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International Journal of Business and Social Science Vol. 5 No. 6; May 2014
130
Structure, Conduct and Performance of Groundnuts Markets in Northern and
Central Malawi: Case Studies of Mzimba and Kasungu Districts
Wisdom Madede Nzima
Department of Agricultural Extension Services
Ministry of Agriculture and Food Security
P.O. Box 30145
Lilongwe 3
Malawi
Joseph Dzanja
Bonnet Kamwana
Department of Agribusiness Management
Lilongwe University of Agriculture and Natural Resources
Bunda College of Agriculture
P.O. Box 219
Lilongwe
Malawi
Abstract
This paper explores and assesses efficiency of the structure, conduct and performance of groundnuts markets in
northern and central Malawi. Smallholder farmers and traders involved in groundnuts were interviewed. Using
time series price data, the spatially distinct groundnuts markets were also examined. The results show that most
smallholder farmers adopted Chalimbana and CG7 groundnut varieties, over-recycle groundnut seed, and do not
use recommended seed rate. Five different groundnut marketing channels are identified. However, there is
minimal value addition in all channels. The markets are weakly integrated and segmented with a few sellers. The
study highlights the need for organised groundnut seed systems to ensure supply of high quality seed to farmers;
strengthened market oriented extension services; improved roads to production areas; improved and affordable
technologies on production and value addition; vibrant farmer organisations and improved market information
generation and dissemination to farmers and traders.
Keywords: Groundnut Market, Structure, Conduct, Performance, Efficiency, Margin, Malawi
1.0 Introduction
1.1 Overview of Agricultural Sector in Malawi
Agriculture continues to remain the main driver of Malawi’s economy despite some growths in the industrial and
manufacturing sectors. It contributes 39% of the country’s Gross Domestic Product (GDP), employs 85% of the
country’s workforce in food and cash production, agro-industries and inputs and outputs markets and accounts for
more than 90% of the country’s foreign exchange earnings (Government of Malawi [GoM], 2009). It is also the
main source of savings and investible funds in Malawi—about 61% of the country’s households depend on crop
sales for their incomes. The sector consists of smallholder and estate subsectors. The estate subsector is mainly for
production of high value cash crops such as tobacco, tea, sugar, coffee and macadamia (Kachule, 2011). The
smallholder subsector accounts for more than 70% of agricultural GDP (GoM, 2009). One of the crops grown
under smallholder subsector is groundnuts. Groundnuts provide about 25% of household’s agricultural income
(Minde et al., 2008).
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131
1.2 Groundnuts Production and Marketing
Groundnut is produced by farmers in all districts of Malawi as source of food and income, livestock feed, for
export and also for improving soil fertility. About 70% of the total groundnut production is consumed locally.
Over the past 10 years, overall production has not significantly increased in Malawi. The annual unshelled
groundnut production grew from 131,543T in 1999 to 282,054T in 2009 (FAO STAT, 2011). This production
accounted for 2% of total groundnuts production in Africa. By 2009, Malawi ranked as 19th largest producer of
groundnuts in the world (FAO STAT, 2011).
In terms of marketing, the Agricultural Development and Marketing Corporation (ADMARC), a statutory
corporation, was the sole buyer and supplier of produce and inputs respectively. However, since mid 1980s
government liberalized market to allow private sector play an active role in the marketing of inputs and produce in
Malawi. Simtowe et al., 2009 noted that Malawi ranked 9th exporter of groundnuts in sub-Saharan Africa. The
export volume over the past ten years has been small and with lots of fluctuations. By 2009, Malawi’s groundnuts
exports had increased to 19,879T (FAO STAT, 2011).
The government still feels there is low groundnut production and marketing despite market liberalization
opportunity to smallholder farmers and traders (GoM, 2008). This contributes to poor human nutrition status,
slow growth of livestock and crop cereals sectors, low income and low foreign exchange earnings from
groundnuts. The low and fluctuating groundnuts production and marketing in Malawi is an indication of market
failure to stimulate production and marketing.
