Area of Study
The study was carried out in Ndokwa West Local Government Area of Delta State. Ndokwa West is one of the twenty five (25) Local Government Areas in Delta State, with it’s headquarter situated in Kwale. The local government area is made up of seven (7) autonomous communities. These include: Abbi, Emu, Ogume, Utagba, Uno, Onicha Ukwuani and Ndemili communities. It is located within Latitude 6.480E and Longitude 5.450N.
It has a population 149,325 people (National population census, 2006) and an area of 816 km². The Local Government Area has natural vegetation that supports
agricultural activities such as crop production, fishing etc. thus; agriculture is the major activities of the people of this area. The principle crops grown in this area are: cassava, yam, potato, plantain among others.
Sampling Techniques
A multiple-stage random sampling techniques will be employed in selecting the respondents. Stage I: involves the random selection of five (5) autonomous communities out of the seven (7) communities. Stage II: Out of the five (5) autonomous communities randomly selected, two (2) villages will be randomly selected, making a total of 10 villages.
Stage III: Out of the 10 villages that will be randomly selected, twelve (12) cassava farmers will be randomly selected. Thus, a total of 120 cassava farmers will be randomly selected for the study.
Data Collection
Primary data was used for the study. The data was collected through the use of structured questionnaire that was administered to the 120 randomly selected respondents.
Analytical Techniques
Data used for the study was analyzed using descriptive statistics such as mean, frequency distribution tables, percentages and inferential statistics. Descriptive statistics was used to analyze objective i, and ii, objective iii was analyzed using multiple regression analysis while objective iv was achieved using gross margin analysis and objective v was analyzed using mean score derived from 4 point likert scale.
Model Specification for objective iii
Multiple Regression Model
Y = f (X1, X2, X3, X4, X5) – – – – – implicit form
Y = a0 + a1x1 a2X2, + a3X3, + a4X4, X4, +a5X5, + et —- Explicit stochastic form
Where
Y=total output of cassava (tonnes)
X1 = farm size (ha)
X2 = labour used in man-days
X3 = fertilizer used (kg)
X4 = cassava cuttings (kg)
X5 = herbicide used (litre)
et = Stochastic Error term
a1 – a5 = Parameters estimate
a0 = constant
Technical efficiency of each parameter was estimated using an index with formula Rxi = biPy/Pxi,
Where
pxi = unit price of input (N),
Py = unit price of output (N),
bi = marginal productivity of the input and
Rxi = Technical efficiency index of the input.
Model for Gross Margin for which objective of iv.
The model used for the estimation of the gross margin according to Olukosi and Ernabor (1988) as
GM = TR – TVC (GI – TVC)
Gross margin = Total revenue – Total variable cost
٢ = GM – TFC
Profit = Gross margin – Total fixed cost
Where
GM = Gross Margin
TR = Total Revenue
GI = Gross income
TVC = Total variable cost
٢ = Profit
Model for Likert scale for objective v.
Xs = ∑fn Nr
Where:
Xs = mean ∑ = Summation
Fn = frequency of respondents responses
Nr = number of response of respondent
Test of Hypothesis
The null hypothesis that states that there is no significance difference between inputs and outputs of cassava production was tested using f-test.
The formula is stated thus as:
F-cal = R2 (N-K)
1-R2 (K-1)Where;
R2 = co-efficient of determination
N = sample size
K = number of variables
Decision Rule
If F-cal > F-tab, reject the null hypothesis otherwise accept the alternative.
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