Study on Utilization of Information and Communication ...CERTIFICATE - I This is to certify that the...

“ Study on Utilization of Information andCommunication Technologies (ICTs) for

Selected Crops in Rewa District of (M.P.)”

THESIS

Submitted to the

Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur

In partial fulfillment of the requirements forthe Degree of

MASTER OF SCIENCE

In

AGRICULTURE

(EXTENSION EDUCATION)

SONAL GUPTA

Department of Extension EducationCollege of Agriculture, Rewa 486002

Jawaharlal Nehru Krishi Vishwa Vidyalaya,Jabalpur (M.P.)

2015

CERTIFICATE - I

This is to certify that the thesis entitled, “Study on Utilization ofInformation and Communication Technologies (ICTs) for Selected Cropsin Rewa District of (M.P.).” submitted in partial fulfillment of the requirement

for the degree of MASTER OF SCIENCE in AGRICULTURE Extension ofJawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur (M.P.) is a record of

the bonafide research work carried out by Mr. SONAL GUPTA under my

guidance and supervision. The subject of the thesis has been approved by the

Student's Advisory Committee and the Director of Instructions.

All the assistance and help received during the course of the

investigation has been duly acknowledged by him.

Place- Rewa

Date …………....... Signature

(Dr. R.A. Sathwane/Dr. A. S. Chouhan)

Chairman of the Advisory Committee

THESIS APPROVED BY THE STUDENT'S ADVISORY COMMITTEE

Chairman (Dr. R.A. Sathwane/

Dr. A. S. Chouhan)

…………….

…………….

Member (Dr. Sanjay Singh) …………….

Member (Dr. A. M. Mishra) ……………..

Member (Dr. R. K.Tiwari) ……………..

CERTIFICATE - II

This is to certify that the thesis entitled “Study on Utilization ofInformation and Communication Technologies (ICTs) for Selected Cropsin Rewa District of (M.P.).” Submitted by Mr. SONAL GUPTA to Jawaharlal

Nehru Krishi Vishwa Vidyalaya, Jabalpur in partial fulfillment of the

requiremen ts for the degree of MASTER OF SCIENCE in AGRICULTUREEXTENSION in the Department of Extension Education, College of

Agriculture, Rewa (M.P.) has been after evaluation approved by the external

examiner and by the Student's Advisory Committee after an oral examination

of the same.

Place -Rewa

Date……………….. Signature

(Dr. R.A. Sathwane/

Dr. A. S. Chouhan)Chairman of the Advisory Committee

THESIS APPROVED BY THE STUDENT'S ADVISORY COMMITTEE

Chairman (Dr. R.A. Sathwane/

Dr. A. S. Chouhan)

…………….

…………….

Member (Dr. Sanjay Singh) …………….

Member (Dr. A. M. Mishra) ……………..

Member (Dr. R. K.Tiwari) ……………..

Chairmain & Head of the

Section

(Dr. R. A. Sathwane/Dr. a. S. Chouhan)

……………

…………....

Director of Instructions (Dr. G. S. Rajput) …………….

Declaration and undertaking by the candidate

I, SONAL GUPTA S/o RATNESH KUMAR GUPTA certify the

work embodied in thesis “Study on Utilization of Information andCommunication Technologies (ICTs) for Selected Crops in Rewa Districtof (M.P.).” is my own first hand bona fide work carried out by me under the

guidance of Dr. R.A. Sathwane, Professor & Head of Section (Departmentof Extension Education), College of Agriculture, Rewa (M.P.), during

2014-15.

The matter embodied in the thesis has not been submitted for the

award of any other degree / diploma. Due credit has been made to all the

assistance and help.

I, undertake the complete responsibility that any acts of

misinterpretation, mistakes, error of fact are entirely of my own.

I, also abide myself with the decision taken by my advisor for the

publication of material extracted from the thesis work and subsequent

improvement, on mutually beneficial basis, provided the due credit is given

thereof.

Place: Rewa (M.P.)

Date: Signature of the student

SONAL GUPTA

Copyright ©Jawaharlal Nehru Krishi Vishwa Vidyalaya,Jabalpur (M.P.) 2014

Copyright transfer certificateTitle of the thesis - “Study on Utilization of Information and

Communication Technologies (ICTs) for Selected Crops in Rewa Districtof (M.P.).”

Name of the candidate – SONAL GUPTA

Subject – AGRICULTURE EXTENSION

Department - Department of Extension Education

College - College of Agriculture, Rewa (M.P.)

Year of thesis submission - 2014-15

Copyright transfer certificateThe undersigned Mr. Sonal Gupta assigns to the Jawaharlal Nehru

Krishi Vishwa Vidyalaya, Jabalpur (M.P.), all rights under copyright Act that

may exists in and for the thesis entitled -“Study on Utilization of Informationand Communication Technologies (ICTs) for Selected Crops in RewaDistrict of (M.P.).” submitted for the award of M.Sc (Ag.) Extension

Education

Place: Rewa (M.P.)

Date:

(Dr. R.A. Sathwane/

Dr. A. S. Chouhan)

Major Advisor Signature of the student

Name and Signature SONAL GUPTA

ACKNOWLEDGEMENT

The author of this manuscript expresses his deep senses of

adoration towards the omniscient and almighty ‘‘God’’ who gave him

this opportunity of doing M.Sc. (Ag.) Extension Education.

It is a moment of great pleasure to put in records my heartfelt

gratitude and indebtedness to my Guide and Chairman of my Advisory

Committee Dr. R.A. Sathwane , Professor & Head / Section (Departmentof Extension Education), College of Agriculture, Rewa (M.P.), for his

able magnificent guidance, inspiration, constructive criticism and

encouragement during the course of investigation and preparation of the

manuscript.

I am highly obliged to the members of by Advisory Committee namely,

Dr. R. A. Sathwane Head of the Department/ Section, Dr. Sanjay Singh, SMS

in KVK, Dr. A. M. Mishra, Department of Agriculture Economics & Farm

management, & Dr. R.K. Tiwari Department of statistics for their generous

help, valuable suggestions, necessary help provided during the course of

present investigation.

I express my heartfelt thanks to Dr. S.K. Pandey , Dean, College of

Agriculture, Rewa, (M.P.) for his encouragement and giving direction.

It is an opportunity for me to extend my regards to my respected

teachers Dr. A. M. Mishra, Professor, Department of agri. Eco. & F M., Dr.

Rajesh Singh, Subject Matter Specialist (Horticulture), K.V.K., Rewa, Dr. R.K.

Tiwari, Associate Professor College of Agriculture, Rewa., Dr. S.K. Tripathi,

Head of section, department of plant pathology, Dr. I.M. Khan Academic in

charge and Scientist (Plant Physiology) College of Agriculture, Rewa for their

cooperation and encouragement during the investigation.

I express my special thanks to my respected seniors, Shri Kuldeep

Singh Dhakar and my lovable juniors for their all time help and excellent

cooperation during this research work.

In the last but not the least words are too less to express my sincere

gratitude to my beloved grandfather Late Shri Biharilal Gupta and my father

Late Shri Ratnesh Kumar Gupta and mother Smt. Suneeta Gupta , and

brother Amit Gupta, and whose love blessing and constant encouragement

throughout my life enable me to achieve this invincible goal, made my

education possible and brought me to present level.

I appreciate and express my cordial thanks to college us friends Mr.

Arun Meena, Mr .Ajit Singh, Mr. Manish Tiwari, Mr.Shyam Patidar, Mr.Antim

Birla, Mr.Lokendra Karode, Miss.Sukhda Sharma, and lovable juniors Suneel

Patel , Rakesh Chouhan , Dharmendra Patel Sachin Bagri for their friendly

co-operation and encouragement my research work.

Place- Rewa SONAL GUPTADate………….

LIST OF CONTENTS

Chapter No. TITLE PAGE NO.

1. Introduction 1- 5

2. Review of literature 6-15

3. Materials and methods 16-29

4. Results 30-58

5. Discussion 59-62

6. Summary, conclusions and suggestions forfuture work

63-69

6.1 Summary

6.2 Conclusions

6.3 Suggestions for future work

BIBLIOGRAPHY

APPENDICES

CURRICULUM VITAE

Name – Sonal Gupta

Place – Village-Sili, Post+ Teh.Gunour, District Panna (M.P.) 488058

Date of birth - 01 Aug. 1988

Institution Degree University Year OGPA

College of Agriculture Rewa(M.P.)

M.Sc.(Ag.)

Extensioneducation

JNKVV,Jabalpur

2015

College of Agriculture Rewa(M.P.)

B.Sc.(Ag.)

JNKVV,Jabalpur

2013 7.06

V.S.D.J. H.S. School, Gunour(Panna) M.P.)

12th M.P.BoardBhopal

2007 70.22

For the partial fulfillment of the master’s degree programme he was

allotted a research problem on, “Studies on Utilization of Information andCommunication Technologies (ICTS) for Selected Crop in Rewa Districtof (M.P.).” Which was successfully conducted by him and being submitted in

the form of this thesis.

List of Tables

Number TitlePages

No.

3.1 Distribution of registered users as farmers of mobilephone message in the Rewa District

17

3.2 Selection of respondents on the basis of highest

number of users from the villages in Rewa block18

4.1 Distribution of the respondents according to their

age30


caste31


level of education31


size of family32


land holding32


social participation33


farming experience33


annual income34


information seeking behavior34


extension contact35


achievement motivation35


scientific orientation

36


innovativeness36

4.14 Utilization of messages on different aspects by the

respondents obtained through mobile phone message37

4.15 The utilization in respect the different fields of mobile

phone message on production technology of wheat39

4.16 Distribution of the respondents according to theirextent of utilization of ICTs

40

4.17 Association between age of the respondents andextent of utilization of ICTs

41

4.18 Association between caste of the respondents andextent of utilization of ICTs

42

4.19 Association between education of the respondents

and extent of utilization of ICTs43

4.20 Association between size of family of the

respondents and extent of utilization of ICTs

44

4.21 Association between land holding of the


45

4.22 Association between social participation of the

respondents and extent of utilization of ICTs46

4.23 Association between farming experience of the


47

4.24 Association between annual income of the

respondents and extent of utilization of ICTs48

4.25 Association between information seeking behavior of

the respondents and extent of utilization of ICTs

49

4.26 Association between extension contact of the


50

4.27 Association between achievement motivation of the


51

4.28 Association between scientific orientation of the


52

4.29 Association between innovativeness of the


53

4.30 Association between profile characteristics of the

farmers and extent of utilization of ICTs

54

4.31 Correlations between profile characteristics of the

farmers and their extent of utilization of ICTs

55

4.32 Constraints faced by the respondents in utilization of

ICTs.

56

4.33 Provide suggestions to the respondent in utilization of

ICTs.57-58

List of Figures

Fig.Number Title

3.1 Map of Rewa District

4.1 Distribution of the respondents according to their age

4.2 Distribution of the respondents according to their caste

4.3 Distribution of the respondents according to their level of education

4.4 Distribution of the respondents according to their size of family

4.5 Distribution of the respondents according to their land holding

4.6 Distribution of the respondents according to their social participation

4.7 Distribution of the respondents according to their farming experience

4.8 Distribution of the respondents according to their annual income

4.9 Distribution of the respondents according to their information

seeking behavior

4.10 Distribution of the respondents according to their extension contact

4.11 Distribution of the respondents according to their achievement

motivation

4.12 Distribution of the respondents according to their scientific

orientation

4.13 Distribution of the respondents according to their innovativeness

4.14 Utilization of messages on different aspects by the respondents obtained

through mobile phone message

4.15 The utilization in respect the different fields of mobile phone message on

production technology of wheat

4.16 Distribution of the respondents according to their extent of utilizationof ICTs

~ 1 ~

INTRODUCTION

India holds second Position among the countries about high population

in the world about approximate 1.2 billion. Among these, 70 per cent live in

rural area and their main occupation is agriculture. The main base is agriculture

which continues to be the occupation and way of life for more than half of

Indian population even today making single largest contribution 15.70 percent

to the GDP of our Nation (Jain, 2011). Sustainable prosperity of the farmers

and the agricultural labourers holds the key for improving the overall human

resource development scenario in the country. There is a need to increase

production and productivity of agriculture. Hence, the Indian farmers need to be

updated with the latest knowledge about new techniques of farming, new

cultivars, farm machinery, market and trade situation etc.

The extension personnel of the department of agriculture disseminated

the technologies and messages to the farmers through various extension

methods. But these approaches have not been able to reach majority of the

farmers spread across the country as the ratio between farmers and extension

worker is 1000:1. This gap remains a challenge for extension system even

today. ICT provides vital access to information, markets by connecting the rural

poor and marginalized to the world's information resources and opportunities.

The ICTs also provide the flexibility in providing information related to the

various modes of farming practices including all the crops, specific commodities

and enterprises, price information and all other information and regarding

technological advances and tracking global competitiveness. Thus, the ICT

play an increasingly important role in linking the research- extension-market

continuum towards developing professional competencies and entrepreneurial

capabilities among specialists and farming communities respectively.

