this study was conducted farmers in particular and the country in general still could not to give an insight into the honey production potential constraints harvest honey to the required amount which in turn income from and opportunities in Jimma Horro District, Oromia region, Ethiopia. this sector to the producer, trader and the country is generally low in honey. In general, it believes that there are different honey Beekeeping by its nature doesn’t need huge investment production challenges which couldn’t enable the beekeepers to maximize beekeeping outputs. This work, therefore, had tried knowledge. Beekeeping strengths and supports the rural (financial asset), large size of land and complicated technical to magnify and suggest possible solutions against production community livelihoods to become less vulnerable to different shocks and avert risks. However, the individual poor beekeeping to product maximization in the study area [6]. constraints and identified some major challenges that are obstacles Materials and Methods Study Area Figure 1: Map of study Area The study was conducted from September 2018 to December 12500 donkeys, 7225 Horses 26650 sheep, 20166 goats and 98271 species of poultry. The farmers in the area practice mixed farming and Abono) of Jimma Horro district, Kellem Wollega Zone in (Figure 1). 2019 in three selected peasant associations (Tonfi Cari, Ilu Kitaye Western Ethiopia. This district is bounded by Begi district in North, Method of Data Collection Gawo Kebe district in East, Yamalogi Wolel district in South and Gidami district in West. The area is located at about 665km west Data essential to the study were collected from secondary of Addis Ababa. The area is located at an elevation of 1400-1830m observation. above sea level. The Topography of this district is characterized by sources, undertaking group discussions and formal survey and field Forest of Wolel Mountain and Dati Wolel Park. The main river in Secondary Data this district is Supe, Burar and Kumbabe. The climatic condition The secondary data necessary for the investigation were alternates with long summer rain fall (June to September), short collected from organizations and PA administrations. rainy season (March to May) and winter dry season (December to February). The minimum and maximum annual rain fall and Focus Group Discussions daily temperature range from 800 to 1200mm and 15 to 25oc, Focus group discussions were conducted in the study area with respectively. Jimma Horro district is characterized by Dega (19.7%), purposively selected community representatives such as: elders are Woyna dega (48.5%) and Kola (31.8%). Livestock population in having rich indigenous knowledge in beekeeping, PA leaders, DAs, area is estimated to be about 91671 heads of cattle, 300 mules, Copyright@ Soresa Shuma | Biomed J Sci & Tech Res | BJSTR. MS.ID.004779. 22315 Volume 29- Issue 2 DOI: 10.26717/BJSTR.2020.29.004779 bee experts and women representatives. In order to gain a greater had an average experience of 15.4 years ranges from 1 to 30 years insight into the topics during the formal survey and to validate (Table 1). or check the data collected. Each of the focus group discussion The level of beekeepers’ experience was taken to be the number consisted of 10 to 21 individuals and 3 group discussions were of years that an individual was continuously engaged in beekeeping. undertaken in the study area (one in each altitude zone). This is what one would expect in a situation where people are Formal Survey actively engaged starting from an early age in helping older beekeepers to undertake basic asks. Based on this exposure, young A formal survey was conducted using structured questionnaire, people gradually move on to become independent beekeepers as with open-ended and closed-ended questionnaires with the help soon as they obtain their own hives (Gichora, 2003). They continue of trained enumerators. Potential, challenges and opportunities accumulating experience by seeking technical advice from fellow of beekeeping in the area: harvesting time, dearth period and beekeepers whenever necessary. The mean age of the respondents amount of honey harvested, honey storage facilities, honey selling were (40years) ranging from 26 to 49years (Table 2). This result showed that beekeeping can be performed by economically active plants, water resources availability, honeybee pests and predators, situation, potential honeybee plants and flowering time, poisonous age groups and in most cases people at younger and old age is herbicides, insecticides and other chemicals applications have been actively engaged in beekeeping activities. Of the total households collected. interviewed, 93.8 % are married while 5%, 1.2% are single, Data Analysis divorced, respectively. With regard to religion, all of the household The statistical analysis used in the study varied depending on respondents 50.7, 27.1, 22.2) are Protestant, Orthodox and Muslim the type of variables and information required. Descriptive statistics respectively. Based on the results of this study, people regardless of such as means, standard deviation, frequency and percentages their marital status undertake beekeeping activities in the district was used to analyze the quantitative data using SPSS version 23 (Table 3).
