Characterization and Analysis of Farming System

Reader Impact Factor Score
[Total: 3 Average: 5]

Published on International Journal of Agriculture & Agribusiness
Publication Date: August, 2019

Beriso Bati, Yassin Esmael, Shimalis Gizachew & Asfaw Negassa
Department of Agricultural Economics, Adami Tulu Agricultural Research Centre
Adami Tulu, Ethiopia

Journal Full Text PDF: Characterization and Analysis of Farming System (Studied in West Arsi Zone, Oromia National Regional State, Ethiopia).

Abstract
Farming system is a complex combination of inputs which influenced by environmental, economical, institutional, political and social factors. Farm type identification and characterization based on agro-ecology, production system and different farm components helps to identify area specific problems and give proper technological intervention to address the problems. Therefore, farming system characterization is a vital activity for agricultural technologies generation, development practitioners and policy makers. Therefore, this study was initiated to identify and characterize the farming system in West Arsi Zone with the objectives of identifying and characterizing the existing farming systems, identify and prioritize constraints of the farming system for identifying potential research interventions. To accomplish the study both Primary and secondary data collection method was used. Secondary data was collected from West Arsi Zone and four selected districts in the zone using checklists. In addition to this published and unpublished materials were used for secondary data collection. Multi-stage sampling technique was employed to select sampled districts, kebeles and household farmers. Primary data was collected by conducting focus group discussion (FGD), key informant interview and household’s interview by using semi-structured questionnaires. One FGD which contains 8-10 farmers was undertaken per selected district to collect data. Key informants interview was made with concerned experts and Development agents at districts and Kebeles levels. A total of 264 sample households were selected from West Arsi Zone to collect primary data through direct interview. Descriptive statistics was used to analyze the collected data using STATA version 14. The study find out that West Arsi Zone was dominated by mixed crop-livestock farming system. Mixed farming system of West Arsi Zone was classified into potato-haricot bean based farming system and cereal based farming system which classified into wheat-teff based, food-malt barley based and maize based farming systems. Major agricultural production constraints within the farming systems across zone are identified and the possible policy implications are suggested to solve the identified problems.

Keyword: Farming system characterization, Constraints, Opportunities, FGD, and West Arsi Zone.