~ 2 ~

ICT can provide vital access to information, markets by connecting the

rural poor and marginalized to the world's information resources and

opportunities. The ICTs provide the flexibility in providing information on

various modes of farming practices including all the crops, specific

commodities and enterprises real time price information and all other

information related to technological advances and tracking global

competitiveness. Thus, the ICT play an increasingly important role in

linking the research-extension-market continuum towards developing

professional competencies and entrepreneurial capabilities among specialists

and farming communities respectively.

ICTs can be broadly interpreted as technologies that facilitate

communication, processing and transmission of information by electronic

means. In this study ICTs is operationalized as the use of communication

devices or applications by the farmers encompassing radio, television, mobiles,

kisan call centers for obtaining information. So, ICTs can make agriculture

more remunerative and a fruitful occupation by providing latest information. It

saves money, time and efforts and reduces dependency on so many actors in

the chain of extension. Keeping in view the above facts, the present study will

be undertaken with the following objectives.

Objectives:

1. To study the profile characteristics of the farmers.

2. To assess the extent of utilization of Information and Communication

Technologies (ICTs).

3. To study the relationship between profile characteristics and extent of

utilization of ICTs.

4. To identify the constraints faced by the respondents in utilization of ICTs

and provide suggestions to overcome them.

~ 3 ~

ROLE OF ICTs

1. ICTs can be helpful in providing the interaction among the researchers,

extension workers and farmers.

2. ICT services to the block and district level development officials leads

to increase efficiency in delivering the services for overall agriculture

development.

3. ICTs help in providing up to date information services to the farmers

such as on package of practices, market information, weather

forecasting, the input supply, credit availability etc; can be provided at

the earliest possible time.

4. ICT provide information services on disease/pest early warning

systems, information regarding Research Development programmes

and crop insurances, post harvest technology.

5. ICT can extend services regarding farm business and management

information to the farmers.

NEED OF THE STUDY

The adoption of new ICTs will demand changes in Agricultural

Extension Systems to more participatory systems and the agricultural

extension agents will pick up a new role of intermediary between farmers and

information and innovation providers. If modern ICT facilities are not

adequately built into the mainstream of agricultural extension system, there is

likely to be stagnation in the dissemination, utilization and application of

scientific agricultural information for purposeful development of the system.

The effective awareness campaign on ICT use, involvement of local self

governments, value added information and combination of services provision

proved as strategic factors behind success of ICT initiatives. Many of the

advances took place in ICTs, but how far the farmers are using them was not

documented for want of such research studies.

~ 4 ~

SCOPE OF THE STUDY

The findings of the study would have immense practical utility. The study

reveals the extent of use of ICT tools by the farmers and focuses on the

factors affecting the use of ICTs and attitude of farmers towards ICTs use.

This helps in formulating strategies to correct the negative attitudes and

promote favourable attitude. Further the study also documents the

constraints faced by the farmers in using ICTs. The ICT project initiators can

come out with solution for the constraints so as to promote the use of ICT

tools. The suggestions for constraints from farmers would serve the ICT

project initiators as ready to use solutions.

The findings would be helpful to policy makers, governmental

and non- governmental agencies, developmental professionals and other

agencies which are working for the agricultural development through the use

of ICTs. The study would contribute to the existing body of research on the

integration of ICT for agricultural development. The findings of the study

may serve as a guide for future researchers who may examine ICT in similar

contexts. The farmer’s information needs, their access to information

sources, ICT role in meeting their needs, their knowledge and attitude

towards ICT extension services would be of huge practical utility for the ICT

projects to be initiated in the future.

In specific, the findings of the study would help planners and policy

makers to apply appropriate strategy and specific actions while formulating

ICT projects so as to achieve greater participation of the farmers in utilizing

information technology in rural areas.

~ 5 ~

LIMITATIONS OF THE STUDY

One of the obvious limitations is the resources and the time available

at the disposal of student researcher, to conduct this research. The

objectivity of the study is confined to the ability of the farmers to recall

and also their honesty in providing the necessary information.

Moreover, it was based on the expressed information and options of the

respondents, which may not be free from individual biases and prejudices.

Despite these limitations, much effort was put to make the study as objective

and systematic as possible.

PRESENTATION OF THE THESIS

The thesis is presented under five chapters. The first chapter deals

with the introduction, need of the study, objectives, scope and limitations of

the study. The second chapter, viz., review of literature, deals with the

review of important studies related to the field of present study. In the third

chapter, the materials and methods used in the research work including

operationalization of the concepts, measurement procedure of the variables

and the statistical tools used are presented. The fourth chapter deals with

result. The fifth chapter deals with discussions and the sixth chapter deals

with Summary, conclusions and suggestions for further work. The

bibliography, appendices and vita are furnished at the end.

~ 6 ~

REVIEW OF LITERATURE

A comprehensive and critical review of past researches provides a

sound base for the scientific investigations. Keeping in view the objectives of

the present study an attempt was made in this chapter to review all the

literatures having direct or indirect bearing on the present investigation. The

review of literature has been presented under keeping in view, the objectives of

the study.






4. To identify the constraints faced by the respondents in utilization of ICTs

and provide suggestions to overcome them.

2.1. To study the profile characteristics of the farmers.

Kushwaha (1999) while studying the adoption behavior of tomato

growers found that 31.00 percent were educated up to higher secondary level.

Gaikward and Gunjal (2000) reported that three fifth of the Krishi Vigyan

Kendra beneficiaries had high social participation, followed by medium

(26.66%) and low (13.34%) levels of social participation.

kumar (2001) reported that 41.10 percent of respondents fell under

low information seeking category followed by 33.34 and 25.00 percent of

respondent fell under medium and high information seeking category

respectively.

Kanal (2005) revealed that maximum percentage of respondents were

having marginal to small size of land holding. He further concluded that the size

of land holding were significantly associated with level of adoption of organic

farming practices by the respondents.

~ 7 ~

Premavathi (2005) inferred that a little less than two third of the farm

women respondents had high (64.00%) level of innovativeness, followed by

medium (34.50%) innovativeness and low (1.50%) innovativeness.

Demiryurek (2006) conducted a study in Turkey and concluded that

there was positive relationship between adoption and communication behavior

supporting the generalization of different theory.

Sarada et al. (2007) reported that more than half of the rural women

SHG members had low (57.00%) level of social participation, followed by high

(30.50%) and medium (12.50%) levels of social participation.

Ashokhan et al. (2008) found that a little less than half of the self help

group members had high (47.33%) level of innovativeness, followed by medium

(43.67%) and low (9.00%) levels of innovativeness.

Ganeshkumar et al. (2008) in a study found that nearly two third of the

farmers under ICT projects had medium (66.00%) level of extension contact,

followed by low (23.33%) and high (10.67%) levels of extension contact.

Sen (2008) found that most of the ICT users (45.83%) belonged to

middle age group (36-50 years). Darshan Programme viewers (29.38%) were

educated up to high school/higher secondary level.

Shaik (2008) conducted a study and found that 50 percent of

functionaries at Gyandoot were matriculates and 50 percent of Warna

functionaries were graduates and 57 per cent of functionaries at ikisan were

professionally qualified.

Shaik (2008) found that among the farmer beneficiaries of gyandoot

ICT project. 45 per cent were young, 45 per cent middle and only 10 per cent

were old. Among the beneficiaries of Kisan ICT project, 47.50 per cent were

young, 32.50 per cent middle and only 20 per cent old. Further, in Warna wired

project, she found that 62.50 per cent were young, 35.00 per cent middle and

only 2.50 per cent old.

~ 8 ~

Khandait et al. (2011) found that highest number of the respondents i.e.

62.92 percent were in medium category in respect of their level of information

source utilization, followed by low level category, which is comprised of 18.75

percent respondents and 18.33 percent respondent were found in high level of

information source utilization.

Kumar et al. (2011) found that the majority of the farmers had

agriculture and labour as their primary occupation with just below half of them

recording their primary occupation with just below half of them recording their

annual income in between Rs. 35,001 to Rs. 60,000/-.

Dhakar et al. (2013) conducted study in Rewa district of MP to about 50

percent of the respondents i.e. 49.60 percent had medium level of risk

orientation.

Singh et al. (2013) in their research study reported that KMS

assessment was done and result opt end were categorized in four different

aspect, that is, understanding of the message- 81.54%, Need and time based

message- 91.20%,applicability of the message - 89.99% and impact of the

technology was 83.35%.

Agrawal et al (2014) Results showed that Chi-square analysis of the

selected five independent variables with dependent variable (i.e. technical

knowledge) indicated that, the variables age, education, annual income,

information seeking behavior, appropriateness of message were positively

significant at 0.05 per cent level of significance. The profile analysis clearly

indicated that majority of the KMS beneficiaries belonged to the young age

group (57.26%) and were having education up to high school (47.00%). Their

main occupation was farming (70.08%), possessed medium size of land

holding (50.42%). Higher percentage of Kisan Mobile Sandesh beneficiaries

(52.99%) had above 5 members in the family and belonged to medium annual

income (46.16. %) category.

~ 9 ~

2.2. To assess the extent of utilization of Information and CommunicationTechnologies (ICTs).

Pandey and Mehta (2003) revealed that half (50.00%) of the

respondents used educational technologies to a medium extent in open

learning system, followed by low (43.00%) and high (7.00%) levels of use.

Tadasad et al. (2003) stated that 42.70 per cent very often used

websites; 33.60 per cent often used; 19.60 per cent occasionally used; 2.80 per

cent rarely used and 1.40 per cent not at all used websites.

Balajee et al. (2007) found that along with ICT based advisory

services, input supply and testing need to be integrated for the greater impact.

Further, he found that content need to be aggregated from of different sources

but it need to be sorted in granular format for rapid adaptation for local use.

Localization and customizability of content are still not practiced on a significant

scale.

Banmeke and Ajayi (2008) found that respondents mostly used

information board, video presentation and the radio programme at the centre.

The most frequently sought information is on fertilizer application, harvesting

methods and market information.

Bhatnagar (2008) found that ICT could make the greatest contribution

by telescoping and reducing the cost of interaction between stakeholders. ICT

has the potential to help farmers in the entire cycle of production, i.e. from

production to sales. ICT impacts both observable and unobservable transaction

costs.

Narasimha and Pushpa (2009) found that due to communication

technology (Television and Computer-internet) in the selected villages

knowledge centre there has been increasing awareness about pesticides,

fungicides, fertilizer, tractors, power-tillers etc.

Rita (2009) found impact and said that there are isolated cases where

farmers adopting agricultural technologies and also say that most common

method used to dissemination of technologies are telephones internet short

message services radio and publication bullets.

~ 10 ~

Jamwal and Padha. (2009) found that the emphasis has to be given to

develop low-cost, relevant and cost-effective ICT. Hence, the operational

challenges of affordability, sustainability, relevance and the scalability of

technology based business model must be pursued.

Shaffril and Samah (2009) found that the overall, members of VDC

perceived information and Communication Technology or ICT from moderate to

high in term of their importance for their village development. Respondents had

significant differences in their perception towards the importance of ICT.

Bhatnagar and Singh (2010) found that respondents who had used both

the manual and computerized systems indicated an overwhelming preference

for computerized service delivery in most projects small gains for the users

could trigger major positive change in perception of service delivery systems.

Dhaka and Chayal (2010) found that majority of the farmers had

favorable attitude towards the information Technology.

Hiremath and Tiwari (2011) found that majority of them considered

always comfortable to use Telephone followed by mobile.

Mohanty and Kumar (2011) found that mobile phones can act as a

catalyst to rejuvenate the collapsing agricultural extension system through e-

Agriculture- Kisan Mobile Advisory Services (KMAS) at different levels i.e.

locally, regionally and globally. In fact, a push towards higher agricultural

productivity requires an information-based, decision-making agricultural

system.

Pant (2011) found that use of phone was appreciated by farming

communities as easy, fast and convenient was to get information on different

aspects of agriculture.

Papzan and Saki (2011) found that more than 90% of literate farmers

believed that ICT has affected economic profitability, limitation and outgrowth of

marketing agricultural productions. There was a direct relationship between

farmer's education and economic factors.

~ 11 ~

Pargniha et al. (2011) found that message was medium

understandable for large majority (44%) of the members of farmers category as

far as applicability of the message is concerned the message was fully

applicable for about 40 percent of KMA members of farmers category.

Singh et al. (2011) found that the identified stakeholders were agreed

100% with delivery of timely information followed by 99.4% with strong linkage

with KVK and 97.60% with need-based information respectively.

Yadav et al. (2011) found that Farmer Mobile Advisory (FMA) service is

an important tool for need based information delivery on mobile phone. The

adoption of rural technologies by farmers through Krishi Vigyan Kendras

(KVKs) is a big leap in this direction.

Michailidis et al. (2012) conducted the study on mobile communications

technology in rural societies of developing countries like Macedonia, & Greece

and found that the motive driving to adopt mobile communication technology is

a way of integrating technologies in less favoured area of developed countries.

Dhakar et al. (2013) conducted study in Rewa District of MP to assess

the utility perception of ICT based program. The study was entirely on the

farmers availing the facility of ICT through mobile advisory services and

revealed that the aspect of ICT i.e. location specific had the highest utility

perception index (86.96) followed by timeliness (utility perception index 82),

understandability (utility perception index 80.4), applicability (utility perception

index 77.36) and simplicity (utility perception index 75.36). The study also

revealed that of the total 125 respondents 40.80% had medium utility

perception, 36.00% high utility perception whereas 23.20% had low utility

perception about mobile advisory services.