Load more

Recommended publications
  • Districts of Ethiopia
    Region District or Woredas Zone Remarks Afar Region Argobba Special Woreda -- Independent district/woredas Afar Region Afambo Zone 1 (Awsi Rasu) Afar Region Asayita Zone 1 (Awsi Rasu) Afar Region Chifra Zone 1 (Awsi Rasu) Afar Region Dubti Zone 1 (Awsi Rasu) Afar Region Elidar Zone 1 (Awsi Rasu) Afar Region Kori Zone 1 (Awsi Rasu) Afar Region Mille Zone 1 (Awsi Rasu) Afar Region Abala Zone 2 (Kilbet Rasu) Afar Region Afdera Zone 2 (Kilbet Rasu) Afar Region Berhale Zone 2 (Kilbet Rasu) Afar Region Dallol Zone 2 (Kilbet Rasu) Afar Region Erebti Zone 2 (Kilbet Rasu) Afar Region Koneba Zone 2 (Kilbet Rasu) Afar Region Megale Zone 2 (Kilbet Rasu) Afar Region Amibara Zone 3 (Gabi Rasu) Afar Region Awash Fentale Zone 3 (Gabi Rasu) Afar Region Bure Mudaytu Zone 3 (Gabi Rasu) Afar Region Dulecha Zone 3 (Gabi Rasu) Afar Region Gewane Zone 3 (Gabi Rasu) Afar Region Aura Zone 4 (Fantena Rasu) Afar Region Ewa Zone 4 (Fantena Rasu) Afar Region Gulina Zone 4 (Fantena Rasu) Afar Region Teru Zone 4 (Fantena Rasu) Afar Region Yalo Zone 4 (Fantena Rasu) Afar Region Dalifage (formerly known as Artuma) Zone 5 (Hari Rasu) Afar Region Dewe Zone 5 (Hari Rasu) Afar Region Hadele Ele (formerly known as Fursi) Zone 5 (Hari Rasu) Afar Region Simurobi Gele'alo Zone 5 (Hari Rasu) Afar Region Telalak Zone 5 (Hari Rasu) Amhara Region Achefer -- Defunct district/woredas Amhara Region Angolalla Terana Asagirt -- Defunct district/woredas Amhara Region Artuma Fursina Jile -- Defunct district/woredas Amhara Region Banja -- Defunct district/woredas Amhara Region Belessa --
    [Show full text]
  • Administrative Region, Zone and Woreda Map of Oromia a M Tigray a Afar M H U Amhara a Uz N M
    35°0'0"E 40°0'0"E Administrative Region, Zone and Woreda Map of Oromia A m Tigray A Afar m h u Amhara a uz N m Dera u N u u G " / m r B u l t Dire Dawa " r a e 0 g G n Hareri 0 ' r u u Addis Ababa ' n i H a 0 Gambela m s Somali 0 ° b a K Oromia Ü a I ° o A Hidabu 0 u Wara o r a n SNNPR 0 h a b s o a 1 u r Abote r z 1 d Jarte a Jarso a b s a b i m J i i L i b K Jardega e r L S u G i g n o G A a e m e r b r a u / K e t m uyu D b e n i u l u o Abay B M G i Ginde e a r n L e o e D l o Chomen e M K Beret a a Abe r s Chinaksen B H e t h Yaya Abichuna Gne'a r a c Nejo Dongoro t u Kombolcha a o Gulele R W Gudetu Kondole b Jimma Genete ru J u Adda a a Boji Dirmeji a d o Jida Goro Gutu i Jarso t Gu J o Kembibit b a g B d e Berga l Kersa Bila Seyo e i l t S d D e a i l u u r b Gursum G i e M Haro Maya B b u B o Boji Chekorsa a l d Lalo Asabi g Jimma Rare Mida M Aleltu a D G e e i o u e u Kurfa Chele t r i r Mieso m s Kegn r Gobu Seyo Ifata A f o F a S Ayira Guliso e Tulo b u S e G j a e i S n Gawo Kebe h i a r a Bako F o d G a l e i r y E l i Ambo i Chiro Zuria r Wayu e e e i l d Gaji Tibe d lm a a s Diga e Toke n Jimma Horo Zuria s e Dale Wabera n a w Tuka B Haru h e N Gimbichu t Kutaye e Yubdo W B Chwaka C a Goba Koricha a Leka a Gidami Boneya Boshe D M A Dale Sadi l Gemechis J I e Sayo Nole Dulecha lu k Nole Kaba i Tikur Alem o l D Lalo Kile Wama Hagalo o b r Yama Logi Welel Akaki a a a Enchini i Dawo ' b Meko n Gena e U Anchar a Midega Tola h a G Dabo a t t M Babile o Jimma Nunu c W e H l d m i K S i s a Kersana o f Hana Arjo D n Becho A o t
    [Show full text]
  • Ethiopia: Administrative Map (August 2017)