1.3 Objectives of the Study
In order to address problems associated with market failure so as to increase groundnuts production and
marketing, knowledge of the structure, conduct and performance of groundnuts markets is required. The type of
market structure that prevails in a market determines efficiency of marketing system (conduct and performance of
markets). The knowledge of structure, conduct and performance of groundnuts markets facilitates further
innovations and productivity growth in the groundnuts subsector. Unfortunately, no studies have been conducted
in Malawi to analyze or investigate the structure, conduct and performance of groundnuts markets. This study
therefore aims at analysing the structure, conduct and performance of groundnuts markets in Northern and Central
Malawi. Specifically, the paper aims to (i) analyse existing marketing systems of groundnuts (ii) conduct
groundnuts profitability analysis (iii) identify factors affecting groundnuts production and (iv) identify
smallholder farmer’s constraints to groundnuts production and marketing.
2.0 Materials and Methods
2.1 Market Structure, Conduct and Performance
Market structure refers to a set of market characteristics that determine the economic environment in which a firm
operates (Thomas and Maurice, 2011). It is characterized on the basis of four industry characteristics: (i) number
and size distribution of active buyers and sellers and potential entrants; (ii) degree of product differentiation; (iii)
amount and cost of information about product price and quality and (iv) condition of entry and exit (Hirschey et
al., 1993).
Market conduct refers to the patterns of behaviours that firms follow in adapting or adjusting to the markets in
which they sell or buy. The dimensions of conduct include methods employed by firms in determining the price of
an output and sales promotion policy, the presence or absence of coercive tactics directed against either
established rivals or potential entrants (Bain, 1968).
Market performance refers to the economic results that flow from the industry and how well it performs in terms
of efficiency and progressiveness or innovation, given its technical environment (Bain, 1968). It is the impact of
structure and conduct as measured in terms of the variables such as prices, costs and volume of output (Bresser
and King, 1970).
2.2 Analytical Framework/Procedure
The structure, conduct and performance of markets have been analysed by researchers using various different
approaches. Nambiro et al., (2001) analysed the structure and conduct of the market in Trans Nzoia district
(Western Kenya) in order to understand the organisation of the market and assess the degree of competition in
hybrid maize seed production and retailing using Gini coefficients.
International Journal of Business and Social Science Vol. 5 No. 6; May 2014
132
Enibe et al., (2008) described the structure, conduct and performance of banana market in Anambra State of
Nigeria using descriptive statistics, Gini coefficients, price spread, behaviour of middlemen, conduct of marketing
functions and gross marketing margins.
Giroh et al., 2010 also examined the structure, conduct and performance of farm gate marketing of natural rubber
in Edo and Delta States of Nigeria using Gini coefficient, Budgetary technique, Market margins, Marketing Costs
and Rate of Return to investment. Odhiambo et al., (2006) analysed the structure and performance of beans
marketing system in Nairobi using descriptive statistics, concentration ratios and co-integration models. Bain
(1968) observed that by analyzing the level of the marketing margins and their cost components, it is possible to
evaluate the impact of structure and conduct characteristics on market performance.
In this study, a number of analytical approaches were used. They include: Herfindahl-Hirschman Index (HHI),
Marketing Margins, Marketing Efficiency Index (MEI), Price Spread, Cobb Douglas Production Function, and
Spatial Market Integration (using bivariate correlation coefficients of price difference). Market structure was
determined by assessing market concentrations and entry conditions of the markets using HHI as follows:
=
−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−(1)
Where: MSi is the Market Share of selleri; and n is the number of sellers in the market. The market shares were
calculated based on quantities of groundnuts handled by each seller as follows:
=
∑
------------------------------------------------------------------------------------------------ (2)
Vi is the quantity of groundnuts handled by seller i (in kg); and ∑ is the total quantity of groundnuts handled by
sellers in the market (in kg)
Marketing margins were calculated by determining price variations at different segments and compare them with
the final price paid by the consumer. The formula for total marketing margin was as follows:
=
∗100 − − − − − − − −(3)
The price spread was applied to measure the degree of pricing efficiency. For farmers, it was calculated by
deducting costs of marketing from gross price. For traders in all the channels, the price-spread focused on the
trader’s surplus as a percentage of total marketing costs.
