Enset (Ensete Ventricosoum) Value Chain in Dawuro Zone, Southern Ethiopia

This study was conducted in Dawuro zone southern part of Ethiopia with aim of analyzing enset value chain with specifi c objectives of identifying actors and their functions along the value chain, examine the share of benefi ts along ‘enset’ value chain, analyze factor affecting market participation and outlet choice of producer. The multi-stage sampling method was employed to select representative producers. The data were collected from both primary and secondary sources. Primary data was collected from 152 producers’ 57 traders and 66 consumers, respectively. While secondary data were collected from published and unpublished documents. Descriptive statistics, econometric models of Tobit regression and multivariate probit methods were used to analyze the data using STATA software. Participation and level of market participation were used as a dependent variable to analyze determinants of enset market participation. Market outlet choice was used as a dependent variable to investigate factor affecting outlet choice of the producer. The fi nding of the study revealed that major actors of the value chain are, input suppliers, enablers, enset producers, local collectors, wholesalers, retailers, and consumers. The performance of actors in value chain emphasized that about 26 % kocho and 25.95% ‘bulla’ profi t margin shared by producers. Similarly, local collectors, wholesaler, and retailers have shared 27%, 22% and 25.08% of kocho; and 25.32%, 22.15% and 26.5% share of bulla margin respectively. Retailers got a high share of profi t 26.5% from bulla. Moreover, local collectors get 27% share of profi t from ‘kocho’. However, farmers have the lowest share of profi t margin (26%) since local collectors and wholesalers govern the chain. the econometric result revealed that distance to nearest market at 10%, family size10% and incidence of the disease at 5% determined the probability of farmer’s market participation negatively and signifi cantly. Education level 1%, quantity produced at 1%, consumer preference at 1%, transport facility at 1% and Price at 1% is determining the market participation of the producer positively and signifi cantly. The result of multivariate probit model indicated that the outlet choices have signifi cantly infl uenced by age of producer, education level, and distances to market, extension contact, packing animal owner, labor availability, output produced and price of the products. Moreover, the model result indicated that the predicted probability of choosing direct-consumers outlet was (29%) which is relatively lower than collectors (44%) retailers (38%) and wholesaler outlets (69%), since they face constraints immediately to get direct consumers, the probabilities of producers jointly to choose and not to choose four outlets were 2.29% and 5.43% respectively. The Wald χ2 test value of 112.64, which is signifi cant at 1% signifi cance level indicating that separate estimation of choice of four outlets is biased, and the decisions to choose the four outlets are interdependent and simultaneous. Therefore, collective efforts required motivation of extension agents and linking actors with the market are recommended to increase value chain of enset product in the study area. Research Article Enset (Ensete Ventricosoum) Value Chain in Dawuro Zone, Southern Ethiopia Ashenafi Haile1, Berhanu Megerssa2* and Rijalu Negash3 1School of Plant and Horticultural Science, Hawassa University, P. O. Box 05, Hawassa,


Background and justifi cation
Ethiopia has diverse agro-ecological and climatic conditions suitable for production of various crops including root and tuber crops which play vital roles in food security of the people for over 20 percent of the population living in South and Southwestern parts of the country. Root and tuber crops are signifi cant contribution to food security, income generation ,source of food ,provision of food energy and resource base conservation [1,2] Among these enset(ensete ventricousoum) is one of the native food security root and tuber crop in Ethiopia ;and ones it has also along been served as an emergency food crop in Vietnam during the second world war [3]. Enset growing farmers in Ethiopia described its importance by saying "it is everything for us; our food, cloth, house, cattle feed and plates. of cultivating and using of root and tuber crops as a staple diet [4].
Kocho, bulla and amicho are the major products obtained from enset in order of signifi cance. Kocho is consumed after being baked in form of a pancake, whereas bulla, which is a solidifi ed residual by-product of enset, is obtained in the process of producing Kocho. The former is the most expensive of all products; and it is mostly served on holidays and cultural occasions [4,8].
Enset is also a source of starch for domestic and industrial uses like making of paper, adhesives and some verities of enset are used for local medicationon bone fracture, diarrhea, discharging placenta, forhumans and animals [4].
Enset penetrating from rural to center and northern part of Ethiopia by creating income opportunity every actor participating in value chain activity and add value to the product at stages of value chain to gain high income and bring with different benefi t at the marketing activity for each and individual actor till to reach the end consumer [9].
The lowest participation of producer to enset market and fewer abilities to good outlet choice generate limitation to output to distant, but rewarding markets due to high transaction cost arising from transportation and the high opportunity cost of labor involved. Therefore, improving the position of producing farmers to actively participating in the market and outlet choice was the most important issue. However, Producers and consumers separated by settlement order, and most farmers have found in the rural areas; consumers and hotel owners market which gave a good price was found at urban market outlets.
Enset is the major food item for rural and urban areas of Dawuro zone to which the increasing population pressure is major barrier affecting different crop production in study area [10]. Similarly, the food potential of enset has not fully been exploited and utilized compared to cereals [2]. Mareka and Loma Woreda are located in this locality in to which enset has signifi cant contribution both as a source of food generation of income for the people in the area. Therefore, this study is focused in fi nding out of the value chain analysis of enset in the study area.