    Ethiopia: Administrative map (August 2017) ERITREA National capital P Erob Tahtay Adiyabo Regional capital Gulomekeda Laelay Adiyabo Mereb Leke Ahferom Red Sea Humera Adigrat ! ! Dalul ! Adwa Ganta Afeshum Aksum Saesie Tsaedaemba Shire Indasilase ! Zonal Capital ! North West TigrayTahtay KoraroTahtay Maychew Eastern Tigray Kafta Humera Laelay Maychew Werei Leke TIGRAY Asgede Tsimbila Central Tigray Hawzen Medebay Zana Koneba Naeder Adet Berahile Region boundary Atsbi Wenberta Western Tigray Kelete Awelallo Welkait Kola Temben Tselemti Degua Temben Mekele Zone boundary Tanqua Abergele P Zone 2 (Kilbet Rasu) Tsegede Tselemt Mekele Town Special Enderta Afdera Addi Arekay South East Ab Ala Tsegede Mirab Armacho Beyeda Woreda boundary Debark Erebti SUDAN Hintalo Wejirat Saharti Samre Tach Armacho Abergele Sanja ! Dabat Janamora Megale Bidu Alaje Sahla Addis Ababa Ziquala Maychew ! Wegera Metema Lay Armacho Wag Himra Endamehoni Raya Azebo North Gondar Gonder ! Sekota Teru Afar Chilga Southern Tigray Gonder City Adm. Yalo East Belesa Ofla West Belesa Kurri Dehana Dembia Gonder Zuria Alamata Gaz Gibla Zone 4 (Fantana Rasu ) Elidar Amhara Gelegu Quara ! Takusa Ebenat Gulina Bugna Awra Libo Kemkem Kobo Gidan Lasta Benishangul Gumuz North Wello AFAR Alfa Zone 1(Awsi Rasu) Debre Tabor Ewa ! Fogera Farta Lay Gayint Semera Meket Guba Lafto DPubti DJIBOUTI Jawi South Gondar Dire Dawa Semen Achefer East Esite Chifra Bahir Dar Wadla Delanta Habru Asayita P Tach Gayint ! Bahir Dar City Adm. Aysaita Guba AMHARA Dera Ambasel Debub Achefer Bahirdar Zuria Dawunt Worebabu Gambela Dangura West Esite Gulf of Aden Mecha Adaa'r Mile Pawe Special Simada Thehulederie Kutaber Dangila Yilmana Densa Afambo Mekdela Tenta Awi Dessie Bati Hulet Ej Enese ! Hareri Sayint Dessie City Adm.
    [Show full text]
  • Benishangul-Gumuz Region
    Situation Analysis of Children and Women: Benishangul-Gumuz Region Situation Analysis of Children and Women: Benishangul-Gumuz Region ABSTRACT The Situation Analysis covers selected dimensions of child well-being in Benishangul-Gumuz Regional State. It builds on the national Situation Analysis of Children and Women in Ethiopia (2019) and on other existing research, with inputs from specialists in Government, UNICEF Ethiopia and other partners. It has an estimated population of approximately 1.1 million people, which constitutes 1.1% of the total Ethiopian population. The population is young: 13 per cent is under-five years of age and 44 per cent is under 18 years of age. Since 1999/00, Benishangul-Gumuz has experienced an impressive 28 percentage point decline in monetary poverty, but 27 per cent of the population are still poor; the second highest in the country after Tigray and higher than the national average of 24 per cent. SITUATION ANALYSIS OF CHILDREN AND WOMEN: BENISHANGUL-GUMUZ REGION 4 Food poverty continued a steep decline from 55 per cent in 1999/00 to 24 per cent in 2015/16; close to the national average of 25 per cent. In Benishangul-Gumuz, in 2014, only 1.1 per cent of rural households were in the PSNP compared to 11 per cent of households at the national level In 2011, the under-five mortality rate in Benishangul-Gumuz was the highest in Ethiopia (169 per 1,000 live births); this declined significantly, but is still very high: 96 deaths per 1,000 births, which is the second highest in the country after Afar.
