Analysis of the causes of low adoption in less developed agrifood chains: the
case of potato supply chain in the Upper Rift Valley region of Ethiopia
Gumataw K. Abebe1, 2, Jos Bijman1, Stefano Pascucci1, Onno Omta1, Admasu Tsegaye3
1
Wageningen University, Management Studies Group, Hollandseweg 1, 6706 KN Wageningen, The
Netherlands, gumataw.abebe@wur.nl; 2 Hawassa University; 3Addis Ababa University, Ethiopia.
Abstract
The main purpose of study was to analyse the causes of low adoption for the released potato
varieties (RVs) by the ware potato growers in the Upper Rift Valley Region of Ethiopia. The
study systematically analyzed the main production and market-related quality characteristics
of both the RVs and the local varieties (LVs), and how information on product quality is
exchanged and controlled in the chain. To achieve this objective, data were collected from a
total of 460 ware potato growers (346 in the first round and 114 in the second round) and 34
downstream actors. The result shows that while the RVs are preferred for their productionrelated characteristics, the LVs are more preferred for their market-related characteristics. In
this situation, growers opt to grow the dominant LVs in order to align (match) their
production decision with the quality requirements of downstream actors. This result
contributes to the existing theory of technology adoption, which has largely focused on
individual characteristics, that market conditions are important factors in improving the
likelihood of technology adoption. The implication for research/policy is that there is need to
change the existing top-down system of technology adoption to include the local knowledge
into the breeding programs of research institutions.
Key words: quality, alignment, local knowledge, adoption, Ethiopia, potato, supply chain
1. Introduction
In an effort to improve the performance of the potato sector, the Ethiopian Institute of
Agricultural Research (EIAR) introduced around 18 improved potato varieties in the last two
decades. However, the rate of adoption1 for those released varieties by ware potato growers
was very low compared to the so called “local2” varieties. Data from a national representative
survey of over 8000 households revealed that the use of improved potato seed varieties in
Ethiopia is about 0.5% (ESCS 2005). The problem of low adoption is not only limited to
potato, it also extends to other crops in Ethiopia (McGuire, 2005; Byerlee et al., 2007; Abate
et al., 2011). For example, in the 2005 crop season, 98% of all the seeds used for planting
were local seeds carried over from the previous harvest.
However, the existing low utilization of improved potato varieties has to be changed for a
number of reasons. First, potato (Solanum tuberosum L.) is a rapidly expanding crop in
Ethiopia (Mulatu et al., 2005) with the potential to grow in the 70% (10M ha) of the arable
land (FAO 2008). Second, since the Ethiopian government considers potato as a strategic
crop, a lot of public money is being spent on potato research. Third, it has increasingly
become an important source of cash for farmers (Gildemacher et al., 2009). Fourth, potato
yields high productivity per unit of area and time; and hence is one of the key crops for food
1
refers to the ware potato growers (not in the context of seed potato growers)
Varieties that were not released from research centers but happened to be grown for many years in certain areas of the
potato growing regions. No information was available on how and when these varieties were first introduced.
2
1
security in response to the growing population. And finally, Ethiopia is strategically
positioned to trade with the Middle East, the EU and the neighbouring African countries;
hence, improved potato varieties are needed to address the needs of local and international
customers.
Although the problem of low adoption is well recognized by the EIAR, the causes for the low
adoption is not yet empirically investigated. The EIAR cites shortage of “improved” seed and
poor seed supply system as the main limiting factors (i.e., supply side constraint,
Gebremedhin et al., 2008). However, the lack of understanding about the underlying problems
of low adoption can only put further scrutiny in the existing research – farmer relationship.
We argue that the problem of the low adoption, to a larger extent, relate to the market
conditions that the potato research centers fail to include in their breeding programs.
Contributing to the problem of low adoption is the lack of (insufficient) information exchange
between the research centers and the farmers. In the absence of proper information exchange
about the quality characteristics of the released varieties, farmers may have difficulties to
understand the quality management practices that need to be followed. Hence, the uncertainty
surrounding the characteristics of the new technology3 may force farmers to continue growing
the LVs in which they have full knowledge of all the necessary agricultural practices.
The paper may add to the existing literature in the following ways. First, although voluminous
of literature exist on the problem of low adoption, most of the studies focus on endogenous
factors (individual characteristics of the adopter, Kevane, 1996). Of the endogenous factors,
risk appetite of the adopter is considered a key determinant for low adoption (Abadi Ghadim
and Pannel, 1999; Feder and Umali, 1993). However, implicit to this assumption is that the
technology being adopted or the knowledge transfer system is correct. For example, Sall et al.
(2000) claim that the literature has omitted some critical factors related to adoption and found
out that exposure to information, membership in an organization, growing cycle, cooking
quality, height of the variety and initial impression of the variety were important factors for
rice variety adoption. We attempt to add to this strand of the literature by examining some
exogenous factors (from a supply chain perspective) that may lead to the problem of low
adoption.
Second, from the perspective of intensifying smallholder participation to a high value market,
this paper provide answers on how quality is viewed and information about product quality
characteristics is exchanged in less developed agrifood chains. Understanding of such
indigenous quality control and information exchange mechanisms could serve as a
springboard to find options for improving the performance of local supply chains. Indigenous
quality control and information exchange mechanisms involving smallholder farmers have
received little attention. In this regard, evidence from the potato supply chain is a good case in
point: (1) as potatoes are produced and supplied by a large number of smallholder farmers in
many developing countries; (2) due to the nature of the crop (perishable, bulky and costly due
to a large volume of planting material needed), potato production and marketing requires high
level of coordination; and (3) there is a rising urban population and an increasing demand for
high quality potatoes in many developing countries (Kaganzi et al., 2009; Devaux et al.,
2009).
3
Technology is used in this paper to refer to new varieties released from the research centers
2
To analyse the causes for low adoption , we set the following specific research questions. (1)
How the quality of existing potato varieties is characterised using farmers’ knowledge? Is
there any significant quality difference between the main LVs and the RVs? (2) How the
quality characteristics of the LVs and RVs are aligned4 to the potato growers’ production and
market decisions and the quality preferences of downstream actors? (3) What quality control
and information exchange mechanisms are used in the potato supply chain?
Concepts from product quality, indigenous knowledge and agricultural innovation systems are
used to understand the causes of low adoption by systematically analysing the main
production and market-related quality characteristics of both the RVs and the LVs, and how
information on product quality is exchanged and controlled in less developed agrifood chains.
The remaining sections of the paper are organized as follows. Section two provides some
background information about the organization of agricultural research and extension systems
in Ethiopia and the relationship between the different actors in the potato supply chain. The
subsequent sections present the literature review, methodology, results and discussion and
conclusions.
2. Background
2.1.Overview of the agricultural research and extension systems in Ethiopia
Agricultural research in Ethiopia was initiated in the 1940’s and later evolved into an
organized form in the 1960’s with the establishment of the then Institute of Agricultural
Research (IAR) in 1966. The Ethiopian Agricultural Researches (EARS) consist of three
actors – the Ethiopian Institute of Agricultural Research (EIAR), the Regional Agricultural
Research Institutes (RARIs), and Higher Learning Institutions (HLIs). The EIAR is
responsible for the supply of improved agricultural technologies, popularization of improved
technologies, coordination of the national agricultural researches, and capacity building of
researchers (www.eiar.gov.et). The EIAR carries out about 86% of the total public
agricultural research activities in the country.
Despite the claim that public sector investment in agricultural research has declined in many
African countries, the 2008 figure put Ethiopia as the 7th largest country in agricultural R&D
investment (USD 69 million) and the second largest in terms of employing fulltime research
staff in Africa (Beintema and Stads, 2011). Similarly, Spielman et al., (2010) reported over 50
million USD (2% of GDP) is being spent every year related to agricultural extension services.
Agricultural research centers in Ethiopia pay little attention on researches related to value
chain development (Abate et al., 2011). In areas where research is carried out, technology
adoption has been slow, crop yields are very low and no sustained breakthroughs are seen
(Abate et al., 2011). Extension is the principal model used for knowledge transfer. However,
primary data collected from extension workers and farmers reveal that the unidirectional
model of extension systems in Ethiopia failed to live up to the expectation that the extension
model (1) has not been participatory, (2) gives little consideration to farmers’ experiences and
knowledge, (3) extension workers lack up-to-date training, and (4) often faces with the
problem of elite capture (biasness towards the richer farmers) (Belay, 2003, 2004).
