CHAPTER – III

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MATERIALS AND METHODS

Adoption of Red gram IPM practices by the farmers of Prakasam

District in A.P was studied by using the following research design and

procedures.

3.1 Research Design

An ex-post-facto research design was followed to achieve the

objectives of the study. According to Kerlinger (1983) the ex-post-facto

research design is a symmetrical empirical enquiry in which the scientist

does not have any direct control of independent variables.

3.2 Sampling Procedure

3.2.1 Location of the study

The state of Andhra Pradesh was selected purposively as the

Researcher belongs to this state and well acquainted with regional

language i.e., Telugu which would help to build a good rapport and also

facilitates in depth study through personal observation.

3.2.2 Selection of the District

Prakasam District was selected purposively for the following reasons

1. Being working place of the researcher, it was possible to establish

good rapport with the local people and also to complete the study with

in the stipulated time.

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2. As the researcher was working in Krishi Vigyan Kendra of ANGRAU,

Darsi, she was well acquainted with research problem, and

components of Agriculture etc. It also facilitated her to go to fields

regularly.

3.2.3 Selection of the Mandals

Out of 56 mandals in Prakasam District, 3 mandals were selected

for the study based on the accessibility and area of red gram cultivation.

3.2.4 Selection of villages : From each mandal two villages were

selected for the study one IPM village, which is nothing but IPM trained

village and the other non-IPM village, nothing but IPM non-trained village.

In IPM villages farmers were trained scientifically by Krsishin Vigyan

Kendra (KVK), Darsi, Prakasam district. So, in these villages they were

exposed to advanced and scientific techniques by method demonstrations,

Front line demonstrations, On farm trials, training programmes, vocational

training programmes, group discussions etc. But in non IPM villages they

were not trained scientifically. So they have been practicing very few

techniques mostly traditional, irrespective of IPM total concept. Thus a

total of six villages were selected randomly as shown below.

Mandal Villages

Darsi Rajampalli Lonkojanapalli

Podili Katurivaripalem Mugachintala

Kurichedu Avulamanda Kalluru

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So, three villages Rajampalli, Katurivaripalem, Avulamanda with

higher adoption of IPM components, as IPM villages and three villages

namely Lonkojanapalli, Mugachintala, Kalluru with very few IPM

components, as non IPM villages were taken for the study. The purpose is

to see the adoption of IPM technologies in Red gram fields to study the

beneficial effects of IPM and factors responsible for higher adoption as

well as constraints in adoption and also to elicit suggestions to overcome

the constraints.

3.2.5 Selection of the respondents

From each village 30 farmers were selected by applying purposive random

sampling method . Selection of the persons according to their respective

villages as follows.

IPM villages No. of respondents

Rajampalli 30 farmers

Katurivaripalem 30 farmers

Avulamanda 30 farmers

non-IPM villages 30 farmers

Lonkojanapalli 30 farmers

Mugachintala 30 farmers

Kalluru 30 farmers

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3.3 Measurement of objectives to assess the results of the study

The following objectives were measured

3.3.1. To study the profile characteristics of practicing IPM and non-IPM

farmers.

3.3.2. To identify relationship between adoption and profile of the

respondents.

3.3.3. To know the extent of adoption of IPM practices by farmers.

3.3.4. To measure pod borer incidence and economics of IPM and non-

IPM fields.

3.3.5. To find the constraints faced by farmers in both IPM and non- IPM

villages

3.3.6. To elicit the suggestions to overcome the constraints.

3.3.1. To study the profile characteristics of practicing IPM and non-

IPM farmers.