Statement of the problem
Poor marketing and institutional services like lack of credit, transport facility and limited extension services has affected producer's market participation and outlet choices for cereal crop products. But these effects accompanied by social institutional demographic and infrastructural challenges were not well studied for enset at study area.
Despite, enset importance in improving welfare of farmers through household income, food security, poverty reduction and promotion of nutritional status, its actors' role and is not well distinguished. Likewise, a share of benefi t along the chain is not well identifi ed in Mareka and Loma Woreda. Similarly, consumers' preference for enset is increasing in urban areas of the study area. Due to institutional and socio-economic factors affecting producers, the participation of farmers to urban consumer's and hotel owner are threatened.
In addition, there is less institutional support for producer and limited organization among enset value chain actors performing different activities from design of enset to production, decorticating, transporting and marketing.
However, there is limited research conducted to address existing challenges in the study area. Thus, this study aimed to examine the entire value chain of enset fi lling the gaps along enset value chain.

Research question
• Who are the actors involved in the enset value chain?
• What is the share of benefi ts distributed along enset value-chain actors?
• What are the factors affecting producers market participation?
• What are factors affecting the enset market out-let choice of the producer?

Description of study area
The study was conducted at Mareka and Loma Woredas of Dawuro Zone. The livelihoods of the Woredas are based on subsistence farming which typically are of mixed type of farming including (enset, maize, teff, cotton, peas, beans spices) and animal husbandry. The soil type of the study areas is well-drained and weathered reddish-brown soil (Nitsoils and Orthic Acrisoils) [11] which are good for enset crop production.
The total population of Mareka Woreda is 145,955 of which (49.2%) are males and the remaining are (50.8%) females.
Simultaneously (91.9%) of in habitants reside in a rural area whereas 36% of them are Highlanders and the rest 51% and 13% are living in mid and lowland areas [1]. Among  5ºC.The annual mean rainfall ranges from 900-1800mm. and Loma located between 6º 56' N-7º 36' N Latitude and 36º 34' E-37º 64' E longitudes. According to the population census of CSA [5], the total population of Loma Woredas was about 109,192 (male 55,214 and female 53,978) and the districts comprise 34 rural kebeles and 5 urban kebeles out of this, 9 high land Keble's have high enset production potential [12].

Farmers' sampling:
Multistage-mixed sampling techniques were used to select sample respondents from the total population. At the fi rst stage, simple random sampling is employed to select study Woredas. Where primarily districts were listed and categorizes in to their production pattern and level of income of farmers. Then, six kebeles were selected from high medium and low enset producing areas. Subsequently, determination of sample size is resolved by means of Cochran [13] sampling formula with as present interval level with 5 present desire level of precision with probabilities of 11 present.

Consumer sampling
Two types of consumers namely households and hotel owners were purposively selected. Hence 21 hotel owners and 45 household respondents were included in the survey from Mareka and Loma Woredas, respectively.

Focus group discussion
Four focus group discussions were made with model farmers, Kebeles representatives, traders and DAs to draw Citation: Haile  points of interventions and to assess internal weakness and strength of actors along the value chain.

Method of data collection
For data collection, well-developed semi-structured interview questions were prepared and fi rst to preceding the survey, adequate training on the questionnaire and ways of the data collecting have been made by researcher himself and 12 sample questionnaires done by the researcher with the enumerators.

Source of data
The primary data were collected using three independent interview schedules, one for producers, the other for traders and the third for consumers. Secondary data was used from sources like reports of agriculture offi ce, published and unpublished materials, marketing and cooperative offi ce report, trade and industry offi ce report and trade and industry departments.
The primary data were collected to know about demographics, socio-economic and institutional factors of the farmers in the study area. In addition, factors affecting farmer participation to market, outlet choice, to whom farmers are selling their product, the cost incurred from production up to marketing, the benefi t in relation to quantity produced per hectare per year, the fl ow of information, service he gets and service providers data have been collected.
Traders demographic, socioeconomic data experience of trading, the fl ow of product from whom he buys and to whom he sales the product, the outlet he buys the product, in relation to fl ow of information and service he gets, the service providers for trader's data were asked. Thirdly, the cost he incurred and benefi t of the trader at different channel and function of the individual trader on value addition of the product would answer.
Finally, the buying trend and preference of the product from which actor they buy the products were answered. Moreover, the income of the consumer, amount of the product they buy, and type of the product bought per week per month as data was collected.

Type of data
To conduct this study, both qualitative and quantitative type data were used like income from another source, age of farmer, and yield of enset, amount supplied to market, amount consumed and distance to market data were collected.

Method of data analysis
To this study, both descriptive and econometric analysis was used to conduct value chain analysis.
Descriptive statistics: To describe the characteristics of value chain actors' descriptive statistics like mean, standard deviation and percentage were used. To this effect, data are coded and entered into STATA version 13 accordingly. Inferential statistics such as hypothesis testing, Chi 2 , t-test, pseudo R 2 and p-value used to test dummy categorical, continuous, and likelihood respectively.