4
Alignment is used in this paper in the context of matching of preferences
3
2.2.Overview of the Ethiopian potato supply chain
In this section we briefly explain the Ethiopian potato supply chain and the major actors.
a. Research
Center
b. Specialized
seed growers
i. Hotels,
restaurants
The weakest link
c. Informal
seed market
d. Ware
Growers
e. Collecting
wholesalers
f. Stationed
wholesalers
g. Retailers
h. Household
consumers
Fig. 1 Schematic representation of the dominant potato supply
chain
a. Research center - the Potato Research Division of national or regional research centers
are responsible to disseminate the technology to the potato growers. Accordingly, newly
released varieties are delivered to selected potato farmers called “specialized seed
growers”. The improved seed is then multiplied by the seed growers with the intention of
further disseminating the technology to the ware potato growers. There is a close link
between the research division and the specialized seed growers.
b. Specialized seed growers – These are seed growers organized as farmer field schools
(FFS), farmer research groups (FRG) or seed cooperatives by the potato research division
in the highland areas. They get improved seed from the national or regional research
center (as a gift). After multiplication, the specialized seed growers largely sell the seed to
NGOs and agriculture offices who in turn give the seed to the ware potato growers in
other regions. So far the role of traders (wholesalers and retailers) in linking the
specialized seed growers with the ware potato growers has been very minimal.
c. The informal seed market- This is the market where the majority of ware potato growers
source potatoes to be used as seed. Over 98% of ware potato growers’ buy seed from
informal sources (Gildemacher et al., 2009). For the informal market, the name of the
variety and the area of production are important for the ware potato growers.
d. Ware potatoes growers - There are two types of potato growers in the region subsistence and commercial growers. The subsistence growers grow in a small plot of
land and use potato for household consumption and to generate some cash by selling into
the immediate (nearby) markets. When the subsistence farmers sell their potato to the
nearby markets they are often forced to sell via town middlemen. The commercial
growers on the other hand are highly market oriented and produce at larger volume. They
sell at farm gate to long distance traders (collecting wholesalers). They often use the
institution of (rural) middlemen to purchase potatoes from growers. The rural middlemen
unlike that of town middlemen live close to the growers and are either have family ties or
belong to same clan with those growers. Most of the ware potatoes are sold at farm gate.
e. Collecting wholesalers – they are long distance traders located close to the potato
growing regions. They buy directly from growers and supply to the central market and to
other major cities in the country. They mostly purchase potatoes from (commercial)
growers at farm gate.
4
f. Stationed wholesalers – These are the buyers located at the central market. They buy
potatoes from collecting wholesaler in bulk and then resale to retailers, hotels, restaurants,
and cafes.
g. Retailers –small traders that buy potatoes in smaller quantity from wholesalers located at
the central market place and who ultimately sell to household consumers.
3. Conceptual framework
Fig 2. Presents the conceptual framework of this paper. Having this conceptual framework in
mind, we explain the relationship between the different boxes using the literature from
product quality, indigenous knowledge and agricultural innovation systems.
A
B
Varieties
Quality characteristics
Released
Local
C
Quality preferences
Production related
Market related
Fig 2. Conceptual framework
Research centers
D
F
Growers
E
Buyers
3.1. Quality perception in agrifood supply chains
Quality is an elusive concept as it is difficult to measure as it depends on many factors, like
the nature of the product, the user of the product and the market situation (Sloof et al., 1996).
Defining quality from a supply chain perspective is even more problematic as different chain
actors may view quality differently based on what characteristics of the product they find
more or less important (see table 1).
Table 1. Interpretation of quality by various chain actors
Actor
Quality aspects
Breeder:
vitality of seed, yield
Grower:
yield, uniformity, disease resistance
Distributor:
shelf life, availability, sensitivity to damage
Retailer:
shelf life, diversity, exterior, little waste
Consumer:
Taste, healthy, perishable, convenience, constant quality
Source: Ruben et al., 2007 p. 30
The literature provides different approaches to study quality (the transcendent, production
management, economics, perceived quality - see Steenkamp, 1989:7). The literature often
define product quality in terms of its intrinsic (properties which cannot be changed without
altering the physical properties of the product – e.g., colour, firmness) and extrinsic
characteristics (properties that are product related but not part of the product –e.g., brand
names, price, Luning et al., 2002). Sloof et al. (1996) provided the distinction between
intrinsic and extrinsic properties in terms of assigned quality of a product and acceptability of
a product. Assigned quality is a result of the evaluation of the intrinsic properties of a product
and reflects the needs and goals of a user, without referring to the extrinsic properties of a
product. On the other hand, acceptability of a product is a combined effect of assigned
5
quality, extrinsic product properties and market condition. According to Sloof et al., (1996),
assigned quality may change because of changes in the criteria or changes on product
properties.
Following the above conceptualization of quality, Sloof et al., (1996) developed a quality
assignment model (QAM) (see Fig. 3). According to the model, intrinsic product properties
constitute the state of the product and are evaluated based on quality criteria imposed by a
producer or a user of the product. The QAM is based on only intrinsic quality attributes and
describes how a group of users assign quality to a particular product. Assignment of quality to
a product’s intrinsic quality attributes takes three steps: (1) perception of intrinsic properties
(using instruments or human senses); (2) evaluation of perceived quality attributes (using
instruments or human senses to determine the values); (3) appreciation of individual quality
attributes to give a uni-dimentional quality measure. Appreciation is a state of the mind. At
the latter step, weights are given to individual quality attributes or to a combination of quality
attributes. The weights may reflect the influence of socio-psychological factors determining
the attributes to be used and the order of importance of these attributes.
Intrinsic
properties
Perception
Evaluation
Appreciation
Assigned
quality
Fig.3 Quality assignment model (Sloof et al., 1996)
Referring to our conceptual framework (fig.2), B refers to the intrinsic quality characteristics
attached to each variety A. Because the definition of quality varieties depending on which
level of the chain the actor is, we grouped quality into two: production-related (production
management approach) and market-related (consumer research approach). Quality
characteristics such as yield, disease tolerance, days to mature, drought resistance, and
management characteristics are production related. On the other hand, tuber size, stew quality,
cooking quality, colour, shape, and shelf life are market related (refer table 1). The arrow
from A to B shows how potato variety (genotype), to a large extent, determines intrinsic
quality characteristics (Richardson, 1973; Howard, 1974; Long et al., 2004; Jemison et al.,
2008). These characterises are the property of the product and can be independently
determined through perception (e.g. by way of using them for many years) and evaluation.
The arrow from A to B will also help us to see whether the quality characteristics of the
different varieties, particularly those of the local and the released ones, are indeed
significantly differ as it was set in our research question 1 (section 1). Box C shows quality
preferences of the different actors. As per the QAM, quality preferences are the assigned
weights after evaluation and appreciation phases. However, in this case, the order of
importance for the different quality attributes may differ based individuals’ appreciation of a
particular characteristics of the product (for example some may prefer tuber size in relation to
the colour of potatoes and others may think differently). Identification of the quality
preferences of the different actors is critical at this stage in order to evaluate the presence of
misalignment or mismatch in preferences between the different actors (as indicated in our
research question 2, section 1).
In less developed agrifood supply chains, the problem is not only how quality is defined but
also how it is communicated. As rural economies become increasingly linked to urban and
export markets (Reardon et al., 2009), consumers’ demand for product quality information
increases (Reardon et al., 2001). However, in this era of liberalized domestic markets and
6
abolished state marketing institutions, it may be costly for the private actors to implement and
enforce formal quality control systems (such as grades and standards) for products delivered
by smallholder farmers. Hence, in less developed agrifood chains, product quality is often
judged on the spot and regulated by personal contact and informal institutions. In situations
where the markets are entirely rural and local, informal quality control mechanisms may be
used to improve the quality alignment in those supply chains (Reardon et al., 2001).