The variables of the study with regard to profile were determined

based on the relevant review of literature on the subject, in consultation

with the experts in the field of Research and Extension, Research guide

and Progressive farmers. The variables selected and empirical

measurements followed were given below

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Table 1. Variables and their empirical measurements

S.No. Independent

Variables

Instruments used for study

1 Education Scale developed by Venkata Ramaiah

(2002) with suitable modifications

2 Farm size Schedule developed for the study

3 Social Participation Scale developed by Venkata Ramaiah

(2002) with suitable modifications

4 Mass media Exposure Schedule developed by Desai(1977)

5 Extension contact Scale developed by Seshachar (1980)

with suitable modifications

6 Risk orientation Scale developed by Supe(1969) with

suitable modifications

7 Scientific Orientation Scale developed by Supe(1969) with

suitable modifications

8 Economic Orientation Scale developed by Supe(1969) with

suitable modifications

9 Achievement

Motivation

Scale developed by Manandhar(1987)

with suitable modifications

10 Innovativeness Scale developed by Rao(1985) with

suitable modifications

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3.3.1.1.Education

Education was operationalized as the formal schooling attended by

the respondents.

Categorization Score

1. No schooling /illiterate 1

2.Primary schooling 2

3.Secondary education 3

4.Intermediate 4

5.Graduate 5

Farmers were asked to indicate their educational qualifications. The

maximum and minimum score of each respondent was 5 and 1

respectively.

3.3.1.2. Farm size

Farm size was operationalized as the number of standard hectares

possessed by the respondents at the time of interview. The dry land and

wet land was taken into account. As per the Andhra Pradesh Land

Reforms Act-1973 “one hectare of wet land shall be deemed to be equal to

2.5 hectares of dry land.” Thus, the total land holding of the respondent

was converted into standard acres using the above conversion formula to

arrive at the farm size of the respondent.

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To calculate the individual respondent’s farm size, the scoring pattern

adopted was as given below.

Category Dry land Wet land Score

Marginal farmers Up to 2.5 acres Up to 1 acre 1

Small farmers 2.6 ha to 5 acres 1.1 to 2 acres 2

Big farmers Above 5 acres Above 2 acres 3

3.3.1.3. Social Participation

Social Participation was operationalized as the degree of involvement

of the respondents in social organizations either as a member or as an

office bearer in one or more organizations. Seven items used to know the

participation of the farmers was measured as non-member, member and

office bearer with the scores of 1, 2 and 3 respectively. The maximum and

minimum score of each respondent was 21 and 7 respectively.

Based on the total scores obtained by the respondents on the

social participation, they were grouped into three categories on the basis

of mean and standard deviation i.e., those with low social participation

(<mean-standard deviation), medium social participation (<mean ±

standard deviation) and high social participation (>mean+ standard

deviation).

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3.3.1.4. Mass media Exposure

Mass media Exposure was operationalized as the extent of

exposure of respondents to the mass media such as radio, television,

news paper, agricultural books, information materials and farm magazines

etc. Six items used to know the frequency of exposure was measured as

regular, occasional, never with scores of 3, 2 and 1 respectively. The

maximum and minimum score of each respondent was 18 and 6

respectively.

By adding the scores of all the items, the individual total score was

worked out. The respondents categorized into three groups based on

mean and standard deviation i.e., those with low mass media exposure

(<mean-standard deviation), medium low mass media exposure (<mean ±

standard deviation) and high low mass media exposure (>mean+ standard

deviation).

3.3.1.5. Extension contact

Extension contact was operationalized as the degree to which an

individual contacted extension agencies for getting information on

agriculture or non-agriculture or both. Five statements used to know the

frequency of contact as regular, occasional and never with scores of 3, 2

and 1 followed by purpose of contact as agriculture or non-agricultural with

the scores of 2 and 1, respectively. The scoring procedure was as follows.

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The total scores of the respondents on their extent of contact were

computed by adding weights against each respondent. The maximum and

minimum score of each respondent was 25 and 10, respectively. Based on

the total scores obtained by the respondents on the extension contact,

they were grouped into three categories on the basis of mean and

standard deviation i.e., those with low extension contact (<mean-standard

deviation), medium extension contact (<mean ± standard deviation) and

high extension contact (>mean+ standard deviation).