Value chain analysis:
Value chain analysis has adopted a framework for understanding key activities, relationships, and mechanisms that allow processors, buyers, sellers, and services they pass from one link to the other [14].
Mapping core processes in value chain, mapping main actors involved in these processes, mapping fl ows of products, information and knowledge, mapping volume of products, numbers of actors and jobs, mapping geographical fl ow of the product or service, relationships and linkages between value chain actors, the business services, that feed into the value chain have done.

Analyzing marketing margin
Estimates of the marketing margins are the best tools to analyze the performance of actors found in the market either selling or buying the commodity. Marketing margin is used to calculate the share of a particular actor in the value chain.
For calculating the marketing margin of a particular actor, the average price of the product has taken. Computing the Total Gross Marketing Margin (TGMM) was related to the fi nal price paid by the end buyer and is expressed as a percentage Mendoza [15].
There are traders at different marketing channel. Thus, the margin was calculated to fi nd the price variation at different segments, comparing them with fi nal price or the consumer's price and hotel owner has done. Hence, the consumer or hotel owner's price is the common denominator for all markets margins at different marketing outlets.  TGPM=TGMM-TOE (5) where TGPM is total gross profi t margin, TGMM is total gross marketing margin and TOE is total operating expense. The study result by [16] showed that, profi t margin by subtracting operating expense from marketing margin.
Quantitative data on the cost and revenue structures, value-added, benefi t distribution were analyzed and computed using the terminologies briefl y described by Marshall, et al. (2006). Profi t margin at each stage was computed to evaluate the benefi ts along enset value chain, as: Profi t margin = Revenue -Total cost (6) Where Revenue=Sales volume * Unit price (7) Econometric analysis   [19]. In this class of models, the response is multivariate correlated and discrete.
The model is a generalization of the probit model used to estimate several correlated binary outcomes jointly Vithala [20]. Since, across-market outlet choice is prevalent among producer, socio-economic and demographic characteristics have varied infl uences on marketing and in different types of outlets.
The study examines the factor-affecting choice of producer The market outlet has categorized into four groups: selling to wholesaler, selling to local collector, selling to retailer and consumers. Each farmer can use one or more marketing outlets or several joints of different outlets that maximize the expected utilities and due to this, there was the same overlapping and many farmers can sale with more than one market outlets.
With respect to the structure of the theoretical model and the dependent variables, a recursive multivariate probit model is as a generalization of the bivariate probit model Maddala [21]. The model specifi ed us:

Identifi cation of actors and their function
Market participation of Enset producer was infl uenced by many socio-economic and fi rm-specifi c characteristics.  In addition, it is greater than both Regional and National family Musah [23] and [24] who reported enset production and marketing is labor intensive activity requiring families with more household members for better market outlet. Similarly, Wolday (1994) showed that, household size had signifi cant positive effect on quantity of left marketed and impact on market participation and volume of sale. Congruently, the study result indicated that enset production and processing in the study area makes use of 60.5%, 17.8% and 15.1% of family labor, hired labor and community support through 'wonfel'/ 'debo', respectively, which is local `dagwa` for digging the soil, tinning and wonder (Supriya) by females for processing products. In line with this Checka [25] has revealed that enset farmers use family labor to share the experience.

Farmers
Population density: The increasing concern related to boosting population density is the fi rst fact that was, largely damage production potential. This is due to a high number of family sizes, which fragment the land owned by the household for crop productions used for construction and urbanization.
The study line with Teshome [26] stated that production potential of the situations has damaged by high population pressure for house construction and settlement apart from enset production.   fi nding is also similar to the fi nding of Gebreselassie and Sharp [30] who reported households with a higher value of production sold their produce with better market participation. products to markets indicating larger quantity of kocho produced can directly infl uence households' decision to participate in the enset marketing. Apart from the total annual enset production, 31% 'kocho' and 92% of bulla produce supplied to markets and this helped to increase market participation of producers. In addition, the remaining 69% of kocho and 8% of bulla consumed at home level reduced participation in the market at the season of the survey period.

Socio-economic factors of farmers
Consumer's preference: From survey result, 74% of the respondents revealed that, positive feeling for enset. Since the plant is highly drought resistant, it provides fi ber for making ropes mats, medicine that helps for wounds and breaks to heal faster and stronger and it provide water to the coffee seedling. In addition, the studies of [31] explained that there was high consumption of enset products in the study area and neighboring areas because of increasing cereals price and in relation to population growth and consumption demand. to credit decreased the fi nancial capacity of farmers to purchase necessary inputs and negatively infl uenced market participation and volume of sale. The result is in line to [33] who emphasized that formal fi nancial sector in Ethiopia have inadequate inclusion to rural areas and have high interest rate who repels users. Hence, access to credit facility has failed to incentivize farmers to produce more and supply better in market (Adugna, 2009).

Market information:
The survey result indicated that 37.5% of produce accessed market information from relatives, friends and extension agents. This result agreed with [34] who found that majority of farmers rely on friends, relatives and agricultural extension agents for market information.

