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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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