1. INTRODUCTION
Agriculture remains the best opportunity for the estimated 1.5 to 2 billion people living in smallholder households to escape poverty. Studies show that income growth generated by agriculture is up to four times more effective in reducing poverty than growth in other sectors (Growth Commission, 2008). Agriculture contributes 36.2 percent of the country’s gross domestic product (GDP) and 72.7 percent of employment and 70 percent of export earnings (Getachew, et al., 2018). The economy of the Ethiopian country is heavily dependent on agriculture, with over 85% of the rural population deriving their livelihoods directly from agriculture.
Farming system is a complex combination of inputs, managed by farming families, influenced by environmental, economical, institutional, political and social factors. Basically, it is a set of interacting activities and inputs which can be managed by farming families, but influenced by environmental, political, economic, institutional and social factors (NRl.org, 2004). Research and extension institutions are increasingly aware that a holistic approach, drawing on both local and external knowledge, is necessary if they are to be effective in addressing poverty and sustainability. The systems approach basically consists of accepting the irreducible complexity of the system under study, of striving to understand the overall operation of the system and not only the mechanisms which are brought into play within it.
Farming systems research is an approach for generating appropriate technologies for studying existing farming systems and involving the technology users – usually the small farmers in the planning and evaluation process. Thus, study of farm typology is of practical interest for precise and effective technological interventions. Farm typology study recognizes that farmers are not a monolithic group and face differential constraints in their farming decisions depending on the resources available to them and their lifestyle (Soule 2001). Ellis (1993) observes that small farmers are always and everywhere typified by internal variations along many lines. Although every farm and farmer is unique in nature, they can be clustered into roughly homogeneous groups. Developing a typology constitutes an essential step in any realistic evaluation of constraints and opportunities that farmers face and helps forwarding appropriate technological solutions, policy interventions (Ganpat 2001, and Vanclay 2005) and comprehensive environmental assessment (Andersen, et al. 2009).
According to FAO (2007), a farming system is defined as a population of individual farm systems that have broadly similar resource bases, enterprise patterns, household livelihoods and constraints, and for which similar development strategies and interventions would be appropriate. The classification of the farming systems of developing regions has been based on the following criteria: available natural resource base, including water, land, grazing areas and forest; climate, of which altitude is one important determinant; landscape, including slope; farm size, tenure and organization; and dominant pattern of farm activities and household livelihoods, including field crops, livestock, trees, aquaculture, hunting and gathering, processing and off-farm activities; and taking into account the main technologies used, which determine the intensity of production and integration of crops, livestock and other activities.
Farming System Characterization involves an understanding of the structural and functional relationships of current farming systems in specific geographical areas and an identification of the constraints to achieving farmers’ goals. Analysis Farming System involves understanding how a system works implies knowing the parts (crop, livestock, and trees interactions) and how they relate to each other and to the environment (Dillon, Plucknet and Vallaeys, 1978). Farming systems are changing rapidly; the prices and availability of agricultural inputs vary, the cost and availability of labor fluctuates, marketing opportunities change, and the incidence of pests and disease may sometimes preclude the production of certain crops. Farming systems have changed substantially in recent decades. Their evolution is directly influenced by internal factors – notably the availability of resources and population growth – as well as by external factors such as markets, new technologies, support services, policies and information.
The bottleneck was the missing knowledge on the existing farming systems and their proportion in the total population of the provinces. Thus, farmers are forced to change their farming system or management practices when the environmental, economic, technical or social conditions change, particularly soil organic matters depletions, soil erosion, changing pattern in land use and socio-economic factors that pose a great threat in meeting the food requirement. Hence, it is required to prioritize agricultural production constraints and developing local solutions to ensure the long term productivity and sustainability of the systems. This signifies the optimization of various agricultural activities and their integration for multi-enterprise farming systems, development of sustainable farm practices to enhance resource use efficiencies under diverse farming situations and farm categories will be of paramount importance.
The decision to introduce changes or adopt any innovation depends entirely on how the household assesses the relative advantages and disadvantages in terms of its own perceptions and priorities. Because of these considerations, FSR is an interdisciplinary, integrative, problem-oriented and farmer-centered approach. In order to improve the productivity, profitability, and sustainability of smallholder farming system of area, Oromia Agricultural Research Institute has gone a long way to establish different research centers at different location. Because improving the productivity, profitability and sustainability of farming system is the main pathway out of poverty in using agriculture for development. Possible future events and emerging situations have not been systematically explored to the same extent farming systems in holistic manner with special reference to small and marginal farmers. Site specific system based resource management practices for sustained productivity and profitability.
Understanding the farming system and maintaining the balance in the complex set of farmer’s objectives are pertinent to outlining promising development strategies for such system Knowing about the farming system is also crucial to generate an appropriate technology that improves the livelihood of farming community and ensure food security. Most of the time proposed plans and programs without detail knowledge of the farming system of the area leads to wastage of resources and incompatible with farmer’s needs. So knowing farming system of one area is very important to recommend appropriate technologies to the farmer. It also helps biological researcher to design appropriate and problem addressing agricultural technologies that fit to the environment which is also important for further agricultural research and development.
The purposes of this study is to understand and describe the resource endowment, environmental, and biological circumstances and it also describe crop production practices, prioritize major constraints, and suggest possible technology interventions in the area.

1.1. Objectives
General objective of this study is to characterize and analyze the smallholder farmers existing farming systems of the area.

1.2 The specific objectives
 To assess and identify the production systems of the study area
 To identify and prioritize constraints of agricultural production of the study area and
 To identify and prioritize potential research intervention areas to harness the existing opportunities of the agricultural production farming system the study areas

2. RESEARCH METHODOLOGY
2.1. Description of the Study Areas
The research was conducted in West Arsi Zone. West Arsi Zone lies between 60 00’ N to 70 35‘N and 380 00’E to 400 00’E and demarcated by Bale Zone in west direction, Arsi Zone in East direction, Southern Nation Nationality and People Regional State in South direction, and East Shewa Zone in north direction. The Zone has 12 districts. Shashemane city is the capital city of West Arsi Zone and located at 250 km from Addis Ababa/Finfinnee towards South direction on Addis Ababa/Finfinnee-Hawassa main asphalt road.
West Arsi Zone encompasses different agro-ecologies namely high land, midland and lowland. In the Zone the high land agro-ecology (47.92%) took more coverage followed by midland (42.50%) and lowland (9.82%) agro-ecologies. The Zone lies within altitude of 1500-3800 meter above sea level.
The total population in the Zone was 2,290,280 of which 45.50% are male and 50.50% are female. The Zone was received 600mm-2700mm annual rain fall and has a bimodal pattern of rain fall. It was also received 12oC-27oC annual temperature per year. The Zone has a total of 1,286,277.50 hectare of land. From the total land, 0.36% is arable land, 29.27% cultivated land, 19.50% forest land, 17.05% grazing land, 4.58% used for construction and 29.26% used for other purposes.