    [Show full text]
  • Benishangul-Gumuz Region
    Situation Analysis of Children and Women: Benishangul-Gumuz Region Situation Analysis of Children and Women: Benishangul-Gumuz Region ABSTRACT The Situation Analysis covers selected dimensions of child well-being in Benishangul-Gumuz Regional State. It builds on the national Situation Analysis of Children and Women in Ethiopia (2019) and on other existing research, with inputs from specialists in Government, UNICEF Ethiopia and other partners. It has an estimated population of approximately 1.1 million people, which constitutes 1.1% of the total Ethiopian population. The population is young: 13 per cent is under-five years of age and 44 per cent is under 18 years of age. Since 1999/00, Benishangul-Gumuz has experienced an impressive 28 percentage point decline in monetary poverty, but 27 per cent of the population are still poor; the second highest in the country after Tigray and higher than the national average of 24 per cent. SITUATION ANALYSIS OF CHILDREN AND WOMEN: BENISHANGUL-GUMUZ REGION 4 Food poverty continued a steep decline from 55 per cent in 1999/00 to 24 per cent in 2015/16; close to the national average of 25 per cent. In Benishangul-Gumuz, in 2014, only 1.1 per cent of rural households were in the PSNP compared to 11 per cent of households at the national level In 2011, the under-five mortality rate in Benishangul-Gumuz was the highest in Ethiopia (169 per 1,000 live births); this declined significantly, but is still very high: 96 deaths per 1,000 births, which is the second highest in the country after Afar.
    [Show full text]
  • Oromiya 4 Zone Code Wereda Code Town Code West
    REGION - OROMIYA 4 ZONE CODE WEREDA CODE TOWN CODE WEST WELEGA 01 MENE SIBU 01 MENDI 1 NEJO 02 NEJO 1 WERE JIRU 2 GORI 3 GIMBI 03 HOMA 1 LALO ASABI 04 ENANGO 1 DENIGORO 2 KILTU KARA 05 KILTU KARA 1 BOJI DIRMEJ 06 BILA 2 AYIRA GULISO 07 GULISO 1 AYIRA 2 JARSO 08 GEBA DEFINO 1 KONDALA 09 GEBA DEFNO 1 BOJI CHEKORSA 10 CHEKORSA 1 BABO GAMBEL 11 DEBEKA 1 YUBDO 12 YUBDO 1 GENJI 13 GENJI 1 HARU 14 GUYU 1 NOLE KABA 15 BUBE 1 BEGI 16 BEGI 1 KOBER 2 GIMBI /TOWN/ 17 GIMBE 1 SEYO NOLE 18 DEBESO 1 EAST WELEGA 02 LIMU 01 GELILA 1 IBANTU 02 HINDE 1 GIDA KIREMU 03 GIDA AYANA 1 KIREMU 2 GUTEN 3 HORO LIMU 04 BONIYA BUSHE 05 BILO 1 WAYU TUKA 06 GEBA JIMATA 1 GUDEYA BILA 07 JERE 1 BILA 2 GOBU SEYO 08 ANO 1 OROMIYA (Cont'd) ZONE CODE WEREDA CODE TOWN CODE EAST WELEGA 02 SIBU SIRE 09 SIRE 1 DIGA 10 ARJO GUDETU 1 IFA 2 SASIGA 11 GALO 1 LEKA DULECHA 12 GETEMA 1 GUTO GIDA 13 DIGA 1 JIMA ARJO 14 ARJO 1 NUNU KUMBA 15 NUNU 1 WAMA HAGELO 16 NEKEMTE /TOWN/ 17 NEKEMTE 1 ILU ABA BORA 03 DARIMU 01 DUPA 1 ALGE SACHI 02 ALGE 1 SUPE 2 CHORA 03 KUMBABE 1 DEGA 04 DEGA 1 DABO HANA 05 KONE 1 GECHI 06 GECHI 1 BORECHA 07 YANFU 1 DEDESA 08 DENBI 1 YAYU 09 YAYU 1 METU ZURIYA 10 ALE 11 GORE 1 BURE 12 BURE 01 1 SIBU 2 NONO SELE 13 BIRBIRSA 1 OROMIYA (Cont'd) ZONE CODE WEREDA CODE TOWN CODE ILU ABA BORA 03 BICHO 14 BICHO 1 BILO NOPHA 15 NOPA 1 HURUMU 16 HURUMU 1 DIDU 17 LALO 1 MAKO 18 MAKO 1 HUKA /HALU/ 19 HUKA 01 1 METU TOWN 20 METU 1 BEDELE TOWN 21 BEDELE 1 BEDELE ZURIYA 22 - 1 CHEWAKA 23 ILU HARERE 1 DORENI 24 JIMA 04 LIMU SEKA 01 ANTAGO 1 LIMU KOSA 02 LIMU GENET 1 AMBUYE 2 BABU
    [Show full text]
  • FAO Quarterly Early Warning Bulletin for Food and Agriculture No
