ECONOMIC ANALYSIS OF HONEY PRODUCTION IN
OSUN STATE
SEKUMADE A.B.1, S.O. AKINLEYE2a AND G.O. OLAYODE3
1. Department of Agricultural Economics, University of Ado-Ekiti, Ado-Ekiti
2. Department of Agricultural Economics, Olabisi Onabanjo University, Ago Iwoye
3. Department of Agribusiness and Farm Management, Olabisi Onabanjo University, Ago Iwoye
ABSTRACT
This study examines the economics of honey production in Ilesa, Osun State. The socioeconomic characteristics of honey
producers showed that 83 per cent of the farmers are aged below 40 years and had secondary education. This means that
information about honey production is easily disseminated and acquired. The farming experience of between 1-5 years also
shows that beekeeping is relatively new within the study area. Results obtained from the regression analysis showed that the
output of honey is positively related to the size of the bee farm, the number of harvestings/month and the number of
employees on the farm which were significant at 5% probability level. The coefficient of determination (R2) in the semi-log
model was 0.78. Bee farmers identified bush burning and human interference as their major problems. It is recommended
that bee keepers increase their scale of production and also improve on their management practices to earn more
Keywords: Beekeeping, Honey production, Economic analysis, Osun State
INTRODUCTION
Honey, the natural food from the bee, has many times been described as man’s
sweetest food. Honey is a near complete and a unique food which can only be produced by
bees. It enjoys an ever-increasing demand because of a growing understanding of its
nutritional quality and curative ability (Agriculture Today, 1993; Morse and Hooper, 1985).
Honey is a very useful product, which, if managed efficiently, could bring about increased
income. Nigeria does not produce enough honey presently as the traditional method of
collecting honey encourages the destruction of bee populations, which reduces honey
production, and thereby results in the reduction of income derivable from honey production.
Beekeeping, also known as apiculture, is the management of colonies of bees for the
production of honey, other hive products and the pollination of crops (Koning, 1994;
1
Winston, 1987). Beekeeping usually refers to the husbandry of the honey bee. An ancient and
widespread profession, beekeeping is believed to have originated in the Middle East. The
early Egyptians kept bees and traded for honey and beeswax along the East African coast
several thousand years ago (Delaplane, 1993). Honeybees are well distributed over the globe
except in the cold polar regions (Seeley, 1985). They exist everywhere on the continent
where man lives; from the equatorial evergreen rainforest to the desert oasis, although they
are more numerous in the drier savannah than in the wetter forest areas. They all produce
honey; the nutritious natural food good for both man and animals. Honey is classified by the
source from which the bees gather the nectar used in producing honey. This source however,
influences the honey’s flavour, colour and viscosity. Honey is collected from tree branches,
hollows and crevices (Seeley, 1985).
Traditionally, honey is harvested by the use of fire or torches which burn the insects
to death. However, this practice has declined in recent times as a result of increasing
urbanisation, increasing population pressure on available land and an improved knowledge of
husbandry practices. However, the period when the practice lasted was one that led to a
depletion of bee populations, thus resulting in a scarcity of honey (Seeley, 1985).
Beekeeping can be a valuable source of supplementary income in conjunction with
other farm enterprises. In the US, of the 125,000 people who owned one or more hives, only
about 2,400 earned a full-time living from bee keeping (Microsoft, 2003). Honey, though
produced principally for human consumption, has other benefits. These other benefits are;
a
Corresponding Author.
2

the medicinal efficiency of honey has initiated a new and highly promising branch of
medicine called apitherapy with the term “api” derived from Apis mellifera (i.e.
honeybee)

honey is used to increase milk production and to treat acetonemia in cattle. It is also
used to substitute for energy in donkeys and race horses

it is used widely in the manufacture of facial cleansers and as an ingredient in the
making of hand lotion.

