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Journal of Rural and Community Development
ISSN: 1712-8277 © Journal of Rural and Community Development
www.jrcd.ca
Journal of Rural and
Community
Development
Fish-farming Value Chain Analysis:
Policy Implications for
Transformations and Robust Growth
in Tanzania
Authors: Francis A. Mwaijande & Prudence Lugendo
Citation:
Mwaijande, F. A., & Lugendo, P. (2015). Fish-farming value chain
analysis: Policy implications for transformations and robust growth in
Tanzania. The Journal of Rural and Community Development, 10(2), 47-62.
Publisher: Rural Development Institute, Brandon University.
Editor: Dr. Doug Ramsey
Open Access Policy:
This journal provides open access to all of its content on the principle that
making research freely available to the public supports a greater global
exchange of knowledge. Such access is associated with increased readership
and increased citation of an author's work.
Journal of Rural and Community Development
ISSN: 1712-8277 © Journal of Rural and Community Development
www.jrcd.ca
Fish-farming Value Chain Analysis: Policy
Implications for Transformations and Robust
Growth in Tanzania
Francis A. Mwaijande
Mzumbe University
Tanzania
fmjande@yahoo.com
Prudence Lugendo
Economic and Social Research Foundation
Tanzania
plugendo@esrf.ot.tz
Abstract
This article sets out data and issues in relation to fish-farming in Tanzania with the
objective of generating information to inform policy decisions required for the
transformations in the fish-farming into a viable commercial activity. It identifies
challenges within the sector that should be addressed through policy reform. Fish
farming in Tanzania is governed by the Fishery Act 2003 No. 22 and the National
Fisheries Sector Policy of 1997. The guiding research problem statement was despite
the National policy objective to develop a robust, competitive and efficient fishery
sub-sector, fish farming in Tanzania is underdeveloped at subsistence production
that contributes to only 1.2% of GDP.
A survey design was used for collecting primary data from 293 respondents
randomly sampled from 8 regions of Dar Es Salaam, Coastal, Morogoro, Njombe,
Mbeya, Ruvuma, Kagera and Kilimanjaro. This data was collected using
questionnaire and interviews. These were triangulated with secondary data obtained
from desk top review. Descriptive statistics and content analysis method were used
to report findings. The study found that the major constraints were lack of value
chain in the fish farming.
We examined the value chain in terms of sources of production, inputs, extension
services, technology, and marketing and found that 60% of fish farmers obtain
fingerlings from local sources such as friendship network. These sources have no
scientific production of fingerlings suitable for commercial fish-farming. In the
overall, farmers don’t have good and reliable sources for fingerlings. It was also
found that 76% of fish farmers make their own feeds using the locally obtained
materials like maize and paddy husks, remains of vegetables from garden, cocoyam
leaves, and cattle dung. However, it was found that the home made feeds lack quality
due to inadequate basic knowledge of producing right fish feeds
Lack of appropriate technology application in the fish-farming was a critical
constraint that minimizes the chance of transforming the sub-sector into a
commercial entity. Technology in fish farming industry include proper pond size,
species, sex selection fingerlings, improved fish feeds, hatchery and storage
facilities. Furthermore, the study found high demand for extension services in the
Mwajiande & Lugendo
Journal of Rural and Community Development, 10, 2(2015) 47-62 48
fish-farming agribusiness, but there is insufficient or non-availability of the
extension services, to impart knowledge, proper use of medicines, fish farm
management practices and appropriate technology application.
For the fish-farming sub-sector to grow from the current 1.2% to the targeted 5%
contribution to GDP, it is recommended that policy actions should be undertaken for
providing capacity building for small farmers in terms of skills for best practice of
fish-farming, credit and or subsidy facility for fish farming infrastructure and inputs,
extension services for knowledge and technology transfer to small farmers and
encouraging public-private partnership along fish-farming value chain for ensuring
availability of quality fingerlings, fish feeds, transportation, and marketing.
Keywords: fish farming, small farmers, constraints, latent potential, policy
implications making.
1.0 Introduction
Tanzania has the greatest fish farming potential in Africa with suitable land and
water sources. Food and Agriculture Organization (FAO) estimates that Tanzania
has a total of 14,100 freshwater fish ponds (FAO, 2013), however it is not yet tapped.
According to the FAO (2013) there is viability of expanding fish farming through
diversifying production and developing the export market in the Tanzanian rural
economy, however this is largely untapped. This is also noted by Chenyambuga,
Madalla. and Mnembuka, (2012), who argue that aquaculture in Tanzania is still
a subsistence activity practiced by small-scale farmers who have low social, cultural
and economic status and are limited by access to technology, markets and capital.
They observed that aquaculture is dominated by freshwater fish farming in which
small-scale farmers usually hold small fish ponds of an average size of 10 m x 15 m
(150 m2). These are integrated with other agricultural activities such as gardening,
crop production, livestock keeping and poultry on small pieces of land.