Marketing efficiencies of all channels were determined by MIE. According to Acharya and Agarwal (2001), MIE
is the ratio of net price received by the farmer to the total marketing cost plus total margin as follows:
=
−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−(4)
Where MEI is the Marketing Efficiency Index; NP is the Net Price received by the farmers (MK/Kg); MM is the
Total Net Marketing Margin (Total Traders Surplus) for Traders in the channel; and MC is the Total Marketing
Cost incurred by Traders in the channel.
The performance of groundnuts markets was also assessed by the volume of output produced by farmers (and its
underlying factors) using production function. The transformed Cobb-Douglas production model (which
combined both physical and non physical factors of production) was applied as follows:
lnOUTPUT =+ + + + + +
+ + +−−−−−−−−−−−−−(5)
Where:
lnOUTPUT = Natural log of Groundnuts produced in household i (kg)
lnLAB = Natural log of amount of labour used in household i (person hours)
lnSEED = Natural log of amount of seed used in household i (kg)
EDUCAT = Education of household head i (number of years in school)
EXTVISIT = Whether a household is in contact with an extension worker (1=yes and 0=no)
VOLSOLDPY = Volume of Groundnuts sold previous year (Kg)
DISTMKT = Distance to market (in Km)
FARMGP = Farm Gate Price (MK/Kg)
AGE = Age of the household i (years)
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133
i = Coefficients (parameters) to be estimated (i= 0,1,2,3,4,5,6,7,8,9)
ui = Error term
Spatial market integration analysis was conducted to compliment assessment of performance of groundnuts
markets in Northern and Central Malawi. Market integration refers to the price transmission in the marketing
chain. Spatial market integration reflects the effects of a price change in one market on the price of the same
commodity in another market location. Bivariate coefficients of Correlation of price differences were calculated
determine degree of groundnut market integration.
2.3 Data Collection
Primary data was collected from groundnuts smallholder farmers and traders in Mzimba and Kasungu districts
using questionnaires and focus group discussions. The two districts are among the major groundnuts producing
areas for Northern and Central Malawi. Stratified random sampling method was used to sample a total of 115
farmers (52 in Mzimba and 63 in Kasungu) and 67 traders. Specifically, farmers were from Extension Planning
Areas of Santhe, Lisasadzi, Kasungu-Chipala and Kaluluma (for Kasungu) and Luwerezi, Champhira and
Vibangalala (for Mzimba) The sampled traders were from the markets of Mzuzu, Mzimba, Kasungu, Jenda,
Embangweni, Nkhamenya, Chatoloma, Chinkhoma, Santhe and Lilongwe. Mzuzu and Lilongwe are the major
market outlets for groundnuts produced in the study area. The study also employed the use of monthly time series
data on price of groundnuts collected from April 2005 to June 2011 for the aforementioned markets.
3.0 Results and Discussions
3.1 Groundnuts Varieties and Seed Sources for Farmers
There are over 10 improved government released groundnut varieties in Malawi (GoM, 2008). However, the most
adopted and used varieties are Chalimbana (67.1% of farmers) and CG7 (64.3% of farmers). Smallholder farmers
access seed from companies (such as ADMARC), agro-dealers, recycling, traders, NGOs, Research stations and
government projects. The major source of seed among farmers is recycling (67.8% of farmers).
3.2 Groundnuts Marketing Channels and Functions
The majority of farmers (85.2%) sold their produce to traders. The traders consisted of vendors, retailers,
wholesalers and individual households or fellow farmers. About 60.9% of farmers sold their produce to vendors,
22.6% to wholesalers, 7.0% to retailers and 7.0% to fellow farmers. Vendors are the major buyers of groundnuts
produce from farmers because they are accessible and available all the time. Farmers (29.6%) also sold
groundnuts produce to consumers at designated government markets. Five marketing channels were identified.