Figure1 : Map of the study area

2.2. Sampling Procedures and Sampling
Multi-stage sampling procedure was applied to select representative districts, kebeles and sample households in West Arsi Zone. On the basis of agro-ecology diversity, representative districts, Kebeles and sample household was selected using systematic sampling technique. From the selected Kebeles, sample households were randomly selected for data collection. Probability Proportional to size used for sampling households. The sampling method was taken into consideration the age–sex composition, educational status, roles and responsibilities in the community. A multi-disciplinary team was established to conduct the survey using different PRA tools. Different PRA tools like direct interview, focus group discussions and personal observations were employed to collect information on different aspects of existing farming systems of the study area. The focus group discussion and key informant interview was undertaken before conducting survey. Focus group discussion and key informant interview were employed to get about the existing farming system, prevailing opportunities and constraints, with key informants (farmers, Development agents, and community leaders) in the study areas.
West Arsi Zone crop production farming system was stratified based agro-ecology and production characteristics depending on consultation workshop result that made with different experts at Zone levels and secondary data. West Arsi Zone farming system is clustered as highland barley belt, highland wheat belt, midland potato belt, and low land maize belt farming system. From each cluster one sample district and from each district four sample Kebeles were selected by using systematic randomly sampling method in each Zone. One FGD was undertaken per each selected district to collect data. A total of 8-10 farmers were selected based on their elder in the community, farming experience, gender, and educational background to conduct FGD and discussion was also made with concerned experts and Development agents at each selected Kebeles to conduct key informants interview. Finally, 264 sample households were selected for primary data collection.

2.3. Types of Data, Sources and Method of Data Collection
Both primary and secondary data was collected from different sources at different levels. Primary data was collected through focus group discussions, key informant interview and household’s interview using checklist and semi-structured questionnaire.
Secondary data were collected from different agricultural and natural resource development offices, trade and market development office, irrigation offices at different levels (Zones, districts, and Kebeles), different NGOs and stakeholders working in the areas, CSA reports, and different un published reports

2.4. Methods of Data Analysis
The collected data was analyzed using STATA version 14 software. The quantitative and qualitative data was analyzed using descriptive statistics like mean, standard deviations, frequency, chi square test and t-test to describe data and see the relationship between variables. The qualitative data collected through FGD and KII was also analyzed by narrating methods.

3. RESULTS AND DISCUSSION
3.1. Socioeconomic Characteristics and Resource Ownership of
3.2. Households
In the farming system analysis socioeconomics factor and household resource endowments play an important role in identifying and characterizing the farming system of a given area. The socioeconomics characteristics included age of household, marital status, education background, total family size, labor availability, and participation in non-farm and off-farm activities under this study. The study was conducted in West Arsi Zone.
The study result indicated that the majority (89.39%) of the sampled households are Muslims followers followed by Protestant (7.95%) and Orthodox (2.27%) and in the study areas. Around 92% of the sample households were male headed households (Table, 1).

Table 1. Description of categorical variables of sample households

In the study areas, farmers were categorized as model, middle, and resource poor based on their wealth status. The majority of the farmers were categorized under middle farmers in West Arsi Zone.
The mean age of the sampled households was 40 years in West Arsi Zone. The mean family members per household were 8 (Table, 2). The mean landholding of the farm households is 2.06 hectares in West Arsi Zone.

Table 2. Description of continues variables of sample households

3.3. Type of Houses Owned by Households
Shelter is one of the basic things that required in human life. There are different types of houses that owned by households in the study areas. Table 3 below indicated that about 49% of the households in West Arsi Zone owned grass roof houses and the remaining farmers owned both grass roof and iron corrugated sheet houses.

