Analysis of the Economy of Beekeeping and Honey Supply in Horo Guduru Wollega Zone, Oromia, Ethiopia

The study focused analyzing the determinants of honey supply, to analyze the economy of beekeeping, honey marketing and income generating activities undertaken in Horo Guduru wollega zone of Oromia Region, Ethipia. About 121 honey producers (110 male & 11 female) were selected randomly from a list of 536 honey producers found in 5 purposively selected ‘kebeles’. The data were generated by individual interview and group discussions using pre-tested semi structured questionnaires and checklists. Secondary data were collected from different published and unpublished sources. The data collected were analyzed with the help of descriptive statistics and econometric model (multiple linear regression model). The results obtained from econometric analysis indicates that colony size, type of beehives used, beekeeping equipment, market information, current honey price, frequency of extension contact per year and trainings were positively and significantly affected honey supply. Of course, some opportunities have also been indicated like availability of bee colony, favorable environment, and annual flora and farmers’ experiences. To boost the economy of beekeeping and honey marketing which in turn increase producers income from honey supply, all concerned bodies need to focus on building farmers capacity via training on improving honey production and supply, increasing access to improved beehives and its accessories, availing extension facilities, improving road facility, organizing honey producers to increase the volume, access to marketing and price setting, and establishing honey market center are recommended for policy intervention.


INTRODUCTION
Beekeeping competitive advantage for on-farm integration is attributed to the low start-up costs, labor requirements, land, technology and reliance on traditional knowledge and skills. It provides complementary services to other on-farm enterprises like crop pollination. It has significant role in generating and diversifying income of subsistent smallholder farmers mainly the small land holders and landless, among marginalized and small income earners such as women, orphans and other vulnerable groups within the society (Tolera, 2014). Oromia region contributes 46% and 54.8% of the national honey production and of the hive number respectively. The honey sector is one of the few sectors that had the most inclusive ability to achieve transformation and growth across all categories of rural households. The situation is similar in Horro Gudruu wollega zone which contributes 2.3% of the Oromia honey production (Central Statistical Agency, 2013) Horro Guduru Wollega zone is one of the 20 administrative zones found in Oromia and comprising 12 districts. Guduru district considered in this assessment is grouped under high potential for beekeeping development and covered with natural vegetation, shrubs, annual and perennial crops. Moreover, it has adequate water resources and large bee colonies, which create conducive environment for honey production (CSA, 2017). Thus, honey production and marketing has the role and contribution to ensuring food security and nutrition, poverty reduction, income diversification, and ecosystem safeguarding and it is believed that can improve living standards of the smallholder farmers. Yet, honey marketing remains low among the farmers. The determinants of honey supply has not yet been studied and analyzed for the target study area, where great potential of its production exists. Therefore, this study will be conducted to identify factors affecting honey supply in Guduru district, Horro Guduru Wollegga zone.

Statement of the problem:
Honey production and marketing in Ethiopia is reliable revenue generating activity and traditionally practiced both by farmers and landless rural smallholders.

Description of the Study Area
This study will be under taken in Horoguduru Wollega Zone; it is one of the Zones found in West Oromia. Today this Zone is sub-divided in to 12 District for its administrative purpose.
Shambu is the capital town of this zone located about 314 km away from the capital town of Oromia called Finfinne. Horo Guduru Wollega zone is bounded by Amahara National Regional state in the North, west shoaw zone in the East, in the West East wollega, in the South West shoaw and West Wellega zone. Based on figures from the Central Statistical Agency (CSA) in 2007, the total population of Horoguduru Wollega zone is projected to be 576,567 of which 65,063 was urban population and 511,504 was rural population in 2007. According Regional Statistics and information from Agricultural office, the total area of the zone is 7867.6 km2. The areas of the districts vary from study to study. However, the following table shows us the areas of each district.
Source: (GRLALUO, 2020) 3.2 Study population: Based on the census carried out recently the total population of the district is estimated to 113,123 (55,433 male and 57,690 Female). The total number of the rural population is 78,664 (38,548 male and 40,116 female). The total number of urban population is 34,459 (16,885 male and 17,574 Female). The total number of rural household head is 10,033 (9,473 male and 560 female) (GDANRO, 2019)

