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SELP Journal of Social Science
Vol. V, Issue. 24 ISSN : 0975-9999 (P), 2349-1655 (O)
April - June 201598
Introduction
Maize is one of the important cereals in
India and planted annually in an area of about 6
million hectares mainly 1
, as a kharif crop. In
terms of national hectares it ranks only next to
rice, wheat, sorghum and bajra. Though
consumed all over the country, it is the staple
food of people in the hilly and sub mountain
tracks of northern India. Maize can give better
yield than rice and wheat even averaging up to
3000 2
kg/ha. It is considered that “the second
most remunerative crop” next to rice is maize,
FACTORS INFLUENCING TOWARDS PRODUCTION AND
MARKETING OF MAIZE IN TIRUPUR DISTRICT
Dr. N. Kathirvel
Assistant Professor,
Department ofCommerce, GovernmentArts College
Udumalpet, Tirupur District.
R. Karthika
Part-Time Ph.D. Research Scholar,
Department ofCommerce, Karpagam University, Coimbatore-21.
ABSTRACT
The economic development of a country depends on the development of the core industry in
which the majority of its people have been engaged for quite a long time. Indian economy has
been largely based on agriculture from time immemorial .Maize is widely cultivated throughout
the world, and a greater weight of maize is produced each year than any other grain. The
United States of America produces 40 per cent of the world’s harvest. Other top producing
countries are China, Brazil, Mexico, Indonesia, India, France and Argentina. The Objective of
the research is to ascertain the factors influencing towards production and marketing of maize
among the farmers in the study area. To conclude this study, the crop insurance is one of the
measures suggested that has to be extended to all the farmers. Steps should be taken to reduce
the losses arising out of high moisture content of the maize.
Key words: Transport, Marketing, Storage, farmers etc.
but hybrid maize changed the scenario in
productivity. Maize is widely cultivated
throughout the world, and a greater weight of
maize is produced each year than any other
grain. The United States of America produces
40% of the world’s harvest. Other top producing
countries are China, Brazil, Mexico, Indonesia,
India, France and Argentina. The worldwide
maize production was 854 million tons in 2011-
12, and over 168 million hectares of maize were
planted worldwide, with a yield of over 5 tones/
hectare. Production can be significantly higher
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SELP Journal of Social Science
ISSN : 0975-9999 (P) 2349-1655 (O)
Research Impact Factor : 1.056
Vol. V, Issue. 24
April - June 2015

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SELP Journal of Social Science
Vol. V, Issue. 24 ISSN : 0975-9999 (P), 2349-1655 (O)
April - June 201599
in certain regions of world. “There is conflicting
evidence to support the hypothesis that maize
yield potential has increased”3
over the past few
decades.
Statement of the Problem
The economic development of a
country depends on the development of the core
industry in which the majority of its people have
been engaged for quite a long time. Indian
economy has been largely based on agriculture
from time immemorial. Number of people are
directly and indirectly involved in the production
and marketing of maize. However, these people
are not getting their reasonable income from the
maize cultivation. Lack of market information,
inaccessibility to modern technology and
exploitation of middlemen may be some of the
areas where the attention of planners and policy
makers is required. This is needed to frame
suitable legislation to improve the productivity
and present production and marketing of maize.
Objective of the Study
1. To analyze the factors influencing towards
production and marketing of maize among
the farmers in the study area.
Hypothesis of the Study
1. All variables related to factors influencing
towards production and marketing of maize
among the farmers are uncorrected
Methodology
The primary as well as secondary data
have been used for this study. The collected data
have been analyzed by making use of statistical
tool offactor analysis. Theprimarydata havebeen
collected by using interview schedule, by making
use of multi stage stratified random sampling
technique in Tirupur district as the universe, block
as the stratum, and village as the primary unit of
sampling and maize farmers as the ultimate unit.
Thus the total sample arrived was three hundred.
The fieldsurvey was carriedout from March2014
to September 2014.
Dimensionality of the Multi-Scale Items
(Factor Analysis)
Factor Analysis is a set of technique
which by analyzing correlations between
variables reduces their numbers into fewer
factors which explain much of the original data,
more economically. Even though a subjective
interpretation can result from a factor analysis
output, the procedure often provides an insight
into relevant psychographic variables, and results
in economic use of data collection efforts. The
subjective element of factor analysis is reduced
by splitting the sample randomly into two and
extracting factors separately from both parts. If
similar factors result, the analysis is assumed as
reliable or stable.
Table -1 Kmo And Bartlett’s Test for Factors
Related to Factors Influencing the
Production and Marketing of Maize.