Fish farming, as identified in the Tanzania Five Year Development Plan (United
Republic of Tanzania, 2012), has the potential for transformation to commercial
orientation that can be a very profitable activity and wealth generating activity for
poverty reduction (Wijkstrom and MacPherson, 1990), but the fish farming sub-
sector is constrained by multiple factors. The objective of this paper is therefore to
identify the challenges and constraints of fish farming which affect the latent
potential for growth in Tanzania.
Fish farming as an approach to economic transformation and poverty reduction must
involve addressing the major constraints faced by fish-farmers, processors, traders
and other related actors in the value chain. This inevitably includes a wide range of
activities such as ensuring access to the full range of necessary resources, inputs and
technology. The identified challenges should be addressed through policy reform
such as facilitating access to cheaper but better inputs, strengthening the delivery of
financial services, enabling flow of market information and market access. The
incentive of fish farmers to produce is when consumers are linked to the needs of
fish farmers, processors, traders, and transporters. This is likely to happen when the
policy environment enables the public-private partnership to operate in the fish
farming sub-sector.
Mwajiande & Lugendo
Journal of Rural and Community Development, 10, 2(2015) 47-62 49
2.0 Problem Statement
Fish farming is among the described latent growth potentials in the Tanzania Five
Year Development Plan. Guided by the Fishery Act 2003 No. 22 and the National
Fisheries Sector Policy of 1997 with the associated regulations that aim at
transformation of the fisheries sub-sector into sustainable commercial fishing, fish-
pond farming, and processing for both domestic and foreign markets (URT, 1997);
the policy objective is to develop a robust, competitive and efficient fisheries sub-
sector that contributes to food and nutrition security, growth of the national economy
and improvement of the well-being of fish farmers. Despite the policy objective, the
fish farming (aquaculture) sub-sector is underdeveloped at subsistence production
that contributes to only 1.2 of GDP (URT, 2012).
3.0 Research Questions
What are the major constraints of fish-farming transformations in Tanzania?
What is the incentive for scaling up fish farming transformations in
Tanzania?
How can fish-farmers increase efficiency?
What are the necessary conditions for fish-farming transformations?
4.0 Previous Literature
There is a paucity of empirical and academic literature on fish-farming in
Tanzania. However, the available studies in Africa and some countries in East
Africa indicate fish farming has the untapped potential for economic growth and
rural poverty alleviation. Maurice, Knútsson, and Gestsson,(2010) conducted a
study in Uganda on the value chain of farmed African catfish and Kariuki (2013)
studied fish farming implementation in Kenya. The study discusses the existing
catfish farming industry and its value chains. The study responds to questions on
the industry structure, value chains, value distribution and how relationships
among actors have an influence on profitability. The study suggests value creation
as a means for improving profitability in catfish farming.
Fish farming potential is limited by constraints. Ike and Onuegbu, (2007) attempted
to improve the aquaculture technology package for Nigerian farmers. The results of
intervention showed that the level of adoption of the technology was low. Farmers
found it difficult to adopt the developed technology because they did not have
adequate funds to maintain the technology.
Though not much literature is known about fish farming in Tanzania, the viability
of implementing fish farming in Tanzania is similarly constrained. Chenyambuga et
al. (2012) argues that aquaculture in Tanzania is still a subsistence activity practiced
by small-scale farmers who have low social, cultural and economic status and
limited access to technology, markets and credit. Despite the paucity of literature,
the cross-examined, empirical evidence shows fish farming as a potential enterprise
for economic growth and poverty eradication for the poor. However, the sub-sector
is constrained by multiple factors that require policy interventions.
Mwajiande & Lugendo
Journal of Rural and Community Development, 10, 2(2015) 47-62 50
5.0 Methodology
A survey design was used for collecting primary data from 293 respondents
randomly sampled in Dar Es Salaam, Coastal, Morogoro, Njombe, Mbeya, Ruvuma,
Kagera and Kilimanjaro regions in 2013 regarding the socio-economic profiles,
constraints, and technologies. In addition, interviews and focus group discussions
(FGDs) were used to triangulate the information obtained on the mentioned
constraints. A desk top review was conducted for secondary data on fish-farming,
necessary skills, knowledge and technology as well as policy and institutional
contexts including; research reports from Tanzania Fisheries Research Institute and
Ministry of Livestock and Fisheries Development.
Data analysis was computed using the Statistical Package for Social Sciences
version 17 (SPSS) for descriptive analysis to obtain frequencies, means, standard
deviations, minimum and maximum values of individual variables in view of the
described constraints and opportunities faced by pond fishing stakeholders and the
Stochastic Frontier Version 4.1 computer software for estimating productivity of
fish farmers by estimating mean efficiency.