Sampling Design:
A cross-sectional survey was adopted for conducting the study. The information were collected at one shot and then organized and analyzed. To increase the reliability of the study, identification and selection of sampling kebeles, where beekeeping activities are practicing, were carried out by employing purposive sampling method.
In the district, currently there are 25 kebeles (20 rural and 5 urban). For the study a two stage sampling procedure was employed to select a specific honey producer household. First, purposive sampling was employed to identify kebeles in which more beekeeping activity is undertaken. Based upon their beekeeping potential and number of involved farmers, socioeconomic homogeneity of the community, researcher's operational area and some factors like financial resources and time, the researcher fixed the number of sample kebeles to be 5. These are: Dilalo Baro, Gamane Gudane, Gudane Kobo, Gobbu and Yeron Ama Tole. Among selected 5 kebeles, the smallholder farmers of honey producers were selected purposively. According to (Storck et al., 1991), cited by (Chali, 2018), the size of the sample depends on the available fund, time and other reasons and not necessarily on the total population. In the second stage, using the population list of honey producer farmers from sample kebeles, the intended sample size was determined proportionally to population size of honey producer farmers. So, by using a simple random sampling a total of 121 sample household head of honey producers were selected.

Sample Size Determination:
The study was used the following formula to calculate sample size. This study applied a simplified formula provided by (Yamane, 1967), cited by (Kassa et al, 2017) to determine the required sample size at 95% confidence level degree of variability = 0.5 and level of precision = 8% (0.08) Where; n =designates the sample size the research uses; N= designates total number of households e =designates maximum variability or margin of error 8 % 1=designates the probability of the event occurring.
The following steps were used to determine sample size derived from the above formula to collect quantitative data using questionnaire. n = ____N__ 1+N (e) 2 Therefore; n= 536 1+536 0.08 2 = 121 Therefore, the total sample size was 121 out of this: 27 from Gamane Gudane, 25 from Yeron Ama Tole, 21 from Dilalo Baro, 24 from Gobbu and 32 from Gudane Kobo kebeles proportionally to population size as shown on the following Table 1. 3.5 Method of Data Collection: Both primary and secondary data were used for this study which is qualitative and quantitative in nature. Primary data were collected from sample households using semi-structured questionnaire and checklist. The data were collected by enumerators (DAs) and the researchers. The enumerators (DAs) were trained on how to conduct the interview schedule and how to approach farmers during the interview. So as to revise and modify the questionnaire for the final survey, a pre-test of the interview schedule was conducted on selected respondents who are assumed to be representative of the households living in the sample Kebeles. Based on the feedback obtained from the pre-test, the interview schedule was customized. In addition to this, Focus Group Discussion and key informant interview were employed to supplement the research finding with qualitative information. Secondary data were gathered from various sources such as records, documents, reports etc. of both governmental and non-governmental organizations such as Guduru district office of livestock and fish, Gurmuu Development Association, Agricultural and Natural Resource Offices, rural land administration & land use office and others office.

Method of Data Analysis
Data Processing: Quantitative data entry was started after all actual data compilation and summary were carefully organized and manual editing was completed. Filled questionnaires were coded and keyed into STATA software of version 14.2. Once the process of data entry was accomplished, polishing and cleaning of the data were started. Data cleaning and editing focuses on checking whether the assigned value for each case is legitimate, on the logical consistency and structure of cases.
Descriptive Statistics: Descriptive statistics such as mean, minimum, & maximum values or scores, percentage, standard deviations and frequency was used along with econometric model to analyze the determinants of honey supply by smallholder farmers. Primary data that were collected through focus group discussions and key informant interviews was analyzed using qualitative technique of data analysis. Identification and then ranking was used for incomegenerating activities practiced by smallholder farmers, opportunity and challenges intended for honey production and honey supply in the study area. On the other hand, data collected through interview were analyzed through narration and interpretation.
Econometric Analysis: Different models can be employed to analyze the determinants of market supply. The commonly used ones are Multiple Linear Regression, Tobit and Heckman's sample selection models. If participation of all beekeepers in marketing of the honey is not expected, using OLS model by excluding non-participants from the analysis introduces selectivity bias to the model. Tobit, Double Hurdle and Heckman two stage procedures have been suggested to overcome such problems. If only probability of selling is to be analyzed, probit and logit models can adequately address the issue. If some households may not prefer to participate in a particular market in favor of another, while others may be excluded by market conditions Tobit or Heckman models are used to analyze market supply. By using Tobit model, the market supply can be analyzed by clustering the respondents' into supplier and non-suppliers.
If censored regression is applied, the model estimates are biased because of there is no clustering honey producers as all of households supply their product to market (Wooldridge, 2010).
Like Tobit model, sample selection model (Heckman) is used in some cases when sample selection biased occurred in addition to clustering of respondents. The first stage of the Heckman model a 'participation equation', used to construct a selectivity term known as the 'inverse Mills ratio' which is added to the second stage 'outcome' equation that explains factors affecting volume of product marketed and estimated by using ordinary least square (Wooldridge, 2010).
However, in the study area all honey producers participate in the market by supplying their produce and therefore there is no clustering of honey producers in honey market participant and non-participant. Thus, for this study, multiple linear regression model and its estimation using ordinary least squares (OLS) was used to identify determinants of honey supply.