    No. 17 October-December 2015 Quarterly Early Warning Bulletin for Food and Agriculture El Niño and Rainfall Source: International Research Institute for Climate and Society Alerts on threats to the food chain and food security in countries and regions FAO Quarterly Early Warning Bulletin for Food and Agriculture No. 17 October-December 2015 The Quarterly Early Warning Bulletin for Food and Agriculture integrates information on food security and threats to the food chain for the three months ahead. It is a product of collaboration between the Emergency Prevention System (EMPRES) for transboundary animal and plant pests and diseases and food safety threats, the Global Information and Early Warning System (GIEWS), and the Intelligence and Coordination Unit of the Food Chain Crisis Management Framework (FCC). Data is provided by GIEWS and EMPRES. Highlights Threats to the food chain1 and food security: Animal and aquatic diseases: o With the upcoming winter, the forecast for Avian Influenza is as follows: − In West Africa, the risk of further spread of Avian Influenza (H5N1 Highly Pathogenic Avian Influenza) to Burkina Faso, Côte d’Ivoire, Ghana, Niger and Nigeria in poultry is persisting. To date no reported cases of human samples tested. − In Southeast Asia and China, a high risk of occurrence of Avian Influenza (H5N1, H7N9, H5N2, H5N3, H5N6, and H5N8) outbreaks is expected with potential spread within endemic countries and to free areas. o The risk of re-occurrence and spread of a vector borne disease - Rift Valley fever (RVF) - is amplified in Eastern Africa with El Niño conditions. Strong persistent El Niño conditions are associated with periods of widespread and prolonged heavy rainfall creating ideal environmental and ecological conditions for the emergence of RVF vectors.
    [Show full text]
  • Ethiopia Census 2007
    Table 1 : POPULATION SIZE OF REGIONS BY SEX AND PLACE OF RESIDENCE: 2007 Urban + Rural Urban Rural Sex No. % No. % No. % COUNTRY TOTAL * Both Sexes 73,918,505 100.00 11,956,170 100.00 61,962,335 100.00 Male 37,296,657 50.46 5,942,170 49.70 31,354,487 50.60 Female 36,621,848 49.54 6,014,000 50.30 30,607,848 49.40 TIGRAY Region Both Sexes 4,314,456 100.00 842,723 100.00 3,471,733 100.00 Male 2,124,853 49.25 398,072 47.24 1,726,781 49.74 Female 2,189,603 50.75 444,651 52.76 1,744,952 50.26 AFFAR Region * Both Sexes 1,411,092 100.00 188,973 100.00 1,222,119 100.00 Male 786,338 55.73 100,915 53.40 685,423 56.08 Female 624,754 44.27 88,058 46.60 536,696 43.92 AMHARA Region Both Sexes 17,214,056 100.00 2,112,220 100.00 15,101,836 100.00 Male 8,636,875 50.17 1,024,136 48.49 7,612,739 50.41 Female 8,577,181 49.83 1,088,084 51.51 7,489,097 49.59 ORORMIYA Region Both Sexes 27,158,471 100.00 3,370,040 100.00 23,788,431 100.00 Male 13,676,159 50.36 1,705,316 50.60 11,970,843 50.32 Female 13,482,312 49.64 1,664,724 49.40 11,817,588 49.68 SOMALI Region * Both Sexes 4,439,147 100.00 621,210 100.00 3,817,937 100.00 Male 2,468,784 55.61 339,343 54.63 2,129,441 55.77 Female 1,970,363 44.39 281,867 45.37 1,688,496 44.23 BENISHANGUL-GUMUZ Region Both Sexes 670,847 100.00 97,965 100.00 572,882 100.00 Male 340,378 50.74 49,784 50.82 290,594 50.72 Female 330,469 49.26 48,181 49.18 282,288 49.28 SNNP Region Both Sexes 15,042,531 100.00 1,545,710 100.00 13,496,821 100.00 Male 7,482,051 49.74 797,796 51.61 6,684,255 49.52 Female 7,560,480 50.26 747,914 48.39 6,812,566
    [Show full text]
  • National Wash Program Selected Woredas and Small Towns