The stochastic frontier model was used to compute productivity of fish farmers by
estimating mean efficiency. The stochastic frontier model is derived from
production function. It was first proposed by Aigner, (1977) and Meeusen and Van
den Broeck (1977). The original specification involved a production function
specified for cross-sectional data which had an error term which had two
components, one for random effect and another for technical inefficiency. The
production frontier model without random component can be written as:
=(;).
whereby:
yi is the observed scalar output of the producer i, i=1,..I,
xi is a vector of N inputs used by the producer i, f(xi, β) is the production
frontier,
is a vector of technology parameters to be estimated TEi denotes the
technical efficiency defined as the ratio of observed output to maximum
feasible output. TEi = 1 shows that the i-th firm obtains the maximum
feasible output, while TEi < 1 provides a measure of the shortfall of the
observed output from maximum feasible output.
A stochastic component that describes random shocks affecting the production
process was added. These shocks are not directly attributable to the producer or the
underlying technology. These shocks may come from weather changes, economic
adversities or plain luck. We denote these effects with exp{vi}. Each producer is
facing a different shock, but we assume the shocks are random and they are
described by a common distribution. The stochastic production frontier will become:
=(;)..exp {}
We also make assumption that TEi is also a stochastic variable, with a specific
distribution function, common to all producers. We can also write it as an
exponential; TEi=exp {-ui}, where ui ≥ 0, since we required TEi ≤ 1. Thus, we obtain
the following equation
=(;).exp{−}.exp {}
Mwajiande & Lugendo
Journal of Rural and Community Development, 10, 2(2015) 47-62 51
Assuming that f (xi, β) takes the log-linear translog production function form, the
model can be written as:
=0+� +� +−
Data from interviews were analyzed through content analysis and summarized
broad categories. These were triangulated with the descriptive statistics.
6.0 Results and Discussion
6.1 Socio-Economic Profile of Fish-Farmers
In order to provide a better description of fish-farming in Tanzania, the
characterizing fish-farming communities and the applied technologies aimed at
describing individual socio-economic characteristics from 293 fish farmers in the
sampled regions. It also aimed at obtaining information on species, and sex of
farmed fish as well as types of feeds, size and number of ponds. The distribution of
the study respondents by region was 49, 59 and 60 for Kagera, Kilimanjaro and
Morogoro regions respectively. Other respondents were from Ruvuma, Njombe and
Mbeya regions composed of 34, 32 and 59 respondents respectively.
The study results show that the fish-farming sub-sector is dominated by males who
formed 82 % of the randomly selected respondents. Chenyambuga et al (2011)
also observed that in Morogoro region, very few women owned fish ponds and
most of them were widowed, divorced or unmarried. This shows fish-farming is
dominated by men due to the fact that local customs and cultural practices in many
farming systems in Tanzania discriminate against women in the ownership of
assets including land. However, the trading of fried fish is predominantly a
women’s business.
Nevertheless, Table 1 shows that Mbeya and Njombe regions have higher
proportions of female fish farmers, respectively, of 25.4% and 21.9%.
According to the information provided in the Table 1, age, experience and education
variables do not vary with variation of regions. It shows that more than 70% of
respondents had attained primary education and very few of them (0.7%) were
university graduates. Furthermore, cross tabulation shows that respondents engaged
in fish farming who had attained a higher degree were aged above fifty years.
From the question that asked farmers to indicate their experience, the results showed
that the majority of fish farmers had a farming experience of one to five years (74%).
However, the fish farming experience among respondents ranged from one year
(20%) to 35 years (0.3%), meaning that fish-farming is a relatively underdeveloped
or not common farm activity. This experience has potential for growth of fish-
farming because the most (69%) of interviewed fish farmers were within the range
of active age from 18 to 50 years (Figure 3). This finding agrees with the finding by
Chenyambuga et al (2011) who reported that the majority of fish farmers
belong in an active working group of age between 25 to 50 years. This was an
interesting observation because many youth shy away from crop farming
activities, but fish-farming has attracted their interests because this type of
farming is less labour intensive.
Mwajiande & Lugendo
Journal of Rural and Community Development, 10, 2(2015) 47-62 52
The results of the study indicate that fish-farming in Tanzania is constrained by lack
of inputs, supply, technologies, capacity of fish-farmers, policy related issues and
the fish value chain.
