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INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026
Functional Aspects of Tapioca Farmers Problems During Sales in
Tamilnadu
Dr. M. Sasikumar
1
, Mrs. R. Prema
2
1
Assistant Professor, Government Atrs and Science College, Mettur-1, Salem,Tamilnadu.
2
Ph D Research scholar in department of commerce, Periyar University, Salem-11,Tamilnadu.
DOI: https://doi.org/10.51583/IJLTEMAS.2026.150500158
Received: 13 May 2026; Accepted: 18 May 2026; Published: 10 June 2026
ABSTRACT
In this study, an effort was made to examine the problems encountered by tapioca farmers during the sales
process. The research is based entirely on primary data collected through a structured interview schedule
administered to farmers. The survey was carried out in Salem District, Tamil Nadu, with a sample of 500 tapioca
farmers selected using a simple random sampling technique to ensure fair representation. A carefully designed
interview instrument was employed to gather information on the challenges faced by farmers. To verify the
reliability of the measurement scale, the data were subjected to item analysis, and the internal consistency was
tested using Cronbach’s alpha coefficient. Subsequently, factor analysis and correlation analysis were applied to
identify the functional dimensions and interrelationships among the problems reported by the farmers during
sales.
Key words: Problems, tapioca, sales, study Area.
INTRODUCTION
Tapioca is a vital root crop extensively cultivated across tropical regions, primarily as a staple food. It is grown
mainly for its tubers, which serve as a supplementary source of nutrition. Among food crops, tapioca provides
the highest caloric yield, producing approximately 2,50,000 calories per hectare, compared to 2,00,000 calories
from maize, 1,76,000 calories from paddy, and 1,00,000 calories from wheat (Katyal and Dutta, 1976).
Recognizing its importance, the Central Tuber Crops Research Institute (CTCRI) was established in 1963 at
Trivandrum to intensify research efforts on tuber crops. To further promote tapioca, the Tapioca Market
Expansion Board was set up in 1972. In Tamil Nadu, a Tapioca Research Station was first established in Salem
in 1971, later relocated to Mulluvadi in Attur Taluk in May 1977. Additionally, under the State Industries
Department, a Sago Testing and Research Laboratory has been operating in Salem since 1964. This laboratory
plays a crucial role in testing tapioca products submitted by factory owners and merchants, certifying their
quality, and issuing ISI certificates under the Ministry of Agriculture and Irrigation, Government of India.
Tapioca (Cassava)
Tapioca (Manihot esculenta Crantz) was introduced into India towards the end of the 18th century. In terms of
global cassava production, Nigeria leads the list, followed by Thailand, Indonesia, Congo, Angola, Ghana,
Brazil, and India (see Appendix II). Within India, tapioca is cultivated across nearly 3 lakh hectares, yielding
between 90 to 96 lakh tonnes of tubers annually. While Kerala holds the top position in terms of cultivation and
overall production, Tamil Nadu is recognized as the leading state for processing tapioca into starch and sago. As
a result, tapioca has gained prominence as one of the most significant commercial crops in Tamil Nadu.
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Mass-Media-Exposure
Oto J. Okwu (2011) highlights that mass media is the most frequently used source of agricultural information.
The study found that literate farmers rely on mass media more than non-literate farmers, and its usage is higher
among those with greater income levels compared to low-income earners. Additionally, male farmers were
observed to use mass media more often than female farmers for accessing agricultural knowledge.
Similarly, Gurav et al. (2009), in their study conducted in Maharashtra, emphasized the need to extend the
duration of the Kisanwani programme broadcast from half an hour to one hour. Their findings suggest that such
an extension would make All India Radio’s agricultural programming more effective and better aligned with
farmers’ needs, thereby supporting the successful adoption of new agricultural technologies.
Objective
The major objectives of this study is as follows:
To study the common issues during the sales of Tapioca farmers in Salem district
Research Design
The research design adopted for the present study is the ex-post facto type. The research has no control over the
independent variables prior to producing their effect.
Area of the Study
The study is carried out in Salem district of Tamil Nadu during the year September 2015.
Selection of District
As this study deals with the tapioca farmers, Salem district in Tamil Nadu is purposefully selected, as it fulfills
the following criteria:
Among the different district of Tamil Nadu, Salem district ranks high in terms of large area and production in
tapioca.
A regional research station of Tamil Nadu Agricultural University, which has released many popular tapioca
varieties, is located at Attur, in Salem district.
Table 1 Agricultural and horticultural institutions in Salem Districts
S.No
Taluk
State
Seed
Farm
Agricultural
School
Seed
Processing
Unit
Research
Station
Agri
Laboratory
Agricultural
Dept.