The frequency of extension contacts: Extension visit was
directly lower when compared to other conventional in study area. This result was in line with Geda [29] who reported current extension approach was limited to conventional and this failed to bring major impacts on enset production where lack of extension service for enset has led to poor linkage to support enset commodity. This fi nding also in line with Carlson, et al. [35] explained, as the current extension approach was more in favor of cereals.
Means of transport: 47% of sampled respondents have no access to transport facility and thus, farmers were habituated using packing animals like Horse, Mules, Donkey, and family labor in that area. Therefore, the households with less or no family labor had exhibited low market participation and there by caused market surplus to decline. This result in line with Nwigwe [36] who underline transportation was a major marketing cost like Yam market participation and thus discharged from the urban market. Likewise, Eshetu [33] reported lack of transport problem was common challenge for producers Figure 3. Pests: Mel bug is a common pest causing less standing of a plant, retarded growth and makes drying of sheaths, locally known as `gorchwa`. The result is similar to the description of [38] who realized plant attacked by Mel bug dried tended to retarded growth and day at the end. The other common vertebrate pest responded from farmers was mole rat locally named as `Ochuwa` which eat the corm part. This is in line with [39] who reported that, enset production and productivity is reduced by vertebrates such as Mole rate and porcupine Table   3.
Citation: Haile  were need food item like enset product with is less costly than cereal crop. The results in line with [31] reported that, increasing enset consumption because of increasing cereals price, population growth.

Market participation characteristics of producer
The average distance to market was 5.25 and 8.72 in kilometer to participants and non-participant respectively.
The mean land size 2.0035 and 1.2083 hectares for participant and non-participant respectively. The quantity produced per

Enset value chain actors and their functions
The study result showed that, major traders of enset in the study area identifi ed are, local collectors (28.1%), wholesalers Value chain analysis systematically maps the actor participating in production processing marketing and consumption of a particular product. The value chain map is a conceptual and practical tool that helps us identifi es policy issues that may hinder or enhance the function of a value chain and also the institutions and organization providing the services (such as market information and quality standards) that the different value chain actors need in order to make betterinformed decisions. The study result by [40] showed that valuechain map was made up of three interlinked components. These are, value chain actors, enabling environment (infrastructure, policies, institutions, and processes that shape the market environment), service providers (the business or extension services that support the value chain operations).
The value chain mapping enables to visualize the fl ow of the product from production to end consumer through various actors [41]. It also helps, to identify the different actors and their function in Enset value chain to understand their role, linkage as an analytical tool.In addition, it provides a useful framework forunderstandingkeyactivities, relationshipand mechanisms thatallowproducers,processors, buyers, sellersand consumers separated by time and spaceto gradually add value to products and servicesas they pass from one link of the chain to another making it, a "value chain" UNIDO [14].The present value chain map of study Woredas was has viewed in (   industry offi ce, Omo-micro fi nance function was not clearly seen at Mareka Woreda.
Input suppliers: Enset products value chain in the study area starts from the concept of production with the use of inputs to consumers and distribution of enset value added Kocho and Bulla. An input includes credit service, extension service agricultural instruments. Thus, input supplier's role had not clearly seen in the study area to encourage value addition along enset value chain except fewer amounts of credit and with less frequency of extension service according to the result of the study.
Producers Are the fi rst most important direct actors along Enset value chain. More amounts of enset were having produced as food and a major source of income. Farmers use their own land, family labor, hired labor, wonfel , debo for production, plantation, weeding, thinning out, decorticating, processing transporting and marketing their products. The survey result revealed that 100% of sampled households were producing local variety.
Enset production per household: The maximum and minimum quantity of kocho produced per plant per year was 110 and 50 kilograms respectively. From this lot of produce 5 kilogram of bulla being produced per week per household via the value addition process of which 8 percent of bulla and 69 percent of kocho was being consumed at home by the producer and the rest was being sent to the markets. However, 35.5%, 10.6% and 35.5% of respondents were challenged by lack of credit, distance to market and both lack to credit with lack of value addition experiences respectively. The value addition stage of enset at farmer level includes: -Enset-fi ber kochosliced kocho-bread and Enset-row bulla simply supplied to market at study area.
Thus, the difference in the quantity of 'enset' produced and level of product value addition and market participation varies in the sampled household due to, management system, fertilizer application, and extension service, and labor availability, size of enset plantation in a hectare and value addition experience. Thus, 35.5%, 10.6% and 35.5% of respondents indicated that enset product market participation of producers was affected by, lack of credit, distance to market and both lack of credit with lack of value addition experience respectively. The value addition stage of enset at farmer level includes Enset→fi ber 'kocho'→sliced kocho →bread and Enset →row bulla simply supplied to the market.

Value chain governance of enset actors
The known value chain actor's play facilitating role, they were determining the fl ow of product and level of price by doing this, and they govern the value chain and most of other chain actor's subscribes the rule set in the marketing process Table 5. collectors infl uence the retailer and producer by controlling However, producers are not providing a quality product and the producer blame that the traders do not give us a good price Table 6.  Table 7.