Table 3. Type of houses owned by the households in the study areas

3.4. The Land Use Patterns
Land is one of an important input in agricultural production. The study result revealed that the sampled households are allocated more lands for cultivation purpose (table, 4). In addition to this, they also allocated their lands for forest and grazing lands. The land degradation was also occurred due to miss-use of the land in the study areas. From focus group discussion and household level survey, there is no communal grazing land. A significant proportion of crop production was harvest by using rain fed agriculture whereas a small amount of crop production was harvested from irrigation based production. This is due to unavailability of irrigation water in the study area.

Table 4. The households land use system

3.5. Households’ Participation in Off/Non-Farm Activities and Food Security Status
The farmers in the study areas engaged in farm (crop) and off/non-farm activities to diversify and improve their livelihoods. The Household’s participated in off/non-farm activities in the study areas to generate income. The off/non-farm activities that households engaged to generate additional incomes are work as labor (causal) on other’s farm activity, trade, salaried worker as guard, petty trade and driving carts. The households participated more in trades (crop and livestock) to generate additional income in the study areas (table, 5).

Table 5. The type of off/ non-farm activities performed in the study areas
Off/non-farm activities West Arsi Zone

Food security status of the household was also assessed during this study whether the households are food secured throughout the year or not. The study result indicated, 59% of the sampled households were food unsecured in West Arsi Zone. The households cover up food shortage period through purchasing food from the market and getting aid from government food aid programs in the areas.

3.6. Institutional Facilities for Agricultural Production in West Arsi Zone
The institutional factors play a crucial role to increase agricultural production. These institutional facilities are irrigation facilities, communication facilities, extension services, credit facilities and market services.
Credit service is an important factor that increases agricultural production. The majority (67.42%) of the sample respondents did not get credit services in the two years period around. The reasons why households did get credit services are high interest rate, lack of collateral and religious influences. However, few respondents (33%) had access to credit services and used credit for purchasing agricultural inputs (fertilizers, improved seeds, and chemicals), purchasing animals for fattening/breeding and for purchasing food for home consumption. The major credit providers in the study areas were saving and credit association (40.40%), microfinance institutions (30%) and Non-governmental organizations (17.17%) respectively.

Table 6. Institutional facilities in the study Zone

Extension service is another institutional factor that affects agricultural production in the areas. Table 6 above indicated that the majority (89%) of the respondents get extension services on agricultural production. Most of the farmers got extension advices from development agents (93.42%), development agents and research center (4.18%), and development agents and NGOs (1.77%) in the study areas. The respondents got advice on fertilizer application, row planting, how to use improve seeds, weed management, and post-harvest handling.
In the study areas, the majority (75%) the households received market information in West Arsi Zone. The major sources of market information in West Arsi Zone were traders (28.46%), traders and neighboring farmers (18.29%), and neighboring farmers (16.26%) followed by union (1.22%) and cooperatives (1.22%). This result revealed the Union and Cooperatives are lees delivering market information for the farmers in the study areas.

3.7. Households Livelihood Diversification
The households in the study areas diversified their livelihood to different activities. The household livelihood diversification could be enterprise diversification or participation in off/non-farm activities. The sampled households livelihoods were majorly (74%) depend on mixed crop-livestock farming (crops production, crops and livestock production, only livestock rearing) activities followed by the combination of farming and off/non-farming (24.17%), and off/non-farming (2.02%) activities.
Even though there is high diversity in important enterprises, the major livelihoods in all farming systems were crop production, cattle, small ruminants (sheep for mid and highland areas and goats for lowland pastoral/agro-pastoral, poultry and off-farm activities. But in each sub-farming system there is a kind of specialization on different enterprises and off-farm activities especially where there were shortage of land both for livestock keeping and crop production.
The small ruminant production/ rearing (sheep and goat) activities were dominant in lowland agro-ecologies of West Arsi Zone with the mean of 4.2 respectively. Therefore, attention should be to small ruminant to improve the development of each sub-sector. In all agro-ecologies cattle and poultry were taken as crucial enterprise so due attention must be given for enterprises to improve the production and enhance the livelihood of the farmers.

3.8. Households’ Farm Labor Availability
Many of the subsistence farming used family labor for agricultural production. The majority of the farmers in the study areas used family for agricultural production. The farmers in the study areas used labor exchange, employing casual labor, and hired labor during labor shortage and busy working time.