Table 1: Social Economic Characteristics of Fish Farmers Regional Wise (n =
293)
Variable
Kagera
(n= 49)
KLM
(n= 59)
Mbeya
(n= 59)
Morogoro
(n= 60)
Njombe
(n= 32)
Ruvuma
(n= 34)
Total
Age 18 to 50 35(71.4) 33(55.9) 40(67.8) 45(75) 26(81.2) 24(70.6) 203(69.3)
51+
14(28.6)
26(44.1)
19(32.2)
15(25)
6(18.8)
10(29.4)
90(30.7)
Education
Degree
1(1.7)
1(2.9)
2(0.7)
Diploma
2(4.1)
2(3.4)
-
2(3.3)
1(3.1)
1(2.9)
8(2.7)
A level
3(6.1)
1(1.7)
1(1.7)
-
1(3.1)
1(2.9)
7(2.4)
O level
19(38.8)
18(30.5)
8(13.6)
11(18.3)
3(9.4)
6(17.6)
65(22)
Certificate
1(2.0)
3(1.0)
Primary
24(49)
38(64.4)
49(83)
44(73.3)
26(81.2)
23(67.6)
204(69.6)
Informal
1(1.7)
1(1.7)
2(5.9)
4(1.4)
Experience
<= 5 yrs
38(77.6)
44(74.6)
45(76.3)
40(66.7)
23(71.9)
27(79.4)
217(74.1)
5 years
11(22.4)
15(25.4)
14(23.7)
20(33.3)
09(28.1)
07(20.6)
076(25.9)
Sex
Male
45(91.8)
44(74.6)
56(94.9)
47(78.3)
25(75.1)
27(79.4)
241(82.3)
Female
4(8.2)
15(25.4)
03(5.1)
13(21.7)
07(21.9)
07(20.6)
052(17.7)
Source: Authors’ analysis. Note: Figures in brackets are expressed in percent.
6.2 Factors Hindering Fish-farming Value Chain—Empirical Evidence
Some of the constraints affecting the farmed fish value chain as identified by
different researchers are classified into three groups; input, production and post-
harvest and marketing factors (MacFadyen et al., 2011). Critical input factors
include non-availability of quality fish feeds; poor quality of fish breeding; poor
water quality of water; feeds; and technology. Limited best management practice for
growing tilapia; farm layout and design; about feed use and fish health management.
In addition,poor post-harvest of fish, sanitary and phytosanitory are other critical
factors for unleashing the potential of fish-farming in Tanzania.
6.3 Fish-farming value Chain Analysis
The concept of value chain as first described by Porter (1985) is a process from
producers to final consumers of products or services. He defined value as the amount
buyers are willing to pay for what a firm provides, and he conceived the “value
chain” as the combination of nine generic value added activities operating within a
firm – activities that work together to provide value to customers (Porter 1996).
Porter (ibid) linked up the value chains between firms to form what he called a value
system. However, in the present era of greater outsourcing and collaboration the
linkage between multiple firms’ value creating processes has more commonly
become the so called value chain. As the name implies, the primary focus in value
Mwajiande & Lugendo
Journal of Rural and Community Development, 10, 2(2015) 47-62 53
chain is on interdependent processes that generate value, and the resulting demand
and funds flows that are created (Feller, Shunk, and Callarman, 2006).
Therefore the concept of value chain describes the full range of activities which are
required to bring fish-farming product through the different phases of production to
final consumers (Knorringa and Pegler, 2006). The concept of Value Chain Analysis
(VCA) for policy analysis (Lorenzo, 2013) allows the examination of multiple
dimensions in the VCA framework of fish-farming value chain in achieving specific
policy objectives, such as poverty alleviation by applying different policy options
and scenarios and their socio-economic impacts (Bellù and Pansini, 2009). The
value chain analysis is therefore an important step to understanding the fish-farming
sector in Tanzania. It helps to understand the nature of the activities involved,
opportunities and constraints for development.
Fish-farming value chain starts at the inputs supplier including fingerlings to the fish
market. However, we have taken the view that fish fingerlings represent a very
important input to the farming operations along with other key inputs such as fish
feed, labour, capital because it has impact on quality of fish. Therefore, hatchery or
breeding sites for fingerlings, input suppliers, agrovets, and harvest equipment are
all considered to be in the first stage of the fish farming value chain. They have the
roles of providing inputs to the fish farmers for production (Macfadyen et al., 2011).
Fish farmers are in the second stage of the value chain, their main role is to perform
all the activities necessary for production of fish products.
The third stage in the value chain is the fish marketers who constitute the role of
bringing products to consumers. This stage is comprised of wholesalers, retailers,
traders and processors. The processors play the roles of freezing, cleaning, cutting into
pieces, packaging and then selling the products. Both wholesalers and retailers have
the role of selling products to final consumers; whereas, traders may export the product
or sell to industries. This segment of the fish farming value chain is relatively
undeveloped and limits the incentive of farmers to engage in the sub-sector.
6.4 Assessment of Fish-farming Technologies
In order to gain insight into the available and employed technology in fish farming,
the study collected information on the type and source of fingerlings, fish feeds,
water, tools, and labour force. In addition, information on rotation of pond water
change, technology application, and schedules of fish harvesting were also gathered.
As far as the use of improved farming equipment is concerned, the study found that
a very small proportion of respondents were using water pumps (5%), weight
balances (4%), and generators (3%). Other technologies such as fish nets and
scooping nets were reported to be used by 17% and 1% of respondents respectively.