IV. Producer, Wholesaler, Retailer and Consumer:
In this channel, about 14% (138.8qts) of kocho was marketed during the period. It is the fourth important channel in term of volume of produce pass through it.

V. Producer, Local collector and Consumer:
In this channel, about 2% (34.7qts) of kocho marketed during the period. This is the seventh-important channel less amount of produce pass through it. In this, channel wholesalers perform better by collecting the produce from local collectors and selling the produce to out of zonal markets and get better profi t.

VI. Producer, Wholesaler, and Consumer:
With this channel, about 1.4% (24.81qts) of kocho marketed during the survey period. This channel is the last channel in term of volume pass through it.

VII. Producer, Wholesaler, and Out of zonal markets:
With this channel, about 5.8% (109.63qts) of kocho marketed during the period according to study data. This is the fi fth important channel with this all produce pass through out of zonal markets. While more benefi t shares to wholesalers directly contacting the producers and selling out zonal markets.

VIII. Producer, Local collector, Wholesaler, Retailer and Consumer:
With this channel, about 4.5% (81.2qts) of kocho marketed during the period as collected. This is the sixth important and longest channel with this, less amount of produce pass through it and more of intermediaries are there until the product reaches to the consumer.

Bulla market channel
Seven marketing channels were identifi ed for bulla market were producers, retailers and consumers carry largest volume of the produce, followed by producers, local collector's wholesalers. From the total 184 Qt produced in 2019 169 qt was supplied to local and terminal market and apart from this 54.7 Qt traded to out of zonal market Jimma, Wolayita, and Shashemene. While the reaming amount fl ow through the identifi ed marketing channels to consumers and hotel owners ( Figure 6).

I. Producer and Consumer channel:
18.5% (30.5qts) of bulla marketed during the study period and this channel was the third important channel in term of volume and it was a relevant channel to the producer to get a good price from producers without intermeddlers.

II. Producer, Retailer, and Consumer channel:
this is the fi rst important channel where 39.2% (67.07qts) of bulla marketed during the period of the survey. This is the fi rst important channel more of produce pass through it. In this channel, retailers perform better by direct contact with producer and selling the produce to consumer.
III. Producer, Wholesaler, and Consumer channel: this is channel, which is least signifi cant by contributing 2.5% (4.18qts) of bulla pass through it.

IV. Producer, Wholesaler, and Terminal markets: this is
the fourth important channel where 14 % (23.7qts) of bulla

Enset marketing channels at study woreda
The analysis of marketing channels could intend to provide a systematic knowledge of the fl ow of goods and services from its origin of production to fi nal destination Abraham (2013).

Kocho marketing channel:
The survey result showed that, eight marketing channels were observed in the study area.

III. Producer, Local collector, Wholesaler and Consumer:
With this channel, about 19% (347.7qts) of kocho was marketed during the period. In this, channel a large amount of kocho sold to the consumer and it is the second existed in the study area. was marketed during the period. In this, channel wholesalers perform better by direct contact with producer and selling the produce to out of zonal markets and get better profi t.

V. Producer, Local collector, Retailer and Consumer
channel: this is six channels which contributed 2.27 % (3.85qts) of bulla to the marketed during the period. This is the last channel less amount of produce pass through it and high amount of intermediary.

VI. Producer, Local collector, Wholesaler and Terminal
market: This is the second -most important channel where 18% (31qts) of bulla was supplied to market. In this, channel wholesalers perform better by collecting the produce from local collectors and selling the produce to out of zonal markets and get better profi t.

VII. Producer, Local collector, Wholesaler, Retailer and
Consumer: This is the fi fth important and longest channel which assisted for supply of 5% (10qts) of bulla to market during the period. With this, less amount of produce passes through it and high numbers of intermediary.

Share of benefi ts along enset value chain
The Performance of enset market: The study indicated that, from the total performances of enset market was To this study, distribution of cost and gross income at different level was evaluated in the business of enset. The marketing of the product mainly involves the cost of postharvest activities incurred before reaching the end consumer and hotel owners. This includes the cost of harvest and packaging (material and labor costs) handling clearing from the fi ber (loading and unloading) and transportation cost. This is in line with [47] reported that, costs which are incurred to perform various marketing activities in the transportation of goods from producer to consumers.
Thus, the component constitutes a large share in the total margin between the fi nal retailer price and the cost of production. Therefore, the margins calculation is done to show the distribution of cost and benefi t throughout the various actors as enset product moves from producers to local collectors, wholesalers, retailers and fi nally to consumers.
Marketing margin has been used to measure the share of the fi nal sailing price which has captured by each actor in the value chain. The relative size of various market participants gross margin can indicate where in the marketing chain value-added.
The study conducted by Enibe, et al. [48] on Banana Market in Anambra State Nigeria showed that, marketing margin as the difference between the consumer price and the price received by producers. In order to calculate marketing margins of an agent, the average price of enset product for that agent was taken. For instance, the buying price of consumer and hotel owners was obtained by taking the average purchasing price of the consumer in order to measure the market share of each agent. Similar studies were conducted by Takele [22] showed that, marketing margins as average selling price minus average buying price. The marketing channels of all actors have participated was identifi ed according to product fl ow.