honey is used in the making of rat and mice repellent compounds (FAO, 1990).
Given the many benefits derivable from honey, beekeeping is thus a useful operation
which should be encouraged as it has the potential to improve the life of the farmers as well
as earn foreign exchange for the country. It is in this wise that this paper will examine the
economics of honey production using modern methods.
METHODOLOGY
The study area is Ilesa in Osun State. It is purposively selected as it is the major honey
production area in Osun State. Twenty five km from Osogbo, the state capital, Ilesa has a
population of 652,288 people, 75% of whom are involved in agriculture/farming. Simple
random sampling is used to select a sample of thirty (30) farmers. Using well-structured
questionnaires, data were collected on the socioeconomic characteristics of the farmers, the
volume of honey produced and the inputs used in the production process.
The data collected were analysed using the following methods;
3
Descriptive statistics: Percentages and frequency distribution are used in the analysis of the
socioeconomic variables of the farmers such as sex, marital status, age distribution, farm size,
etc.
Regression analysis: Honey output per farm is regressed against the variable inputs
considered and other factors expected to affect output. This is to establish the effects of
production inputs on honey output.
The explicit production equation for honey production is given by
Y = f (X1, X2, X 3, X 4)
where Y = Output of honey produced in kg
X1 = Experience of honey producers in years
X2 = Size of the bee farm
X3 = Number of harvestings/month
X4 = Number of employees
The lead equation will be chosen from the linear, semi-log, exponential and doublelog models based on the value of the coefficient of multiple determination R2 (which explains
the proportion of variation in the regressand that is explained by the regressors). The a priori
signs of the parameters are also considered and the t-test is used to determine the significance
of the parameters. The closer R2 is to one, the better the goodness of fit of the regression
model.
RESULTS AND DISCUSSION
Table 1 shows that 73.3% of the respondents are males while 26.7% of the
respondents are females. The result indicates that bee farming in this zone is male-dominated.
4
This could be attributed to fear of bees as males are likely to show more courage than females
in approaching bee swarms. From the table, it is also seen that most of the respondents are
within the ages 31-40 (56.7%) and 21-30 (23.3%). This result indicates that a larger majority
of the respondents (80.0%) are relatively younger. This phenomenon is good for beekeeping
as energy, ability to stay long at work and initiative are required. In situations where the bee
farms are located far from the home, the young and virile workforce will be better able to trek
such long distances.
Furthermore, it is seen that 80.0% of the respondents are married while just 20% are
single. The greater involvement of married people in this business is driven by the desire to
increase family income. Additionally, families use honey for a variety of reasons. Therefore,
a farmer who keeps bees can always have available honey for use at any time rather than
spend part of the income on such purchases.
According to the table, 63.3% of the respondents had secondary education. This result
attests to the lack of complexity of bee keeping. Also, information about the business can be
easily passed and acquired. This probably informs why a majority of the respondents have
taken to modern methods of bee farming rather than the traditional method.
Furthermore, it was seen from the table that majority of respondents (73.3%) had a
household size of 1-5 people while the 11-15 category had the lowest percentage (6.7%). This
distribution may be a reflection of the level of education and the age of the respondents. Most
educated people have small families, as do young people. As one or two experienced persons
can handle most of the jobs in beekeeping where total hive (box) number is under forty in this
study, the respondent with the largest number of boxes had twenty, the husbandry of this
hives is within the capability of the small households.
5
It is also seen that 96.7% of the respondents had farming experience of between 1-5
years. This can be attributed to the pioneering effort of the Leventis Foundation Nigeria
Agricultural School (LFNAS) Ilesa which is known to have introduced beekeeping into its
programme since 1989. This has implications for the level of skill and exposure that these
farmers have vis a vis bee keeping.
Majority of the beekeepers (93%) obtained information on beekeeping from other
farmers (50%) or from research institutes (43.3%). The data on source of beekeeping
information shows that farmers represent the major source of spreading awareness in honey
production. The ability to pass such information is enhanced by the educational status of the
farmer.
Also, a large portion of the respondents (93.3%) were into beekeeping for any or both of
two reasons; income or home consumption. While half of the farmers indicated income
(50%) as their sole reason, 43.3% showed that both income and home consumption were
important reasons for keeping bees. Most of the farmers interviewed have gone into
beekeeping to augment their income as well as produce honey because of its various
medicinal uses. The income from honey production usually comes between the periods of
October and April. These are months when most farming produce would have been sold and
the farmers may not have any income from crops. The income from honey production,
therefore, comes at a time when the farmer is seriously in need. Such income is even used for
the purchase of seeds, chemicals and fertilisers for the next production season.
To explain the cause-effect relationship between the income from honey production (N)
and the production inputs (years of experience, numbers of operating bee hives, numbers of
harvesting sites and educational qualification), the regression analysis was carried out. The
6
independent variables were operationalised to reflect both physical factors of production and
the managerial factor as influenced by educational qualification.
From the four fitted models, the semi log functional form was chosen as the lead
equation. The semi log model with a coefficient of multiple determination (R2) value of 0.78
means that the model has a “good fit.” It also reveals that the identified independent variables
account for up to 78 percent of the variations observed in the output of honey.
Three (3) out of the four (4) independent variable were found to be significant at 5
percent probability level. The significant variables are the size of the bee farm (X2), number
of harvestings/month (X3) and the number of employees on the farm (X4). The standard
errors of the coefficients are in parentheses.
Y = - 70425.05* + 4405.41X1 + 20080.63X2* + 26586. 53X3* + 27609.3 X4*
(-3.121)
(0.582)
(3.24)
(2.646)
(2.907)
R2 = 0.883
Adjusted R2 = 0.780
F-Stat = 22.19`
CONCLUSION
This study was on the economics of honey production using modern methods. The
respondents, while acknowledging honey production as a worthwhile economic activity, do
however identify bush burning and human interference as the major problems they face.
These problems have a negative effect on the income derivable from the production of honey.
Based on the findings of the study, it is recommended that;