Econometrics Model Specification
The econometric model specification of the variables is as follows. Y = f (Age, Gender, Family size, education, Farm Land size, Colony size, types of beehives, beekeeping equipment, non-bee farm income, credit, Market information, honey price, Frequency of extension contact per year, training, etc.) (1) Econometric model specification of supply function in matrix notation is the following.

Y =βX+U (2)
Where Yi = honey supplied to the market β = a vector of estimated coefficient of the explanatory variables X= a vector of explanatory variables Ui = disturbance term

Variables Specification and Working Hypotheses
Hypotheses o H0 = There is no statistically significance on honey supply by smallholder farmers due to personal attributes, socio-economic factors and institutional factors.
o HA = There is statistically significance on honey supply by smallholder farmers due to personal attributes, socio-economic factors and institutional factors.

Dependent Variable:
The main objective of this research is to analyze the determinants of honey supply by smallholder farmers. Honey is produced mainly for market and is one of the most beekeeping product and cash commodities for in the study area. For this, the honey marketed or supplied is dependent variable and it is continuous variable measured in Kg.

RESULTS AND DISSCUSSIONS
This section presents the results of descriptive and econometric analysis. The descriptive analysis describes the general characteristics of the sampled beekeepers, income-generating activities undertaken, opportunity and challenges on honey production and market supply. The econometric analysis is used to identify factors that affect supply of honey in Guduru district

Socio-economic Characteristics of the respondent
Land Size of the respondents: In agriculture, landholding size plays a significant role in the rural farmers' household livelihood situation. Respondent beekeepers in the study area have access and use of land for their various agricultural activities; they have land for crop farming, livestock keeping and beekeeping activities as well (Chali, 2018). The average land holding of the respondents is 2.9 hectares, whereas the minimum and maximum land holding size of the respondents are 0.25 and 8.53 hectares respectively with standard deviation of 1.59 refer to table 3 below. survey showed that, the most common bee hive used by smallholder beekeepers was traditional hives (85%), the second one was KTB (4%) and framed hive ranked third (1%) as per shown on the following Figure 5. The source of traditional and transitional bee hives of the respondents was from own construction. They are very familiar with how to construct different types of traditional and transitional bee hives from locally available materials. This result is consistent with the result reported by (Chali, 2018) that found that, the main areas of indigenous beekeeping knowledge are hive construction from locally available materials, swarm catching; hive fumigation and plastering. It was found that all Framed (improved box) beehives were prepared in private small and micro enterprise manufacturing centers found in the area. At the time of survey, the price of one framed (improved box) beehives was Birr 1,800.00. But others accessories mentioned above are not found in the study area.

Marketing of Honey in the area
Share of honey for sell and home consumption: According to the study result shown on the figure 6 below, sampled beekeepers were taking the majority of their product to the market 26,205.45kg (95%); they only used a small amount of honey for home consumption 1,363.6 (5%), mainly during the holiday and for their cultural ceremony, medicinal purposes, as food and gifts for relatives from the total production of 27,569.05kg (20,724.05kg crude & 6,845.00kg pure honey of 2018/2019). It is nearly similar with (Tizazuet al, 2017) study result revealed, that of 96.7% the total production of honey by sample respondents was marketed. According to (Mulubrihan, 2014) also, the beekeepers were taking the majority of their product to the market; they only used a small amount of honey for home consumption, mainly during the holiday and for their cultural ceremony.   The result of this study indicates that, the majority of buyers determine the price of the honey depending on the quality of beekeepers honey. The honey with white color and purified (semiprocessed) honey by local materials has got a higher price than the red color and crude honey in the area respectively. As shown on the table 12 below, the average selling price of sample respondents were 48.38 ETB and 142.86ETB for crude and pure honey respectively. The minimum and the maximum selling price were 38 and 80 ETB for crude honey respectively. And  This is also might be the same case with the reason for trends of honey yield increment that is due to favorable weather condition, increment of beekeeping participants, introduction of improved (KTB & Modern) bee hives, a slight improvement of extension serves, the demand for the honey is raised throughout the country and out of the country and newly starting initiation honey producers on honey purification and providing for consumers of local and town in the study area. The rise of demand for the honey in turn raises the price of honey in the district. The availability of different non-governmental organizations that support beekeepers in different aspects like product quality and handling improvements in the study area was another cause for the increment honey prices.