Channel 1 consisted of farmers who sold groundnuts to vendors at a local market in their area. The vendors then
incur storage, transport and packaging costs for groundnuts to reach consumers.
Channel 2 consists of farmers that sold groundnuts to vendors who in turn sold groundnuts to the retailers. The
retailers then sold to final consumers. Channel 3 has farmers that sold directly to retailers, who in turn sold to
individual consumers. The retailers in channels 2 and 3 consisted of retail shop owners, super markets and agro-
dealers. Channel 4 consisted of farmers that sold groundnuts directly to consumers. Channel 5 comprised of
farmers who sold groundnuts to wholesale-retail companies that in turn sell to consumers. The companies include
ADMARC, Mulli Brothers Group, National Smallholder Farmers Association of Malawi, Farmers World, Export
Trading and Takondwa Company. The major marketing functions carried out in all five marketing channels are
storage, grading and processing.
3.3 Market Structure of Groundnuts
Herfindahl-Hirschman Indices were calculated to assess market concentration for the markets of Mzuzu, Mzimba,
Jenda, Nkhamenya, Chatoloma, Chinkhoma, Kasungu, Santhe, Embangweni and Lilongwe. The degree of seller
concentration was high (above 0.5) in the markets of Chatoloma, Embangweni, Kasungu, Jenda and Nkhamenya.
This means that the markets were dominated by a few sellers. The markets for Chinkhoma, Lilongwe, Mzimba,
Mzuzu and Santhe were also dominated by a few sellers since their HHI were above perfect competition index
(0.1) despite being below 0.5. Table 1 below shows HHI of seller concentration for each market.
International Journal of Business and Social Science Vol. 5 No. 6; May 2014
134
Table 1: HH Indices of Seller Concentration in the Markets
Market
Groundnuts HHI Indices
Chatoloma
0.879
Chinkhoma
0.502
Embangweni
0.710
Jenda
0.850
Kasungu
0.607
Lilongwe
0.154
Mzimba
0.280
Mzuzu
0.109
Nkhamenya
0.924
Santhe
0.271
The dominance of few sellers in most markets implies low competition among sellers. This would in turn make
farmers receive low prices for their groundnuts produce. It would also make other potential traders fail to
penetrate the markets resulting into no further innovations in the groundnuts industry.
3.3 Conduct of Groundnuts Markets
There were no trader based organisations or marketing groups in all the markets to affect the bargaining power.
This means that setting of prices was done on individual basis. The behaviour was reflected in purchase of
produce from farmers in that it’s the individual traders that most of times determine the price. The determination
of prices in groundnuts markets was dependent on the demand (58.2%), transport cost (56.7%), quality in terms of
maturity and grading (26.9%) and purchase price (20.9%).
3.4 Performance of Groundnut Markets
3.4.1 Marketing Margins and Marketing Efficiency Indices
The mean selling prices (MK/Kg) at farm gate, vendor, wholesale-retailer and retailer levels were K94.62,
K174.72, K227.93 and K262.33 respectively. The marketing margins were calculated for all the five marketing
channels. Farmers’ share was lowest (73.76%) in channel 1 and highest (100.00%) for channel 4. The producer
share increased to 100% because farmers played the role done by vendors and retailers and took the profits that
could have gone to them. The producer share for channels 2 and 3 was the same (75.63%) despite the difference
in the number of players in between each of the channels. The reason for the same producer shares was because
farmers sold their produce to all the types of traders in their locality. So, farmers’ selling price was the same for
all the channels but the consumer price differed. Table 2 below shows marketing margins and producer share for
each channel.
Table 2: Gross Marketing Margins (GMM in %)
GMM
Channel 1
Channel 2
Channel 3
Channel 4
Channel 5
Total GMM
45.84
63.93
63.93
0.00
58.49
GMM
-
Middleman
45.84
30.53
-
-
-
GMM
-
Wholesale
-
Retailers
-
-
-
-
58.49
Retailers
-
33.40
63.93
-
-
Producer Participation
73.76
75.63
75.63
100.00
74.34
The price spread method was applied to assess efficiency of marketing channels by removing marketing costs.