~ 12 ~

Meshram Y (2014) observed that utilization of messages on the aspect

of applicable of message was found to be maximum as indicating the utilization

index- 87.50 followed by Understandability of message need based message

and time based message. Out of 120 respondents i.e. 42.50 percent indicate

medium utilization of Kisan Mobile Advisory Services followed by 34.17 percent

high utilization of Kisan Mobile Advisory Services. It is evident from the data

that 23.33 percent respondents showed low utilization of Kisan Mobile Advisory

Services.

2.3. To study the relationship between profile characteristics and extentof utilization of ICTs.

Meena Bigai et al.(1999) reported the education had positive and

significant association with media utilization behavior.

Bhagat et al. (2004) reported that the variables like land holding,

cosmopoliteness and management orientation had positive relation with extent

of use of information.

Grover et al. (2007) found that the extent of adoption of technologies

through ICT increased with land holding size and adoption was low in families

of landless, small and marginal farmers. Land holding size, education and

occupation were found to have a significant affect on adoption of ICT.

Chouhan (2009) revealed that age had negative but significant

correlation (r= -0.681) with the perception of viewers regarding Krishi darshan

programme of doordarshan.

Chouhan (2009) reported that risk performance of the viewers had

positive and significant correlation (r= 0.430) with perception of viewers

regarding KIrishi Darshan Programme of Doordarshan.

Shaffrill and Samah (2009) found that income per month of the VDC

members indicated positive and significant relationship with their perception

towards the importance of ICT.

~ 13 ~

Shinde and Mall. (2009) reported the correlation analysis revealed that

independent variables viz., education, cadre, service experience, facilities

available, job satisfaction, and training had positive and significant relationship

with electronic media use behavior of the farm scientists.

Patra (2011) found that the majority of the farmers opined that time

specific advisories are most important followed by marketing information. The

messages on climatic information and management of disease & pests are

found to be most suitable.

Mukherjee et al. (2012) conducted study in Aligarh district of Utter

Pradesh to find out factors associated with farmer’s membership in Tata Kisan

Sansar and found that education, occupation, social participation, extension

agency contact, economic motivation, innovation proneness and marketing

orientation were positively and significantly correlated with dependent variable

farmers' membership in Tata Kisan.

2.4. To identify the constraints faced by the respondents inutilization of ICTs and provide suggestions to overcome them.

Grigg et al. (1999) reported that lack of adequate training was the

main obstacle in using ICTs.

Tiwari et al. (1999) reported that ‘choupal’ the regional rural telecast

was less successfully disseminating information about the latest farming

technology for viewers.

Rajab and Baqain. (2002) reported that lack of time and availability

of equipment are the two main barriers found in using ICTs.

Maniar (2002) concluded that the respondents need to be motivated to

use ICTs.

Isman and Dabaj. (2004) stated that negative perceptions and attitudes

about ICTs should be eliminated by creating awareness.

Bertolini (2004) reported that most efforts to make ICT available to rural

farmers have sought to improve the availability and quality of information either

indirectly through producer associations, extension workers and the like, or

directly through broadcast radio information, telecentres, and mobile short

~ 14 ~

messaging services (SMS).

Meera et al. (2004) suggested that ICT projects to serve resource poor

farmers require qualified and well-motivated staff to serve as an interface with

computer systems.

Ward and Moule. (2006) inferred from their study that lack of time,

attitudes towards computers and ICT skills affected the use of ICTs.

Bhavnani et al. (2008) found that the main constraints under ICT

programmes are the lack of a policy and regulatory environment and the poor

availability of ICT and mobile infrastructure.

Tintawi and Saleh. (2008) suggested to upgrade the ICT skills of

the respondents regularly through trainings.

Ahmed et al. (2008) indicated time constraints, poor skills and high cost

were the major barriers in using ICTs.

Flaki et al. (2008) reported correlation analysis showed that there was a

significant relationship between the attitude of extension professional towards

ICTs application in agriculture and their educational attainment.

Patil et al. (2008) found that illiteracy, cost and lack of awareness are

the major adoption constraints of ICT programme.

Lohar and Kunvar. (2008) reported that lack of time, lack of net

connection at home and lack of knowledge were the barriers in using ICTs.

Adhiguru et al. (2009) suggested the promotion of farmers-led

extension and strengthening of public extension services to improve coverage

and efficiency of agricultural information delivery systems.

Reddy (2009) found that narrow band width is a basic barrier in the

developing countries to make efficient use of internet.

Gawande et al. (2009) reported that among the problems faced, the

language used in broadcast/ telecast is difficult to understand (47.33%) was a

major constraint, followed by short duration of time for broadcast/ telecast and

programmes on broadcast/ telecast are not repeated (46.66%).

~ 15 ~

Sinha (2009) found that recommended that perceptions of ICTs, as

well as traditional access and usage statistics, continue to be monitored.

Moreover, a systems-oriented approach is recommended when examining the

mutual influence of gender relations and ICTs.

Purnomo and Lee (2010) found that technological and organisational

cultures were seen as the main barriers of ICT programme implementation.

The findings show that they felt that the two demographic variables, regency

and age, must also be considered when ICT programme are implemented.

Das et al. (2011) suggested providing SMS in ICT in addition to voice

mail as it could be stored, followed and shared with fellow farmers.

Jamwal (2011) suggested that agriculture universities would play an

important role in familiarizing farmers with the use of ICT, so that they become

self dependent.

Singh et al. (2011) found that ICTs can be used to increase the

effectiveness and efficiency of extension work and also help the farmers to

utilize such information in solving their problem.

~ 16 ~

MATERIALS AND METHODS

This chapter deals with the method and procedures designed for

planning and conducting the research study. It consists of the following

subheads.

1. Location

2. Research design

3. Sampling technique used

4. Operationalization of variables

5. Source of data collection

6. Method of data collection

7. Statistical analysis of the data

8. Hypotheses

1. Location

The Rewa block is located on the north –east border of Madhya

Pradesh Rewa lies Between 24 “18 and 25”12 North latitude 81”2 and 82”20

East longitudes. Its geographical area is 6287.55 K.M. The district is bounded

on the north and east by the state of Uttar Pradesh, in the south Sidhi District

and in the west with Amarpatan and Raghurajnagar tahsils of Satna District

The District can be divided into the four natural parts: Kamour Plateau,

Vindhyachal plateau, Rewa plateau and lower Northen plain. Hujur tehsil

comes under Kaymore plateau.

2. Research Design

The design of research is the most important and crucial aspect of the

research methodology. It is the entire process of planning and carrying out the

research. To seek the answers for the research question, a descriptive

research design was used in the investigation because it is describing

phenomena with adequate interpretation. It clearly states the characteristics of

the particular situation of group or individuals. In this design the variables are

to be known.

~ 17 ~

3. Sampling technique used

The sample of the present study was selected by proportionate random

sampling method. The various stages of the sample were -

1) Selection of the district

2) Selection of the block

3) Selection of the village

4) Selection of the respondents

1) Selection of the district

The present study was conducted in Rewa district M.P. Rewa District

was selected purposively since presently having the maximum concentration

of mobile phone message users among and low efficiency of existing rural

information delivery system among the region of Rewa.

ATMA supply the mobile phone message on agriculture who

are registration of farmer for the mobile phone message. This study

entirely concerned with the rabi crop like wheat.

2) Selection of the block

The Rewa block of Rewa District was selected purposely since a total

maximum concentration of mobile phone message total number of registered

users as compared to other blocks.

Table-3.1. Distribution of registered users as farmers of mobile phonemessage in the Rewa District.

Source -: ATMA, (Rewa) (2014-15)

S.N. Block Total no of Registered usersas farmers

1. Rewa 2896

2. Raipur 2500

3. Gangev 2000

Total 7396

~ 18 ~

3) Selection of the villages

From Rewa block, the five villages namely Tikar, Sahiiana, Baijnath,

Sumeda and Naikin were selected on the basis of higher number of registered

users of mobile phone message utilized.

4) Selection of the respondents

The mobile phone message users from each selected village were

selected through proportionate random sampling method. Finally the sample

consisted of 120 respondents. The allocation of respondents from each

selected village is shown in the table 3.2.

Table-3.2 Selection of respondents on the basis of highest number ofusers from the villages in Rewa block.

4. Operationalization of variables:

Social scientists hold the view that there exists a gap between theory

and empirical research. The theorists use conceptual variables that are

formulated at high level of abstraction. Most of the social scientists attempt to

solve measurement problems by operationally defining the conceived

variables and then by either using available measures or by designing one's

own measure (Sharma, 1991).

A number of terms and variables have been used in the present study

with specific meaning. Obviously these terms require operationalization.

S.N. Village Name Total no .of registeredusers as farmers

Selection of respondent

1. Tikar 480 29

2. Sahijana 450 28

3. Baijnath 400 24

4. Sumeda 350 21

5. Naikin 300 18

Total 1980 120

~ 19 ~

(A) Independent Variables

1) Age

It refers to actual age of the respondents in complete year, i.e.

chronological age of the respondent. The actual age was recorded as

reported by the respondents at the time of interview. The data obtained were

grouped into following three age groups.

S. N. Categories Weightage

1. Young(upto 35) 1

2. Middle(36-50) 2

3. Old(above 50) 3

2) Caste–

The caste refers to an individual's ritual caste in which he was born.

The respondents were grouped into the following four categories on the basis

of their caste.


1. Schedule Caste 1

2. Schedule Tribe 2

3. Other Backward Caste (O.B.C.) 3

4. General 4

~ 20 ~

3) Education

It refers to the number of classes of the formal education passed

by the respondents. The respondents were grouped into the following

four categories on the basis of their educational level.

S. N. Category Weightage

1. Upto primary 1

2. 6to8 middle 2

3. 9to12 high school 3

4. Graduates and above 4

4) Size of family

It was operationalized as the total number of members in the family

and was categorized into three groups as follows.


1. Small 1

2. Medium 2

3. Large 3

5) Land Holding

The size of land holding refers to total number of hectares of lands

under cultivation possessed by the respondent. For quantitative measurement

of the land holding, the criteria of M.P. Govt. have been followed. It has been

categorized as under.


1. Small 1

2. Medium 2

3. Large 3

~ 21 ~

6) Social participation:

It refers to the degree of extent of involvement of an individual in formal

and informal social organization at village, block or district level. A list of these

organizations was prepared with the help of the village prior to collection of

data. The scores assigned for member and office bearer were 1 and 2

respectively. The degree of involvement and frequency of participation in an

organization was measured with the allotment of scores of membership and

frequency of participation represents the degree of social participation of a

respondent. The respondents were further classified in to the following three

categories on the basis of maximum and minimum scores obtained by them.


1. Low 1

2. Medium 2

3. High 3

7) Farming experience:

It refers to the number of years of experience in agriculture possessed

by farmer. The experience of farmers in completed years at the time of

investigation was considered. It was classified into three categories as

follows.


1. Low 1

2. Medium 2

3. High 3

~ 22 ~

8) Annual income

It refers to the total income of the respondents obtained from farming

and allied occupations. The respondents were classified into three categories

on the basis of the following range of income.


1. Low 1

2. Medium 2

3. High 3

9) Information seeking behavior

It refers to the degree of frequency of contact by an individual with

various information sources. This is the pattern by which a farmer gets his

information either seeking on its own or as a consequence of behavior was

measured with the help of scale developed by Nandapurkar (1982).

In the present study, the degree of frequency of control with information

sources of respondents was measured on three points response category

namely, regular’, ‘occasional’ and ‘never’ For each information source

consulted by the respondent a score of 2, 1, and 0 were assigned,

respectively. The scores were summed up for each respondent and following

three categories were made.

S.N. Categories Weightage

1. Low 1

2. Medium 2

3. High 3

~ 23 ~

10) 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. The variable was measured using schedule

developed for the study. The schedule consisted of six statements and the

respondents were asked to indicate their responses on a three point

continuum viz., regularly, occasionally and never. The scoring pattern adopted

was 3 to regularly, 2 to occasionally and 1 to never.


1. Low 1

2. Medium 2

3. High 3

11) Achievement motivationAchievement motivation was operationalized as a social value that

emphasizes a desire for excellence for an individual to attain a sense of

personal accomplishment.

The variable was measured with the help of scale developed by Rani

(1985) with suitable modifications. The scale consisted of five statements of

which three were negative and the rest were positive. The respondents were

asked to indicate their degree of agreement or disagreement with each

statement on a five point continuum namely strongly agree, agree, undecided,

disagree and strongly disagree. The weightages given to these responses

were 5, 4, 3, 2 and 1 respectively for positive statements and 1, 2, 3, 4 and 5

to negative statements.

S. No. Categories Weightage

1. Low 1

2. Medium 2

3. High 3

~ 24 ~

12) Scientific orientation

It is operationally defined as’ the degree to which respondents was

oriented to use scientific method in agricultural and allied activities for getting

higher return. scientific orientation scale" of Supe and Singh (1969).The

responses were recorded on 5- point continuum as strongly agree, agree,

undecided, disagree and strongly disagree and were given 5 4,3,2 and 1

scores, respectively. The total scores indicated the degree of scientific

orientation an individual. On the basis of maximum and minimum obtained

scores, the respondents were categorized as below.