Kaiser-Meyer-Olkin Measure of
Sampling Adequacy
0.759
Bartlett’s Test of Sphericity:
Approx. Chi-Square
1214.507
Sig 0.00**
S/NS S
**P<0.01 S-Significant
From the above table, two tests namely,
Kaiser-Meyer-Olkin Measure of Sampling
Adequacy (KMO) and Bartlett’s Test of
Sphericity have been applied to test whether the
relationship among the variables has been
significant or not. The Kaiser-Meyer-Olkin
Measure of sampling adequacy shows the value
of test statistics is 0.759, which means the factor
analysis for the selected factors is found to be
appropriate or good to the data. Bartlett’s test of
sphericity is used to test whether the data is
statistically significant or not with the value of
test statistics and the associated significant level.
It shows that there exists a high relationship
among variables.

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SELP Journal of Social Science
Vol. V, Issue. 24 ISSN : 0975-9999 (P), 2349-1655 (O)
April - June 2015100
Table-2 Eigen Values and Proportion of Total Variance of Each Underlying Factors
Influencing towards Production and Marketing of Maize.
Initial Eigen values
Extraction Sums of Squared
Loadings
Rotation Sums of
Squared loadings
Component
Total
% of
Variance
Cumulative
%
Total
% of
Variance
Cumulative
%
Total
% of
Variance
Cumulative
%
1 3.977 36.152 36.152 3.977 36.152 36.152 3.304 30.037 30.037
2 1.760 16.000 52.152 1.760 16.000 52.152 1.845 16.775 46.813
3 1.179 10.716 62.868 1.179 10.716 62.868 1.766 16.055 62.868
ExtractionMethod: PrincipalComponentAnalysis
Theresults ofthefactor analysis presented
in thetable 2, regardingfactors influencingtowards
production and marketing of maize farmers, have
revealed that there areeleven factors that had Eigen
value exceeding “one”. Among those three factors,
the first factor accounted for 36.15 per cent of the
variance, the second 16 percent and the third factor
10.72 per cent of the variance in the data set. All
the three factors together represent 62.87 per cent
of the total variance in the scale items measuring
the factors influenced towards production and
marketing of maize. Hence from the above results,
it is certain that the factors influencing towards
production and marketing of maize are necessary.
Table-3 Communalities Related to Factors
Influencing the Production and Marketing
of Maize.
S.
No.
Variables Initial
Extra-
ction(h2
)
1 Supply & quality of
seeds
1.000 .782
2 Supply of fertilizers 1.000 .802
3 Availability of
labourers
1.000 .523
4 Expected yield 1.000 .636
5 Storage facility 1.000 .671
6 Transport facility 1.000 .465
7 Marketing facility 1.000 .453
8 Price stability 1.000 .692
9 Prompt payment of
trader
1.000 .703
10 Advice and training
from agriculture
department
1.000 .615
11 Sufficient water facility 1.000 .627
The above table 3, (Communalities)
represents the application of the Factor Extraction
Process, it was performedby Principal Component
Analysis to identify the number of factors to be
extracted fromthe data and by specifying the most
commonly used Varimax rotation method. In the
principal component analysis, total variancein the
data is considered. The proportion of the variance
is explained by the elevenfactors ineach variable.
The proportion of variance is explained by the
common factors called communalities of the
variance. Principal ComponentAnalysis works on
initial assumption that all the variance is common.
Therefore, before extraction the communalities
are all 1.000. Then the most common approach
for determining the number of factors to retain
i.e., examining Eigen values was done.
Source: Primary Data
Table 4 Rotated Component Matrix for
Factors Influencing towards production and
marketing of maize
Factor Factor FactorVariable
codes I II III
X5 .793 .151 .136
X10 .765 .172 -.010
X11 .748 .258 -.023
X4 .696 -.116 .371
X6 .641 .206 .107
X7 .604 -.213 .207
X1 .229 .849 .095
X2 .052 .838 .311
X8 .111 .181 .804
X9 .086 .300 .779
X3 .441 -.280 .501
Extraction Method: Principal Component
Analysis.

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SELP Journal of Social Science
Vol. V, Issue. 24 ISSN : 0975-9999 (P), 2349-1655 (O)
April - June 2015101
The above table 4 represents the Rotated
Component Matrix which is an important output
of principal component analysis. The
coefficients are the factor loadings which
represents the correlation between the factors
and the eleven variables (X1
to X11
). From the
above factor matrix it is found that coefficients
for factor - I have high absolute correlations with
Variables likes (X5
), (X10
), (X11
), (X4
), (X6
), and
(X7
) 0.793, 0.765, 0.748, 0.696, 0.641 and 0.604
respectively. Similarly factor II has high absolute
correlation with variable X1
and X2
, 0.849 and
0.838 respectively. Next, factor III, has high
absolute correlation with variables like X8
X9
and
X3
(0.804, 0.779 and 0.501). So we proceed to
compute the rotated factor matrix.
