The study will be carried out in Kaduna State

of Nigeria. Kaduna State is located between latitude 090 and 110

N and longitude 060 and 090 E. The state has an estimated

population of 6,766,562 people. The mean annual temperature varies between 240C

and 280C. The vegetation consists of Northern Guinea savannah in the

north and Southern Guinea savannah in the south. The length of rainfall varies

from 150 days in the north and 190 days in the southern part. The annual

rainfall varies from 1107mm in the north to 1286mm in the south. Relative

humidity is low ranging between 60 and 80% in July. The soil pH (level of

acidity/alkalinity) ranges from 5.5 and 6.5 characterize the soil which may be

generally described as sandy-loam soil. The major economic activity of the

inhabitants is farming and trading. The state occupies a major position in the

agricultural economy of northern Nigeria.

Geo-politically, Kaduna is divided into three

zones; the Northern zone comprises of the following Local Government Councils,

Zaria, Sabon Gari, Makarfi, Kudan, Ikara, Soba, Kubau and Lere. The Central

zone is made up of the following, Kajuru, Chukun, Kaduna South, Kaduna North,

Birnin Gwari, Igabi and Giwa. While the Southern zone, is made up of Kachia,

Kagarko, Jaba, Jama’a, Sanga, Kaura, Zango-Kataf and Kauru.

The State is made up of 23 Local Government

Areas (LGAs). Kaduna State Agricultural Development Project (KADP), the state’s

agricultural extension outfit, is divided into four agricultural zones: Lere,

Maigana, Samaru and Birnin-Gwari.

3.2

Sample Size and Sampling Technique

A multi-stage sampling procedure which involved

a combination of purposive and random sampling techniques will be adopted for

this study as follows; First stage: Random

selection two agricultural zones out of the four ADP zones in Kaduna State. Second

stage: random selection of one LGA out of the two zones. Third stage: random

selection of 4 wards (two wards each) out of the two LGAs selected. Finally, A

total of 75 farmers were randomly selected proportionate to the number of

farmers from each of the five wards using Ta Yamane’s formula as adopted by

Kalpana (2011).

The formula is expressed as;

n =

Where;

n = number of

farmers;

N = population of the study;

e = (10%)error.

Table 3.1 Target Population and Sample Size

S/N

Wards

selected

No. farmers

(sampling frame)

No. of

farmers selected

1

2

3

4

5

Jada 1

Leko

Mapeo

Nyibango

Mayo-kalaye

43

54

58

75

65

11

14

15

19

16

Total

295

75

3.3 Method of

Data Collection

The data was obtained by primary source using

questionnaires administered to the farmers and through personal interview with

the respondents.

3.4 Method of

Data Analysis

The analytical tools that were used for this research

were descriptive statistics (include percentages, means and Gross margin) and

inferential statistics (Multiple Regression analysis).

3.4.1

Percentages and Averages

These were used to analyse the socio-economic

characteristics of the respondent as well as problems associated with cowpea

production to achieve specific objective (i) and (iv).

i.

Arithmetic Mean =

Where:

? = summation

sign.

Xi = individual observation

N = Total Number of Observation

ii.

Percentages =

3.4.2 Gross

Margin Analysis

This was used to estimate cost and return in cowpea

production to achieve specific objective (ii).It is express as follows;

GM=TR-TVC

TR = QyPy

TVC = P1X1 +

P2X2 + P3X3 + P4X4 +

P5X5 + Tc + other cost

Where:-

GM = Gross Margin (?/ha);

TR = Total Revenue from the

Crop (?);

Qy = Output of crop

(kg);

Py = Unit price of

the output (?/kg);

TVC = Total Variable Cost

associated with the input per ha (?);

X1= Quantity of seed

(kg);

X2 = Labour used

(Man- days);

X3 = Agro-chemical

(litres);

X4 = Fertilizer

(kg);

X5 = Empty Sacs

(number);

P1 =Unit cost of

seed (?/kg);

P2= Cost of labour

(?/man-day);

P3 = Unit cost of

agro-chemical (?/litre);

P4 = Unit cost

fertilizer (?/kg);

P5 = Unit cost of

Empty Sacs (?);

Tc = Transport Cost

(?);

While the Net farm income (NFI)

NFI = GM – FC

FC = Fixed Cost (?)

Also the depreciation of the fixed inputs is given

bellow:

Depreciation (D) =

Where:

P

= cost of asset (?)

L

= Salvage value (?)

N

= Life span (years)

3.4.3

Multiple Regression Analysis

Multiple regression analysis was used to determine the

influence of some variable inputs on cowpea yield, and the coefficients

obtained from the analysis was used to estimate the resource use efficiency in

cowpea production to achieve objective (iii). Four functional forms were

tested. These are;

·

Linear function

Y = b0 + b1x1 + b2x2

+ b3x3 + ….. + b6x6 + e

·

Semi-logarithm

function

Y = logb0 + b1logx1 +

b2logx2 + b3logx3 + …. + b6logx6

+ e

·

Exponential

function

Log Y = b0 + b1x1 + b2x2

+ b3x3 + …….. + b6x6 + e

·

Double logarithm

function

Log Y = logb0 + b1logx1 +

b2logx2 + b3 logx3 +…..+ b6logx6

+ e

Where:

Y= Cowpea output (kg);

X1= Quantity of seed (kg);

X2 = Farm size (ha);

X3 =Family labour used (Man- days);

X4 = Hired labour used (Man- days);

X5 = Agro-Chemical (litres);

X6 = Age (year);

X7 = Education level (years spend in formal

education);

X8 = Farming experience (years).

e = Error term

b0 = Intercept

b1 – b5 = parameters

3.4.4

Determining Economic Efficiency of Resource Use

The following ratio was used to estimate the relative

efficiency of resource use;

r =

MVP = MPP.Py

MPP = =b. y

MFC = PX1

Where:

r =

Efficiency ratio;

MFC= Unit price of particular resource;

MVP= Marginal value product;

MPP = Marginal Physical Product of an input;

b = Regression co-efficient of an input;

y = Mean Value of an output;

MFC = Marginal Factor Cost or Px1

Decision

Rule:

If;

r = 1 resource is efficiently utilized

r > 1 resource is under – utilized

r < 1 resource is over-utilized.