S. No. Categories Weightage

1. Low 1

2. Medium 2

3. High 3

13) InnovativenessInnovativeness was operationalized as the degree to which an

individual adopted new ideas relatively earlier than others in his social system.

The variable was measured using schedule developed for the study. The

schedule consisted of seven statements of which one was negative and the

rest were positive. The respondents were asked to indicate their degree of

agreement or disagreement with each statement on a five point continuum

namely strongly agrees, agree, undecided, disagree and strongly disagree.

The scores given to these responses were 5, 4, 3, 2 and 1

respectively for positive statements and 1, 2, 3, 4 and 5 for negative

statements.


1. Low 1

2. Medium 2

3. High 3

~ 25 ~

(B) Dependent variable

1. Extent of Use of ICTs in selected crop by the respondents

The Utilization refers to the process of perceiving the usefulness of

external objects, events and information by means of senses. In the present

study utilization of the farmers regarding ICT programmes namely Mobile

Phone message was assessed. A comprehensive scale was developed with

the help of extensionists working at various levels and ICT experts to quantify

the utilization of the farmers in relation to messages delivered to their mobile

phone through expert mobile phone messages under ICT. The four point’s

continuum scale now this aspects have been measured in four scales that is

high, medium, low and not absolutely this was only way to assess different

levels of perception of the respondents for such aspects like growth in

message provide the different information about wheat production, level of

wheat production increasing due to information of message, quality of wheat

increasing due to information of message and message provide the

information to protect the wheat from infestation of insect and pest.

Another part of this special information has been measured on the

basis of stabilized scales with fifteen statement in 5 point continuum scales

absolutely correct, partially correct, undecided, partially wrong and absolutely

wrong in respect to each items these has been given statements on

technologies of wheat such as land preparation of sowing of wheat, method of

sowing, right time of seed sowing of wheat, actual quantity of seed sowing of

wheat, seed treatment, depth of seed sowing of wheat , use of improved

variety of seed , right time of irrigation in wheat field, weed control in wheat

field, use of manure in wheat field, use of fertilizer in wheat field, information

related to insect and disease control in wheat crop, insurance scheme is

related to wheat crop, information related to loan for wheat production ,

information related to available selling rate of wheat in market were scored 5,

4, 3, 2 and 1 respectively.

In this study constraints and suggestion are measuring in percentage.

~ 26 ~

Response from each respondent against each item was recorded.

Total utilization scores of respondent for each component was calculated by

adding scores together obtained by her against all items. This score was

converted in to utilization index by using the following formula as

Score obtained by the respondentUtilization index = ------------------------------------------------------- x 100

Maximum obtainable score

On the basis of maximum and minimum scores obtained by the

respondents they were categorized in to following three categories:-


1. Low 1

2. Medium 2

3. High 3

Validity and reliability of data:

Validity refers to whether the data collection instruments measures

what it is supposed to measure.

Validity of the interview schedule for this study was maximized by

taking the following steps:

i. The interview schedule was thoroughly discussed with the members of

the advisory committee and scientists and their suggestions were

incorporated.

ii. Pre-testing of the interview schedule provided an additional check for

improving the instrument.

iii. The relevance of each question in terms of the objectives was used

carefully.The reliability of an interview schedule refers to its

consistency. It was observed properly that the interview schedule had

reliability before it was used as a data collection instrument.

~ 27 ~

5. Sources of data collection

The following sources were used for the purpose of data collection.

(i) Primary data

The researcher collected the primary data personally by interviewing

the selected respondents with the help of structured and pre-tested interviews

schedule.

(ii) Secondary data

The secondary data were obtained from the various government offices

and publications.

6. Method of data collection

An interview schedule was designed for collecting the relevant

information of selected variables. The data were collected personally with the

help of pre tested interview schedule on dairy farming. The researcher

personally contacted the respondents. They were assured that the information

given by them would be kept confidential and it would only be used for the

academic purposes.

7. Statistical analysis of data

Data collected were qualitative as well as quantitative. The quantitative

data were interpreted in terms of percentage and qualitative data were

tabulated on the basis of approved categorization method as described

earlier, the following statistical techniques were used in the study.

Chi-square testThe association of different attributes of the respondents with their

performance of dairy enterprise was tested by chi-square test (2). For this

purpose the following formula was used.

Ei

EiiO 22 )(

With d.f. (r - 1) (c - 1)

Where,

Oi = observed frequency

Ei = Expected frequency

~ 28 ~

2

2

NC

= Summation over all differences

r = Number of rows

c= Number of columns

d.f. = Degree of freedom

The extent of association was calculated by using

Pearson’s contingency coefficient ‘C’ formula

Where,2 : Value of chi-square

N: total number of observation

C: Co-efficient of association

For practical explanation of the extent of association, the

contingency co-efficient of association values were interpreted as -

i) To 0.20 (negligible association)

ii) 0.21 to 0.40 (fair association)

iii) 0.41 to 0.60 (good association)

iv) Above 0.60 (excellent association)

Correlation Analysis:The relationship of selected independent variables with dependent

variable will be ascertained with the help of person`s product moment

correlation coefficient. The value of correlation coefficient will be worked out

by using the following formula.

)()((

).(

yVxV

YXCOVrxy

Where,

rxy = Correlation coefficient between x and y.

COV (X.Y) = Co-variance between x and y

V(x) = Variance of x and V(y) = Variance of y.

~ 29 ~

8. Hypotheses

On the basis of objectives and variables incorporated the study, thefollowing null hypotheses were formulated for the study.

1) There is no association between age of the respondents and their

extent of utilization of ICTs.

2) There is no association between caste of the respondents and their


3) There is no association between education of the respondents and

their extent of utilization of ICTs.

4) There is no association between size of family of the respondents

and their extent of utilization of ICTs.

5) There is no association between land holding of the respondents


6) There is no association between social participation use of the

respondents and their extent of utilization of ICTs.

7) There is no association between farming experience of the


8) There is no association between annual income of the respondents


9) There is no association between information seeking behavior of

the respondents and their extent of utilization of ICTs.

10) There is no association between extension contact of the


11) There is no association between achievement motivation of the


12) There is no association between scientific orientation of the


13) There is no association between innovativeness of the

respondents and their extent of utilization of ICTs .

~ 30 ~

RESULTS

This chapter deals with the analysis and interpretation of the data.

The data were collected from a sample of 120 respondents through a well

structured interview schedule. The data were processed and analyzed in

line with the objectives of the study.

This chapter has been presented under the following sections.1. To study the profile characteristics of the farmers.





4. To identify the constraints faced by the respondents in utilization of

ICTs and provide suggestions to overcome them.


Table 4.1: Distribution of the respondents according to their age.

S. N. Age group Number ofrespondents

Percentage

1. Young(upto35) 41 34.17

2. Middle(36-50) 54 45.00

3. Old(Above50) 25 20.83

Total - 120 100

The data in Table 4.1 exhibit that out of 120 respondents, 45.00

percent belong to Middle age group, 34.17 percent were from young age

groups and only 20.83 percent were from old age group.

~ 31 ~

Table 4.2: Distribution of the respondents according to their caste.

S.N. Caste category Number of respondents Percentage

1. Schedule Caste 23 19.16

2. Schedule Tribe 29 24.17

3. OBC 41 34.17

4. General 27 22.50

Total 120 100

The data of Table 4.2 indicate that out of 120 respondents the

majority i.e. 34.17 percent belonged to OBC category, 24.17 percent were

found to be in schedule tribe category, 22.50 percent belonged to general

category and 19.16 percent were found to be in schedule caste category.

Table 4.3: Distribution of the respondents according to their levelof education.

S. No. Level of education Number ofrespondents

Percentage

1. Primary 21 17.50

2. Middle 29 24.17

3. High School 48 40.00

4. Graduates 22 18.33

Total - 120 100

The data of Table 4.3 indicate that out of 120 respondents, 40.00

percent were found to be in high school education group level, 24.17

percent had middle education level, 18.33 percent were educated up to

graduate’s level and remaining 17.50 percent were primary.

~ 32 ~

Table 4.4: Distribution of the respondents according to their size offamily.

S. N. Size of Family Number ofrespondents

Percentage

1. Small (up to 4 members) 35 29.17

2. Medium (5 to 7 members) 61 50.83

3. Big (Above 7 members) 24 20.00

Total - 120 100

The data of Table 4.4 reveals that out of 120 respondents, 50.83

percent indicate medium size of family, 29.17 percent small size of family,

while only 20.00 percent showed big family.

Table 4.5: Distribution of the respondents according to their landholding.

S. N. Land holding in ha. Number ofrespondents

Percentage

1. Small (up to 1 ha.) 36 30.00

2. Medium(1.1 to 2 ha.) 55 45.83

3. Big (above 2 ha.) 29 24.17

Total 120 100

The data in Table 4.5 depicts that out of the 120 respondents, 45.83

percent indicate medium land holding, 30.00 percent small land holding,

while only 24.17 percent showed big land holding.

~ 33 ~

Table 4.6: Distribution of the respondents according to their socialparticipation.

S.N. Categories Number ofrespondents

Percentage

1. Low(8- 15) 33 27.50

2. Medium(16-23) 56 46.67

3. High (above 23) 31 25.83

Total 120 100

The data in Table 4.6 depict that out of the 120 respondents the

majority i.e. 46.67 percent had medium social participation, 27.50 percent

had low social participation, while only 25.83 percent had high social

participation.

Table 4.7: Distribution of the respondents according to their farmingexperience.

S. N. farming experience Number ofrespondents

Percentage

1. Low (up to 5 years) 30 25.00

2. Medium (6-10 years) 58 48.33

3. High (Above 10 years) 32 26.67

Total 120 100

The data of Table 4.7 indicate that out of 120 respondents, 48.33

percent possessed medium farming experience, 26.67 percent high farming

experience and remaining 25.00 percent indicate low farming experience.

~ 34 ~

Table 4.8: Distribution of the respondents according to their annualincome.

S. No. Annual income Number ofrespondents

Percentage

1. Low (up to 50,000Rs.) 59 49.17

2. Medium (50,001 to 75,000Rs.) 35 29.17

3. High (Above 75,000Rs.) 26 21.66

Total 120 100

The data of Table 4.8 indicate that out of 120 respondents the majority

i.e. 49.17 percent showed low annual income, 29.17 percent medium

annual income and remaining 21.66 percent indicate high annual income.

Table 4.9: Distribution of the respondents according to theirinformation seeking behavior.

S. No. Information seekingbehavior

Number ofrespondents

Percentage

1. Low (up to 6 score) 28 23.33

2. Medium (7 to10 ) 36 30.00

3. High (Above 10scores) 56 46.67

Total 120 100

The data in the Table 4.9 show that out of 120 respondents, 46.67

percent indicate high information seeking behavior, 30.00 percent showed

medium information seeking behavior while 23.33 percent indicate low

information seeking behavior.

~ 35 ~

Table 4.10: Distribution of the respondents according to theirextension contact.

S. N. Extension contact Number ofrespondents

Percentage

1. Low (8- 10) 32 26.66

2. Medium (11-13) 53 44.17

3. High (above 13) 35 29.17

Total 120 100

The data of Table 4.10 indicate that out of 120 respondents the 44.17

percent indicate medium extension contact, 29.17 percent high extension

contact and remaining 26.66 percent showed low extension contact.

Table 4.11: Distribution of the respondents according to theirachievement motivation.

S. No. Achievementmotivation

Number ofrespondents

Percentage

1. Low (9-13) 34 28.33

2. Medium (14-15) 51 42.50

3. High (above 15) 35 29.17

Total 120 100

Table 4.11 indicates that 42.50 percent respondents indicate

medium achievement motivation, 29.17 percent high achievement

motivation while only 28.33 percent showed low achievement motivation.

~ 36 ~

Table 4.12: Distribution of the respondents according to theirscientific orientation.

S. No. Scientific orientation Number ofrespondents

Percentage

1. Low (up to 18 score) 52 43.33

2. Medium (19 to 21) 37 30.84

3. High (Above 21 Scores) 31 25.83

Total 120 100

The data in the Table 4.12 revealed that out of 120 respondents, 43.33

percent indicate low scientific orientation, 30.84 percent medium scientific

orientation while only 25.83 percent showed high scientific orientation.

Table 4.13: Distribution of the respondents according to theirinnovativeness.

S. No. Innovativeness Number ofrespondents

Percentage

1. Low (11-18) 59 49.17

2. Medium (19-26) 34 28.33

3. High (about 26) 27 22.50

Total 120 100

The data in the Table 4.13 show that out of 120 respondents, 49.17

percent were low innovativeness, 28.88 percent medium innovativeness

while 22.50 percent were in high innovativeness.

~ 37 ~

2. To assess the extent of utilization of Information andCommunication Technologies (ICTs).

(A)Utilization of messages on different aspects by the respondentsobtained through mobile phone message .

Different kind of messages concerning to different aspects have

been delivered to the respondents through mobile phone message. The

utilization of messages of each aspect have been presented in the Table

4.14.

Table 4.14 Utilization of messages on different aspects by therespondents obtained through mobile phone message.