In our conceptual framework (fig. 2), the double arrows at D & E show the ideal information
flow from/to research centers to growers and buyers about the quality preferences at C. In this
regard, different information exchange mechanisms (such as variety name, production region,
etc.) may be used. Research question 3 is set to examine this relationship. If there is an
alignment (as indicated by a line) between the preferences of the three major actors, then the
improved varieties released from research centers should meet the quality requirements of
both the growers and buyers.
The role of indigenous knowledge (IK) and its implication for agricultural research
Sillitoe (1998), Sillitoe and Marzano (2009) provide an extensive review regarding IK. They
argue that research based on IK recognizes the complexity of local decision processes and
tries to integrate the local knowledge into scientific perspective. While IK lacks homogeneity
between cultures, age group, gender, and social class and is being criticised due to its lack of
defined theory providing a coherent and structured methodology, there is a growing consensus
in the literature that the interplay between science (agricultural research) and IK could lead to
a higher success rate for development projects involving smallholder farmers (Sillitoe, 1998;
Mosse, 2005; Sillitoe and Marzano, 2009). The importance of IK has long been recognized in
the field of medicine, botany, and zoology, particularly, to study taxonomic systems (i.e.,
human beings classification abilities) (Sillitoe, 1998). IK initiatives facilitate more successful
interventions through creating better understanding of local situations. Many development
programs in developing countries failed due to the use of “top-down” approaches that lack
local roots (Sillitoe and Marzano, 2009). Perhaps, in recognition to the shortcomings of this
approach, “bottom-up” paradigms, such as incorporating indigenous knowledge in scientific
studies, gradually started to take shape5.
The need for a bottom-up approach in agricultural research lies on the view that poor farmers
living in less developing countries have failed to benefit from the agricultural research outputs
as expected (Sumberg, et al, 2003). Hence, there is a renewed interest about the importance of
indigenous knowledge and end-user participation in agricultural research (Beintema and
Stads, 2011). There are generally two views on agricultural research in the literature. One
view relates to the “central source model” which assumes farmers as passive recipients of new
technology and hence follows a unidirectional flow of research, extension and adoption
process. According to Biggs (1990) – innovations are seen to arise from international
research centers then passed down to national research systems, extension agencies and
finally to farmers. In contrast, in the “multiple source model” of innovation, farmers are
considered as active innovators and information flow is multi-directional. The main feature of
the multiple source model is its acknowledgment that agricultural research and technology
promotion systems contain diverse objectives of different actors (Biggs, 1990).
In this paper, local knowledge, indigenous knowledge or farmers’ knowledge are interchangeable used
(Sillitoe, 1998).
5
7
In line with the central view model, the innovation diffusion theory (Rogers, 1983) has been
dominant for several decades. However, Biggs (1990) and the literature of Agricultural
Knowledge Information Systems (AKIS) highlight the need for integrating the local
knowledge and local processes of innovation with formal research activities. The main
argument behind this notion is that farmers have an intimate knowledge of their local
environment, conditions, problems, priorities and criteria for evaluation as part of their
farming routine than anybody else. Sumberg et al. (2003) propose some hypotheses under
what condition farmers’ (users of the technology) participation is most likely to be beneficial.
According to Sumberg et al. (2003), when the formal research and farmers’ research are
partially substitutable, no synergy effect is anticipated from participation (the additive model).
On the other hand, when there is heterophily6 between research paradigms, objectives and
methods, there is a possibility for synergy effects (the synergy model). Sumberg et al (2003)
uses the synergy model to draw the following hypotheses (table 2).
Table 2. Hypothesised relationship between heterophily and potential synergy
Degree of heterophily
Potential for synergy
Low
Low
Intermediate
High
High
Low
In our conceptual framework (fig. 2), farmers’ indigenous knowledge is introduced to
characterize the production and market related characteristics of the local and released
varieties (A). This characterization serves as a base for identifying quality preferences of both
growers and buyers. The double arrows between E & D are intended to show the importance
of participatory (bottom-up) approaches in agricultural research as suggested in the multiple
source model. This increases the likelihood of farmers’ decision to adopt the improved
varieties.
4. Methodology
Data has been collected in the context of the Ethiopia potato supply chain, with a particular
emphasis in one region. This is because variety names in Ethiopia lack standardization and are
mainly attached to local languages. Even the RVs are given local names (Cavatassi et al.,
2011). This made it difficult to know if various names refer to the same or different
genotypes. Our research design was, therefore, to focus on one region, in fact the most
important potato production region in the country, in order to avoid any problem arising from
confusion of names for possibly the same variety.
As introduced in section 1, the paper provides answers to the following research questions. (1)
How the quality of existing potato varieties is characterised using farmers’ knowledge? Is
there any significant quality difference between the main LVs and RVs? (2) How the quality
characteristics of the LVs and RVs are aligned to the potato growers’ production and market
decisions and the quality preferences of downstream actors? (3) What quality control and
information exchange mechanisms are used in the potato supply chain?
This section provides the data sources, data collection and the analytical procedures and
methods employed to answer the above research questions.
6
the degree to which two or more individuals who interact are different in certain attributes (in terms of beliefs,
education, social status, and the like) (Rogers, 1983).
8
In order to answer research question 1, data were collected from a total of 346 potato growers.
The main objective of this part of the study was to uncover the most important quality
attributes each variety possesses, not the variety per se.
Characterisation of the different potato varieties was made in the following manner. First,
variety classification was based on variety names and was made by farmers, triangulated with
information from agricultural agents, secondary data and focus group discussions. Farmer
based classification is important in understanding varietal choices (Cavatassi et al., 2011).
Following this classification, we documented seven potato varieties. Second, in an attempt to
establish relationship between variety and quality, we followed two dimensions for assessing
quality - production and market-related.


Measures for quality characteristics related to production
 Productivity/yield – Kg/Timad (=0.25ha)
 Disease resistance –very low to very high (1-5)
 Drought resistance – very low to very high (1-5)
 Intensity of quality management practices – very low to very high (1-5)
 Maturity period – in days
Measures for quality characteristics related to marketing
 Keeping ability – in weeks
 Tuber size – very small to very large (1-5)
 Tuber shape – full round, semi oval, oval (1-3)
 Cooking quality – very low to very high (1-5)
 Stew quality – very low to very high (1-5)
Even though variety names are short-lived and can simply die out, our systematic approach
allowed us to understand the relatively stable quality characteristics each variety possesses.
Third, growers were asked to evaluate different varieties on their production-related quality
attributes and market-related quality attributes. The quality characteristics were identified by
reviewing the literature on potato quality (Richardson, 1973; Howard, 1974; Long et al.,
2004; Jemison et al., 2008) and after assessing their relevance to the local context in a pilot
study.
Our conceptualization of quality follows the definition given by, among others, Lancaster
(1966, 1971) where he defines quality as a function of objectively measurable properties of
goods. He further argues that a good possesses multiple characteristics and many
characteristics will be shared by more than one good. Unobservable characteristics of potatoes
were not considered in our analysis as information on these attributes is rarely conveyed along
the chain. Molnar and Orsi (1982) suggest that it is not necessary to investigate every property
of a product but only those important ones required to determine product quality.
To answer the second research question, we needed to understand the quality preferences of
the different chain actors. The characterisation of varieties in the first part was simply to
obtain an account of how farmers perceive a particular variety and was not meant to indicate
individual preferences. In this part of the study, we were interested to know individual
preferences for the different quality attributes. Growers were asked to allocate 100 points to
the different production related quality characteristics. This follows the quality assignment
model (fig. 3) that farmers (users) first perceive and evaluate the different varieties (as it was
done in question 1) using their experiences. Then appreciation follows in order to provide
weights for the different quality measures (ranging from 0 to 100 points). These weights are
assumed to reflect individual preferences and may vary from person to person based on a
number of factors. For this part of the study, we collected additional data from a randomly
9
selected 114 potato growers regarding their preferences to production-related attributes.
Similarly, downstream actors were asked to give their preferences as to the market-related
quality characteristics. Because collecting wholesalers largely supply potatoes to the central
market, Addis Ababa, we purposely selected buyers at the central market. Accordingly we
were able to collect data from 10 major wholesalers (from a population of about 26
wholesalers), 13 retailers and 11 hotels stationed in the capital who were willing to share the
information we needed.