Access to Services
Access to different services could be essential to improve production and productivity of smallholder's farmers. More specifically, access to credit, training, extension contact and market information, are the most important factors that promote production and marketing of honey and thereby increase income of the producer are displayed below in table 13.   Access to market information: With regard to access to the market information, 45.5 % (f=55) of the sampled respondents had access to the nearby market price information as table able 13.
The survey result presented in table 12 also shows that, 54.5% (f=66) honey producers were limited to some source of market information. Accordingly, 45.5% of the total sampled households respond that, they obtain price information from NGOs (Gurmuu Development Association), extension agent and personal observation on market.

Results of Econometric Analysis
The econometric analysis was planned to analyze factors affecting volume of honey supply to market in the area.

Determinants of Honey Market Supply:
Fourteen explanatory variables were hypothesized to determine the household level marketable supply of honey. Among the hypothesized seven variables were found to be significantly  0.452 Note: "***", "**" shows the significance level of variables at 1%, and 5% respectively. Dependent variable is volume of honey marketed (in natural logarithm).

Source: Own computation from survey result, 2020
Total number of honeybee colonies (COLONYSIZ): It is proxy variable for quantity of honey produced and positively influence the volume of honey supplied to market at 1 percent significance level. This indicates that producer with more number of beehives with bee colony can harvest more volume of honey and not only having of better market surplus but will able to sell more. The model result indicated that as the number of hives with bee colony used increased by one, the volume of honey marketed increased by 58.67 percent. It is confirmed that the use of large number of hives directly related with the amount supplied to the market and return earned by beekeeper (Kerealem et al, 2009). This result is also in line with finding of (Tizazu et al, 2017;Getachew, 2009& Kassaa et al, 2017.

Types of beehives (HIVETYP):
As it was expected improved hive use is positively related with quantity supply of honey and the coefficient is statistically significant at 1 percent significance level. The model result shows that using both improved (Transitional and Framed hive) and traditional beehives affected quantity of honey supplied significantly and positively. Keeping a unit increase in improved hive leads to increase in quantity supplied of honey by 44.68 percent.
The possible reason for this result is the use of improved hive is directly related with the amount of honey produced, supplied to the market and return earned by beekeepers. Improved beehives allow honey bee colony management and use of a higher-level technology with larger colonies and can give higher yield and quality of honey thus in turn increase market supply. This result is also coincides with finding of (Zegeye, 2018& Kassaa et al, 2017 Case of Damot Gale district of Wolaita Zone and Chena district of Kaffa zone in Southern Ethiopia respectively.

Equipment Beekeeping (EQPMNT):
It was expected that possessing beekeeping equipment (accessories) affect quantity of honey produced and positively influence the volume of honey supplied to market at 5 percent significance level. This indicates that producer with beekeeping accessories can harvest more volume of honey and abled to supply more honey to the market by 23.99 percent. This is in line with (Chali, 2018), who found that, the positively relationships between access to beekeeping accessories and honey production, which in turn with the quantity of honey supply to the market.

Access to market information (MARKTIFO) : Access to market information significantly and
positively influences quantity honey market supply at 1 percent significance level. The model result confirms that as compared to households who have no access to market information, households who have access of market information increases quantity of honey supply to the market by 28.45 percent, all other factors held constant. Market information is vital instrument during marketing because it informs the farmers about marketing conditions. Farmers who have price information prior to marketing tend to sell more of their produce than those without. The finding is consistent with the results of (Nugusa, 2018) who found the existence of positive relationship between the market information and market participation decision of maize at Guduru district.

Price of honey in kg (PRICE):
In this study it was hypothesized that price of honey in 2019 G.C. was one of the major determinants of quantity supply. The finding shows price of honey is positively related to quantity supply and statistically significant at 1 percent significance level.
Producers checked the price of honey for their best benefit. Other variables remain constant at their mean value, as price of honey increase, quantity supply of honey increase by 90.21 percent.
Similarly, previous studies conducted by (Asseffa, 2009& Zegeye, 2018 found that, current honey prices affected marketable supply of honey significantly and positively. This is in line with (Nugusa, 2018), who find out that there is positive relationship between maize sold and current price.

