THE STUDY AREA:
The
study area is Anambra state of Nigeria.
It is located at the south east of Nigeria. It is made of twenty-one
Local Government area which include; Aguata, Anambra East, Anambra West, Anaocha, Awka North, Awka
South, Ayamelum, Dunukofia, Ekwusigo, Idemili North, Ihiala, Njikoka,
Nnewi-North, Nnewi South, Ogbaru, Onitsha North, Onitsha SOUTH, Orumba North,
Orumba South and Oyi . It has a total population of 4, 182, 032 (N. P.C. 2006).
The
specific area in Anambra State that this research took place is at Ihiala Local
Government Area. Ihiala Local Government Area’s one of the twenty-one (21)
Local Government Area, which sprawls into various towns namely: Okija, Azia,
Ihiala, Amorka, Iseke, Lili, Mbosi, Orsumoughu,
Ubuluisiuzor, Uli. With the
headquarter situated at Ihiala which has some communities namely: Uzoakwa, Ogboro-isi-ala,
Ihite, akwa, Okohia, Ubahekwem.
RELATED
INFORMATION
Ihiala
Local Government Area has a total population of 229, 638 (N. P.C. 2006). It has
a total area of 304 square kilometers . Ihiala is a village north-east of Oguta
and is located at latitude 050 510 north and longitude 060
520 east.
The
Local Government Area has boundary with Ekwusigo Local Government Area and Orlu
of Imo state. The Local Government Area
has the climate that is relatively uniform as it influenced by two main trade
winds.
The
south west wind and the north east wind. The trade winds give rise to the two
distinct seasons. The rainy season which begins in April and last till October
and the dry season occurs between November and March. Dry harmattan wind is
experienced from December to February. There usually a very dry period in
August popularly known as “August break”.
The
average monthly rainfall is 140mm- 160mm (ANADEP annual report, 1995). The relative humidity of the study area fall
within 60-80% (illoeje 1981). Mean temperature of 19.73oc and 30oc
has been obtained in the state (ANADEP annual report, 1995). Obihara (1983)
opined that the soil type of the six eastern states of Nigeria is deep, porous
and sand loam with the clay content increasing as depth increases. Also pH is
5.0- 5.5 on the surface.
Therefore,
the soil type of Ihiala is sandy loam and clayey (Obihara, 1983). The major products in the study area
include; food crops, palm produce, fish,
livestock, starch, arts and crafts. Cash crops found in the area include: Mango
(Magnifera indica), cashew (Anacendium occodentale), orange (Citrus spp) oil
palm (Eleais guinensis) and Ogbono (Irvingia gabonesis).
Cultivation
of crops in the farm is based entirely on traditional methods with hoe and
matchet as major farming tools.
Consequently,
the agricultural system mostly practiced at the area is mixed cropping system
where farmers grow crops like; yam, maize, okra, cassava, pepper and melon, on
the same piece of land for a particular season.
Apart
from mixed cropping, the other systems of farming practiced in the area are:
shifting cultivation, crop rotation and mixed farming. In Nigeria, the practice
of mixed cropping is adopted as a risk aversion strategy designed to arrest
possibilities of crop failure and heavy loss of capital and labour inputs
(Norman 1974, Nweke 1980 and Okorji 1986). Also mixed cropping is known to be
more profitable than sole cropping and is assistants with farmer. Food security
objectives (Abalu, 1976). Apart from these systems of cassava, yam and mixed cropping.
women are mostly concerned and responsible for sowing and processing of other
crops.
Ihiala
Local Government Area has some existing physical and social services such as
two notable Government hospitals, 20 Government health centers and dispensaries,
14 Industries and 20 local government Wards.
SOURCES OF DATA:
Entirely,
primary and secondary data were used in this research. The primary data was
collected from the farmers (respondent) and the secondary data was also
collected from the textbooks, journals, magazines and newspapers.
TYPE OF DATA:
Primary
and secondary data were used in this research. Social
and economic data was employed. Under social data: age, experience, education
etc were considered. For economic data: income, expenses, profit, were
considered.
INSTRUMENT FOR DATA
COLLECTION:
Questionnaire
was used to collect data from the farmers (respondent).
RESEARCH APROACH:
Hypothesis
one, was tested using the Z-test to determine the level of profitability.
Hypothesis two was also tested
using the F-test.