S.N. Messages of differentaspect & wheat

information

TotalUtilization

score

Utilizationindex

%

Rank

1. Message provide the

different information

about wheat production

390 81.25 I

2. Level of wheat

production increasing

due to information of

message

260 54.16 III

3. Quality of wheat

increasing due to

information of message

220 45.83 IV

4. Message provide the

information to protect

the wheat from

infestation of insect

and pest

310 64.58 II

~ 38 ~

The data in the Table 4.14 indicate the utilization of the messages of

different aspects by the respondents namely message provide the different

information about wheat production, Level of wheat production increasing

due to information of message, Quality of wheat increasing due to

information of message and message provide the information to protect the

wheat from infestation of insect and pest. It was observed that utilization of

messages of the aspect message provide the different information about

wheat production was found to be maximum as indicating the utilization

index- 81.25% followed by message provide the information to protect the

wheat from infestation of insect and pest (utilization index- 64.58%), level

of wheat production is increased due to information of message (utilization

index- 54.16%) and quality of wheat is increased due to information of

message (utilization index- 45.83%).

(B)The utilization in respect the different fields of Mobile phonemessage on production technology of wheat.

The utilization in respect the different fields of mobile phone

message namely land preparation of sowing of wheat, method of sowing,

right time of seed sowing of wheat, actual quantity of seed sowing of

wheat, seed treatment , depth of seed sowing of wheat , use of improved

variety of seed , right time of irrigation in wheat field, weed control in wheat

field, use of manure in wheat field, use of fertilizer in wheat field,

information related to insect and disease control in wheat crop, insurance

scheme is related to wheat crop, information related to loan for wheat

production , information related to available selling rate of wheat in market

etc have also been assessed in the present study and presented in the

Table 4.15.

~ 39 ~

Table 4.15: The utilization in respect the different fields of mobilephone massage on production technology of wheat.

S.N.

Different field of productiontechnology of wheat

TotalUtilization

score

Utilizationindex

%

Rank

1. Land preparation of sowing of wheat 509 84.33 II

2. Method of sowing 494 82.33 IV

3. Right time of seed sowing of wheat 514 85.66 I

4. Actual quantity of seed sowing ofwheat

502 83.66 III

5. Seed treatment 480 80.00 VI

6. Depth of seed sowing of wheat 440 73.33 X

7. Use of improved variety of seed 477 79.50 VII

8. Right time of irrigation in wheat field 436 72.66 XI

9. Weed control in wheat field 488 81.33 V

10. Use of manure in wheat field 428 71.33 XII

11. Use of fertilizer in wheat field 443 73.83 IX

12. Information related to insect anddisease control in wheat crop

470 78.33 VIII

13. Insurance scheme is related towheat crop

394 65.66 XIII

14. Information related to loan for wheatproduction

333 55.50 XV

15. Information related to availableselling rate of wheat in market

375 62.50 XIV

~ 40 ~

The data in ten Table 4.15 indicate that utilization index of different

fields of the programme as perceived by the respondents. It was found that

the field right time of seed sowing of wheat had the highest utilization index

(85.66%), followed by land preparation of sowing of wheat (utilization index-

84.33%), actual quantity of seed sowing of wheat (utilization index-

83.66%), method of sowing (utilization index- 82.33%), weed control in

wheat field (utilization index- 81.33%), seed treatment (utilization index-

80.00%), use of improved variety of seed (utilization index- 79.50%),

information related to insect and disease control in wheat crop (utilization

index- 78.33%), use of fertilizer in wheat field (utilization index- 73.83%),

depth of seed sowing of wheat (utilization index- 73.33%), right time of

irrigation in wheat field (utilization index- 72.66%), use of manure in wheat

field (utilization index- 71.33%), insurance scheme is related to wheat crop

(utilization index- 65.66%), information related to available selling rate of

wheat in market (utilization index- 62.50%), and information related to loan

for wheat production (utilization index- 55.50%).

Table 4.16 Distribution of the respondents according to their extent ofutilization of ICTs.

S. No. Category Number ofrespondents

Percentage

1. Low 26 21.67

2. Medium 52 43.33

3. High 42 35.00

Total 120 100

Table 4.16 Indicates that the majority of the respondents i.e. 43.33

percent indicate medium extent of utilization of ICTs. followed by 35.00

percent high extent of utilization of ICTs. It is evident from the data that

21.67 percent respondents showed low extent of utilization of ICTs.

.

~ 41 ~

3. To study the relationship between profile characteristics andextent of utilization of ICTs.

Table 4.17: Association between age of the respondents and extentof utilization of ICTs.

Age

Extent of utilization of ICTs.Total

Low Medium High

No. % No. % No. % No. %

Young 12 29.28 16 39.02 13 31.70 41 34.17

Middle 8 14.81 28 51.86 18 33.33 54 45.00

Old 6 24.00 8 32.00 11 44.00 25 20.83

Total 26 52 42 120 100

2 = 4.89 non significant at 5% level with 4 d.f.

Table 4.17 shows that out of 41 respondents who were from young

age group, 39.02 percent showed medium extent of utilization of ICTs,

31.70 percent high extent of utilization of ICTs and only 29.28 percent

indicated low extent of utilization of ICTs.

Out of 54 respondents from the middle age group, 51.86 percent

indicated medium extent of utilization of ICTs, 33.33 percent high extent of

utilization of ICTs where as only 14.81 low extent of utilization of ICTs.

Similarly, out of 25 respondents from the old age group, 44.00

percent showed high extent of utilization of ICTs, 32.00 percent medium

extent of utilization of ICTs whereas only 24.00 percent indicated low extent

of utilization of ICTs.

When the 2 test was applied to the data the calculated 2 value 4.89

was found to be non significant at 4 d.f. and 5% level of non significance.

Hence, the null hypothesis was accepted and it could be concluded

that there was no significant association between age and extent of


~ 42 ~

Table 4.18: Association between caste of the respondents andextent of utilization of ICT.

Caste

Extent of utilization of ICTsTotal

Low Medium High

No. % No. % No. % No. %

Schedule

Caste

8 34.78 10 43.49 5 21.73 23 19.16

Schedule

Tribe

7 24.13 13 44.84 9 31.03 29 24.17

O.B.C. 6 14.63 19 46.35 16 39.02 41 34.17

General 5 18.52 10 37.04 12 44.44 27 22.5

Total 26 52 42 120 100

2 = 6.06, non significant at 5% level with 6 d.f.

Table 4.18 shows that out of 23 respondents who belonged to

schedule caste category, the majority i.e. 43.49 percent had medium extent

of utilization of ICTs, 34.78 percent had low extent of utilization of ICTs and

only 21.73 percent showed high extent of utilization of ICTs.

Out of 29 respondents belonging to the schedule tribe category, the

majority i.e. 44.84 percent had medium extent of utilization of ICTs, 31.03

percent had high extent of utilization of ICTs whereas only 24.13 percent

had low extent of utilization of ICTs.

As regards 41 respondents who belonged to OBC caste, the majority

i.e. 46.35 percent had medium extent of utilization of ICTs, 39.02 percent

had high extent of utilization of ICTs where as only 14.63 had low extent of


Out of 27 respondents who belonged to general caste category, the

majority i.e. 44.44 percent had high extent of utilization of ICTs, 37.04

~ 43 ~

percent had medium extent of utilization of ICTs where as only 18.52 had

low extent of utilization of ICTs.


was found to be non significant at 6 d.f. and 5 percent level.

Hence the null hypothesis may be accepted and it could be

concluded that there was non-significant association between caste and


Table 4.19: Association between education of the respondents andextent of utilization of ICTs.

Education


Low Medium High

No. % No. % No. % No. %

Primary 8 38.09 6 28.58 7 33.33 21 17.50

Middle 7 24.13 12 41.38 10 34.49 29 24.17

High School 6 12.5 28 58.33 14 29.17 48 40.00

Graduates 5 22.73 6 27.27 11 50.00 22 18.33

Total 26 52 42 120 100

2 = 11.32, significant at 5% level with 6 d.f.

Table 4.19 shows that out of 21 respondents who were from primary

education category, 38.09 percent showed low extent of utilization of ICTs,

33.33 percent high extent of utilization of ICTs, and only 28.58 percent

indicated medium extent of utilization of ICTs.

Out of 29 respondents from the middle education category, 41.38

percent indicated medium extent of utilization of ICTs, 34.49 percent

showed high extent of utilization of ICTs whereas 24.13 percent showed


Similarly, out of 48 respondents educated had high school, 58.33


showed high extent of utilization of ICTs and only 12.50 percent showed


~ 44 ~

Out of 22 respondents educated up to the graduate’s education, 50.00

percent showed high extent of utilization of ICTs, 27.27 percent indicated

medium extent of utilization of ICTs and only 22.73 percent had low extent


When the 2 test was applied to the data the calculated 2 value

11.32 was found to be significant at 6 d.f. and 5% level of significance.

Hence, the null hypothesis was rejected. The value of coefficient of

association 0.29 also indicates a fair association between education and


Table 4.20: Association between size of family of the respondentsand extent of utilization of ICTs.

Sizeof family


Low Medium High

No. % No. % No. % No. %

Small 9 25.71 19 54.29 7 20.00 35 29.17

Medium 12 19.68 25 40.98 24 39.34 61 50.83

Big 6 20.83 8 33.33 11 45.84 24 20.00

Total 26 52 42 120 100


Table 4.20 depicts that out of 35 respondents who had small size of

family, 54.29 percent showed medium extent of utilization of ICTs, 25.71

percent low extent of utilization of ICTs, and 20.00 percent indicated high


Out of 61 respondents who had medium size of family, 40.98 percent

indicated medium extent of utilization of ICTs, 39.34 percent showed high

extent of utilization of ICTs whereas 19.68 percent showed low extent of


As regards 24 respondents who had big size of family, 45.84 percent

showed high extent of utilization of ICTs, 33.33 percent showed medium

extent of utilization of ICTs whereas 20.83 percent indicated low extent of


~ 45 ~


was found to be non significant at 4 d.f. and 5% level of significance.

Hence, the null hypothesis may be accepted and it could be

concluded that there was no significant association between size of family

and extent of utilization of ICTs.

Table 4.21: Association between land holding of the respondents andextent of utilization of ICTs .

Landholding


Low Medium HighNo. % No. % No. % No. %

Small 11 30.55 13 36.12 12 33.33 36 30.00

Medium 10 18.18 31 56.36 14 25.46 55 45.83

Big 5 17.24 8 27.59 16 55.17 29 24.17

Total 26 52 42 120 100


Table 4.21 depicts that out of 36 respondents who had small land

holding, 36.12 percent showed medium extent of utilization of ICTs, 33.33

percent high extent of utilization of ICTs, and only 30.55 percent indicated

high extent of utilization of ICTs.

Out of 55 respondents who had medium land holding, 56.36 percent

showed medium extent of utilization of ICTs, 25.46 percent indicated high

extent of utilization of ICTs whereas 18.18 percent showed low extent of


As regards 29 respondents who had big land holding, 55.17 percent

indicated high extent of utilization of ICTs, 27.59 percent showed medium

extent of utilization of ICTs whereas only 17.24 percent showed low extent




~ 46 ~

Hence the null hypothesis may be rejected. The value of coefficient

of association 0.28 indicates a fair association between land holding and


Table 4.22: Association between social participation of therespondents and extent of utilization of ICT.

Socialparticipation


Low Medium High

No. % No. % No. % No. %

Low 9 27.28 14 42.42 10 30.30 33 27.5

Medium 12 21.42 26 46.43 18 32.14 56 46.67

High 5 16.13 12 38.70 14 45.17 31 25.83

Total 26 52 42 120 100


In the present study data from table 4.22 show that out of 33

respondents who had low social participation 42.42 percent showed

medium extent of utilization of ICTs, 30.30 percent high extent of utilization

of ICTs whereas only 27.28 percent indicated low extent of utilization of

ICTs.

Out of 56 respondents who had medium social participation, 46.43

percent showed medium extent of utilization of ICTs, 32.14 percent showed

high extent of utilization of ICTs whereas only 21.42 percent indicated low


Similarly out of 31 respondents who had high , 45.17 percent

indicated high extent of utilization of ICTs, 38.70 percent showed medium

extent of utilization of ICTs whereas only 16.13 percent showed low extent



was found to be non significant at 4 d.f. and 5% level of non significance.

Hence, the null hypothesis was accepted and it could be concluded

that there was no significant association between social participation and


~ 47 ~

Table 4.23: Association between farming experience of therespondents and extent of utilization of ICT.

Farmingexperience


Low Medium High

No. % No. % No. % No. %

Low 11 36.67 9 30.00 10 33.33 30 25.00

Medium 10 17.24 33 56.89 15 25.87 58 48.33

High 5 15.62 10 31.26 17 53.12 32 26.67

Total 26 52 42 120 100


The data of Table 4.23 show that out of 30 respondents who had low

farming experience, 36.67 percent showed low extent of utilization of ICTs,

33.33 percent high extent of utilization of ICTs, whereas only 30.00 percent

indicated medium extent of utilization of ICTs.