The questions for growers were stated as “Please distribute 100 points over the different quality
attributes that you may take into account when you select a particular potato variety to grow. Give the
highest value to the most important quality attribute, the second highest value to the second most
important quality attribute, etc. The total of all values should be equal to 100 points”. Similarly, the
questions for downstream actors were stated as “Please distribute 100 points over the different quality
attributes that you may take into account when you are buying potatoes. Give the highest value to the
most important quality attribute, the second highest value to the second most important quality
attribute, etc. The total of all values should be equal to100 points”
For the third research question, both the growers and the downstream actors were asked to
choose what kind of information exchange mechanisms they use to identify the quality of
potatoes when they sell/or buy. Moreover, the growers were asked about the kind of quality
control mechanisms they use in their relationship with the collecting wholesalers.
The survey was conducted in person using structured questionnaire by trained personnel, who
had a first degree either in sociology or management. Supervision and quality checks were
made on the spot by the principal investigator.
5. Results
5.1.Growers’ evaluation of quality characteristics
5.1.1. Characteristics of the sampled potato growers
Table 3 provides the main characteristics of the study areas and the surveyed growers. The
distribution of sub districts and growers included in the survey follow the patterns in the level
of production and the type of potato variety grown. Since our focus was on household heads,
only 14 women headed households happened to be included in the random sample. From the
result, the average age (year), education level (school year), land (ha) and livestock (TLU)
owned were 37, 6, 1.5, and 8.1, respectively. About 56% of sampled potato growers lived in a
house with a corrugated iron sheet. The descriptive statistic also shows a dependency ratio of
1.3 and an average family size of 10. Over 33% of the respondents had two or more wives.
Compared to the sample average, those growers practicing polygamy were older farmers (42
years of age) and less educated (4 school years) with an average family size of 14. In terms of
access to information, 67% and 65% of surveyed growers reported to have a mobile phone
and radio respectively. Potato farming on average generated about 50% of the total cash
income for the sampled households. There is low agro-ecological variability between the three
districts in the sample.
10
Table 3. Characteristics of the study areas and sampled growers
General information
Sub districts (Kebeles)
Agro ecology (altitude above sea level in meters)
No. of growers in the sample
Personal and household characteristics
Sex
Male
Female
Marital status
Unmarried
Widow
Married (1 wife)
Married (>=2 wives)
Position of the respondent
Head of the household
Other
Age (years)
Family size
Education of the respondent (years in school)
Highest education in the family (years in school)
Dependency ratio{(<=14yr+>64yr)/(15-64 yr)}
Wealth (as approximated by)
At least a house with corrugated iron sheet (% yes)
Land (owned) in ha
Domestic animals in equivalent unit (TLU7)
Having a mobile phone (% yes)
Having a radio (% yes)
Having a TV (% yes)
Cash income from potato sales* (previous year)
Mean value (in ETB**)
% of potato cash income (from total cash income)
Distance to the central market, Addis Ababa (km)
Total
16
346
Shashemene
8
1700 - 2300
228
Siraro
5
1500 -1900
75
Shala
3
1500 - 2075
43
332
14
214
14
75
0
43
0
12
1
218
115
9
1
159
59
1
0
39
35
2
0
20
21
342
4
36.8
9.6
5.7
8.3
1.3
224
4
37.8
9.1
6.4
9.3
1.2
75
0
35.7
10.3
4.1
6.3
1.4
43
0
33.6
11.0
4.5
6.4
1.5
55.8
1.5
8.1
66.8
65.0
9.5
67.5
1.2
4.9
66.2
69.3
12.3
28.0
2.1
11.0
60.0
53.3
1.3
41.9
2.1
19.9
81.4
62.8
9.3
9,905
49
6,233
40
250
13,324
65
300
23,412
68
280
* Potatoes not sold till the time of the interview were not included; **1€ ~23ETB
5.1.2. Characterising varieties using farmers’ knowledge
Before we assess the mean scores given by the growers, we first present their knowledge on
the different quality attributes following the QAM discussed in section 3. Hence, table 4 and
5 present the percentage of sampled growers who had knowledge on the production and
marketing related quality characteristics of the different varieties respectively. The LVs Nechi
Abeba, Agazer, and Key Dinich were common to the majority of potato growers. Of these, the
production and market characteristics of Nechi Abeba seem overwhelmingly known by
growers followed by Agazer than particularly those of the three released varieties (Bule,
Gudane, and Jalene). We believe that the number of growers who had knowledge on each
variety was fair enough to make the characterisation on the seven varieties. Moreover, we
focused on observable quality characteristics which would make it easier for the growers’
evaluation task.
7
Tropical livestock units, used as a common unit to describe livestock numbers of various species as a single figure that
expresses the total amount of livestock present. Accordingly oxen/cow=1TLU; Calf=0.25TLU; Heifer=0.75TLU;
sheep/goat=0.13TLU; Young sheep/goat=0.06TLU;donkey=0.7TLU
11
Table 4. Growers’ knowledge on the production related quality characteristics (PRQCs)
Yield
of
57
89
38
25
12
22
5
Do you know the
Agazer?
Nechi Abeba?
Key Dinich?
Key Abeba?
Gudane?
Jalene?
Bule?
Percent Yes (N=346)
Disease
Drought
tolerance of
tolerance of
71
72
99
98
64
62
64
59
22
20
39
32
21
19
Maturity day
of
72
99
65
60
23
38
21
Management
intensity of
71
98
62
54
21
35
17
Table 5. Growers’ knowledge on the market related quality characteristics (MRQCs)
% Yes (N=346)
Do you know the
Agazer?
Nechi Abeba?
Key Dinich?
Key Abeba?
Gudane*?
Jalene*?
Bule*?
Cooking quality of
77
99
72
69
25
41
34
Keeping ability of
62
89
53
47
16
27
14
Stew quality of
75
99
69
64
19
37
29
Taste of
78
99
72
67
25
41
34
Tuber size of
79
99
77
73
31
50
36
*released varieties
5.1.2.1.Evaluation of production related quality characteristics(PRQCs)
Evaluation of the PRQCs is reported on table 6. Accordingly, the yield per “Timad” was
highest for the RVs Jalene (JL) and Gudane (GD) followed by the LVs Nechi Abeba (NA)
and Agazer (AZ). Key Abeba (KA) and Key Dinich (KD) were the lowest yielding varieties
as reported by sampled growers. The RVs, with the exception of Bule (BL), were better with
respect to yield characteristics. In terms of disease tolerance, the mean scores of RVs are
higher than the LVs. This is, of course, not a surprising result given the focus of the research
institutions on yield and disease tolerance aspects.
Table 6. Average results of PRQCs as evaluated by growers
Variety
AZ
NA
KD
KA
GD*
JL*
BL*
N
Chi-Square
df
Asymp. sig
Yield
(100kg per
Timad)
26.5 (10.5)
31.2 (11.8)
21.7 (8.3)
21.5 (7.8)
43.8 (18.3)
45.7 (20.1)
24.4 (11.9)
24
34.46
3
.000
Days to maturity
(No. of days)
88 (10)
101 (15)
70 (11)
82 (15)
122 (16)
123 (18)
112 (20)
67
157.594
3
.000
Tolerance to
disease Scale
(1-5)
3.7 (1.2)
3.5 (1.2)
2.6 (1.2)
1.8 (0.9)
4.1 (1.0)
4.2 (1.2)
3.8 (1.1)
63
43.57
3
.000
Tolerance to
drought
Scale (1-5)
3.8 (1.1)
3.9 (1.2)
2.8 (1.2)
2.2 (1.1)
3.8 (1.2)
3.7 (1.3)
3.5 (1.4)
56
2.56
3
.464
Management
intensity
Scale (1-5)
3.7 (1.0)
4.3 (0.9)
2.9 (1.1)
3.1 (1.2)
3.7 (1.3)
3.7 (1.3)
2.8 (1.3)
56
2.563
3
.464
*released varieties (RVs); () STD
In terms of tolerance to drought, the scores given to the LVs NA and AZ were similar to the
RVs GD and JL. Differences exist with regard to maturity period. The two RVs GD and JL
mature in 123 days with a STD of 17 days compared to the dominant LV, NA, which takes
about 100 days to mature with a STD of 15 days. In terms of management practice intensity,
12
the LVs NA and AZ scored higher than the RVs, GD and JL. To see if there is a difference in
PRQCs between the seven potato varieties, we run the Friedman Test (Friedman, 1937).The
result suggests the presence of an overall statistically significant difference (p<0.01) between
the mean ranks of yield, days to maturity, and disease tolerance.