    National WaSH Program Selected Woredas and Small Towns 1. Oromiya Region No Oromiya Woredas No Oromiya Woredas 41 Dugda 83 Ana Sora No Oromiya Woredas 42 Liban Chukala 84 Seba Boru 1 Digalu Tijo 43 Lume 85 Uraga 2 Gololcha 44 Bora 86 Odo Shakkiso 3 Jeju 45 Gudeya Bila 87 Liban 4 Limu Bilbilo 46 Guto Gida 88 Fentale 5 Tiyo 47 Sasiga 89 Babile 6 Zuway Dugda 48 Sibu Sire 90 Chinaksen 7 Adaba 49 Wayu Tuka 91 Qumbi 8 Gedeb Asasa 50 Seyo Nole 92 Guba Korcha 9 Agarfa 51 Nedjo 93 Chiro 10 Dawe Serer 52 Haru 94 Chewaka 11 Dinsho 53 Dale Sedi 95 Hurum 12 Gindhir 54 Dale Wabera 96 Darimu 13 Goro 55 Gawo Kebe 97 Dedo 14 Rayitu 56 Lalo Kile 98 Sokoru 15 Sinana 57 Seyo 99 Seka Chokorsa 16 Bedeno 58 Yubdo 100 Limu Seka 17 Gorogutu 59 Ayira 101 Ilu 18 Girawa 60 Guliso 102 Sodo Dachi 19 Kurfa Chale 61 Sude 103 Weliso 20 Kombolcha 62 Doddota 104 Ameya 21 Haromaya 63 Inkolo Wabe 105 Seden Soddo 22 Kersa 64 Robe 106 Nonno 23 Fedis 65 Lege Hidha 107 Dera 24 Boke 66 Sewena 108 Girar Jarso 25 Darulabu 67 G/Dhamole 109 Yaya Gulele 26 Doba 68 Siraro 110 Kuyu 27 Oda Bultum 69 Arsi Negele 111 Wuchale 28 Tulo 70 Kofele 112 Sululta 29 Hawi Gudina 71 Shashemene 113 Mulo 30 Burqa Dimtu 72 Kokosa 114 Sebeta Hawas 31 Becho 73 Akaki 115 Wolmera 32 Bedele 74 Teltale 116 Berek 33 Bilo Nopha 75 Dhas 117 Dendi 34 Didu 76 Yabello 118 Meta Robi 35 Metu 77 Arero 119 Abuna Ginde Beret 36 Yayu 78 Bule Hora 120 Ambo 37 Dorani 79 Gelana 121 Ilu Gelan 38 Adea 80 Moyale 122 Jibat 39 Adama 81 Hambela Wamana 123 Mida Kegn 40 AT/Jido Kombolcha 82 Kercha 124 Toke Kutaye National WaSH
    [Show full text]
  • Prioritization of Shelter/NFI Needs End of September 2017
    Prioritization of shelter/NFI needs End of September 2017 Life-saving nature of shelter/NFI assistance Shelter is a basic human need and a critical determinant for survival and coping in the majority of crises. Beyond survival, shelter and core relief items are necessary to provide security and ensure personal safety and protection, and to promote resistance to ill-health and disease. ` Response activities As of 30 September 2017: 60,492 full emergency shelter & NFI kits distributed to displaced households in 6 regions, additionally to cash grants and vouchers to 982 households. 900 supplementary kits presently being distributed or already funded and procured for distributions. 22,600 kits in stock & pipe-line. TOTAL = 84,974 full kits or equivalent in cash and vouchers Outstanding needs The DTM round 6 figures collected in 7 regions, the 2017 Belg assessments conducted in 4 regions, requests received from the authorities notably for the needs induced by the conflict along the border between Oromia and Somali regions, the needs induced by the 2017 kiremt season as shared by the flood task force and assessments conducted by cluster members revealed that the total of households in need of shelter/NFI assistance is 231,240 HHs. Prioritization criteria As agreed upon among cluster members on 31 of August 2017, Shelter/NFI assistance for people who are currently in need of assistance will primarily be directed to: Newly displaced in 2017, IDPs who have not had access to shelter/NFI assistance, durable solutions or coping mechanisms and
    [Show full text]
  • Summary and Statistical Report of the 2007 Population and Housing Census Results