Frequency of extension contact per year (EXCOFRQ):
It was positively and significantly related to the volume of honey supplied to the market at 1 percent significance level. The positive and significant effect was mostly due to the reality that beekeepers who frequently contact extension worker concerning beekeeping particularly about modern honey production, harvesting and handling methods contributed to increase the amount of honey supplied to market. The model result predicts that increase in number of extension contacts per year by one in relation to honey production, increases the amount of honey marketed by 32.95 percent. This suggests that frequent extension contact avails information regarding improved technology which improves production that in turn affects the marketed supply. The result is consistent with earlier results of (Getachawu 2009;Kassaa et al, 2017& Samuel, 2017.

Beekeeping training (TRAIN) :
The model result in table 21 also showed that participation in beekeeping training was significantly affecting the volume of honey supplied at households' level in Guduru distrct. It was a dummy variable and significant at 5 percent significance level. It is known that giving trainings for producers on beekeeping can fill the knowledge gap that constrained production and productivity. The model result predicted that as compared to those households who did not participate in beekeeping trainings, the marketed supply of honey for those households who participated in beekeeping trainings increases by 32.03 percent. The result is consistent with previous results of (Samuel, 2017& Tizazu et al, 2017.

Major Sources of Income generating activities undertaken in the area:
Although the entire household heads in Guduru district are primarily engaged in agricultural production or mixed farming (crop production and animal rearing), most of them are also making living out of off farm and non-farm activities. Non-farm activities refers to both self-employment in non-farm sectors such as beekeeping, petty trade and craft work/carpentry and off-farm employment such as daily labor works, masonry and guard (Chali, 2018).
Accordingly, in the study area rural households earn income from different sources. The major sources of income in the area were classified in to three categories as farm income, off-farm income and non-farm income during this study. Farm income is the income that households earn from their direct engagement in different farming activities. According to the information gathered from agricultural and natural resources office of Guduru District and shown on the figure 7, the major farming activities in the area are Crop production includes maize (27%), sorghum (4%), wheat (14%), barley (1%), teff (20%), sesame (5%), Niger seed (19%), Beans (4%), peas (3%), and others (3%). The rest 1% is accounted for fruit and vegetables farming activities. Major fruits production includes avocado, banana, mango, papaya, orange and lemon.
Vegetables like potato, tomato, pepper, onion, garlic and cabbage are means of livelihood and income generation. According to the information gathered from livestock and fishery offices, Livestock activities: such as cattle rearing (51%), equines (6%), Shoat (Goat and sheep production (14%) and poultry production (26%) are the important one in the study area as per shown in the following figure 8. Regarding to off-farm activities, it is the income that is earned from farmers' engagement in income generating activities during off-farm period. The major source of off-farm income in the area is daily labor. Whereas, non-farm income is defined as the income earned from non-farm activities like beekeeping, petty trade, handicraft, and other non-farm sources.

Livestock proportion
According to (Chali, 2018) study result, Guduru farmers are engaged in beekeeping activity for year as a sideline activity. Crop production and livestock rearing are their mainstay livelihood source while other off-farm activities, tree and fruit tree planting are additional means of cash income for the respondent households. Their main annual income is generated from the five sources; crop, livestock, off-farm, forest product and beekeeping. Similarly, (Mulugeta, 2014) study shows that, for those who practice beekeeping, it is the third important household economic activity following crop and livestock production. The result also coincides with the findings of (Mulubrihan, 2014) revealed that, honey is the main source of income for smallholder beekeepers of Anderacha district, Sheka Zone of South Nation Nationalities and People Regional State of Ethiopia. According to his result of the study, most sample beekeepers ranked beekeeping as it is the first main source of their income, which is followed by livestock production and crop production. This is in line with finding of (Kassa et al, 2017) who illustrated beekeepers of the study area practice various livelihood strategies and income generating activities mainly crop production in addition to animal husbandry, honey production, petty trade and daily labor.
The The pie chart of figure 9 shows that, the largest contributor to household income of the area is crop production, which accounted for 45.72% of the total annual household income. The production of animal husbandry ranked second and accounted for 27.59% of the total annual household income. Honey is the third important components of household income, which accounted for 21.55%. Off-farm activities contributed 2.67% to households' income. Trees accounted for 1.13%, fruits and vegetables accounted for 0.92% and the remaining 0.42% of household income is accounted from beekeeping by-product (ex. wax) income sources.