Out of 58 respondents who had medium farming experience, 56.89

percent showed medium extent of utilization of ICTs, 25.87 percent high

indicated extent of utilization of ICTs whereas 17.24 percent showed low


In case of 32 respondents who had high dairy experience, 53.12

percent indicated high extent of utilization of ICTs, 31.26 percent showed

medium extent of utilization of ICTs whereas only 15.62 percent showed




Hence, the null hypothesis may be rejected. The value of coefficient

of association 0.31 indicates a fair association between farming experience


~ 48 ~

Table 4.24: Association between annual income of the respondentsand extent of utilization of ICT.

AnnualIncome


Low Medium High

No. % No. % No. % No. %

Low 14 23.73 31 52.54 14 23.73 59 49.17

Medium 7 20.00 15 42.86 13 37.14 35 29.17

High 5 15.39 6 26.92 15 57.69 26 21.66

Total 26 52 42 120 100


The data of Table 4.24 shows that out of 59 respondents who had

low annual income, 52.54 percent showed medium extent of utilization of

ICTs, 23.73 percent high extent of utilization of ICTs, whereas only 23.73

percent indicated low extent of utilization of ICTs.

Out of 35 respondents who had medium annual income, 42.86

percent indicated medium extent of utilization of ICTs. 37.14 percent



In case of 26 respondents who had high annual income, 57.69





was found to be significant at 4 d.f. and 5% level of significance.


of association 0.27 indicates a fair association between annual income and


~ 49 ~

Table 4.25: Association between information seeking behavior of therespondents and extent of utilization of ICT.

Information seekingbehavior


Low Medium High

No. % No. % No. % No. %

Low 13 46.43 9 32.15 6 21.42 28 23.33

Medium 6 16.66 19 52.78 11 30.56 36 30.00

High 7 12.50 24 42.86 25 44.64 56 46.67

Total 26 52 42 120 100

2 = 15.2 significant at 5% level with 4 d.f.

Table 4.25 reveals that out of 28 respondents, who had low

information seeking behavior, 46.43 percent showed low extent of utilization

of ICTs, 32.15 percent medium extent of utilization of ICTs, and 21.42

percent indicated high extent of utilization of ICTs.

Out of 36 respondents who had medium information seeking

behavior, 52.78 percent indicated medium extent of utilization of ICTs,

30.56 percent showed high extent of utilization of ICTs whereas 16.66

percent indicated low extent of utilization of ICTs.

Out of 56 respondents who had high information seeking behavior,

44.64 percent showed high extent of utilization of ICTs, 42.86 percent

showed medium extent of utilization of ICTs whereas only 12.50 percent



was found to be significant at 4 d.f. and 5% level of significance.


of association 0.33 indicates a fair association between information seeking

behavior and extent of utilization of ICTs.

~ 50 ~

Table 4.26: Association between extension contact the respondentsand extent of utilization of ICT.

Extension contact


Low Medium High

No. % No. % No. % No. %

Low 12 37.50 10 31.25 10 31.25 32 26.66

Medium 9 16.98 33 62.27 11 20.75 53 44.17

High 5 14.29 9 25.71 21 60.00 35 29.17

Total 26 52 42 120 100


Table 4.26 show that out of 32 respondents who had low extension

contact, 37.50 percent showed low extent of utilization of ICTs, 31.25

percent medium extent of utilization of ICTs, and only 31.25 percent

indicated high extent of utilization of ICTs.

Out of 53 respondents who had medium extension contact, 62.27




Remaining 35 respondents who had high extension contact, 60.00

percent indicated high extent of utilization of ICTs 25.71 percent showed

medium extent of utilization of ICTs, whereas only 14.29 percent showed





of association 0.39 indicates a fair association between extension contact


~ 51 ~

Table 4.27: Association between achievement motivation of therespondents and extent of utilization of ICT.

Achievementmotivation


Low Medium High

No. % No. % No. % No. %

Low 12 35.29 14 41.18 8 23.53 34 28.33

Medium 9 17.65 27 52.94 15 29.41 51 42.50

High 5 14.28 11 31.44 19 54.28 35 29.17

Total 26 52 42 120 100

2 = 11.89, Significant at 5% level with 4 d.f.

The data from table 4.27 revealed that out of 34 respondents who

had low achievement motivation, 41.18 percent showed medium extent of

utilization of ICTs, 35.29 percent low extent of utilization of ICTs whereas

only 23.53 percent indicated high extent of utilization of ICTs.

Out of 51 respondents who had medium achievement, 52.94




Similarly out of 35 respondents who had high achievement

motivation, 54.28 percent showed high extent of utilization of ICTs, 31.44

percent indicated medium extent of utilization of ICTs whereas only 14.28

percent showed low extent of utilization of ICTs.




of association 0.30 indicates a fair association between achievement

motivation and extent of utilization of ICTs.

~ 52 ~

Table 4.28: Association between scientific orientation of therespondents and extent of utilization of ICT.

Scientificorientation


Low Medium High

No. % No. % No. % No. %

Low 15 28.84 21 40.38 16 30.78 52 43.33

Medium 6 16.22 22 59.46 9 24.32 37 30.84

High 5 16.13 9 29.03 17 54.84 31 25.83

Total 28 51 41 120 100


Table 4.28 shows that out of 52 respondents who had low scientific

orientation, 40.38 percent showed medium extent of utilization of ICTs,

30.78 percent high extent of utilization of ICTs, whereas only 28.84 percent


Out of 37 respondents who had medium scientific orientation, 59.46




In case of 31 respondents who had high scientific orientation, 54.84







of association 0.28 indicates a fair association between scientific orientation


~ 53 ~

Table 4.29: Association between innovativeness of the respondentsand extent of utilization of ICT.

Innovativeness


Low Medium High

No. % No. % No. % No. %

Low 12 20.33 34 57.64 13 22.03 59 49.17

Medium 9 26.47 13 38.24 12 35.29 34 28.33

High 5 18.52 5 18.52 17 62.96 27 22.50

Total 28 51 41 120 100

2 = 16.19 significant at 5% level with 4 d.f.

Table 4.29 shows that out of 59 respondents who had low

innovativeness, 57.64 percent showed medium extent of utilization of ICTs,

22.03 percent high extent of utilization of ICTs whereas only 20.33 percent


Out of 34 respondents who had medium innovativeness, 38.24


high extent of utilization of ICTs whereas only 26.47 percent showed low


In case of 27 respondents who had high innovativeness, 62.96


medium extent of utilization of ICTs whereas 18.52 percent showed low





of association 0.34 indicates a fair association between innovativeness and


~ 54 ~

Summary Sheet

Table- 4.30: Association between profile characteristics of thefarmers and their extent of utilization of ICTs.

S. N. Characteristics 2

Value

d. f. C d.a.

1 Age 4.89NS 4 0.19 Negligible

2 Caste 6.06NS 6 0.21 Negligible

3 Education 11.32* 6 0.29 Fair

4 Size of family 5.37NS 4 0.20 Negligible

5 Land holding 10.93* 4 0.28 Fair

6 Social participation 2.47NS 4 0.14 Negligible

7 Farming experience 13.34* 4 0.31 Fair

8 Annual income 9.84* 4 0.27 Fair

9 Information seeking

behavior

15.2* 4 0.33 Fair

10 Extension contact 21.94* 4 0.39 Fair

11 Achievement

motivation

11.89* 4 0.30 Fair

12 Scientific orientation 10.89* 4 0.28 Fair

13 Innovativeness 16.19* 4 0.34 Fair

Significant at 5% level with 4 d.f & 6 d.f.

~ 55 ~

Table 4.31: Correlations between profile characteristics of thefarmers and their extent of utilization of ICTs .

S. No. Characteristics Co-relation coefficient

1. Age -0.11

2. Caste -0.13

3. Education 0.27*

4. Size of family -0.12

5. Land holding 0.25*

6. Social participation -0.09

7. Farming experience 0.29*

8. Annual income 0.23*

9. Information seeking behavior 0.30*

10. Extension contact 0.34*

11. Achievement motivation 0.28*

12. Scientific orientation 0.24*

13. Innovativeness 0.32*

*Significant at 5% level of probability

Table 4.31 depicts the co-relation coefficient values indicating the

relationship of profile characteristics of the farmers and their extent of

utilization of ICTs .The data indicate that the characteristics of the

respondents namely education, land holding, farming experience, annual

income, information seeking behavior, extension contact, achievement

motivation, scientific orientation and innovativeness had significant

relationship with extent of utilization of ICTs of respondents at 0.05 level of

probability. The result also depict that the characteristics namely age,

caste, size of family and social participation had no relationship with extent

of utilization of ICTs of respondents.

~ 56 ~

4. (A) Constraints faced by the respondents in utilization of ICTs.The respondents were asked to express the constraints faced by the

farmers in using mobile phone message techniques. The major problems

faced by them have been presented in Table 4.32

Table 4.32: Constraints faced by the respondents in utilization ofICTs.

S.N. Constraints No. of

Respondents

% Rank

1. Problems related to network

of cell phone

76 63.33 II

2. Problems related to content of

message

67 55.83 IV

3. Lack of information about

availability of resources /

inputs

65 54.17 V

4. Untimely delivery of message 56 46.67 VIII

5. Problems related to language 73 60.83 III

6. Non- availability of KMS

related literature

51 42.50 X

7. Lack of extension activities 61 50.83 VII

8. Use of complex words 79 65.83 I

9. Short duration supply or

insufficient availability of

electricity

62 51.67 VI

10. Application of message in

fields are too much expensive

52 43.33 IX

~ 57 ~

The major constraints experienced by the respondents were

arranged in descending order on the basis of rank order as use of complex

words (65.83%), problems related to network of cell phone (63.33%),

problems related to language (60.83%), problems related to content of

message (55.83%), lack of information about availability of resources /

inputs (54.17%), short duration supply or insufficient availability of electricity

(51.67%), lack of extension activities (50.83%), untimely delivery of

message (46.67%), application of message in fields are too much

expensive (43.33%). non- availability of mobile phone message related

literature (42.50%),

4. (B) Provide suggestions to the respondent in utilization of ICTs.

The farmers were asked to offer suggestions for enhancing its utility

and applicability for agricultural and allied technology through Mobile phone

message. Out of many suggestions offered by them the important

suggestions surfaced have been presented in the Table 4.33

Table 4.33: Provide suggestions to the respondent in utilization ofICTs.

S.N. Suggestions No. ofRespondents

% Rank

1. Use of local & familiar words in

messages

73 60.83 II

2. Local needs & preference for

the messages should be

considered

85 70.83 I

3. Economics of techniques

delivered through message

should be highlighted

62 51.66 III

4. Qualified & well – motivated

staff to serve as an interface

51 42.50 VI

5. Location specific research &

data based information should

be provided

41 34.17 VIII

~ 58 ~

S.N. Suggestions No. ofRespondents

% Rank

6. Information regarding

resources/ inputs availability

should also be provided

43 35.83 VII

7. To improve coverage

&efficiency of agricultural

information delivery systems

59 49.16 IV

8. Mobile short messaging

services(SMS)

56 46.66 V

The important suggestions offered by the respondent for enhancing their

profitability for mobile phone message have been arranged in descending

order on the rank basis as local needs & preference for the messages

should be considered (70.83%), use of local & familiar words in messages

(60.83%), economics of techniques delivered through message should be

highlighted (51.66%), to improve coverage & efficiency of agricultural

information delivery systems (49.16%), mobile short messaging services

(SMS) (46.66%), qualified & well – motivated staff to serve as an interface

(42.50%), information regarding resources/ inputs availability should also

be provided (35.83%), location specific research & data based information

should be provided (34.17%), providing SMS in mobile in addition to voice

mail as it could be stored, followed & shared with fellow farmers (33.33%),

farmers–led extension & strengthening of public extension services

(31.66%).

~ 59 ~

DISCUSSION

The main findings of the study have been presented in line with the

objectives of the study. The details of the main findings are as under.

(A)To study the profile characteristics of the farmers

1. Out of 120 respondents i.e. 45.00 percent of the respondents were

from middle age group .This finding is in line with the findings of

Singh (2003) and Shaik (2008).

2. About 34.17 percent of the respondents were engaged in OBC

category.

3. More than one third of the total respondents i.e. 40.00 percent

were educated up to high education level category. The finding of

Sen (2008) is similar to the present finding.

4. More than 50 percent of the farmers i.e. 50.83 percent

respondents had medium size of family. Similar result was

reported by Oluwatayo (2011).

5. Out of 120 respondents i.e. 45.83 percent respondents had

medium land holding. Similar result was reported by Kanal (2005).

6. Among the total respondents i.e.46.67 percent were having

medium social participation.

7. Among the total respondents i.e. 48.33 percent were medium in

farming experience. Similar result was reported by Natikar (2001).

8. Less than 50respondents i.e. 49.17 percent were from low annual

income. Similar result was reported by Kumar et.al. (2011) and

Sunil kumar (2004).

9. Out of total respondents i.e. 46.67 percent respondents had high

information seeking behavior. This finding is in line with the

Krishnan (1997) and Vijay kumar (2001).

10.About 44.17 percent of the respondents were indicate medium

extension contact.

~ 60 ~

11.Less than 50 percent respondents i.e. 42.50 percent of the total

indicate medium level of achievement motivation.

12.About 43.33 percent respondents showed low level of scientific

orientation. Similar result was reported by Ram (2005).