Kocho market performance: Cost and price information
was computed to construct marketing cost and margin.
Therfore, total gross marketing margin (TGMM) was worked out to identify fi nal price paid by end buyer. Consequently the result indicated that, chain actors had added value to Kocho as the exchange takes place from one actor to another. To this effect, actors through changing the form of produce i.e from enset to bulla and amciho and baking; and by improving grades through sorting, cleaning fi ber, transporting and packing in clean sheath, plastic, plastic bags. This result line to Chaka, et al. [25] who illustrated restaurants and hotels were involved to sell food stuffs and likewise farmers and traders were participated in improving quality for better profi t Table 8.
Compared to farmers, traders (local Collectors, wholesalers, and retailers) expense is about 60%. However, the profi t margin of a trader is more than 76% that of the farmer.
The result shows that kocho traders are simply buying from the farmers at the different outlet of product and selling to consumers, and earn 74% of the total profi t margin. Hence, farmers operating all work from plantation up to market taking challenges and risks in production had only 26% of the profi t margin. This miss share of benefi t happened with the factors affecting farmers on value addition and level of market participation. Therefore, enset producers added only 26% local collectors, wholesalers and retailers add up to 27%, 22%, and 25.08% respectively, and the change of producer's price to consumer price interval is 68%.

Marketing margin of Kocho at different market channels:
The result of study area shows that Marketing margin of Kocho has eight channels in each group of market actors are given in Table 9; GMMF, GMMc, GMMw, and GMMr are gross marketing margins of farmers, local collectors, wholesalers, and retailers respectively.  from the producers. The retailers due to small operational cost earn the highest profi t. The study by [32] shows that from enset value chain, retailer's share of profi t is high due to small operational cost.
Distance to nearest market affects farmer's participation negatively at less than 5% signifi cance level. The result shows that farmers far from the market by 1-kilometer decrease participation to market; the increase in a unit kilometer distance reduces the actual amount of 'enset' supply condition to market by 5.16%. This is due to lack of transportation facility and 'enset' products are bulk and high water content to transport long distance. This study also agrees with Tadesse Woreda. Therefore, Farmers who have price information prior to marketing tend to sell more of their products than those without.
As hypostasized, the result shows that farmer's market participation signifi cantly affected by quantity produced per Table 11: Benefi t distribution of actors in bulla marketing channels. I  II  III  IV  V  VI  VII   TGMM  0  59  63  67  70  73  81.6   GMMF  100  41  37  33  30  27  18.4   GMMc  ----38  33  -GMMw  --63  67  -40  60   GMMr  -59  --32  -53 Source: Own survey result (2019) year at 1% the level of signifi cance positively. The positive coeffi cient revealed that a unit increase in the quantity of produced increases farmer's participation in the market. Hence, a unit increase on kocho and bulla produced the actual amount of kocho and bulla supply to the market increases by 3.12%.

Market Margin
This indicates that an increase in enset product yield per year by a quintal results increase in the level of market participation because this was explained by the fact that those smallholder farmers with more harvest were in the better position to sell more kocho than earlier sales.
In agreement with this [52] South Africa and Niger were households with larger maize harvests were likely to have more surpluses for sale and more participation to market.
In addition, the study by Cunguara, et al. [53] realizes that increases in the proportion of households producing these crops which indicate that increased market participation was accompanied by increased production. This fi nding is similar to the fi nding of [30] because households with a higher value of produced crop sell a higher proportion of their products and thus, increase participation in the market.
Consumer preference is dummy variable which had a positive impact and statistically signifi cant at 1% level. This shows that the number of supply increases in response to the consumer. Thus, consumer preference increases by one unit than the actual farmer's participation to market and likelihood increases by 11.61%. Thus, consumer preference for value-added enset production increases market participation of producers. In this regard [54] explained that from social and cultural factors consumer preference to output market increases farmers' market participation of producer.
Off-farm, activity has a negative infl uence on the volume of kocho supplied to the market at less than 5% level of signifi cance and the result shows that increase in the quantity of off-farm caused decreased farmer market participation on enset product. Nuri, et al. [55] support this in explaining that income from non/off-farm has a negative relationship with the 'kocho' market participation. The result of Tobit regression model shows that a unit increases in off-farm activity decreases the farmer's participation in 'enset' product market by 8.23%.
This result shows that farmers engaged in off-farm activity to earn income other than enset. Thus, they tend to reduce more time to produce other crop and off-farm activity than enset production. The study similar to [23] realizes that off-farm income in total annual household income positively related to the participating in the maize market, it is negatively related to the quantity of maize sold. Access to transport facility had also a positive impact on market participation and statically signifi cant at 10% level of signifi cance. This implies that access to transport facility increases producers market participation. Therefore, the access to transport facility and own packing animals increases the actual amount of kocho and bulla supplied to market by 7.98%.
So, it hypostasized to affect farmer's participation positively and signifi cantly. If there are no means of transport, they do not participate in the market due to different costs. In line with this study Weisbrod [56] explains the ideas by imposing an effective limit on output raising travel times and costs, reducing reliability and diminishing access to the product. Moreover, in line with this [57] conducted study on potato value chain and indicated that the availability of transportation facilities helps to reduce long market distance constraints, offering greater depth in marketing choices The incidence of disease was dummy variable which had a negative impact and statically signifi cant at the level of less than 5%. This shows that by keeping other explanatory variables constant, the incidence of disease in production year reduces farmer's market participation to the market the marginal result of Tobit regression also explained that, with a unit decrease by the incidence of disease reduces the actual amount of supply to market by 8%. In agreement with this study [37] explained that 'enset' bacterial wilt is a major constraint to enset production in Ethiopia endangering the livelihoods of millions of farmers and threatening the food security of over 15 million people for whom enset was a staple food and source of income.
In addition, the study conducted by illustrates that Enset (Xanthomonal wilt) disease rated the fi rst in its devastation. Another study by [58] shows that, low level of improved agricultural technologies, risks associated with weather conditions, diseases and pests are the main reasons for low productivity.
Price infl uence farmer's participation positively and it is signifi cant at 1% level. When, price increases by one Birr, the level of market participation increases. The regressions of the model also described that a unit increase in price increases the actual increase of participation by 8.3%. In relation to this [59] conducted a study on horticultural crop pineapple emphasized that better output price is the key incentive for the sellers to supply more to the market. Therefore, higher price perceived to increase the extent of market participation of enset producers [60][61][62][63][64][65][66][67][68][69][70][71][72][73][74][75].