5.1.2.2.Evaluation of market related quality attributes (MRQCs)
Table 7 presents growers’ evaluation of MRQCs. Scanning through the results, the mean
scores for cooking quality and taste are nearly the same across varieties implying that both
seem to be understood in a similar way. In terms of cooking quality and taste, the LV AZ
scored highest followed by the RVs BL and JL. KA was given the lowest score. Growers say
when they eat variety AZ as boiled it is dry in the mouth and tastes very good. In terms of
keeping ability, the RVs BL, GD and JL scored highest while the LVs KA and NA scored
least. In terms of stew quality, NA scored highest whereas BL, KD and KA were rated least.
With regard to tuber size, JL and GD were given the highest scores followed by the dominant
LV NA. As to colour, there was no major variability between the main varieties. Except BL
and KD, which have red colour, the others generally have white colour. Regarding tuber
shape, except AZ and KD which have oval shape, the others generally have a round and semiround shape.
Table 7. Average results of MRQCs as evaluated by growers
Variety
AZ
NA
KD
KA
GD*
JL*
BL*
Tuber size
Scale(1-5)
Stew quality
Scale (1-5)
Cooking quality
Scale (1-5)
Keeping
ability(week)
Taste
Scale(1-5)
3.4 (0.7)
3.9 (0.3)
2.3 (0.9)
2.2 (1.1)
4.4 (0.6)
4.8 (0.4)
3.0(1.0)
3.8 (1.0)
4.8 (0.6)
2.5 (1.1)
2.6 (1.1)
3.3 (1.0)
3.4 (1.1)
2.2 (1.3)
4.6 (0.8)
3.9 (0.9)
3.1 (1.1)
2.2 (1.0)
3.5 (1.1)
3.9 (1.1)
3.8 (1.4)
11.5 (5.5)
8.7 (5.3)
11.1 (5.6)
8.5 (4.5)
13 (7.6)
11.9 (6.6)
15.6 (7.6)
4.7 (0.6)
3.9 (0.9)
3.2 (1.1)
2.0 (1.0)
3.3 (1.0)
4.0 (0.9)
4.2 (1.1)
*Released varieties () STD
In terms of keeping ability, it is shown that the three RVs have the potential to be kept longer
than the LVs, particularly compared to the dominant LV NA. However, ware potato growers
generally don’t keep potatoes in their storages, perhaps, due to the lack of modern storage
systems and the highly susceptibility of the traditional storage systems 8 for high quality losses
(transpiration, respiration, sprouting, soil borne diseases, and physical damages). As a result,
most of the growers tend to sell their potatoes immediately after harvest (within 24 hours of
harvest). Because taste and cooking quality are similar and keeping ability is not considered
important for the aforementioned reason, they are dropped for further analysis. The Friedman
Test result shows that there is an overall statistically significant difference (p<0.01) between
the mean ranks of tuber size, stew quality, and cooking quality.
The fact that the varieties have significance quality differences between each other leads to
our second research question. More specifically, how are the quality characteristics of each of
the varieties are aligned to the needs of the different supply chain actors?
5.2.Analysis of the alignment of quality requirements of different actors
In section 2 (figure 1), we have identified the main actors in the potato supply chain in the
ware potato sector. We have also shown how farmers characterised the different potato
varieties based on their knowledge (tables 6 and 7). In this section, we present the relative
8
Such as postponed harvesting (i.e., leaving the tubers in the soil), local granary, keeping on bed, or on the floor
of their house ( Endale et al., 2008; Hirpa et al., 2010)
13
preferences of both growers and downstream actors towards those quality characteristics in
order to evaluate the alignment of preferences between the different actors (including the
research priorities of the state research centers.
Table 8. State research priorities
Quality Requirements
Yield
Ecological adaptability
Disease tolerance
Priority
1
2
3
Source: Gebremedhin et al. (2008)
5.2.1. Quality preferences of growers
For this part of the study, we collected additional data from a randomly selected potato
growers using a structured questionnaire specifically designed to identify growers’
preferences. Table 9 provides the descriptive statistics for sampled growers. The mean age of
growers that provided the weights was about 37 years and 74% of them had education at the
level of either junior high school or above. Moreover, 63% of the growers had mobile phones.
These characteristics are considered very important to effectively assimilate and evaluate the
different quality attributes.
Table 9. Mean value of growers’ characteristics (N=114)
Sex (%)
Age
(year)
Male
Female
36.5
99.1
0.9
Education level (%)
primary
junior
high
school
school
school
26.3
43.9
22.8
some
college
7
Land
size
(in ha)
Mobile
phone (%
yes)
0.8
62.3
Table 10 shows the weights assigned by growers for PRQCs. From the results, characteristics
related to yield was given the highest weights followed by days to maturity and disease
tolerance. Characteristics related to quality management intensity and drought tolerance were
given lower scores. Referring back to the test statistics on table 6, the seven varieties were not
significantly different with regard to the two characteristics. Perhaps, the availability of cheap
family labour in most rural areas could explain the former. Based on the result displayed on
table 10, we may generalize that growers prefer a high yielding, short maturing and a disease
tolerant variety in their order of importance.
Table 10. Growers’ assigned weights (from 100 points)
PRQCs
Yield
Days to maturity
Disease tolerance
Drought tolerance
Quality management intensity
Mean (N=114)
40.1
29.7
20.3
9.8
0.1
SD
12.9
13.9
12.8
10.6
0.9
However, no one variety reported before has all the three quality characteristics together.
Even if there exists there is no guarantee that this variety will be liked by buyers in the
downstream part of the chain. The next section discusses this point.
5.2.2. Quality preferences of downstream actors
Table 11 summarizes the description of traders who buy directly from growers in the study
area. On average the surveyed traders had 8.8 years experience in potato trading. A collecting
wholesaler on average hired 30 people (men-hour) per day due to the fact that potatoes were
14
harvested by hired daily workers. 78% of collecting wholesalers’ revenue during 2009/10
came from potato sales. The average volume sales by a collecting wholesaler during the same
year was 2,478 tons, with 65% of them delivered to the central market, Addis Ababa; whereas
retailers from the potato growing region often sold to the local consumers in the immediate
market.
Table 11. General description traders who directly buy from growers in the study areas
Mean values
Experience in potato trade (year)
Mean number of workers hired per day
Potatoes delivered per year per trader* (tons)
Potato sales (% total revenue)
Sales outlet (%)
Nearby Markets (<=75 Km )
Central Market (250 km)
Other Distant Markets (>75 km)
Total (N=49)
Retailer (N=12)
Collecting
wholesaler (N=37)
8.8 (5.7)
23.5 (29.2)
1974
72.7
6.4 (3.7)
5.1 (3.3)
428
55.4
9.6 (6.0)
29.5 (31.3)
2478
78.2
38.8
49
12.2
91.7
0
8.3
21.6
64.9
13.5
*own computation () STD
As far as the buyers located at the central market are concerned, the mean purchased volume
during the year 2009/10 was 957 tons for stationed wholesalers, 42 tons for retailers and 7
tons for hotels. While all sampled stationed wholesalers knew production region of potatoes
they purchased none of the hotels and only 15% of retailers did know about it. The sampled
stationed wholesalers on average purchased 65% of their potatoes originated from the study
area.
Table 12.General description of potato buyers at the central market place (Addis Ababa)
Mean values
Amount purchased previous year (in tons)
Place Purchased (%)
Addis Ababa (central market)
Addis Ababa (Supermarket)
Knew production region of potatoes purchased (% yes)
If yes, potatoes purchased originated from (in %)
West Arsi Zone (the study area)
East Arsi zone (South East)
Holeta area (West)
Gojam (North West)
Total
(N=34)
Hotels
(N=11)
Stationed
wholesalers (N=10)
Retailers
(N=13)
299.5
6.8
956.8
42.1
91.2
8.8
35.3
72.7
27.3
0
100
0
100
100
0
15.4
65.8
25.3
7.2
1.7
0
0
0
0
65
28
11.7
5.3
70
26.5
7
0
Table 13 provides an overview of buyers’ assigned weights for market related characteristics.