3.3.1.6. Risk Orientation

Risk Orientation was operationalized as the degree to which the

farmer was oriented towards encountering risk and uncertainty in adopting

any new ideas or innovations. This was measured with the help of risk

preference scale developed by the Supe (1969). The scale consisted of

six statements of which first and fourth were negative and the rest were

positive. The positive statements were scored 3, 2 and 1for agree,

Undecided and Disagree, respectively, where as the scoring system was

reversed in case of negative statements. The maximum and minimum

score of each respondent was 18 and 6, respectively.

The final score for risk orientation was arrived at by summing up all

the corresponding response scores. Then the respondents were grouped

in to three categories on the basis of mean and standard deviation i.e.,

those with low risk orientation (<mean-standard deviation), medium risk

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orientation (<mean ± standard deviation) and high risk orientation

(>mean+ standard deviation).

3.3.1.7 Scientific Orientation

Scientific Orientation was operationalized as the degree to which a

person was oriented towards scientific methods of farming. This was

measured with the help of scale developed by the Supe(1969). The scale

consisted of six statements of which first and fourth were negative and the

rest were positive. The positive statements were scored 3, 2 and 1for

agree, Undecided and Disagree, respectively, where as the scoring

system was reversed in case of negative statements. The maximum and

minimum score of each respondent was 18 and 6, respectively.

The final score for scientific orientation was arrived at by

summing up all the corresponding response scores. Then, the

respondents were grouped into three categories on the basis of mean and

standard deviation i.e., those with low scientific orientation (<mean-

standard deviation), medium scientific orientation (<mean ± standard

deviation) and high scientific orientation (>mean+ standard deviation).

3.3.1.8. Economic Orientation

Economic Orientation was operationalized in terms of profit

maximization and relative value by the farmer on economic needs. The

degree of economic orientation of the respondents was measured with the

help of scale developed by the Supe (1969). The scale consisted of six

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statements of which first and fourth were negative and the rest were

positive. The positive statements were scored 3, 2 and 1for agree,

Undecided and Disagree, respectively, where as the scoring system was

reversed in case of negative statements. The maximum and minimum

score of each respondent was 18 and 6, respectively.

The final score for economic orientation was arrived at by summing

up all the corresponding response scores. Then, the respondents were

grouped into three categories on the basis of mean and standard deviation

i.e., those with low economic orientation (<mean-standard deviation),

medium economic orientation (<mean ± standard deviation) and high

economic orientation (>mean+ standard deviation).

3.3.1.9. Achievement Motivation

Achievement motivation was operationalized as the degree for

excellence to attain a sense of personal accomplishment. Achievement

motivation of the respondents was measured with the help of scale

developed by the Manandhar (1987). The scale consisted of six

statements of which all were positive and responses were obtained on

response categories viz., Agree, Undecided and Disagree with scores 3, 2

and 1, respectively. The maximum and minimum score of each

respondent was 18 and 6, respectively.

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The final score for economic orientation was arrived at by summing

up all the corresponding response scores. Then, the respondents were

grouped into three categories on the basis of mean and standard deviation

i.e., those with low Achievement motivation (<mean-standard deviation),

medium Achievement motivation (<mean ± standard deviation) and high

Achievement motivation (>mean+ standard deviation).

3.3.1.10 Innovativeness

Innovativeness was operationalized as the degree to which an

individual adopted new ideas relatively earlier than others in his social

system. The degree of Innovativeness of the respondents was measured

with the help of scale developed by the Rao (1985). The scale consisted of

six statements of which fourth and sixth were negative and the rest were

positive. The positive statements were scored 3, 2 and 1 for agree,

Undecided and Disagree, respectively, where as the scoring system was

reversed in case of negative statements. The maximum and minimum

score of each respondent was 18 and 6, respectively.

The final score for innovativeness was arrived at by summing up all

the corresponding response scores. Then, the respondents were grouped

into three categories on the basis of mean and standard deviation i.e.,

those with low Innovativeness (<mean-standard deviation), medium

Innovativeness (<mean ± standard deviation) and high Innovativeness

(>mean+ standard deviation).

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3.3.2. To identify relationship between adoption and profile of the

respondents

The influence of each independent variable on adoption level of

the farmers was calculated to scale the correlation between each variable

and adoption.