13.Among the total respondents i.e. 49.17 percent indicate low level

of innovativeness.

(B)Utilization of mobile phone message in respect the different field bythe respondents.

1- It was observed that utilization of messages of the aspects by the

respondents namely message provide the different information about wheat

production, level of wheat production increasing due to information of

message, quality of wheat increasing due to information of message and

message provide the information to protect the wheat from infestation of insect

and pest. It was observed that utilization of messages of the aspect message

provide the different information about wheat production was found to be

maximum as indicating the utilization index- 81.25% followed by message

provide the information to protect the wheat from infestation of insect and pest

(utilization index- 64.58%), level of wheat production is increased due to

information of message (utilization index- 54.16%) and quality of wheat is

increased due to information of message (utilization index- 45.83%).

This finding gets the support from the work of Dix singh et al. (2013) and

Rita (2009).

2- It was found that the field right time of seed sowing of wheat had the

highest utilization index (85.66%), followed by land preparation of sowing of

wheat (utilization index- 84.33%), actual quantity of seed sowing of wheat

(utilization index- 83.66%), method of sowing (utilization index- 82.33%), weed

control in wheat field (utilization index- 81.33%), seed treatment (utilization

index- 80.00%), use of improved variety of seed (utilization index- 79.50%),

information related to insect and disease control in wheat crop (utilization

index- 78.33%), use of fertilizer in wheat field (utilization index- 73.83%), depth

of seed sowing of wheat (utilization index- 73.33%), right time of irrigation in

wheat field (utilization index- 72.66%), use of manure in wheat field (utilization

~ 61 ~

index- 71.33%), insurance scheme is related to wheat crop (utilization index-

65.66%), information related to available selling rate of wheat in market

(utilization index- 62.50%), and information related to loan for wheat production

(utilization index- 55.50%).

This finding gets the support from the work of Banmeke et al. (2008) and

Narasimha & pushpa (2009).

3- Out of 120 respondents i.e. 43.33 percent indicate medium extent of

utilization of ICTs. Followed by 35.00 percent high extent of utilization of ICTs.

It is evident from the data that 21.67 percent respondents showed low extent of


(C) (a) The Association between profile characteristics of the farmersand their extent of utilization of ICTs.

It was found that the association between profile characteristics of

the farmers and their extent of utilization of ICTs. These are characteristics of

the respondents namely education, land holding, farming experience, annual

income, information seeking behavior, extension contact, achievement

motivation, scientific orientation and innovativeness had significant relationship

with extent of utilization of ICTs of respondents at 0.05 level with 4d.f.& 6d.f.

The result also depict that the characteristics namely age, caste, size of family

and social participation had no significant with extent of utilization of ICTs of

respondents.

This finding gets the support from the work of Meena Bigai (2001) and

Chouhan (2009).

(b) Correlations between profile characteristics of the farmers andtheir extent of utilization of ICTs.

The study indicated that the characteristics of the respondents namely

education, land holding, farming experience, annual income, information

seeking behavior, extension contact, achievement motivation, scientific

orientation and innovativeness had significant relationship with extent of

utilization of ICTs of respondents at 0.05 level of probability. The result also

depict that the characteristics namely age, caste , social participation and size

of family had no relationship with extent of utilization of ICTs of respondents.

~ 62 ~

(D) Constraints faced by the respondents in utilization of ICTs.Constraints experienced by the respondents as arranged in descending

order on the basis of rank order as use of complex words (65.83%) problems

related to network of cell phone (63.33%), problems related to language

(60.83%), problems related to content of message (55.83%), lack of information

about availability of resources / inputs (54.17%), short duration supply or

insufficient availability of electricity (51.67%), lack of extension activities

(50.83%), untimely delivery of message (46.67%), application of message in

fields are too much expensive (43.33%). Non- availability of mobile phone

message related literature (42.50%).

This finding gets the support from the work of Patil et al. (2008) ,Lohar

&Kunvar (2008) and Gawande et al. (2009).

(E) Provide suggestions to the respondent in utilization of ICTs.

Suggestions offered by the respondent for enhancing their profitability

for mobile phone message have been arranged in descending order on the

rank basis as local needs & preference for the messages should be considered

(70.83%), use of local & familiar words in messages (60.83%), economics of

techniques delivered through message should be highlighted (51.66%), to

improve coverage & efficiency of agricultural information delivery systems

(49.16%), mobile short messaging services (SMS) (46.66%), qualified & well –

motivated staff to serve as an interface (42.50%), information regarding

resources/ inputs availability should also be provided (35.83%), location

specific research & data based information should be provided (34.17%),

providing SMS in mobile in addition to voice mail as it could be stored, followed

& shared with fellow farmers (33.33%), farmers–led extension & strengthening

of public extension services (31.66%).

This finding gets the support from the work of Adhiguru et al. (2009) and

Das et al. (2011).

~ 63 ~

SUMMARY, CONCLUSIONS & SUGGESTIONS FOR FUTUREWORK

6.1 SUMMARY

Information Communication Technologies (ICT) are widely found as

important resources for socio- economic development. Information technologies

(IT) has been described as the acquisition, processing, storage and

dissemination of vocal, pictorial, textual and numeric information by a micro

electronics based to a combination of computers and telecommunication. In the

past few years, the usefulness of Information Communication Technologies

(ICTS) especially, Internet and cell phone has been felt in agriculture sector to

bridge the gap between scientific recommendation and its application by the

farmers.

mobile phone message has been considered as such a communication

approach by which short message services is being provided by the SMS

through ATMA. Madhya Pradesh has population of about 7 crores, out of which

90 lakhs are mobile phone user . Main features of mobile phone message are

multi language support (16 language), long SMS facility (160 characters) and

sending of 2 SMS in a week based on urgent local needs covering all important

field like crop production, horticulture, plant protection & animal science, etc.

This service is one such initiative of ICT which provides location-

specific and crop-specific farm advisory services and facilities to the farming

community in a particular area. It was launched 2007 by J.N.K.V.V.in

Chhindwara District of Madhya Pradesh and was extended in different districts by

J.N.K.V.V. Jabalpur through Krishi Vigyan Kendra,s (KVKS) in October 2008.

Presently the mobile phone message is becoming the largest ICT initiative in

~ 64 ~

Madhya Pradesh by providing need based and regular farm advisory services to

the farmers in shortest time. The mobile phone message delivers real-time based

agricultural information and customized knowledge to improve farmers’ decision

making ability so that they may enable to increase their production and

productivity, better aligning the farm output to market demands, securing better

quality and improved price recovery.

ATMA started mobile phone message in Jan. 2014 under ICT as for

providing location specific and problem oriented, information to farming

community. The major problem of the district Rewa is low efficiency of existing

rural information delivery system and short fall of field staff in Department of

Agriculture. As a result overburden exists in all time and performance in this

regard was poor. In order to overcome the above mentioned problem ICT has

played a vital role in spreading the desired information to the farming community,

at proper time. Based on the above circumstances and important role played by

information & communication technology (ICT) the present study was undertaken

and entitled as “Studies on utilization of Information and Communication

Technologies (ICTS) for selected crop in Rewa District of (M.P.).”

has been undertaken with the following objectives.

1) To study the profile characteristics of the farmers.

2) To assess the extent of utilization of Information and Communication


3) To study the relationship between profile characteristics and extent of


4) To identify the constraints faced by the respondents in utilization of ICTs and

provide suggestions to overcome them.

~ 65 ~

Methodology

Selection of block

The Rewa block of Rewa District was selected purposely since a

total maximum concentration of mobile phone message total number of

registered users as compared to other blocks.

Selection of villages

From Rewa block, the five villages namely Tikar, Sahiiana, Baijnath,

Sumeda and Naikin were selected on the basis of higher number of (50%)

registered users of mobile phone message utilized.

Selection of the respondents

The Mobile Phone message users from each selected village were

selected through proportionate random sampling method. Finally the sample

consisted of 120 respondents.

Independent variables

Age, caste, education, size of family, land holding, social participation,

farming experience, annual income, information seeking behavior, extension

contact, achievement motivation, scientific orientation and innovativeness

Dependent variables

Extent of Use of ICTs in selected crop by the respondents

~ 66 ~

6.2 CONCLUSION

The conclusion of the present study are presented here on the basis of

objectives .

Independent VariableTo study the profile characteristics of the farmers.

1. Out of 120 respondents i.e. 45.00 percent of the respondents were

from middle age group.

2. About 34.17 percent of the respondents were engaged in OBC

category.

3. More than one third of the total respondents i.e. 40.00 percent were

educated up to high education level category.

4. More than 50 present of the farmers i.e. 50.83 percent respondents

had medium size of family.

5. Out of 120 respondents i.e. 45.83 percent respondents had medium

land holding.

6. Among the total respondents i.e.46.67 percent were having medium

social participation.

7. Among the total respondents i.e. 48.33 percent were medium in

farming experience.

8. Less than 50respondents i.e. 49.17 percent were from low annual

income.

9. Out of total respondents i.e. 46.67 percent respondents had high

information seeking behavior.

10.About 44.17 percent of the respondents were indicate medium

extension contact.

~ 67 ~

11.Less than 50 percent respondents i.e. 42.50 percent of the total

indicate medium level of achievement motivation.

12.About 43.33 percent respondents showed low level of scientific

orientation.

13.Among the total respondents i.e. 49.17 percent indicate low level of

innovativeness.

Independent Variable2). To assess the extent of utilization of Information andCommunication Technologies (ICTs).

1- It was observed that utilization of messages of the aspects by

the respondents namely message provide the different information about

wheat production, level of wheat production increasing due to information of

message, quality of wheat increasing due to information of message and

message provide the information to protect the wheat from infestation of

insect and pest. It was observed that utilization of messages of the aspect

message provide the different information about wheat production was found

to be maximum as indicating the utilization index- 81.25% followed by

message provide the information to protect the wheat from infestation of

insect and pest (utilization index- 64.58%), level of wheat production is

increased due to information of message (utilization index- 54.16%) and

quality of wheat is increased due to information of message (utilization index-

45.83%).

2- It was found that the field right time of seed sowing of wheat had the

highest utilization index (85.66%), followed by land preparation of sowing of

wheat (utilization index- 84.33%), actual quantity of seed sowing of wheat

(utilization index- 83.66%), method of sowing (utilization index- 82.33%), weed

control in wheat field (utilization index- 81.33%), seed treatment (utilization index-

80.00%), use of improved variety of seed (utilization index- 79.50%), information

~ 68 ~

related to insect and disease control in wheat crop (utilization index- 78.33%),

use of fertilizer in wheat field (utilization index- 73.83%), depth of seed sowing of

wheat (utilization index- 73.33%), right time of irrigation in wheat field (utilization

index- 72.66%), use of manure in wheat field (utilization index- 71.33%),

insurance scheme is related to wheat crop (utilization index- 65.66%),

information related to available selling rate of wheat in market (utilization index-

62.50%), and information related to loan for wheat production (utilization index-

55.50%).

3- Out of 120 respondents i.e. 43.33 percent indicate medium extent of

utilization of ICTs. Followed by 35.00 percent high extent of utilization of ICTs. It

is evident from the data that 21.67 percent respondents showed low extent of


3).To study the relationship between profile characteristics and extent ofutilization of ICTs.

It was found that the association between profile characteristics of the

farmers and their extent of utilization of ICTs. These are characteristics of the

respondents namely education, land holding, farming experience, annual income,

information seeking behavior, extension contact, achievement motivation,

scientific orientation and innovativeness had significant relationship with extent of

utilization of ICTs of respondents at 0.05 level with 4d.f.& 6d.f. The result also

depict that the characteristics namely age, caste, size of family and social

participation had no significant with extent of utilization of ICTs of respondents.

Constraints faced by the respondents in utilization of ICTs.

Constraints experienced by the respondents as arranged in descending

order on the basis of rank order as use of complex words (65.83%), problems

related to network of cell phone (63.33%), problems related to language

(60.83%), problems related to content of message (55.83%), lack of information

about availability of resources / inputs (54.17%), short duration supply or

~ 69 ~

insufficient availability of electricity (51.67%), lack of extension activities

(50.83%), untimely delivery of message (46.67%), application of message in

fields are too much expensive (43.33%). Non- availability of mobile phone

message related literature (42.50%).

6.3 SUGGESTIONS FOR FUTURE WORK

1. Since the present study is confined to the farmer’s of a Rewa Block of

Rewa district only. Hence the results may not be applicable to a large

area, for give relization. Similar work should be undertaken in other block

& districts.

2. This investigation was based on only 120 farmers hence the future studies

may be conducted on a large sample size.

3. In this study the dependent and independent variables selected were very

limited, therefore the number of variables for future research may be

increased.

4. Comparative study of urban and rural farmers may be planned for finding

actual status of rural farmers and extent of their involvement in decision

making as related to ICTs tools.

5. A similar study may be planned with other sampling procedures.

6. Use of different ICTs programme such as private & government impact to

the farmer’s of a different field.