    Summary and Statistical Report of the 2007 Population and Housing Census Results Summary and Statistical Report of the 2007 Population and Housing Census Results 1 2 Summary and Statistical Report of the 2007 Population and Housing Census Results This document was printed by United Nations Population Fund(UNFPA) Summary and Statistical Report of the 2007 Population and Housing Census Results Summary and Statistical Report of the 2007 Population and Housing Census Results 3 Acknowledgements The third Population and Housing Census of Ethiopia was conducted in May and Novem- ber 2007. In accordance with the Census Commission Re-establishment Proclamation, the House of Peoples Representatives endorsed, on 4 December 2008, the census findings as organized by age, sex, religion, ethnicity, region and urban and rural residence. This sum- mary report contains an extract of the census data from this first release and the remaining census results will be disseminated subsequently. The Population and Housing Census which is a huge, complex and costly statistical opera- tion has been successfully completed through the concerted efforts of different government and non-government organizations, development partners, and individuals. The Office of the Census Commission and the Central Statistical Agency would, therefore, like to thank all who have contributed to the successful completion of the census. The Office of the Census Commission is very grateful to the Government of Ethiopia for its huge financial and administrative support. The Office is grateful to development partners particularly the United Nations Population Fund (UNFPA) and the Department for International Development (DfID) for their generous financial, logistics and technical support.
    [Show full text]
  • Prevalence of Bovine Trypanosomosis and Associated Risk Factor in Jimma Horro District, Kellem Wollega Zone, Western Ethiopia
    Vol. 10(8), pp. 185-191, August 2018 DOI: 10.5897/JVMAH2018.0695 Article Number: 17C59BF57840 ISSN: 2141-2529 Copyright ©2018 Journal of Veterinary Medicine and Animal Author(s) retain the copyright of this article http://www.academicjournals.org/JVMAH Health Full Length Research Paper Prevalence of bovine trypanosomosis and associated risk factor in Jimma Horro District, Kellem Wollega Zone, Western Ethiopia Dereje Tulu1*, Surra Gebeyehu2, Negash Aseffa2 and Chaluma Negera3 1Ethiopian Institute of Agricultural Research, Tepi Agricultural Research Center, P. O. Box 34,Tepi, Ethiopia. 2Kelem Wollega Zone Livestock Development and Fishery Office, Dembi Dolo, Ethiopia. 3Southwest Shoa Zone Livestock Development and Fishery Office, Woliso, Ethiopia. Received 4 June, 2018: Accepted 19 June, 2018 Trypanosomosis is a serious disease that causes a significant production loss in cattle. A cross sectional study was conducted in Jimma Horro District of Kellem Wollega Zone, Western Ethiopia to determine prevalence and associated risk factors of bovine trypanosomosis from October 2016 to October 2017. Blood samples from randomly selected 384 cattle of both sex and different age group were collected and examined with parasitological techniques. The overall prevalence of bovine trypanosomosis was 3.7% (14/384) in the study areas. The infection was highest due to Trypanosome congolense (50%) followed by Trypanosome vivax (28.6%) and Trypanosoma brucei (21.4%). Multivariable logistic regression analysis identified body condition as risk factors (P<0.05) for trypanosomosis in the district. However, there were no statistically significant difference observed among age groups, sex, skin color and different peasant associations (P> 0.05). The overall mean Packed Cell Volume (PCV) value was statistically significant difference between aparasitaemic and parasitaemic cattle (P< 0.05).The study showed that bovine trypanosomosis is one of the constraints to cattle production in Jimma Horro District.
    [Show full text]