1
Attur
2
-
-
1
-
4
2
Mettur
1
-
1
-
-
3
3
Omalur
1
-
1
-
-
3
4
Salem
4
1
-
1
6
3
5
Sankari
-
-
-
-
-
2
6
Yercaud
1
-
-
1
-
1
7
Edappadai
-
-
-
-
-
2
8
Gengavalli
-
-
-
-
-
2
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9
Vazhappadi
-
1
-
-
-
1
Sample and Sampling Procedure
Appropriate sample size depends on various factors relating to the subject under investigation like the time, cost,
degree of accuracy desired etc. (Rangaswamy 1995).
Salem district is predominantly an agriculture district. Tapioca farmers of this district are the sampling unit of
this study. Salem district is divided into four divisions, nine taluks and twenty blocks.
After selecting the villages, random sampling method is followed for selecting the respondents in each village.
Table 2 Block selected for the study
S.No
Name of Taluk
Block
No. of Respondents
1
Salem
1
Salem
25
2
Veerapandi
25
3
Panamarathupatti
25
4
Ayothyapattinam
25
2
Vazhappadi
5
Vazhapadi
25
3
Yercaud
6
Yercaud
25
4
Gengavalli
7
Gengavalli
25
8
Thallaivasal
25
5
Attur
9
Attur
25
10
Peddanaickenpalayam
25
6
Mettur
11
Mecheri
25
12
Nangavalli
25
13
Kolathur
25
7
Omalur
14
Omalur
25
15
Tharamanagalam
25
16
Kadayampatti
25
8
Sankari
17
Sankari
25
18
Magudanchavadi
25
9
Edappadi
19
Edappadi
25
20
Konganapuram
25
Total
500
Data Collection
For the purpose of the study both primary and secondary data were used. The primary data were collected
structured interview schedule employed and secondary data in website, books and journal were collected.
Statistical Tools Used
The data collected are analyzed by using the following statistical tools.
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Chi-square Analysis
The Chi square test is used in this study on social science and management for testing the independence of two
attributes. It used to identify the socio economic variables and awareness factors influencing in the problems
during sales among the farmers in Salem District.
Factor Analysis and Correlation Analysis
Factor analysis is a multivariate statistical technique used to condense and simplify the set of large number of
variables to smaller number of variables. Correlation analysis is involves various methods and techniques used
for studying and measuring the extent of the relationship between two variables. These tools help to Assessing
the level of variability of the respondents and relationship of variables in problems during tapioca sales.
Table 3: Chi Square: Personal and the awareness factors on the Problems identifying during Tapioca
sales
Personal factors
Chi-square Value
p values
Significant/ Not Significant
Age
6.365
0.384
NS
Sex
0.465
0.792
NS
Literacy level
11.738
0.303
NS
Family Income
3.580
0.466
NS
Number of family members
4.583
0.333
NS
Nature of land holding
0.546
0.969
NS
Sources of irrigation
8.640
0.195
NS
Awareness factors
Chi-square Value
p values
Significant/ Not Significant
Activity of Tapioca cultivation
5.318
0.070
S
Aware of Tapioca cultivation
3.804
0.149
NS
Types of Tapioca
32.591
0.008
S
Engaging cultivation of Tapioca
14.253
0.027
S
Area of cultivation of Tapioca
0.625
0.960
NS
S – Significant at 5% level (p value< 0.05); NS – Not Significant at 5% level (p value>0.05)
It is found from the Table 5.2.4 that the hypothesis is rejected (Significant) in three cases of awareness factors
in other cases the hypothesis is accepted (Not Significant).
It is concluded that the activity of Tapioca cultivation, Types of Tapioca and Engaging cultivation of Tapioca
have significant influence on the Tapioca Problems identifying during Tapioca sales analysis.
Level of problems identifying during Tapioca sales
Kaiser-Meyer-Olkin Measure of Sampling Adequacy
The significance (0.000) is less than the assumed value (0.05) & KMO coefficient = 0.618. This implies that the
factor analysis is valid.
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Table -4 Rotated Factor Loadings for the level of problems identifying during Tapioca sales
Variables for level of problems
identifying during Tapioca sales
F1
F2
F3
Communality
B1
0.599
0.076
-0.058
0.368
B2
-0.196
0.270
-0.655
0.540
B3
-0.036
0.546
0.010
0.300
B4
0.736
0.043
0.025
0.544
B5
0.545
-0.174
0.215
0.373
B6
-0.162
-0.659
0.012
0.461
B7
-0.559
-0.368
0.132
0.466
B8
-0.201
0.356
0.728
0.698
Eigen value
1.66
1.07
1.02
% of var. explained
20.72
13.34
12.80
46.86
Cum. % explained
20.72
34.06
46.86
Table 4 gives the rotated factor loadings, communalities, Eigen values and the percentage of variance explained
by the factors. Out of the 8 level of problems identifying during Tapioca sales variables, 3 factors have been
extracted and these 3 factors put together explain the total variance of these variables to the extent of 46.86%.