Furthermore, technology in the fish farming industry includes pond structure and
size, species and sex of fingerlings, fish feeds, fishing gear, hatchery and storage
facilities. The study inquired into the species, sex, and number of fingerlings. The
majority of farmers (97%) were found to farm tilapia (perege/ sato in Swahili) and
very few raised catfish (Kambale in Swahili). With respect to sex of farmed fishes,
a significant proportion (21.8%) of respondents did not know the sex of fish they
raised, while majority of them (76.5%) raise both male and female fish. Keeping
both sexes increases reproduction, but creates high competition for space, air and
food. According to extension services and best practice management, mono-sex fish-
farming is more profitable as fish can be harvested at 1.5kg in 6 months. Mono-sex
Mwajiande & Lugendo
Journal of Rural and Community Development, 10, 2(2015) 47-62 54
fish farming technology has been used for the purpose of increasing the productivity
of fish farmers in many places. Some of the empirical reviews from different places
suggest that the technology can increase productivity and reduce the problems of
food security and poverty within the fish farmers’ communities.
According to WorldFish (2012) an improved breed (mono-sex) of Nile Tilapia,
which grows 30% faster than non-improved strains, is helping to increase
aquaculture productivity and food security in Ghana. The Water Research Institute
(WRI) in partnership with WorldFish, has developed Nile Tilapia (Oreochromis
niloticus) that grows 30% faster than its wild ancestors. This could be translated
into greater income for farmers as they can produce more fish per year and have
both labour and cost savings. An increase in productivity also has an effect on food
security and nutrition available. The above described technologies had limited
application amongst the sampled farmers in Tanzania, This is a challenge that
requires policy action for the sub-sector to make significant contributions to the
desired socio-economic transformation in the country by the 2025 target of
becoming a Middle Income Country.
The sampled respondents from Kilimanjaro region reported that their ponds had the
average size of 200-400m2, whereas more than half of respondents from Kagera,
Njombe and Morogoro regions had fish ponds of less than 200-400m. According to
the national fisheries extension services, the recommended pond size is 200m x
400m, sufficient for introducing 900 fingerlings in commercial fish farming. It was
further observed that 86% of respondents were underutilizing the fish ponds by
planting smaller number of fingerlings, whereas 33% of respondents were planting
fingerlings which were more than the recommended number of fingerlings per pond
size for commercial farming. This means there is low or inadequate knowledge on
the best practices for fish-farming.
One of the best practices in fish-farming is the requirement for rotational change of
water. A significant proportion of respondents (37%) reported that they do not
change pond water; whereas, 82% of respondents were found not using any type of
energy for pumping water. With respect to fish harvesting schedules and the weight
of fish at harvest, the proportions of respondents who reported that the harvest was
after exactly six months was the smallest (19%). More than half of respondents
reported the weight of fish on harvest to be either below half a kilogram (37%) or
unknown (26%). According to the Ministry of Fisheries, the recommended harvest
schedule and fish weight for commercial fish farming takes 6 months and the harvest
weight should be between 0.5 and 1kg. Therefore, this finding connotes that majority
of respondents were at a subsistence level.
The study asked farmers their main motives for engaging in fish-farming. Four main
reasons mentioned by farmers as their motives in order of importance include; fish
as household staple food accompaniment (65.2%), source of income (24.6%), leisure
activity (5.5%) and just induced by friends (4.8%). This has implications for the
targeting of farm groups who can undertake fish-farming as a business for
transforming their socio-economic status.
6.5 Skills and Knowledge Gap
Fish-farming requires basic as well as specialised training such as, pond
management, feed production, fingerling selection and water management (Adinya,
Offem, and Ikpi, 2011). The study asked farmers whether they received any
Mwajiande & Lugendo
Journal of Rural and Community Development, 10, 2(2015) 47-62 55
relevant training and the type and source of training. It was interesting to note that
the majority (82%) of respondents had some training in general fish farming;
however only 12% had attended entrepreneurship courses. This is an area with
limited knowledge that calls for capacity building as a fundamental intervention for
transforming the sub-sector into commercial fish-farming.
6.6 Economic Opportunities Through the Fish-farming Value Chain
Value chain analysis (VCA) can be a tool for unleashing the potential economic
opportunities for the fish-farming sub-sector economy. This is because VCA seeks
to understand the nature of the activities involved, opportunities and constraints in
relationships and their implications for development from inception to final
consumption of the product or service. The description of the fish-farming value
chain is comprised of input supply, processors, traders, and markets. The vertical
participants within input suppliers include input suppliers of fish feeds (24.2%),
input suppliers of medicine (2.5%), input suppliers of machinery (0.6%), extension
officers who provide extension services (6.5%) and breeder of fish fingerlings
(10.4%). Producers or fish farmers (80.1%) made up the second and the largest part
of key players in the fish farming value chain. However, producers do not have
vertical participants. Processors made up the third part of the value chain and consist
of vertical participants within the node. These participants include processors
dealing with packaging (0.6%), filleting (5.9%), smoking (1.4%), drying (0.8%),
salting (0.6%), canning (0.8%) and freezing (0.8%). The last part of fish farming
value chain consists of traders. Within traders there are vertical participants which
include buyers on farm site (7.9%), retailers (22.2%) and whole sellers (2.3%).