Table 7. Labor availability in West Arsi Zone

3.9. The Farming System of West Arsi Zone
The farming system of West Arsi Zone is totally mixed crop-livestock farming system. These mixed crop-livestock farming system is dominant in all agro ecologies (Highland, midland and low land) of the Zones. The crop-livestock mixed farming is clustered into two sub-farming clusters as potato-haricot bean based and cereal based farming. The cereal sub-cluster is also further clustered into food barley-malt barley belt, wheat-teff belt and maize belt farming system. There is also further clustering based on number of cropping per a year as double cropping and single cropping. All of cereal sub-cluster are double cropping because they have two rain fed cropping seasons except maize based. Potato-haricot bean based farming is also double cropping, even potato belt area produce triple without any irrigation access.

Figure 1. Classification of farming system in West Arsi Zone

3.9.1. Characteristics of sub- clusters farming system
Under this sub chapter, potato-Haricot bean based, maize-wheat based, food-malt barley based and maize farming systems with their respective constraints are discussed in detail.

3.9.1.1. Potato-Haricot bean based farming system
This farming system is found in highland and midlands of Shashemane, Kofale, Shalla and Siraro districts of West Arsi Zone. The major crops produced in this sub-cluster are potato, haricot bean, wheat, teff, maize, millet, finger millet and other vegetables. Potato was used as rotational crops for cereal crops to maintain the fertility of soil especially with wheat and teff whereas; haricot-bean used as intercropping crops with maize. Potato is the first leading cash crop produced in large amount in these sub-clusters farming system whereas haricot bean is the second major cash crop produced next to potato. Both Potato and haricot bean are cash crops and produced and supplied to the market. In mean time both of them used for household home consumption.
Potato is the most favorable sub-enterprise in this sub-cluster and it accounts for about 40% of total land allocation (0.64ha for potato production from 1.60ha of total cultivated land) of the total farm land followed by haricot bean which accounts about 17% of total land. Pulse crops like faba bean, lentils, and field peas were also grown on considerable size of farmland cultivated land. Mean productivity of potato was 103 quintal per hectare while Haricot bean was 10.23 quintal her hectare. Livestock production especially cattle breeding, sheep, dairy production and beekeeping were also the most important enterprises in this sub-cluster farming system.
Potato is produced for the purpose of consumption and sale in this farming cluster. From total sample respondents, 42.86% of them perceived that trends of potato production in the past five years were increasing. In this sub-cluster farming system majorities of potato producers produce potato by rain-fed and only 4.17% use irrigation. Both local and improved varieties were used for potato production in this farming cluster. Currently, improved potato varieties being grown in are Gudane, Jalane and Kulumsa whereas, the major local varieties grown are Agazer, Bule, Nech ababa, Dima, Key ababa, China and Durame. From local varieties grown Bule is the most commonly known for home consumption whereas, Agazer was commonly known for market. Farmers look for specific traits and characteristics which suit their production and marketing situations when choosing varieties for production.

Major production constraints of the sub-cluster
Index ranking was employed to prioritize the major production constraints of the sub-sector during focus group discussion (FGD) with farmers and discussion with agricultural experts at district level. The result further attests that the major opportunities of production in this farming system are good weather condition, good infrastructure and good market availability while, the major constraints of production are unavailability of quality seed at the right time, lack of cash and credit, lack of irrigation, poor input supply such as chemicals and fertilizers, lack of modern storage, disease and insect incidence, market problem and climate change (drought). According to the sample respondents, 79.19% of respondents used traditional storage mechanism (dark space in the house, ground bin (Gotera), spread outside the house and covers it with crop residues, inset leaf and others) whereas, 15.83% of the sample respondents practiced postponed storage mechanism (farmers store seed potato by leaving the tubers in the soil un-harvested/ delay harvesting) in this sub-cluster farming system.
The major reasons for discontinuing use of improved potato varieties are unavailability of quality seeds at the right time, high seed price and hence unaffordable to most subsistence potato producers, unavailability of credit access (in kind), low yield, diseases and pest problem. In general, fear of market risks, unavailability of quality seeds at the right time (supply shortage) and financial constraints were some of the reasons for discontinuing use of improved potato varieties. As a result, most sample farmers planted improved potato varieties in combination with local potato varieties.
In general about eight production constraints of this sub-cluster were identified by farmers and they were ranked according to their importance. In root-crop production the major constraint was mentioned to be storage and market related. The perish ability nature of the crop and lack of storage or processing technologies lead the producers to sell their produce at unreasonably lower price during peak production seasons and huge postharvest losses (table, 8).