SAMPLING TECHNIQUES:
A
two-stage random sampling technique was adopted in the research. Stage one-the
communities and stage two the respondents. Since cassava is produced virtually
in all communities in Ihiala local Government Area. Four communities were
randomly selected from each of the above mentioned communities, 20 cassava
producers were randomly selected to give a total of 80 cassava producers for
the study.
ANALYTICAL TECHNIQUE:
Objective
one, two, and five was analyzed using descriptive statistic such as mean,
frequency distribution and percentage. Objective three was analyzed using gross
margin analysis. While objective four was analyzed by the use of multiple
regression analysis.
Gross
margin was used to determine the financial cost and returns of cassava. Again,
gross margin was equally used to find out the profit margin of cassava
production within the study areas. Gross margin is the summation of total
revenue minus total variable cost. Thus, gross margin model is shown as
follows:
GM = TR- TVC…………………………….1
GP = GM-TFC…………………………….2
Where GM = Gross Margin
TR = Total Revenue
TVC= Total Variable Cost
TFC = Total Fixed Cost
GP = Gross Profit
Z-test
Z-test was employed to taste the
profitability of the enterprise.
Z= X1-X2
S d
S2 = Variance
X1 = Total Revenue
(TR)
X2 = Total Variable Cost (TVC)
X1 = Total Revenue (Mean)X2 = Total Variable Cost
(Mean)
N = Number of observation
MODEL SPECIFICATION
Multiple Regression Analysis:
Multiple
regression analysis was to determine the relationship existing between the
farmers socio-economic characteristic and there level of output obtained in the
production processes.
The functional forms are as follows:
Y = a0 + a1x1
+ a2 x2 + a3 x3 + a4 x4
+ a5 x5 + a6 x6 + a7 x7
Y = output valued in Naira
X1= Sex
X2= Farmers experience
(in years)
X3= Level of education
(in years)
X4 = Marital status
X5= Household size
X6= No of occupation
X7= Farm size
Implicit Function:
Y = f(X1, X2,
X3, X4, X5,X6, X7)+ et
Linear= a0+b1x1i+
b2 x2i + b3x3i+ b4x4i
+ b5x5i + b6x6i + b7x7i
+ et ……………………………………………………………..1
Semi-log = ao+ b1logx1i+
b2logx2i + b3logx3+ b4
logx4i + b5logx5i + b6logx6i
+ b7log x7i + et ………………………2
Double log = a0+ b1
logx1i +b2logx2i +b3 logx3i
b4logx4i+ b5logx5i + b6logx6i
+ b7 logx7i + et…………………….3
VARIABLE DESCRIPTION:
The dependent
variable (y) was an output, obtained from cassava production and was measured
in kilogram (kg) and as well valued in naira. When the agricultural inputs such
as; fertilizer, herbicides and improved varieties were adequately and
effectively utilized, it will generate more output in cassava production.
Sex
(x1): This comprises male and female
gender. An increase in gender will in turn increases output in cassava
production. b1>0
Farmers
experience (x2): This was measured in years. An increase in the
years of farming experience will increase production of the farmer conversely;
decrease farmers years of experience will definitely decrease output in cassava
production. b2>0.
Level
of education (x3): This was measured in years and an increase in the
level of education increases output in cassava production of the farmer b3>0.
Martial
status (x4): This comprises married and unmarried (single) farmers.
Increase in martial status will definitely increase output in cassava
production. b4>0.
Household
size (x5): This is the total number of people living in the
household. Increase in the size of the household will increase production b5>0.
Number
of occupation (x6): This comprises various job opportunities such as
farming, civil services, public services, and trading. When farmer tends to be
engaged with job opportunities other than farming, the output tends to reduce.
Thus, increase in the number of occupation will definitely decrease the output
in cassava production. b6 <0
Farm size(x7): This
was measured in hectare and increase in farm size will invariably increase
output in cassava production.b7>0.
The a priori expectations were stated as follows: b1>0,b2>0,b3>0,b4>0,b5>0,b6<0,b7>0.Thus,b1,b2,b3,b4,
b5, and b7 are greater than zero, proving that, there is
a positive relationship with the dependent variable. While b6 is
lesser than zero, also implies that, there lies an inverse relationship between
b6 and the dependent variable.
RELATED
INFORMATION