The study results show that there are many fish farmers, but few processors, traders
and input suppliers in the value chain. This implies that the fish farming value chain
of Tanzania is weak, limiting the growth and transformation of fish-farming into a
commercial activity. Learning from the respondents, most of fish farmers (60.4%)
obtain fingerlings from each other. Only a few fish farmers obtain their fingerling
from government (23.5%), and 11.9% obtain fingerlings from rivers. About 2.7% of
the respondents obtain from private breeders. Overall, farmers don’t have good and
reliable sources for fingerlings. This implies that there is weak supply but creates an
opportunity for private sector to invest in fish hatchery. This shall require policy
reforms for unleashing the potential of the sub-sector. In addition, there is a need for
the government and agricultural research institutions to support the required
transformations in the fish-farming sub-sector by enhancing the entire value chain.
Again, transformations in fish-farming require quality and reliable sources of feeds.
The needs assessment found that 76% of fish farmers produce fish feeds themselves
while only 17% obtain their feeds from fish local feed manufacturers who produce
fish feeds using locally obtained materials like maize and paddy husks, remains of
vegetables from garden, cocoyam leaves, and cattle dung. However, it was found
that many of them don’t have basic knowledge of producing the right fish feeds.
This implies firstly, that there is an opportunity for the private sector to invest in the
production of fish feeds and the government to encourage and prepare. Secondly,
there is a need also for the government and research institutions to support them by
introducing capacity building programs for fish farmers to be able to produce
required fish feeds as per required fish feed ratio.
Regarding markets, most (71.3%) of fish farmers sell their product to their
neighbours while other fish farmers sell their fish products to the village market
Mwajiande & Lugendo
Journal of Rural and Community Development, 10, 2(2015) 47-62 56
(36.9%). Some traders (retailers and wholesalers) buy fish from the farming site
(22.9%). Very few (3.1%) export their fish product. None of fish farmers
respondents claim to sell his/her fish product to the fish processing industry. This
implies that they have not utilized other markets like the export market, processing
industries, supermarkets and regional markets. This may be contributed to by the
poor quality of the produced fish and products and low capacity to meet the required
market demand.
Findings from the study (Table 2) indicate that there is significant higher price
margin between producers and traders of Nile tilapia and tilapia at the 1kg weight
when brought to market. This indicates that there is an opportunity for traders and
processors to maximize revenue through trading farmed fish with weight greater
than 1kg.
Table 2: Average Price between Producer and Traders
Fish type
t
Sig.
(2
-tailed)
Average
Producer
Price
(TZS)
Average
Trader
Price(TZS)
Mean
Margin(T
ZS)
95% Confidence
Interval of the
Difference
Lower
Upper
Sato (>1Kg)
47.03
.000
2470.58
7670.73
5200.14
4980.5
5419.82
Perege (>1kg)
6.81
.000
2132.78
3462.19
1329.41
944.9
1713.90
Sato (>0.5Kg)
7.49
.000
1626.47
2563.41
936.94
688.7
1185.22
Pe
rege (=< 0.5kg)
13.16
.000
423.97
1093.90
669.93
569.7
770.15
Perege (>0.5kg)
4.69
.000
1303.28
1943.90
640.62
372.3
908.95
Sato (=<0.5Kg)
6.20
.000
702.00
1052.68
350.68
238.4
462.97
Kambale(>0.5kg)
0.06
.951
2250.00
2287.31
37.32
-1170.7
1245.36
Kambale(>1kg)
-0.01
.993
3041.67
3036.58
-5.08
-1170.1
1159.90
Kambale(=<0.5kg)
-0.72
.473
1200.00
990.97
-209.02
-789.9
371.81
Source: Authors' analysis.
As evidenced in Table 2, the capacity of fish farmers to produce fish at optimum
supply weight (>1kg) is limited. Therefore capacity building for fish-farming along
with advocacy of fish farmers to produce at the required weight and supply could be
a necessary action.
Unleashing the potential opportunities along the value chain of fish farming sub-
sector is necessary measure for the efficiency of fish farmers in production. This is
important because if the production process is not efficient first of all it is very
difficult for other nodes within the chain to grow and it also shows that there is more
room for production opportunities. Therefore this justifies the analysis of efficiency
of fish farmers in this study. Analysis of production efficiency has been done in
many empirical studies using translog production function estimation, we use
stochastic frontier version 4.1 software to estimate technical efficiency.
Mwajiande & Lugendo
Journal of Rural and Community Development, 10, 2(2015) 47-62 57
The translog production function is a generalization of the Cobb–Douglas
production function. The name translog stands for 'transcendental logarithmic. It is
the function which is used to estimate the efficiency in the use of input in relation to
the output obtained. Inputs such as ponds, fish feed, fingerlings planted and
education were considered as independent variables; while the dependent variable
was the number of fish caught for the last season.