Factors affecting enset market outlet choice of producer:
The multivariate probit model is the generalization of the probit model used to estimate several correlated binary outcomes jointly. The syntax mv probit estimates the multivariate probit model. The parameter estimates are simulated maximum likelihood (SML) estimators. The marginal success probability for each equation is estimated by the command mvppred varnnam, pmarg. The command mvppred, pa computes the joint probabilities of all equation success or failure . Table 13 shows that, there are four outlet choices to the producer which are wholesalers, collectors, retailers and direct consumer outlets. The sample was drawn 5 times since; simulated maximum likelihood estimate was computed from the parameters estimated as the sample drawn. The matrix Rho21, Rho31, Rho32, and Rho42 were shown that the correlation coeffi cient matrix between farmer direct consumer, farmer collector, farmer retailer and farmer wholesaler respectively. to transport facility negatively affected. This was because, with access to transport and they have capital, they want to choose consumer market outlet giving a good price. The predicted probabilities of the choice collector market outlet are 69% [120][121][122][123][124][125][126][127][128].
The joint probability of choosing for all outlets was only 2.29%. It was unlikely for farmers to choose four outlets simultaneously. Since all four outlet choices were not profi table for farmers from the channel they choose the important outlets to maximize utility. However, the joint probability is not to choose all market outlet was 5.43%. This implies that the household is less likely to fail without choosing one market outlet at a time by assuming the need for conducting institutional services and outlets that maximize the benefi t of farmers.

Summary, conclusions and recommendation
Summary : The study was aimed at analyzing value chain of 'enset' at Mareka and Loma Woredas of Dawuro zone southern part of Ethiopia. The specifi c objective of the study includes identifi cation and mapping the function of actors along the value chain, examine cost and share of benefi ts distribution along the value chain, analyzing factor affecting farmer participation and outlet choice of the producer. The data was generated both from primary and secondary sources. The primary data were collected from individual interviews using pre-tested semistructured interview schedules and checklists. Multistage sampling technique was employed to select Woredas, kebeles and Sample respondents by using Cochran (1963:75) sampling formula 152 farmers selected randomly and 57 traders and 66 consumers selected purposively, totally 275 respondents used for the study.  The result of the study shows that the traders operating expense for 'kocho' and bulla were 26% and 20% respectively from a total value chain expense. However, their profi t margin is almost 74% and 80 % of the total profi t margin for 'kocho' and 'bulla' respectively. The result of the study shows that kocho trader s are simply buying from the farmer at the different outlet of product and selling to the consumer are earning 74% of the total profi t margin. Therefore, farmers operating all work from plantation up to market with taking challenges and risks in production have only 26% of the profi t margin.
The share of the profi t margin of local collectors' wholesalers and retailers from kocho was 27%, 22%, and 25.08% respectively. This shows that local collectors were benefi ted more than other actors in kocho value chain and retailers are benefi ted more than other actors in 'bulla' market chain.
The distribution of benefi t along enset value-chain actors varies from marketing channel in which the product was distributed to each actor. The gross marketing margin of producer (GMMF) in channel I is 100%. This result shows that producer directly sold kocho to consumers at a better price without the interruption of the intermediary. Wholesalers get the highest marketing margin at channel IV, III and VI 67%, 63%, and 40% respectively. The lowest share of gross margin registered for the farmer at channel VII accounts about 39%.
The retailers got highest gross marketing margin at channel II and V and lowest at marketing channel VII. GMMr is high on the channel I indicated that they purchase 'bulla' at an optimum price from producer directly and sold to a consumer for good price. This implies retailers not incur more marketing cost, but benefi t more in channel II than other channels. The share of the profi t margin of local collector's wholesalers and retailers were 25.32%, 22.15%, and 26.58% respectively from the sales of one quintal of 'bulla'. The wholesalers got the highest marketing margin at channel IV, III, VI 67%, 63% and 40% respectively and the lowest at marketing channel VII accounts about 39 %. The retailers got highest gross marketing margin at channel II and V and lowest at marketing channel VII. This implies that retailers of bulla in the study area are incurring less marketing cost and benefi t more in these two channels than others. From the study result, the main value chain actors were input suppliers, enset producing farmers, local collectors, wholesalers, retailers, and consumers. Woreda agricultural and rural development offi ce (WORD) and the Offi ce of Trade and Industry is the main supporter of enset product value chain in the study area. The data of research shows that less accessibility to market information, less power for market penetration and less market arrangement make the farmers less price taker and trader in a better position to dominate the market price and govern the chain.