Because 65% of potatoes purchased by the collecting wholesalers were delivered to the
stationed wholesalers located at the central market, we only focused on the latter to assess the
relative quality preferences. From the results, it seems that retailers prefer most tuber colour
followed by tuber size but not for tuber shape. On the other hand, stationed wholesalers give
priority for tuber size followed by colour and keeping ability of the tuber. For hotels, colour
received the highest score followed by tuber size and tuber shape. Generally, cooking quality,
price, stew quality, and keeping ability were assigned low points by buyers. One surprising
result relates to stew quality. Almost all household consumers in Ethiopia use potatoes for
making a stew. However, the result doesn’t seem to reflect it. One possible explanation is that
stew quality characteristics may have been intermingled in other quality characteristics such
as tuber size. In general, we can say that tuber size and colour are the most important quality
characteristics for the downstream actors’ purchase decision.
15
Table 13. Downstream actors’ assigned weights for MRQCs
Mean value of weights (from 100
points) for
colour
tuber size
keeping ability
tuber shape
stew quality
purchase price
cooking quality
Total
(N=34)
37.3
32.8
7.2
6.9
6.2
5.8
4.1
Hotel
(N=11)
35.4
32.6
5.0
15.8
6.8
2.1
2.3
Stationed
wholesaler (N=10)
30.3
38.2
11.5
6.0
6.7
2.0
5.3
Retailer
(N=13)
44.2
28.8
5.8
0
5.4
11.9
4.6
5.2.3. Quality alignment between state research centers, growers and
downstream actors
As indicated on table 8, the research cetnters release new potato varieties based on three
quality criteria – yield, disease tolerance and agro-ecological adaptability (Gebremedhin et
al., 2008). With regard to agro-ecological adaptability, the three RVs included in this study
can be grown at an altitude ranging from 1600 - 2800m (JL), 1700 – 2700m (BL), and 1600 –
2800m (GD) (Gebremedhin et al., 2008). This implies that all the three RVs are technically
adaptable to the agro-ecology of the study areas. As shown above, the two RVs JL and GD
are rated as high yielding and high disease tolerant.
Our data suggest tuber size and colour are the most important quality criteria both for growers
and buyers. Further analysis revealed that the desired colour by all of the buyers is white.
With regard to tuber size, 80% of wholesalers prefer large tubers and about 85% retailers
prefer small, medium, or large size tubers instead of very large tubers. Similarly, 73% of the
sampled hotels prefer either medium or large size tubers, and only the remaining 27% prefer
very larger tubers. Generally, larger tuber size potatoes are preferred to small, medium, or
very large tubers by both growers and traders. Though tuber shape was not as such found to
be an important selection criterion by the major supply chain players, all wholesalers and
retailers in the sample preferred round shape tubers and only 46% of the hotels preferred oval
shape tubers. In terms of colour, there is no much difference between the most common LVs
and RVs, implying that the main difference lies on tuber size. Generally, the two main RVs
seem to have very large tuber size. From table 14, it seems that very large tuber size potatoes
are less desirable by both growers and buyers.
Table 14. Some desired quality characteristics by major participants of the potato chain
Mean values
Desired colour
Desired tuber size (mean value)
large
very large
medium
small
Desired tuber shape (mean value)
round
semi round
oval
indifferent
Growers
(N=114)
White
Hotel
(N=11)
White
Stationed wholesaler
(N=10)
White
Retailer
(N=13)
White
61.4
28.1
10.5
0
36.4
27.3
36.4
0
80.0
20.0
0
0
46.2
15.4
15.4
23.1
67.5
15.8
14.0
2.6
54.5
0
45.5
100
0
0
100
0
0
To examine the optimal tuber size, we further collected sample potatoes from two potato
quality categories. One quality category, based on tuber size, was meant for retailers who
generally sell to household consumers (we call it “second class”) and the other category was
meant for hotels and supermarkets (we call it “first class”). We randomly selected 25 first
16
class potatoes that were available for supermarkets and hotels, and 40 second class potatoes
that were available for retailers. All the sampled potatoes were selected randomly from the 10
wholesalers included in our sample. Accordingly, the mean tuber size available for retailers
and for hotels and supermarkets is significantly different (p<0.001). This further reinforces
the significance of tuber size in grading the quality of (ware) potatoes.
Table 15. Optimal tuber size
Tuber size
(mm)
Type of buyers
N
Class 1: Supermarket & Hotels
Class 2: Retailers
40
42.54
25
57.28
Levene's Test
Independent Samples Test
Tuber size
(mm)
Equal variances assumed
Mean
SD
Std. Error Mean
4.877
0.771
6.516
1.303
t-test for Equality of Means
F
Sig.
t
df
Sig. (2-tailed)
1.437
0.235
-10.402
63
0.00
Taking the above results and the weights assigned by the downstream actors, we can better
explain why certain varieties are more preferable than others. It seems clear that the LV NA is
very popular by both growers and downstream actors particularly compared to that of the
RVs. It has large tuber size (average score of 3.9), white in colour, round in shape, and scored
the highest in terms of stew quality (mean score 4.8). On the other hand, variety JL (mean
tube size score 4.8) and GD (mean tuber size score 4.4) seem over the desired tuber size level
as perceived by sampled growers. When asked about the problem of very large tubers, the
response from both growers and buyers was that internal quality would compromise as the
tuber size gets very large. Moreover, since household consumers in general buy in smaller
quantities, retailers generally don’t like very large tubers as it creates measurement problem 9.
All these factors seem to have led the LV NA as the most desired potato variety in the region;
it has been consistently grown by more than 80% of sampled growers over the last five years
(see table 16). On the other hand, the RVs GD and JL were the least grown varieties during
those years. The seemingly increased percentage during 2009/10 season for the RVs was due
to the fact that one NGO supplied the RVs to some growers free of charge.
Table 16: Growers’ experience in growing the different potato varieties
Did you grow the
following potato varieties?
AZ
NA
KD
KA
GD
JL
BL
2009/10
49.1
81.2
21.4
4
9.5
22.3
1.7
Percent yes (N=346)
2008/9
2007/8
2006/7
46
42.8
35.3
84.1
82.1
80.3
25.7
24.6
20.5
6.4
6.6
9.5
2.6
1.7
1.2
2.9
2
1.2
2.9
2.6
2.9
2005/6
37.3
82.1
23.7
30.6
0.9
0.3
5.5
5.3.Quality control and information exchange in the potato supply chain
9
For example, should a consumer wants to buy 1kg of potatoes then putting 1 tuber could weigh a bit less but
making it two could weigh well over 1kg.
17
5.3.1. Quality control mechanisms
No third party or publicly owned formal quality control mechanisms were observed in the
potato supply chain. Rather, different (informal) quality control mechanisms have been
practiced to govern the relationship between growers and collecting wholesalers. One way of
controlling the quality of potatoes is visiting of the potato fields by the buyer or his agent to
verify quality in person before making any purchase commitment. Most of the time,
agreement of sales between the buyer and the grower is reached before harvest. Once the
buyer is satisfied with the quality of potatoes on the field then the harvesting task is the next
concern as it may pose additional quality risks related to prematurity, mechanical damages
and the freshness of potatoes. As a consequence, buyers often opt to undertake the harvesting
task by themselves.
Table 17 provides a summary report about such practices in the study area. 67% of buyers did
visit the potato fields before harvest and 56% of the respondents replied that harvesting was
done by the buyer. In 64% of the time, the level of quality was measured from the buyer’s
point of view or that of his agents (middlemen). It was only in 26% of the time that both the
buyer and the grower mutually decided the quality level of potatoes.