The analysis shows that fish farmers were efficient by 43.8% which means that they
are inefficient by 62.2%. This implies that, there is more room for increasing
production through adding more inputs by increasing pond size in the area suitable
for fish farming, planting appropriate fingerlings according to the pond size and
supplying more appropriate fish feed. Also the comparisons of efficiency across
regions show that the Ruvuma region has the highest (53.6%) mean efficiency
followed by the Mbeya and the Morogoro regions respectively. Njombe region has
the lowest (33.8%) mean efficiency.
In the overall, fish farmers in Tanzania are not efficient due to un-addressed constraints
and this finding is supported by the available literature. The Board of External Trade
(2003) reports that, “despite of the big aquaculture potential the fish harvests may
continue to be low in Tanzania if the constraints facing fish farmers are not addressed
properly”. The constraints include; little information regarding aquaculture in the
country and quality of data; ineffective extension services; lack of co-ordinated policies
across sectors; farm management and accessibility to credit facilities. Interviews with
extension officers showed that if the constraints are well addressed, a pond size of
200m x 400m is sufficient for 900 fingerlings in commercial fish farming. This
could be translated into US$2,500 earning in six months when 1kg of farmed
fish is sold at 5,000 Tanzania shillings; implying that the sub-sector has a
potential of transforming smallholders income poverty.
7.0 Constraints Facing Fish-farming in Tanzania
The study objective was to identify constraints facing fish-farming in Tanzania. In
other words, the study explored the question; why the fish-farming subsector is
underdeveloped in Tanzania? The constraints facing fish-farming in Tanzania are
many (Board of External Trade, 2003), however little research has been conducted
in the academic literature focusing on Tanzania. Wetengere (2011) identified
marketing constraints facing the sub-sector. The respondents identified lack of
necessary inputs (88%), lack of bank loans (81%) and fishing education (62%). The
relative critical challenges include lack of preservation cold rooms (45%), thieves
and wild animals (44%) and extension services (43%). The overall observation is
that there are multiple problems facing the fish-farming sub-sector that contributes
to its underdevelopment in the country.
It was important to know how farmers address these challenges. Fish-farmers find
coping strategies for the identified problems (Table 3). It was noted that farmers had
some innovative ways for addressing the challenges. For example, to overcome the
inadequate feed supply, about 90% of farmers make their own feeds which were
found to be of low quality affecting fish growth and body weight. The recommended
feeding is 8% of body weight for the first 2 months, followed by 5% of body weight
for the next 2 months, and 3% of body weight for the last 2 months (Ministry of
Livestock and Fisheries, 2013). Some farmers reduce the required amount for
feeding to minimize costs that in the end affects the quality of the farmed fish. Table
Mwajiande & Lugendo
Journal of Rural and Community Development, 10, 2(2015) 47-62 58
3 summarizes the compounded constraints of fish farming in Tanzania and the
coping strategies adopted by farmers.
Table 3: Ways Used to Overcome Fish-farming Challenges (n=293)
Strategy to overcome shortage of feeds
Percentage
Confidence Interval (95%)
Lower
Upper
Make own feeds
90.0
85.3
94.0
Purchase
5.3
2.0
8.7
Reduce required feeds
.7
.0
2.6
Substitute with garden vegetables
1.3
.7
2.7
Do nothing
2.7
.7
5.3
Strategy for medication
Do not use
91.3
88.0
94.7
Unaware
7.3
4.0
10.7
Follows best practices
.7
.0
2.0
Strategy to overcome shortage of fingerlings
From own pond
28.0
21.3
35.3
Purchase from others
15.3
10.0
20.7
Friendship hospitality
26.0
20.0
32.7
From local ponds/ rivers
30.0
22.7
37.3
Strategy to overcome shortage of extension services
Learn from peers
12.7
8.0
18.6
From government and private extension
services 20.7 15.3 26.0
Do not seek extension services
64.0
58.0
70.7
Self-learning
2.0
.0
5.9
Strategy to overcome loans
No strategy
63.3
56.7
70.0
Personal savings
21.3
15.3
27.3
Never sourced
9.3
5.3
14.0
Sourced but failed access
5.3
2.0
8.7
Strategy for fish preservations
Nothing
83.3
78.0
88.0
Sun drying
4.7
2.0
8.0
Cold containers
8.0
4.7
12.0
Smoking
1.3
.0
3.3
Freezer / fridge
1.3
.0
3.3
Source: Authors' analysis.
Mwajiande & Lugendo
Journal of Rural and Community Development, 10, 2(2015) 47-62 59
Obtaining quality fingerlings is another critical problem facing fish-farming in
Tanzania. About 30% of the surveyed farmers obtain fingerlings from rivers or
ponds and 28% farmers raise their own fingerlings. This situation has no quality
assurance of the fingerlings.