Citation: Haile
The study shows that traders operating expense from 'kocho' and bulla were 26% and 20% of a total value chain expenses, but their profi t margin is almost 74% and 80% of the total profi t margin for kocho and bulla respectively. The study results of demographic factors such as age, education level, sex, family size, socio-economic factors, land size, labor, and quantity of 'enset' produced, hectares of 'enset' crop owned, wild animals and population pressure. Institutional factors such as access to extension service, access to credit, access to market information and access to transport facility and distance to market, consumer preference and physiological factors, like incidence to disease, pest, are hypostasized infl uential factors to the participation and outlet choice of producer. As a source of food and income for producers there is limitation of institutional support for the sector, such as access to credit, market information, and extension services.
According to a wide range of difference between farmers was due to not using inputs like manure, the poor frequency of extension contact, less training given for product value addition and poor disease controlling system. Therefore, the focus of extension service has to be improved to increase farmer's access to market information and extension support through giving training and awareness creation from agricultural offi ces and research center.
The share of benefi t distribution among 'enset' value-chain actors is different from producer to the retailers. The profi t share of the producer is less than 26% of 'kocho' and 25.95% of 'bulla' which is less than traders. Therefore, putting in place and strengthening appropriate extension and marketing institution for giving timely and good market information for enset producer is so important and farther studies to be done by Action Aid, Areca research center and the policy issue by government for the sector of 'enset' marketing should be considered.
Marketing portals for the product are not arranged in observation to marketing actors. Therefore, the market segment for the product in relation to actor's participation should improve by Woreda Trade and Industry Offi ce according to convenience to buyers and sellers massive contact to the produce.
Therefore, the farmers have to link production with marketing products based on market signals, consumer preferences or advising good quality and packing material to improving quality. Therefore, it is recommended to make effi cient extension system on the produce improving the knowledge and skill of extension agents with production and marketing of 'enset'.
The 'enset' product 'bulla' directly traded in row form between producer and traders to consumers at Zonal, local and urban markets at a low price. While this shows that less knowledge of producers and trader to process and pack in powder form. Therefore, to capacitate bulla producers and traders on processing powder bulla and packaging technology training should be needed from agricultural organizations.
In case of production, households with the limited education distant market and with a large number of dependent age group and less extension frequency contact, limited participation in the market. Therefore, Actin Aid, SLM, Agriculture offi ce and Trade and Industry Offi ce have to create infrastructural and institutional development.
In addition, large numbers of farmers have responded the existence of disease incidence, pest, and wildlife attack. Thus the presence of crop disease in production year created yield reduction of the product according to this survey and reduced market participation of the producer. In order to avoid the reduction of production and increase market participation of the farmer, awareness creation for integrated disease and pest management to be done and crop protection services through availing chemicals for enset Melbug and bacterial welt or locale ('Woluwa') required preventing disease.
From the factors affecting enset value chain of study area: education level of households, access to market information, access to transport, price and consumer preference had positive implications are maintained and further encouraging work to be done. In another side, the factors, which show negative implication on enset, value chain that are -distance to market, incidence to disease and off-farm activities in relation which affect the production marketing and value chain activity, considers policy implication in enset value chain needs work from agriculture offi ce and research center.
The joint probability of choosing for the outlet was only 2.29%. It was unlikely for farmers to choose four outlets simultaneously. Since all four outlets choices were not profi table for farmers they choose the important outlets to maximize utility. However, the joint probability not to choose all market outlets was 5.43%. This implies that the household less likely to fail without choosing one market outlet at a time by assuming the need for conducting institutional services to choose outlets that maximize the benefi t of farmers.
Moreover, there has to be an institution that can provide true information required for producers timely. This makes the marketing system effi cient for all actors participating in the value chain of 'enset'. Therefore, as the study conducted shows zonal and woreda agricultural offi ces and respective offi ces, Areca research center, zonal and woreda cooperative and trade offi ces need to work improving the capacity of producers in order to encourage and improve their skill on choosing appropriate market outlet for their product and focus on identifi ed constraints and opportunities to improve the value chain of enset at study area.