Table 17: Quality control mechanisms between growers and collecting wholesalers (N=346_)
Did your main buyer know (visit) where you grew the potatoes sold last season? (% yes)
Who did the harvesting of the potatoes sold in the previous year? (% yes)
The buyer himself
You (the grower)
Who measured the quality of potatoes sold in the previous year? (% yes)
The buyer himself
The middleman
Joint consent of the grower and the buyer
You (the grower)
Third party arbitration
66.9
55.6
44.4
36.1
28.0
26.3
9.2
0.3
The sampled wholesalers and retailers in the central market reported a number of problems
related to potato quality. Supplying prematured tubers, spoilage losses, blackening of tuber
and physical damage during harvesting were highlighted as quality problems in their order of
importance. We also observed prematured potatoes during our visit to the wholesale market. It
was learned that farmers tempted to harvest potatoes earlier than required in order to make the
potato field ready for another crop. This explains why many collecting wholesalers are
increasingly involved in visiting potato fields and finally in harvesting activities.
5.3.2. Information exchange mechanisms
Once potatoes are harvested, they have to be delivered fresh (for the next day) to the central
market. Buyers at the different level of the chain had no proper infrastructure (such as cold
storages) to minimize the risk of quality loss. This presupposes the need for an efficient and
effective information exchange mechanism between collecting wholesalers located at the
production region and those of stationed wholesalers and retailers located at the central
market. Our data from stationed wholesalers, retailers and hotels revealed that they use
production region to screen quality. However, the problem with this kind of information
exchange mechanism is that it lacks specificity, particularly when several varieties, having
different quality characteristics, co-exist in one region. On the other hand, in the potato
growing region, knowledge of variety names is important and serves as a quality signal in the
relationship between growers and collecting wholesalers. Here, the collecting wholesalers
play a key role in facilitating the information exchange. The surveyed growers revealed that
before collecting wholesalers actually observe the potatoes and evaluate other main quality
18
attributes (such as tuber size) on the farm, they first ask about the type of potato variety
grown. This happened in about 94% of the time during 2009/10 season(s).
Table 18. Type of information collecting wholesalers ask priori (N=346, % yes)
Variety name
Inorganic fertilizer (amount & time of application)
Pesticides (amount & time of application)
Tuber size
Tuber colour
94.4
10.9
5.6
99
91.8
Once they get variety information the buyers start to inquire further for important quality
attributes, such as tuber size. As shown on table 18, tuber size and colour found to be very
important unlike the unobservable quality characteristics. High transaction costs, lack of
awareness by the final consumers, absence (or ineffectiveness) of quality regulations, and/or
little access to international market could be responsible for the low importance given to the
unobservable quality characteristics.
6. Discussion and conclusion
6.1.Discussion
We presented a conceptual framework that could help to systematically analyse quality
alignment and thereby the problem of low adoption, particularly, in situations where formal
quality classification is lacking. The conceptual framework uses the local context of defining
quality (variety) and then translates it to the more generic quality characteristics that may
have greater influence on the growers’ adoption decisions. This approach is important to
narrow down differences in quality interpretation and to facilitate information exchange
between the different chain actors. In addition, the conceptual framework attempts to show
how the product, characteristics of the product and the preferences of supply chain actors can
be systematically analysed using a single framework. It incorporates two approaches of
studying quality - the product management approach (as product characteristics are evaluated
based on the criteria imposed by the growers) and a consumer research approach (as buyers
at the different level of the chain evaluated and assigned weights for the different quality
characteristics of the product). However, the conceptual framework does not explicitly show
how individual characteristics can influence quality preferences (variety selection) as the
paper mainly focused on exogenous factors that could lead to low adoption.
The problem of low adoption has been largely associated to individual factors such as risk
preferences, land endowments and education level, and to institutional factors like credit
constraints (Winters et al., 2006; Benin et al., 2006). For example, in the Ethiopian case,
Dercon and Christiaensen (2011) reported fear of taking risky production technologies while
Cavatassi and Lipper (2011) claim access to markets and social capital as drivers for
improved variety adoption in addition to risk factors. Our contribution to this strand of the
literature lies on the importance of market characteristics for improved variety adoption and
the use of local knowledge in understanding important quality characteristics that could
influence smallholder farmers’ production and market-related decisions.
The implication to research /policy is that potato has increasingly become a source of cash
income for smallholder farmers (Kaganzi et al., 2009; Devaux et al., 2009). Hence, market
conditions cannot be ignored and, in fact, should be given priority in developing and
disseminating a new technology. Knowledge on the important market-related quality
attributes would help research institutions to develop or introduce new potato varieties with a
19
higher likelihood of adoption. For example, the Michigan potato-breeding program used
quality as an important criterion to develop new potato cultivars (Douches et al. 2001).
The result suggests the need for a bottom-up approach, which seems more feasible these days
than before due to the advent of mobile technology in the rural areas. As indicated in this
study, nearly 7 out of 10 surveyed growers have access to mobile phones. With farmers’ use
of mobile phone technology likely to increase, research centers can make use of the mobile
technology as an alternative model for reaching out a large number of farmers and other
supply chain actors. This reinforces earlier suggestions made by Byerlee et al. (2007) that a
rethinking of the existing technology adoption systems is needed in Ethiopia. So far
information exchange remained top-down with a little room for the local knowledge albeit a
large amount of public money is being spent on research and extension that put Ethiopia
among the largest spenders in Africa (Byerlee et al., 2007).
The problem of quality uncertainty, particularly the oversupply of premature potatoes to the
market, might have brought a change in the organization of the traditional potato supply
chain. Most transactions at the lower end of the chain are governed by a “quasi-vertical” type
of relationship, where the collecting wholesalers are increasingly involved in the harvesting
part of the production cycle. On the other hand, dyadic relationships between downstream
actors at the upper end of the chain remain trust-based, where closer personal ties and
repetitive interaction seem to be more important than formal contracts (see table 19).
Table 19. Relationship between buyers at the central market and collecting wholesalers
Have main supplier (% yes)
Have written contract (% yes)
Total
(N=34)
79.4
11.1
Hotel
(N=11)
81.8
33.3
Stationed
wholesaler (N=10)
60
0
Retailer
(N=13)
92.3
0
6.2.Conclusion
This paper attempts to explain the problem of low adoption for the released potato varieties by
the (ware) potato growers in context of Ethiopia. Farmer based characterisation of the
different potato varieties show that there are quality differences between the released and the
local varieties, particularly with respect to tuber size, stew quality, yield, maturity period, and
disease tolerance. While yield, maturity period, and disease tolerance are considered as the
most important production-related quality characteristics, tuber size and colour remained the
most preferred market-related characteristics.
Preferences for the different quality characteristics were analysed based on the Quality
Assignment Model (QAM) developed by Sloof et al. (1996). Since the model conceptualises
quality based on observable quality characteristics (of perishable products), it nicely fits to the
(Ethiopian) potato supply chain context as the chain is characterised by a large group of
smallholder farmers and traders, where information on unobservable quality characteristics is
hardly conveyed or not considered at all. Accordingly, the released varieties are preferred in
terms of production-related characteristics but the local varieties are more preferred for their
market-related characteristics. In this situation, ware potato growers tend to align their
production in a way to satisfy the quality requirements of downstream actors.
In Ethiopia, formal quality classification is lacking. Hence, supply chain actors use informal
mechanisms such as variety names or production region for information exchange and
continue to involve in the harvesting activities to control potato quality.
20
References
Abadi Ghadim, A. K. and Pannell, D. J. 1999, 'A conceptual framework of adoption of an agricultural
innovation', Agricultural Economics, vol. 21, no. 2, pp 145-154.
Abate, T., Shiferaw, B., Gebeyehu, S., Amsalu, B., Negash, K., Assefa, K., Eshete, M., Aliye, S. and
Hagmann, J. 2011, 'A systems and partnership approach to agricultural research for development:
Lessons from Ethiopia', Outlook on Agriculture, vol. 40, no. 3, pp 213-220.
Beintema, N. and Stads, G. J. 2011, 'African agricultural R&D in the new millennium: Progress for some,
challenges for many', Food Policy Report. Washington, DC: International Food Policy Research
Institute.
Belay, K. 2003, 'Constraints to agricultural extension work in Ethiopia: the insiders' view', South African
Journal of Agricultural Extension, vol. 31, no. 1, pp 63-79.
Belay, K. and Abebaw, D. 2004, 'Challenges Facing Agricultural Extension Agents: A Case Study from
South‐western Ethiopia', African Development Review, vol. 16, no. 1, pp 139-168.