Traders’ surplus was calculated as a percentage of the total marketing costs to determine how well markets
perform in terms of prices. The mean vendor’s surplus was 58.5%, wholesale-retailer’s surplus was 117.3%,
retailers’ surplus was 36.5% (for channel 2) and 105.5% (for channel 3). This implies that all the intermediaries
make super normal profits as since they are above the acceptable range of 20-30%, according to Hay and Morris
(1979) as quoted by Nakhumwa (2001). Marketing Efficiency Indices were then calculated to determine level of
marketing efficiency for all channels. Channel 4 was the most efficient since it had the highest index of positive
infinity. This was followed by Channels 1, 5, 2 and 3 respectively. Table 3 below shows the price spread and
marketing efficiency indices.
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Table 3 Groundnuts Price Spread and Marketing Efficiency Indices
Participant
Description
Channel
1
Channel
2
Channel
3
Channel 4
Channel
5
Farmers
Selling Price
94.62
94.62
94.62
94.62
94.62
Storage
2.27 (1.3)
2.27 (0.9)
2.27 (0.9)
2.27 (2.4)
2.27 (1.0)
Grading
3.1 (1.8)
3.1 (1.1)
3.1 (1.1)
3.1 (3.3)
3.1 (1.4)
Net Margin
74.73
(42.8)
162.34
(61.9)
162.34 (61.9)
89.25
(94.3)
127.94 (56.1)
Gross Margin
80.1 (45.8)
167.71
(63.9)
167.71 (63.9)
0
133.31 (58.5)
Farmers Share
73.76
75.63
75.63
100
74.34
Vendors
Buy price
94.62
(85.9)
94.62 (85.9)
0
0
0
Transport Cost
12.24
(11.1)
12.24 (11.7)
0
0
0
Storage Cost
1.84 (1.7)
1.84 (1.7)
0
0
0
Market Costs
1.51 (1.3)
1.51
(1.3)
0
0
0
Total Costs
110.21
110.21
0
0
0
Selling Price
174.72
174.72
0
0
0
Traders
Surplus
64.51
(58.5)
64.51 (58.5)
0
0
0
Wholesale
-
Retailers
Buy price
0
0
0
0
94.62 (90.2)
Transport Cost
0
0
0
0
7.83 (7.5)
Storage Cost
0
0
0
0
0.62
(0.6)
Market Costs
0
0
0
0
1.83 (1.7)
Total Costs
0
0
0
0
104.9
Selling Price
0
0
0
0
227.93
Traders
Surplus
0
0
0
0
123.03
(117.3)
Retailers
Buy price
0
174.72
(90.9)
94.62 (74.1)
0
0
Transport Cost
0
7.5 (3.9)
19.74 (15.5)
0
0
Storage
Cost
0
4.32(2.2)
6.16 (4.8)
0
0
Market Costs
0
5.63 (2.9)
7.14 (5.6)
0
0
Total Costs
0
192.17
127.66
0
0
Selling Price
0
262.33
262.33
0
0
Traders
Surplus
0
70.16 (36.5)
134.67
(105.5)
0
0
Marketing Efficiency Index
1.11
0.53
0.53
∞
0.67
NB: Numbers in the parentheses are percentages of retail price (for farmers) and percentages of cost (for
vendors, retailers and wholesale-retailers)
3.4.2 Groundnuts Production Analysis
The transformed Cobb-Douglas production model was used to determine the factors that affect production of
groundnuts. The analysis shows that quantity of groundnuts seed, extension-farmer contact and volume of
groundnuts sold in the previous (last) year positively and significantly influenced groundnuts production. This
implies that a unit percent increase in each of the aforementioned variables will lead to an increase in groundnuts
production by their percent parameter estimates (size of their coefficients) and vice-versa. It is quite obvious that
an increase in quantity of groundnuts seed will lead to an increase in area planted to groundnuts thereby
increasing production (and vice versa).