Figure 4 Contribution of honey for respondent household income
Source: Own survey data, 2020.

CONCLUSION
The study was conduct with the objective of analyzing the determinants of honey supply by smallholder farmers in Horro Guduru Wollega Zone in Oromia Regional state. The specific objectives includes analyzing the determinants of honey supply, identifying the types of incomegenerating activities undertaken by smallholder farmers, analyze factors influencing honey supply by smallholder farmers; assess the opportunity and challenges in honey production and supply activity the study area. Both primary and secondary data were used for this study which is qualitative and quantitative in nature. The primary data were collected from sample households using pre-tested semi-structured questionnaire and checklist. The primary data were collected from 121 sampled households. In addition to this, Focus Group Discussion and key informant interview were employed to supplement the research finding with qualitative information.

Proportion of income generating activities undertaken by the respondents (%)
proportion of income generating activities undertaken by the respondents (%) A total of 121 beekeeper farmer respondent's, 91% (110) males and 9 % (11) females were selected randomly from a list of 536 beekeepers from 5 kebels in the district. The average age of the sample respondents were 37 years with the minimum and the maximum age of 22 and 62 years respectively. The family size of the sample respondents were ranged from 2 to 14 that means farmers with different family size were practicing beekeeping activities and the average family sizes were 6. Educationally, the respondents of 37.2%) attended secondary school (from grade 5-8), 33% attended first cycle (grade 1-4), 13.2% are illiterate, 11.6% of the respondents can read and write and the rest 5% attended high school (grade 9-12). Therefore, the majority of sampled household heads were can read and write. Honey production is the third important components among the smallholder farmer's incomegenerating activities in the area, which accounted for 21.55 percent and beekeeping by-product like wax accounted 0.42 percent. The largest contributor to household is crop production which, accounted for 45.72 percent of the total annual household income in the area. The production of animal husbandry ranked second and accounted for 27.59 percent of the total annual household income. Off-farm (daily labor) income contributed 2.67 percent to households' income. Trees accounted for 1.13 percent of the total annual household income, fruits and vegetables accounted for 0.92 percent of income sources.
Estimation of determinants of marketable supply of honey with the help of multiple regression models (OLS estimator) analysis was employed with fourteen hypothesized variables. The result of the model analysis pointed out that, among the hypothesized seven variables were found to be significantly and positively affected the market supply of honey at household level as expected.
These are colony size (number of beehives owned), type of beehives used (improved and traditional), beekeeping equipment, market information, honey price of 2019, frequency of extension contact per year and training. The remaining seven variables (age, gender, family size, education, farm land size, non-bee farm income and credit) were found to have insignificant effect on honey market supply.

Recommendation
Possible recommendations that could be given on the basis of the study so as to be considered in the future intervention strategies which are amid at the promotion of honey production and marketing of the study area were as follows:  The colony size (number of beehives owned), type of beehives used (improved and traditional), beekeeping equipment, market information, honey price of 2019 G.C, frequency of extension contact per year and training was found to influence the quantity supply significant positively during the survey time. The positive significant effects of the variable propose that by the all mentioned above for smallholder farmers, sale volume of the honey can be expanded.
 Therefore, increasing the number of hives with colony, distribution of improved (both transitional and framed) hives accompanied by safety protective materials and other accessories for farmers of the district would bring additional marketable supply of the produce.
 Availing the strategies to support farmers with beekeeping business through facilitating access serves like credit availability, extension contact, trainings on improved beekeeping approach, cooperative formation, input supply and market facilitation/linkage also bring additional marketable supply of honey product,  Additionally, addressing the identified problems like designing effective honeybee pests and predators controlling methods; planting different flora especially, considering for dry period; improving pre-and post-harvest handling of bee products and make ready for market, ;  Accordingly, the district Livestock and Fishery offices, NGO, and other development partners should give weight on adequate practical skill training, facilitate on credit access for beekeeping purpose, implementing new technology, continuous follow up and technical support on honey production and marketing, design ways to collect and disseminate business information timely for beekeepers,.
 District and Zonal cooperative office and farmers union should give attention for honey producers and increase ability of smallholder producers to organize themselves into effective commercial entities (honey producers group) and encourage their participation in local and global trade  Farmers' cooperative Union should have to construct standardized honey collection center and create enabling environment for processors and exports make smallholder farmers beneficial;  All development agents of apicultural activities in the area should develop branding strategy and ensure traceability.