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de

Ø- dFku iw.kZ:i

ls

vkaf”kd

:i ls

dHkh

ugha

1. D;k ;s [ksrh o vU; lgk;d C;olk; YkkHkdkjh gSSa

2. vk/kqfud d`f’k viukus esa jkstxkj feyus dh laHkkouk

gSA

3. d`f’k ds lkFk vU; O;olk;ksa dks viukus ls vk;

cM+rh gSA

4. D;k d`f’k ds lkFk vU; O;olk; thou ;kiu ds fy,

lgk;rk iznku djrs gSaA

8- okf’ksZd vk;&

vkidh okf’kZd vk; fofHkUu L=ksrksa ls fdruh izkIr gksrh gS

Ø- L=ksr okf’kZd ¼:-

½

1. d`f’k

2. nSfud Je

3. nqX/k mRiknu

4. ukSdjh

5. C;kikj

9- lwpuk izkIr djus dh izzo`fRRk & eksckby Qksu lans”k ls xsgwW ls lacaf/kr fofHkUUk

tkudkjh izkIr djus dh izc`fRr gkW@ugha

;fn gks rks foHkUu tkudkjh izkIr djrk gks&

Ø- fo’k; fu;fer dHkh

dHkha

dHkh ugha

1. mUur d`f’k rduhfd

2. chtksipkj laca/kh tkudkjh

3. chtksipkj dh cqokbZ laca/kh tkudkjh

4. dhVuk”kd nok ds mi;ksx laca/kh tkudkjh

5. [kkn ls lacaf/kr tkudkjh

6. moZjd ds mi;ksx laca/kh tkudkjh

7. ekSle laca/kh tkudkjh

8. ef.M;ksa ds Hkko ls laca/kh tkudkjh

9. vU;

10 izlkj laidZ

v½ D;k vkidk izlkj dk;ZdrkZ ls laidZ gS

c½ vxj gS rks vki fdlls feys gkW@ugha

Ø L=ksr fujUrj dHkh&dHkh dHkh ugha

1. d`f’k foHkkx (REO, RHEO, ADO)

2. JNKVV oSKkfud ,oa KVK oSKkfud

3. Input Dealer

4. iapk;r lnL;

5. NGO xSj lgdkjh laLFkk

6. vU;

11- izsj.k miyfC/k;k

Ø- dFku iw.kZ

lger

lger vfuf”pr vlger iw.kZ

vlger

1- tc rd dh dksbZ fdlku

fdlh ubZ rduhfd esa dfBu

ifjJe djds lQy ugha gks

tkrk rc rd dksbZ nwljk

fdlku ml rduhfd ls

mRizsfjr ugha gksrk gSA

2- lewg esa dk;Z djrs le;

nwljksa dks Hkh mlh dk;Z esa

feykus dk mRre iz;kl djuk

pkfg, ftlls fd nwljs yksx

mRizsfjr gksrs gSaA

3- fdlku fdlh dk;Z dks

izkFkfedrk nsa Hkys gh mls

vkjke u gksA

4- dksbZ fdlku vius fy, ,d

dfBu y{; fu/kkZfjr djs vkSj

mldks ikus dh dksf”k”k djsa

A

5- fdlh fdlku ds }kjk ?kfVr

gksus okyh ?kVuk dk rjhdk

nwljs fdlku dh dfBu ifjJe

gksus ls jksdrs gSaA

12- oSKkfud vfHkeq[kdj.k& fuEufyf[kr dFkuksa ds laca/k esa viuh jk; nsa&

Ø- dFku iw.kZ

lger

va”kr%

lger

vfuf”pr vlger iw.kZ

vlger

1- [ksrh dh ubZ oSKkfud rduhdh

vkRek }kjk izkIr eksckby Qksu

lans”k lsok ds ek/;e ls iqjkuh

rduhd ls vPNs ifj.kke nsrh gS

A

2- fdlkuksa dks [ksrh ds u;s&u;s

vuqHkoksa dks vkRek }kjk izkIr

eksckby Qksu lans”k lsok ds

ek/;e ls iz;ksx djuk pkfg, A

3- [ksrh ds u;s rjhds lh[kus esa

vf/kd le; yxrk gS ij ;g

rjhds fdlku dks eksckby Qksu

lans”k lsok ds ek/;e ls lh[kuk

pkfg, A

4- fdlkuksa ds thou Lrj esa lq/kkj

ds fy, ijEijkxr [skrh dh

fof/k;ksa esa eksckby Qksu lans”k

lsok ds ek/;e ls ifjorZu djuk

vko”;d gS A

5- izzxfr”khy fdlku ogh gS tks

[ksrh ds u;s rjhdksa dks eksckby

Qksu lans”k lsok ds ek/;e ls

viukrk gS,6- vius iqj[kksa dh [ksrh vkt dh

oSKkfud [ksrh ls vPNh FkhA

13- uopkfjrk

Ø- dFku iw.kZlger

lger vfuf”pr vlger iw.kZvlger

1- os bu fnuksa ubZ rduhd ijckr djrs gSa ysfdu dkSu dgrkgS fd os iqjkuh ls csgrj gS

2- eS vius vki dks vkjke jfgreglwl d:xk tc rd fdd`’k.k fØ;kvksa dh eq>s tkudkjhugha gks tkrh ftuds ckjs esa lqupqdk gwW

3- eS le;≤ ls cgqr lkjhd`’kd fØ;kvksa ds ckjs esa lqurkvk jgk gwW vkSj fiNys dqNlkyksa ls muds ckjs esa tkuus dhdksf”k”k dj jgk gwWA

4- [ksrh ds ubZ rjhds iqjkus rjhdsdh vis{kk csgrj ifj.kke nsrsgSaA

5- fdlku ds thus ds Lrj dslkFk&lkFk [ksrh ds ijEijkxrrjhds cnyrs tkrs gSaA

6- vius vki dks d`f’k dh ubZd`’k.k fØ;kvksa dks lwpukvksa lsges”kk lacaf/kr jgwWxk vFkkZr

le;≤ ij lwpukvksa ds ckjsesa tkurk jgwWxk

7- dksbZ ,d uopkfjrk ges”kk ghfdlh ubZ rduhfd dkss tkuusds fy, ges”kk gh rRij vFkkZrizFke jgrk gSA

[k.M **c**

fo”ks’k tkudkjh

1- lans”k ds dkj.k xsgw Qly ds mRiknu dh lVhdrk

Ø- dFku mPp e/;;e fuEu fcYdqy

ugha

1- lans”k ls xsgwW ds mRiknu ls lacaf/kr fofHkUu

tkudkjh feyrh gS

2- lans”k dh tkudkjh ls xsgwW dk mRiknu Lrj

c<+rk gS

3- lans”k dh tkudkjh ls xsgwW dh xq.koRrk esa Hkh

c<+ksRrjh gksrh gS

4- lans”k ls xsgwW ij yxus okys fofHkUu jksxksa ,oa

dhVksa ds izdksi ls cpko lacaf/kr tkudkjh feyrh

gS

2- lwpuk lapkj izkS|ksfxdh ds varxZr vkidks eksckby ij tks xsgwW dh [ksrh ls lacaf/kr

tks Hkh lans”k izkIr gksrs gSa mudk vkius fdl Lrj rd viuh [ksrh esa mi;ksx

fd;k gSA

xsgwwW dh QLky esa eksckby lans”k ij D;k vkidks tkudkjh feyh gkW@ugha

;fn gkW rks crkb;s&

Ø- dFku iw.kZr%

lgh

vkaf”kd

:i ls lgh

rVLFk vkaf”kd :i

ls vuqfpr

vkaf”kd :i

ls iw.kZ

vuqfpr

1. xsgwW dh cqokbZ ds

fy, Hkwfe dh

rS;kjh

2. cqokbZ dh fof/k;kW

3. xsgwW dh cht cqokbZ

dk lgh le;


dh lgh ek=k

5. chtksipkj


dh xgjkbZ

7. mUur iztkfr;ksa ds

cht dk mi;ksx

8. xsgwwW ds [ksr esa

flapkbZ dk lgh

le;

9 xsgwW ds [ksr esa

[kjirokj fu;a=.k

esa

10 [kkn dk mi;ksx

11 moZjd dk mi;ksx

12 xsgwW dh QLky esa

jksx o dhVks ds

fu;a=.k lacaf/kr

13 xsgwW dh Qly esas

chek ;kstuk ls

lacaf/kr

14 xsgwW ds mRiknu ds

fy, _.k ysus ls

lacaf/kr tkudkjh

15 xsgwW dh cktkj esa

miyC/k fcØh nj

dh tkudkjh

[k.M& l

v½& eksckby Qksu lans”k ds ek/;e ls xsgw ds mRiknu ls lacaf/kr rduhdh tkudkjh ds

mi;ksx esa vkus okyh leL;k;sa&

1) --------------------------------------------------------------------------------------------------------------------------------------------------

2) --------------------------------------------------------------------------------------------------------------------------------------------------

3) --------------------------------------------------------------------------------------------------------------------------------------------------

4) --------------------------------------------------------------------------------------------------------------------------------------------------

5) --------------------------------------------------------------------------------------------------------------------------------------------------

6) --------------------------------------------------------------------------------------------------------------------------------------------------

7) --------------------------------------------------------------------------------------------------------------------------------------------------

8) --------------------------------------------------------------------------------------------------------------------------------------------------

9) --------------------------------------------------------------------------------------------------------------------------------------------------

10) --------------------------------------------------------------------------------------------------------------------------------------------------

c½& eksckby Qksu lans”k dk;ZØe dks vf/kdre mi;ksxh o izHkkoh cukus ds fy, vkids

lq>ko &

1) --------------------------------------------------------------------------------------------------------------------------------------------------

2) --------------------------------------------------------------------------------------------------------------------------------------------------

3) --------------------------------------------------------------------------------------------------------------------------------------------------

4) --------------------------------------------------------------------------------------------------------------------------------------------------

5) --------------------------------------------------------------------------------------------------------------------------------------------------

6) --------------------------------------------------------------------------------------------------------------------------------------------------

7) --------------------------------------------------------------------------------------------------------------------------------------------------

8) --------------------------------------------------------------------------------------------------------------------------------------------------

9) --------------------------------------------------------------------------------------------------------------------------------------------------

10) --------------------------------------------------------------------------------------------------------------------------------------------------

Fig 4.15- Utilization in respect the different fields of mobile phone message on productiontechnology of wheat.

84.33 82.33 85.66 83.66 8073.33

79.572.66

81.33

71.33 73.8378.33

65.66

55.562.5

0102030405060708090

Fig 4.1- Distribution of the respondents according to their age.

34.17

45

20.83

0

5

10

15

20

25

30

35

40

45

50

Young Middle Old

Fig 4.2- Distribution of the respondents according to their caste.

Fig 4.3- Distribution of the respondents according to theirlevel of education.

19.16

24.17

34.17

22.5

0

5

10

15

20

25

30

35

40

Schedule Caste Schedule Tribe OBC General

17.5

24.17

40

18.33

0

5

10

15

20

25

30

35

40

45

Primary Middle High School Graduates

Fig 4.4 - Distribution of the respondents according to theirsize of family.

Fig 4.5 - Distribution of the respondents according to theirland holding.

29.17

50.83

20

0

10

20

30

40

50

60

Small Medium Big

30

45.83

24.17

0

5

10

15

20

25

30

35

40

45

50

Small Medium Big

Fig 4.6 - Distribution of the respondents according to their socialparticipation.

Fig 4.7 - Distribution of the respondents according to their farmingexperience.

27.5

46.67

25.83

0

5

10

15

20

25

30

35

40

45

50

Low Medium High

25

48.33

26.67

0

10

20

30

40

50

60

Low Medium High

Fig 4.8 - Distribution of the respondents according to their annualincome.

Fig 4.9 - Distribution of the respondents according to theirinformation seeking behaviour.

49.17

29.17

21.66

0

10

20

30

40

50

60

Low Medium High

23.33

30

46.67

0

5

10

15

20

25

30

35

40

45

50

Low Medium High

Fig 4.10 - Distribution of the respondents according to theirextension contact.

Fig 4.11 - Distribution of the respondents according to theirachievement motivation.

26.66

44.17

29.17

0

5

10

15

20

25

30

35

40

45

50

Low Medium High

28.33

42.5

29.17

0

5

10

15

20

25

30

35

40

45

Low Medium High

Fig 4.12 - Distribution of the respondents according to theirscientific orientation.

Fig4.13 - Distribution of the respondents according to theirinnovativeness

43.33

30.84

25.83

0

5

10

15

20

25

30

35

40

45

50

Low Medium High

49.17

28.33

22.5

0

10

20

30

40

50

60

Low Medium High

Fig 4.14 - Utilization of messages on different aspects by therespondents obtained through mobile phone message.

81.25

54.16

45.83

64.58

0

10

20

30

40

50

60

70

80

90

Messageprovide the

differentinformationabout wheatproduction

Level of wheatproduction

increasing dueto information

of message

Quality of wheatincreasing dueto information

of message

Messageprovide the

information toprotect thewheat from

infestation ofinsect and pest

Series1

Fig 4.16 - Distribution of the respondents according to theirExtent of utilization of ICTs.

21.67

43.33

35

0

5

10

15

20

25

30

35

40

45

50

Low Medium High

FIG. 3.1 MAP OF RESEARCH AREA OF THE REWA DISTRICT

Tikar

Sahijana

Baignath

Sumeda

Naikin

Study on Utilization of Information and Communication ...CERTIFICATE - I This is to certify that the...

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