International Journal of Business and Social Science Vol. 5 No. 6; May 2014
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The extension-farmer contact showed a positive relationship with groundnuts production because farmers that are
more visited or in contact with extension workers are likely to follow recommended groundnuts husbandry
practices and also adopt new or improved technologies on production hence increasing groundnuts production.
The volume of groundnuts sold in the previous year determines how much the farmer should produce in the
following season. An increase in the volume of groundnuts sold in the previous year makes the farmer allocate
more resources to that crop to increase production in the following year and vice versa.
Labour, distance to the market and farm gate price and education level also positively influenced groundnuts
production. This means that a unit percent increase in each of the variables (for the household) will result into an
increase in groundnut production by the magnitude of their parameter estimates. Similarly, a unit percent decrease
in each of the variables will result into a decrease in groundnut production by the percent magnitude of their
parameter estimates. This could be so because an increase in labour enables the farmer to increase amount of land
cultivated to groundnuts thereby increasing production. As for distance to market, it was surprising to find a
positive relationship with groundnuts production. However, the reason could be that markets that are very far
from production areas tend to fetch high prices of groundnuts. This makes farmers opt for these markets to realise
more income as a result of high production hence a positive relationship with groundnuts production.
The rise or increase in farm gate price (if done before planting) makes the farmer allocate more resources to
groundnuts thereby contributing to increase in production. Similarly, a decrease in farm gate price makes the
farmer reduce or sometimes abandon production of that crop thereby decreasing production. Education level of
the household head positively contributed to an increase in groundnuts production because as education level of a
farmer increases, the understanding and management ability also improves (increases). This helps the farmer to
easily and quickly adopt improved technologies and recommended farming practices. It also helps the farmer to
properly manage the crop and easily access extension services on groundnuts through reading. The overall result
is an increase in groundnuts production.
Age negatively influenced groundnuts production. This implies that an increase age of the farmer will lead to a
decrease in groundnuts production. This could be so because further increase in age makes the farmer to be less
productive thereby decreasing groundnuts production. This is economically justified by the fact that the curve of
production of an individual increases with age, reaches a maximum before decreasing with increase in age. This is
true too with the curve of margin productivity of labour that increases with age, reaches maximum before
decreasing in old age. Table 6 below shows the coefficients, standard errors, t-values, p values, variance inflation
factor (VIF) and the white’s test. The coefficients constitute parameter estimates.
Table 4: Parameter Estimates of Transformed Cobb Douglas Production Model on Groundnuts
Production in Mzimba and Kasungu, 2011
Variable
Parameter
Estimate
Standard Errors
t
-
ratio
p
-
value
Variance
Inflation Factor
Tolerance
lnLABOUR
0.095
0.149
0.638
0.526
1.230
0.813
lnSEED
0.406***
0.123
3.304
0.002
1.396
0.716
EDUCAT
0.051
0.032
1.578
0.120
1.214
0.824
AGE
-
0.013
0.009
-
1.559
0.125
1.205
0.830
EXTVIST
0.496**
0.218
2.271
0.027
1.150
0.870
VLSOLD LY
0.002***
0.000
3.581
0.001
1.347
0.742
FARMGATP
0.001
0.003
0.518
0.607
1.102
0.908
DISTMKT
0.008
0.011
0.742
0.461
1.112
0.899
CONSTANT
3.253***
1.203
2.703
0.009
R
-
squared
0.503
Adj R
-
squared
0.431
White’s Test
p = 0.315
Note: Significant at *** (1%), ** (5%)
3.4.3 Spatial Market Integration of Groundnuts Markets
The spatial market integration between two markets for Mzuzu, Mzimba, Jenda, Embangweni, Santhe, Kasungu
and Lilongwe markets was measured using bivariate correlation coefficients of price difference.