3.3.3. To know the extent of adoption of IPM practices by farmers

It was operationalized as the extent to which an individual

adopted number of various IPM practices. The schedule consisted of 20

practices. The positive statements were scored with 1 and the negative

with 0. For each practice in both IPM and non IPM villages frequencies

and percentages were measured to see the extent of adoption of each

practice by the farmers. And also, based on the number of IPM practices

adopted, farmers were grouped into 3 categories with low adoption,

medium adoption and high adoption to assess the difference in adoption

between IPM and non IPM villages, whether it is significant or non-

significant. The crops were monitored continuously to see the extent and

efficacy of the adoption. Primary data was obtained directly from the

farmers and fields.

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3.3.4. To measure pod borer incidence and economics of IPM and

non-IPM fields.

It was operationalized as the extent to which an individual could

control the pest incidence and maintain the crops in healthy condition to

achieve profits. The schedule consisted of various aspects like number of

good pods per plant, number of damaged pods per plant. These were

assessed by counting the pods per plant both good and damaged. From

each field by taking plants randomly the pods were counted and the

average was taken. From these observations total number of pods per

plant was counted. And also percentage of pod damage was assessed.

To estimate economics of the cultivation, whether it is profitable or

not, cost of agronomic practices, costs of plant protection were assessed.

From these observations total cost of cultivation was calculated. Yield was

also quantified during harvesting. From the entire fields average yield was

assessed. Gross income was calculated and from this total cost of

cultivation was deducted to gain the net profit for each and every field.

3.3.5. To find the Constraints Faced by Farmers

It was operationalized as the extent to which various constraints like

personal, socio-economic, technical and organizational constraints

influence the farmer in adoption of various IPM techniques. The schedule

consisted of various probable constraints the farmers face like Not willing

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to take risk, Lack of awareness about training programme, Lack of self –

confidence, Lack of decision making ability, Less outside contacts, Less

exposure to mass media with regard to personal constraints; High cost of

Pesticides, High wage rate of labour, Lack of exposure, High cost of

organic manures, Less Social Participation pertaining to Socio-Economic

constraints; Lack of proper technical guidance, Lack of knowledge about

IPM technology, Non-availability of labour, Lack of sufficient technical

staff, Lack of skill related to technical constraints; and Improper distribution

of inputs, Training centers are far, Less training periods, Lack of field visits

by officers, Lack of field visits by officers connected to organizational

constraints. The responses were obtained and the scores given were 1 for

positive answer and 0 for negative answer.

3.3.6. To elicit the suggestions to overcome the constraints.

This was operationalized as the suggestions that are given by the

respondents to get rid of the constraints. Schedule contained space for the

suggestions. And the opinion of the respondents to adopt more number of

IPM practices was recorded and ranks were given according to the priority

of the suggestion expressed by majority of the farmers.

3.4. Collection of Data

It includes both crop monitoring and collection of the data from

respondents. Red gram fields in all the six villages were monitored

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continuously for one kharif season (2009 june-2010 January). In

Prakasam district due to aberrations in monsoon red gram sowings usually

taken up from June to July. Since it is the long durational crop, the

harvestings are usually done from December to January. Besides this

monitoring of the crop, home visits were made continuously till the total

information was collected from all the 180 respondents, from 2008

October to 2010 October, for a period of two years. The collected

information was primary data directly from the fields and farmers, not the

secondary data which means not from any institution or organization or

office.

3.4.1. Designing the Interview Schedule

The schedule consisted of three parts. The first part associated with

profile characteristics of farmers .The second part dealt with extent of

adoption of IPM practices by farmers. Third part meant for pod borer

incidence and economics of IPM and non-IPM fields. The final and fourth

part dealt with the constrains and suggestions perceived by the farmers of

IPM practiced and non-practiced villages. The interview schedule was

constructed in English and translated into telugu vernacular language.

3.4.2 Pre-testing of the Schedule

Before giving a final shape to the interview schedule the schedule

was pre-tested with 10percent of the respondents of the non sample area

who involved in agriculture and their allied activities. While taking the pre-

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testing, care was taken to select the respondents for required information.