Benin, S., Smale, M., Pender, J., 2006, 'Explaining the diversity of cereal crops and varieties grown on
household farms in the highlands of Northern Ethiopia', in Valuing Crop Diversity: On Farm
Genetics Resources and Economic Change, ed M. Smale, CABI Publishing, Wallingford.
Biggs, S. D. 1990, 'A multiple source of innovation model of agricultural research and technology
promotion', World Development, vol. 18, no. 11, pp 1481-1499.
Byerlee, D. R., Spielman, D. J., Alemu, D. and Gautam, M. 2007, 'Policies to promote cereal intensification
in Ethiopia: A review of evidence and experience'.
Cavatassi, R., Lipper, L. and Narloch, U. 2011, 'Modern variety adoption and risk management in drought
prone areas: insights from the sorghum farmers of eastern Ethiopia', Agricultural Economics.
Dercon, S. and Christiaensen, L. 2011, 'Consumption risk, technology adoption and poverty traps: evidence
from Ethiopia', Journal of Development Economics, vol. 96, no. 2, pp 159-173.
Devaux, A., Horton, D., Velasco, C., Thiele, G., López, G., Bernet, T., Reinoso, I. and Ordinola, M. 2009,
'Collective action for market chain innovation in the Andes', Food Policy, vol. 34, no. 1, pp 31-38.
Douches, D., Jastrzebski, K., Coombs, J., Chase, R., Hammerschmidt, R. and Kirk, W. 2001, 'Liberator: A
round white chip-processing variety with resistance to scab', American journal of potato research,
vol. 78, no. 6, pp 425-431.
Endale, G., W. Gebremedhin, K. Bekele, and B. Lemaga 2008, 'Potato variety development ', in Root and
tuber crops: The untapped resources, ed G. E. W. Gebremedhin, and B. Lemaga, Ethiopian
Institute of Agricultural Research, Addis Ababa.
ESCS (Ethiopian Smallholders Commercialization Survey). 2005. Unpublished data from a survey
conducted by the Ethiopian Development Research Institute, the Central Statistical Authority, and
the International Food Policy Research Institute. Addis Ababa.
Ethiopian Institute of Agricultural Research. www.eiar.gov.et. Date of access:15/3/2012.
Feder, G. and Umali, D. L. 1993, 'The adoption of agricultural innovations:: A review', Technological
forecasting and social change, vol. 43, no. 3-4, pp 215-239.
Gebremedhin, W., G. Endale, and B. Lemaga 2008, 'Potato variety development', in Root and tuber crops:
The untapped resources ed G. E. W. Gebremedhin, and B. Lemaga, Ethiopian Institute of
Agricultural Research, Addis Ababa.
Gildemacher, P., Kaguongo, W., Ortiz, O., Tesfaye, A., Woldegiorgis, G., Wagoire, W., Kakuhenzire, R.,
Kinyae, P., Nyongesa, M. and Struik, P. 2009, 'Improving Potato Production in Kenya, Uganda
and Ethiopia: A System Diagnosis', Potato Research, vol. 52, no. 2, pp 173-205.
Hirpa, A., Meuwissen, M. P. M., Tesfaye, A., Lommen, W. J. M., Oude Lansink, A., Tsegaye, A. and
Struik, P. C. 2010, 'Analysis of Seed Potato Systems in Ethiopia', American journal of potato
research, pp 1-16.
Howard, H. 1974, 'Factors influencing the quality of ware potatoes. 1. The genotype', Potato Research, vol.
17, no. 4, pp 490-511.
Jemison Jr, J. M., Sexton, P. and Camire, M. E. 2008, 'Factors influencing consumer preference of fresh
potato varieties in Maine', American journal of potato research, vol. 85, no. 2, pp 140-149.
Kaganzi, E., Ferris, S., Barham, J., Abenakyo, A., Sanginga, P. and Njuki, J. 2009, 'Sustaining linkages to
high value markets through collective action in Uganda', Food Policy, vol. 34, no. 1, pp 23-30.
Kevane, M. 1996, 'Agrarian structure and agricultural practice: Typology and application to Western
Sudan', American Journal of Agricultural Economics, vol. 78, no. 1, pp 236-245.
Lancaster, K. 1971, Consumer demand: A new approach, Columbia University Press New York.
21
Lancaster, K. J. 1966, 'A new approach to consumer theory', The Journal of Political Economy, vol. 74, no.
2, pp 132-157.
Long, C. M., Snapp, S. S., Douches, D. S. and Chase, R. W. 2004, 'Tuber yield, storability, and quality of
Michigan cultivars in response to nitrogen management and seedpiece spacing', American journal
of potato research, vol. 81, no. 5, pp 347-357.
Luning, P. A., Marcelis, W. J. and Jongen, W. M. F. 2002, Food quality management: a techno-managerial
approach, Wageningen Pers.
McGuire, S. 2005, Getting genes: Rethinking seed system analysis and reform for sorghum in Ethiopia,
Wageningen Universiteit.
Molnar, P. and Orsi, F. 1982, 'Determination of weighting factors for the sensory evaluation of food',
Food/Nahrung, vol. 26, no. 7/8, pp 661-667.
Mosse, D. 2005, 'Cultivating Development: An Ethnography of Aid Policy and Practice (Anthropology,
Culture and Society Series)'.
Mulatu, E., Ibrahim, O. E. and Bekele, E. 2005, 'Improving Potato Seed Tuber Quality and Producers'
Livelihoods in Hararghe, Eastern Ethiopia', Journal of New Seeds, vol. 7, no. 3, pp 31-56.
Reardon, T., Barrett, C. B., Berdegué, J. A. and Swinnen, J. F. M. 2009, 'Agrifood industry
transformation and small farmers in developing countries', World Development, vol. 37, no. 11,
pp 1717-1727.
Reardon, T., Codron, J.-M., Busch, L., Bingen, J. and Harris, C. 2001, 'Global Change in Agrifood Grades
and Standards: Agribusiness Strategic Responses in Developing Countries', International Food
and Agribusiness Management Review, vol. 2, no. 3, pp 195-205.
Richardson, D. 1973, 'An external ringspot of potatoes', Plant Pathology, vol. 22, no. 3, pp 120-122.
Rogers, E. M. 1995, Diffusion of innovations, Free Pr.
Ruben, R., van Boekel, M., van Tilburg, A. and Trienekens, J. 2007, Tropical food chains: governance
regimes for quality management, Wageningen Academic Publishers.
Sall, S., Norman, D. and Featherstone, A. M. 2000, 'Quantitative assessment of improved rice variety
adoption: the farmer's perspective', Agricultural Systems, vol. 66, no. 2, pp 129-144.
Sillitoe, P., Bentley, J. W., Brokensha, D., Cleveland, D. A., Ellen, R., Ferradas, C., Forsyth, T., Posey, D.
A., Stirrat, R. and Stone, M. P. 1998, 'The Development of Indigenous Knowledge: A New
Applied Anthropology [and Comments and Reply]', Current Anthropology, pp 223-252.
Sillitoe, P. and Marzano, M. 2009, 'Future of indigenous knowledge research in development', Futures, vol.
41, no. 1, pp 13-23.
Sloof, M., Tijskens, L. and Wilkinson, E. 1996, 'Concepts for modelling the quality of perishable products',
Trends in Food Science & Technology, vol. 7, no. 5, pp 165-171.
Spielman, D. J., Byerlee, D., Alemu, D. and Kelemework, D. 2010, 'Policies to promote cereal
intensification in Ethiopia: The search for appropriate public and private roles', Food Policy, vol.
35, no. 3, pp 185-194.
Steenkamp, J. B. E. M. 1989, Product quality: An investigation into the concept and how it is perceived by
consumers, Van Gorcum AssenMaastrich.
Sumberg, J., Okali, C. and Reece, D. 2003, 'Agricultural research in the face of diversity, local knowledge
and the participation imperative: theoretical considerations', Agricultural Systems, vol. 76, no. 2,
pp 739-753.
Winters, P., Cavatassi, R. and Lipper, L. 2006, 'Sowing the seeds of social relations: the role of social
capital in crop diversity', Working Papers.
WDR, 2008. Agriculture for Development. World Development Report, 2008. World Bank, Washington,
DC.
22