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137
Differencing removes time trends, non-stationarity and other problems associated with time series data. The
coefficients ranged from -0.03 (for Mzimba—Kasungu) to +0.17 (for Embangweni—Lilongwe). Markets that
have negative coefficients (such as Mzuzu—Mzimba, Jenda—Mzuzu, Embangweni—Mzimba, Lilongwe—
Jenda) are not integrated to each other. So, an increase in price of groundnuts in one market would not lead to an
increase in groundnuts prices in the other markets. This could be due to poor infrastructure and lack of
information flows between spatially separated markets. On the other hand, markets with positive coefficients
(such as Mzuzu—Kasungu, Jenda—Embangweni, Mzuzu—Lilongwe, Kasungu—Jenda, Lilongwe—Kasungu)
are integrated to each other. An increase in price in one market would lead to an increase in price in other
markets. This indicates competitiveness and information and trade flows between spatially separated markets.
The results are shown in Table 5 below.
Table 5: Groundnuts Bivariate Correlation Coefficients of Price Difference
Mzuzu
Mzimba
Emban
gweni
Jenda
Santhe
Kasungu
Lilongwe
Mzuzu
1.00
Mzimba
-
0.14
1.00
Embangweni
0.01
-
0.04
1.00
Jenda
-
0.08
0.14
0.01
1.00
Santhe
0.12
0.10
0.06
0.08
1.00
Kasungu
0.03
-
0.03
0.14
0.14
-
0.04
1.00
Lilongwe
0.13
-
0.18
0.17
-
0.07
0.05
0.02
1.00
3.4.4 Constraints to Groundnuts Production and Marketing
The smallholder farmers and traders cited various constraints hindering increased groundnuts production and
marketing. The major constraints included: lack of markets, low producer prices, labour demanding, lack of
improved seeds, pests and diseases, low supply of produce, lack of technology for value addition and high market
fees. Figures 1 and 2 show percentages of farmers and traders that indicated aforementioned constraints to
groundnuts
Figure 1 Farmers’ constraints to groundnuts production
International Journal of Business and Social Science Vol. 5 No. 6; May 2014
138
Figure 2 Traders’ constraints to groundnuts marketing
4.0 Conclusions
The study has shown that there are five groundnuts marketing channels. However, there is minimal value addition
in all the channels. Most farmers over recycle seed due to in accessibility and unavailability of improved seed.
The markets consist of a few groundnut sellers. Groundnut traders make supernormal profits. There are a number
of factors and constraints to groundnuts production and marketing as identified by the study.
5.0 Recommendations
Based on the results and discussions, the study made the following recommendations:
Establish organised groundnuts seed systems to ensure supply or availability of high quality seed to farmers.
Farmers also need training in certified seed production under phytosanitory control of research and extension.
The building of farmer capacity in improved seed production seems to be sustainable than other systems that
do not involve farmers.
Strength market oriented extension services on groundnuts among government, farmer organisations and non-
governmental organisations. This will help to increase production of high quality groundnuts.
Government and other organizations should improve roads and road networks to production areas to facilitate
trading of the produce and acquisition of farm inputs for use during production. Market infrastructures and
storage facilities should also be increased and improved to ensure availability of high quality products on the
market.
There is need to develop and improve existing technologies on production and value addition. The
technologies should be affordable to most farmers and traders. These will ensure an increased productivity,
production of high quality produce, reduce losses or wastage and increase value addition.
Vibrant farmer organisations (such as cooperatives) should be developed to ensure farmers are more
organized. Farmer organizations will help farmers in accessing high quality farm inputs, better markets, better
extension services, credit and capacity building.
0
5
10
15
20
25
30
35
40
45
50
11.9%7.5% 9% 16.4%
7.5% 3%
47.8%
13.4%
19.4%
10.4%7.5%11.9%
© Center for Promoting Ideas, USA www.ijbssnet.com
139
Promote value adding activities such as processing among farmers and traders. Processing of groundnuts into
different products would lead to an increase in the market value thereby increasing the margins. In addition,
technologies that add value need promotion at all levels.
6.0 References
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