Table 5 - Component Transformation Matrix
Component 1 2 3
1 .844 .319 .432
2 -.479 .811 .337
3 -.243 -.491 .837
The above table reveals the factor
correlation matrix. If the factors are uncorrelated
among themselves, then in the factor correlation
matrix, the diagonal elements will be 1’s and off
diagonal elements will be 0’s. Since matrix was
rotatedwithVarimax,barringsomevariablesallother
variables are found to have, even if not zero
correlations but fairly low correlation. Thus the
eleven variables in the data were reduced to three
Component factorsandeachfactormaybeidentified
with the corresponding variables as follows:
X5 Storage facility 62.88%
X10
Advice and training from
agriculture department
58.52%
X11 Sufficient water Facility 55.95%
X4 Expected yield 48.44%
X6 Transport facility 41.09%
X7 Marketing facility 36.48%
Factor
I
X1
Supply & quality of
seeds
72.08%
X2 Supply of fertilizers 70.22%
Factor
II
X8 Price stability 64.64%
X9
Prompt Payment of
trader
60.68%
X3 Availability of labourers 25.10%
Factor
III
Findings of the Study
The Kaiser-Meyer-Olkin Measure of
sampling adequacy shows the value of test
statistics is 0.759, which means the factor
analysis for the selected variable is found to be
appropriate or good to the data. Bartlett’s test of
sphericity is used to test whether the data are
statistically significant or not with the value of
test statistics and the associated significant level.
It shows that there exists a high relationship
among variables.
Table -6 Showing the Factors Identified and
Influencing towards Production and
Marketing of Maize
Source: Primary Data
Factor - I has high absolute correlations
with Variable (X5
), (X10
), (X11
), (X4
),(X6
),and
(X7
) 0.793,0.765,0.748.0.696,0.641 and 0.604
respectively. Out of eleven factors, six factors
are mostly influenced towards production and
marketing of maizethat is namely, Storagefacility
(62.88%), Advice and training from agriculture
experts (58.52%), sufficient water facility
(55.95%), Expected yield (48.44%), Transport
facility (41.09%), and Marketing facility
(36.48%).
Factor II has high absolute correlation
with variable X1
and X2
, 0.849 and 0.838
respectively. That is namely Supply and quality
of seeds and supply of fertilizer.
Factor III, has high absolute correlation
with variable X8
X9
and X3
(0.804, 0.779 and
0.501). That is namely Price stability, Prompt
payment of trader and availability of labourers.
Suggestions
1. Transportation and storage facilities with
scientific knowhow were not well developed
and hence the authorities concerned may have

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SELP Journal of Social Science
Vol. V, Issue. 24 ISSN : 0975-9999 (P), 2349-1655 (O)
April - June 2015102
their research and development cell and the
findings may be extended to the benefits of
the farmers.
2. The official of the horticultural department at
the taluklevels shouldvisit thefarms andguide
the maize cultivating farmers to overcome
their problems regarding the availability of
hybrid seeds, pest management, and water
management, use of manures, and increased
production.
3. The non-availability of quality seed is a
problem for the farmers. The Government
should make arrangements for availing newer
varieties of seeds at reasonable rates to
increasethe productivity and quality of maize.
4. The cost of fertilizers and pesticides is more
as the farmers buy them from private traders.
The Government should come forward to
supply themthrough agricultural co-operative
organizations either as subsidies or at
reasonable price.
5. Credit-linked marketing is compromising
innovation both to get credit facilities easily
through government agencies and to repay
the loans in time while marketing them.
Conclusion
The Government can pay attention by
providing transport facilities, maintaining good
roads and providing subsidies for suckers and
fertilizers, so that the small and medium farmers
may be benefited. In the areas chosen for the
research, majority of the population are
agriculturists. Their agricultural lands depend on
monsoon rains. Majority of the lands are rain-
fed areas. If the monsoon fails, then the farmers
will be in trouble. In this situation, the
Government should give financial support to
farmers, especially to the small and medium
farmers. The crop insurance is one of the
measures suggested that has to be extended to
all the farmers. Steps should be taken to reduce
the losses arising out of high moisture content
of the maize. The maize is also seriously affected
by various diseases. Therefore, a permanent
research station may be set up to protect the
maize from disease.
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