Other constraints of fish-farming value chain are the lack of marketing and access
to capital. Most fish-farmers sell their farm outputs to neighbourhood and local
markets at the farm gates. This implies that the fish-farming is undertaken as
subsistence activity. Farmers’ access to credit facilities for developing fish-farming
is another serious constraint as it was found that about 49% of the surveyed fish-
farmers did not have any access to credit or loans; whereas 29% get finance for
starting fish-farming from their own sources and social networks.
The analysis showed a multitude of constraints that explain why fish-farming is
underdeveloped in Tanzania. Since there is government will for transforming fish-
farming into sustainable commercial ventures, interventions such as policy
framework to support the transformations are very much necessary for the
development of the sub-sector in the country. The way forward for increasing the
economic potential contribution of the sub-sector is to address the above
constraints including increasing fingerlings production at the fingerling production
centres of Kingolwira (Morogoro region) and Mbarali (Mbeya region). More
fingerling production centres should be established in designated regions to reduce
the distance covered in the fingerling distribution chains. Semi-intensive and
intensive aquaculture should be encouraged in order to commercialize aquaculture
fish production.
In addition, extension services for aquaculture farmers should be improved to enable
farmers to improve farm management skills. The country has 7,974 extension
officers which represents 53% of the demand (Kayandabila, 2013). Although
the draft of National Aquaculture Research and Development Strategic Plan (2012)
identifies similar constraints, the major challenge has remained in the weak
implementation framework. The government’s capacity to produce the required
inputs at Kingolwira public institution has deteriorated. Fingerling production at the
time of this research had stopped despite the demand for fingerlings still being high.
This is an area where public-private partnership is required from the policy
environment for unleashing potentials in fish-farming.
Extension services are epistemologically designed to “extend research based
knowledge to rural sector” in order to improve farm productivity, technology
transfer and farm management practices. The demand for extension services in the
transformation of fish-farming as agribusiness is enormous. The evidence gathered
from this study indicates insufficient or non-availability of the extension services,
has tremendous effect on famers’ knowledge, proper use of medicines, fish farm
management practices and appropriate technology application. The National
Fisheries Sector Development acknowledge that aquaculture extension services are
required for information and experience sharing with farmers in order to increase
sustainable fish production and productivity (URT, 2010). However, there are
critical constraints in the delivery of extension services to fish farmers including;
inadequate extension capacity, weak research-training-extension, and inadequate
infrastructure and facilities. It is recommended that the policy framework must be
able to put in place the required technology through a supportive extension services.
Mwajiande & Lugendo
Journal of Rural and Community Development, 10, 2(2015) 47-62 60
Another important policy option for increasing fish farming is establishing subsidy
for fish-farming. The policy can be considered within the public-private partnerships
by way of providing incentives for the private-sector to engage in the feed
production and processing industries since fish farming is an important subsector
that can increasingly contribute to food security and nutrition as well as create
employment. This realization can be made operational by the policy of putting in
place an investment plan for small, medium and large-scale commercial aquaculture.
For example, the Kenyan Government has translated its policy into action by
establishing and supporting programmes including the Fish Farming Enterprise
Productivity Program with a purpose of stimulating economic opportunities in rural
areas for employment creation, improving nutrition and and income
opportunities.This has been done by increasing production of farmed fish from 4000
MT to over 20,000 mega tons in the medium term and over 100,000 mega tons in
the long term by constructing 28,000 fish ponds in the country (Kariuki, 2013).
Similarly, the Tanzania fish farming constraints could be addressed through a policy
promoting incentives for investment in fish farming. The interventions require a
practical policy agenda for the investment implementations in the responsible
ministry and other stakeholders.
8.0 Conclusion and Policy Recommendations
This study examined the constraints that limit transformation of fish farming from
subsistence to commercial farming in Tanzania. The sub sector is guided by the
Fisheries Act, 2003, the National Fisheries Sector Policy, 1997 and the Fisheries
Sector Development Programme, 2010. Despite of the existence of policy instruments,
fish-farming hasn’t effectively been harnessed to the full potential for it to contribute
to smallholder poverty alleviation.
The paper observed multiple constraints facing the fish farming sub-sector including
insufficient inputs supply, technology application, lack of processing plants, trading
and weak government policy support.. For the fish-farming subsector
transformations from subsistence to commercial fish farming to happen in Tanzania,
the following policy actions are recommended to be undertaken;
Strengthen Public-Private Partnerships in the value chain for increasing
smallholder access to quality fingerlings, feeds, medicines, processing, and
markets.
Providing capacity building programmes for small farmers focusing on
knowledge and skills development for small and medium fish-farmers.
Extension services be provided to accelerate technology adoption to small
farmers. This is important at the moment because farmers are not able to
access the necessary technologies such as raising mono-sex fish that have a
potential of reducing labour and time costs while maximizing profit.
Establish fish-farming subsidy programme for promoting pond construction
and inputs.
Mwajiande & Lugendo
Journal of Rural and Community Development, 10, 2(2015) 47-62 61
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