Based on the experiences gained in the pre-testing, the interview schedule

was modified wherever needed. The final format of the interview schedule

was enclosed in the appendices.

3.4.3 Method of Data Collection

Each of selected respondents was interviewed personally by the

investigator in local language i.e., Telugu at his /her village or farm or

home and the responses were recorded directly on the schedule. For field

data, fields were monitored continuously from preparation of land for

sowings to till the time of harvesting, to see adoption of IPM practices,

Incidence of pest, crop condition, yield etc.

3.4.4. Preparation of Report

The data thus collected from the respondents was, tabulated and

presented in the form of tables in order to make findings meaningful and

understandable. Statistical analysis was done to the scores obtained for

different variables. The findings emerging from the analysis of data were

suitably interpreted and conclusions were drawn accordingly.

3.5 Statistical Tools used

To convert the results into findings few stastical tests were also used as

given below for analyzing the data

1. Arithmetic Mean ( X )

2. Standard Deviation ( σ )

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3. Frequency and percentage

4. Pearson’s correlation coefficient®

5. ‘z’ Test

3.5.1 Arithmetic Mean ( X )

It is defined as the sum of all values of the observations divided by the

total number of observations. Symbolically it is represented as X .

Arithmetic mean ( X ) = ∑xi = x1+x2+…..Xn n n

Where X = Arithmetic mean

Xi=Value of i th item of x

Where, i= 1,2………………n

n=Total numbers of respondents

3.5.2 Standard Deviation (S.D/σ )

It is positive square root of the mean of the squared deviations taken

from arithmetic mean. It is represented by symbol

2

1

1. ( )n

ii

S D x xn

Xi =values of random variable x

X = Mean of all the variables or observations

n = number of observations.

3.5.3 Frequency and Percentage

Frequency and percentages were used to know the distribution

pattern of the respondents according to the objectives under study.

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Percentages were also used for primarily for analysis of different

variables and also making simple comparison.

3.5.4 Pearson’s Correlation Coefficient (r )

This was used to study the relationship between the scores of

independent variables and the scores of dependent variables. It measures

the degree of relationship between the two sets of variables.

r = Correlation coefficient

∑x = Sum of scores of independent variables

∑y = Sum of scores of dependent variables

∑x2 = Sum of the squares of scores of an independent variables

∑y2 = Sum of the squares of scores of a dependent variable

∑xy = the Sum of productivity of x and y

n = Size of the sample

The calculated ‘r’ value was verified for it’s by using ‘r’ table value

for 5percent and 1percent level of significance at n-2 degrees of freedom.

3.5.5 ‘Z’ Test:

‘Z’ test was employed to study the difference between the farmers of IPM

adopted and non adopted villages regarding profile characteristics, direct

and indirect changes.

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2 21 2

1 2

x yzs sn n

Where

X = First sample mean

Y = Second sample mean

S12 = First sample variance

s22 = Second sample variance

n1 = First sample size

n2 = Second sample size

Null Hypothesis (N.H):

There was no significant difference between farmers of IPM and

non-IPM villages regarding profile characteristics, adoption of IPM

practices.

Empirical Hypothesis (E.H)

There was significant difference between farmers of of IPM and non-

IPM villages regarding profile characteristics, adoption of IPM practices.

Note: The ‘Z’ value was calculated and compared with ‘Z’ table

value at 0.01 and 0.05 level of probability. If the value was significant, the

null hypothesis was rejected and empirical hypothesis was accepted.

Description about Study Area

Prakasam is one of the 23 districts of Andhra Pradesh with its

administrative head quarter located at Ongole. Initially named as Ongole

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district on 2nd February 1970, again renamed as Prakasam (12-5-1972) in

memory of the great patriot and Andhra Leader, Tanguturi Prakasam

Panthulu, also known as Andhra Kesari (Lion of Andhra) who was born in

Kanuparthi village of this district. The district shares common boundaries

with Bay of Bengal in the East, Cuddapah and Nellore districts in the

South, Kurnool district in the West and Guntur and Mehaboobnagar

districts in the North directions.