In order to reduce the number of factors and enhance the interpretability, the factors are rotated. The rotation
increases the quality of interpretation of the factors. There are several methods of the initial factor matrix to
attain simple structure of the data. The varimax rotation is one such method to obtain better result for
interpretation is employed and the results are given in Table .2.
Table .5: Clustering of level of problems identifying during Tapioca sales variables into factors
Three factors were identified as being maximum percentage variance accounted. The 3 level of problems
identifying during Tapioca sales variables B1, B4 and B5 were grouped together as factor I and accounts 20.72%
of the total variance. The 2 level of problems identifying during Tapioca sales variables B2 and B3 constituted
the factor II and accounts 13.34% of the total variance. The 3 level of problems identifying during Tapioca sales
variables B6, B7 and B8 constituted the factor III and accounts 12.80% of the total variance.
The three level of problems identifying during Tapioca sales variables namely “To whom do sell most of Tapioca
produce” (B1), “When do sell Tapioca after harvest” (B4) and “Mode of sale” (B5) were grouped together as
factor I and accounts 20.72% of the total variance.
Factors
Level of problems identifying
during topica sales
Rotated factor loadings
1. (20.72%)
1 – B1
0.599
2 – B4
0.736
3 – B5
0.545
2. (13.34%)
4 – B2
0.270
5 – B3
0.546
3. (12.80%)
6 – B6
0.012
7 – B7
0.132
8 – B8
0.728
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Correlation Analysis
The correlation is the study of finding the relationship between the variables. If there are only 2 variables in the
study of correlations there it is called simple correlation otherwise the study in either partial or multiple
correlation. In this study the simple inter-correlations analysis is performed between the selected variables and
the results are presented in the form of correlation matrix. Further the significance of correlation was tested at
the 1% level of significance.
The Table 6 describes the results of inter-correlation analysis in terms of correlation coefficient & its significance
at 1% level.
Table 6: Correlation Matrix - Problems identifying during Tapioca sales variables basis of the factor I
Problems identifying during Tapioca
sales variables
To whom do sell
most of Tapioca
produce
When do sell
Tapioca after
harvest
Mode of sale
To whom do sell most of Tapioca
produce
1
0.231
**
0.185
**
When do sell Tapioca after harvest
1
0.200
**
Mode of sale
1
**Significant at 1% level
It is found from the Table 6 that all the problems identifying during Tapioca sales on the basis of factor I
considered have significant inter-correlation between their in respect of Tapioca cultivation analysis.
It is concluded that all the problems identifying during Tapioca sales variables such as ‘To whom do sell most
of Tapioca produce’ (B1), ‘When do sell Tapioca after harvest’ (B4) and ‘Mode of sale’ (B5) for Tapioca
cultivation study have significant interrelationship between them.
Suggestions of the study
The problems identifying during Tapioca sales variables such as ‘To whom do sell most of Tapioca produce’
(B1), ‘When do sell Tapioca after harvest’ (B4) and ‘Mode of sale’ (B5) for Tapioca cultivation study have
significant interrelationship between them.
State Department of Agricultural extension personnel should regularly contact the tapioca Framers and provide
required and timely information related to tapioca cultivation. Agricultural tours particularly for tapioca
Framers and agricultural functionaries should be organized more frequently to exchange
their experience with their counterparts in other states and similar agro-climatic zones.
CONCLUSION
This study concluded that majority of farmers have expressed the non-availability of improved equipment
followed by lack of irrigation facilities as their major short comings. Government should take necessary steps to
promote the marketing facilities, irrigation facilities, training facilities, credit facilities and availability of crop
insurance. Farm or Agricultural implements like tapioca set planter and harvester should be manufactured and
supplied to farmers.
REFERENCE
1. Acharya S.S. and Agarwal N.C. “Agricultural markeitng in India”, Rural marketing, 1997, pp.13.
2. Asthana Harishankar, “Statistics for Social Sciences with SPSS Applications”, Prentice-Hall of India;
2007.
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3. Description of Salem district: the sources of information collected from corporation records, Salem
Corporation, Salem.
4. Gurav, K.V., Chavai, A.M. and Bhange, S.B. “Farmers feedback about the farm broadcast on All India
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