bee keepers are encouraged to increase their scale of production. This is so given the
significance of the size of the bee farm which shows a positive relationship between
honey output and the size of the farm.
7

improved management practices as shown by the significance of the harvesting
frequency and number of employees variables. This agrees with research that shows
that intensiveness in apiary management leads to higher output, and by implication,
higher profits.
REFERENCES
Agriculture Today, 1993. Beekeeping in Nigeria. Vol. I, No. 3; pp 8-12.
Delaplane, K.S. 1993. Honey bees and beekeeping: A year in the life of an apiary, The
University of Georgia, Georgia Center for Continuing Education, Athens, Georgia.
Food and Agricultural Organisation, 1990. Beekeeping in Africa. FAO Agricultural
Services Bulletin, 68/69, Rome, Italy.
Koning,
R.
E.
1994.
Honeybee
biology.
http://plantphys.info/plants_human/bees/bees.html.
Plant
Physiology
Website.
Microsoft Corporation, 2003. Beekeeping. Microsoft Corporation Encarta Online
Encyclopedia. http://encarta.msn.com.
Morse, R.A. and T. Hooper, 1985. The illustrated encyclopedia of beekeeping, E. P. Dutton,
Inc., New York, New York.
Seeley, T.D. 1985. Honeybee ecology, Princeton University Press, Princeton, New Jersey.
Winston, M.L. 1987, The biology of the honey bee, Harvard University Press, Cambridge,
Massachusetts.
8
Table 1: Socioeconomic Characteristics of Bee Farmers in Osun State
Frequency
Percentage (%)
Sex
Male
22
Female
8
Age (years)
11- 20
1
21 – 30
7
31 – 40
17
41 – 50
5
Marital status
Married
24
Single
6
Education
Primary
8
Secondary
19
Technical
2
University
1
Household size
1–5
22
6 – 10
6
11 – 15
2
Farming experience (years)
1–5
29
6- 10
1
Source of beekeeping information
Res. Institutes
13
Other farms
15
Others
2
Reasons for production
Consumption
2
Income
15
Both
13
Source: Field Survey, 2004
73.3
26.7
3.3
23.3
56.7
16.7
80.0
20.00
26.7
63.3
6.7
3.3
73.3
20.0
6.7
96.7
3.3
43.3
50.0
6.7
4.7
50.0
43.3
9
Table 2: Summary of Regression Analysis
Functional Form
β0
β1
-22853.84*
243.09
Linear
(-2.582)
(0.191)
8.873*
-0.00240
Exponential
(20.44)
(-0.039)
-70425.05*
4405.41
Semilog
(-3.121)
(0.582)
7.750*
0.01748
Double log
(16.934)
(0.114)
β2
5817.80*
(9.056)
0.161*
(5.105)
20080.63*
(3.24)
0.868*
(6.899)
β3
5356.36
(1.475)
0.0957
(0.56)
26586.53*
(2.646)
0.266
(1.307)
Source: Computed from Survey Data, 2004
* Parameters are significant at the 5 per cent probability level.
10
β4
1297.00*
(2.127)
0.01004
(0.34)
27609.3*
(2.907)
0.413*
(2.143)
F-stat
92.15
R2
0.936
Adjusted R2
0.926
26.06
0.898
0.807
22.19
0.883
0.78
48.359
0.886
0.867