The District is bounded by the following places and features on all

the four sides.

East : Bay of Bengal

West : Kurnool District

North : Part by Guntur and Mehaboobnagar District.

South : Partly by Nellore and Cuddapah.

The District is situated in tropical region between 14-57’-00 to 16-

17’00’Northern latitude and 78-43-00’ to 80-2500” Eastern longitude. The

central portion of the District contains large tracts of low shrubs Jungle

diversified with rocky hill and stony plains which is a peculiar features of

the District. The erstwhile tauluks of Giddalur and Markapur drawn from

Kurnool district are purely an upland area.

In Prakasam District the sea breeze renders the climate moderate

both in winter and summer seasons in the coastal areas of the district. In

the non-coastal areas of the district, the heat in the summer is severe

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especially in the tracts of up land areas and adjoining hills. The normal

and maximum temperatures recorded in the district are 38.2 C and 19.7 C

respectively. The maximum temperature is usually recorded in the months

April, May and June.

The district receives its rain fall mostly and predominantly from

south – west as well as north – east monsoon whose normal rain fall is

389.0 mm and 393.0 mm respectively, the receipt of actual rain fall during

2000-2002 from south- west monsoon is 671.7 mm while 146.3 mm from

north- east monsoon. The agriculture activity in the district is deplorable

owing to gambling of monsoons and unreliable rain fall and much

dependence on tanks and wells for irrigation.

The district occupies an area of 17626 Sq.Kms with a density of 173

per Sq.Kms. It accounts for 6.4% of the total area of the State and is

ranked 4th in size. The area of the district is much more in size when

compared to other coastal districts of Andorra Prudish. This district has

102 Kms. of coastal line spread over the 10 mandals.

The district is situated in the south coastal region of Andhra Pradesh

and is the biggest among all the coastal districts of the state in area.

Prakasam district is divided into 56 mandals under “Mandalika Vyavastha”

system. There are 1104 revenue villages in the district. The entire district

is divided into 12 agricultural sub-divisions with each 4-6 mandals.

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The physical characterstics, natural resources and potentialities of

the mandals in the district are not homogenious. As per 2001 Census, the

total population of the district is 30,54,941. It accounts for 4.03% of the

total population of the State and is ranked 14th in the size of the

population. The female population of the district is 15,05,056 and forms

49.27% of the district and 4.02% of the State female population. 15,49,891

are males out of total population in the district. The total literates are

15,52,382 forming 50.82% of the total population of the district. As much

as 3,71,947 population is there for the children in the age group of 0-6

years.

Three mandals were selected for the study- Darsi, Kurichedu, Podili

1.Darsi is located at 15°46′00″N 79°41′00″E15.7667°N 79.6833°E in the

Prakasam district of Andhra Pradesh. The town has a population of

approximately 23,487.Darsi is the centre of a predominantly agricultural

area. Darsi is 70 km away from the district headquarters, Ongole.

2.Kurichedu is a Town in Kurichedu Mandal in Prakasam District in

Andhra Pradesh State . Kurichedu is located 87.72 km distance from its

District Main City Ongole. It is located 209 km distance from its State Main

City Hyderabad . Kurichedu is 19 km from Darsi.

3.Podili is a Town and a Mandal in Prakasam district in the state of

Andhra Pradesh in India Before British Rule its name was Prudhulapuri,

meaning Head Quarters of the Universe, there is Purana reference to this

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related to Prudhu Chakravarthi. Podili is 50 km away from the district

headquarters, Ongole.

CONCEPTUAL MODEL OF THE STUDY

The conceptual model in Fig.2 contains five major divisions.

1. Profile characteristics of practicing IPM and non- IPM farmers.

2. Relationship between adoption and profile of the respondents.

3. Extent of Adoption of IPM practices by farmers

4. Pod borer incidence and economics of IPM and non-IPM fields.

5. Constraints faced by farmers

6. Suggestions to overcome the constraints.

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Fig. No. 3 Map Showing Prakasam District of Andhra Pradesh

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