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Southw est M ichigan fruit and vegetable farm ers’ use o f sources
and channels to gain inform ation in regard to new agricultural
practices
Vergot, P ete, III, Ph.D .
Michigan State University, 1991

UMI

300 N. Zeeb Rd.
Ann Arbor, MI 48106

SOUTHWEST MICHIGAN FRUIT AND VEGETABLE FARMERS’
USE OF SOURCES AND CHANNELS TO GAIN INFORMATION
IN REGARD TO NEW AGRICULTURAL PRACTICES

By
Pete Vergot, III

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
DOCTOR OF PHILOSOPHY

Department of Agricultural and Extension Education
1991

ABSTRACT
SOUTHWEST MICHIGAN FRUIT AND VEGETABLE FARMERS’ USE OF
SOURCES AND CHANNELS TO GAIN INFORMATION IN REGARD TO
NEW AGRICULTURAL PRACTICES
By
Pete Vergot, III

In 1990, many sources and channels of information for new agricultural practices
influenced farmers. It became necessary for formal and non-formal agriculture educators
to understand the use of these sources and channels to better disseminate information and
market this information to clientele. This study was designed to determine the sources
and channels o f information and to determine if selected personal and demographic
characteristics have an effect on methods that farmers use in gaining information on new
agricultural practices.
A random sample was drawn from a population of fruit and vegetable farmers
from mailing lists in five counties of Southwest Michigan including Allegan, Berrien,
Cass. Kalamazoo and Van Buren. Information re.parHino Frpnnpnrv
o f n«* o f «nmvv»c
-- J
------------------ O

--------- 1 ------------

**

and channels, selected personal and farm characteristics were collected by mail using a
questionnaire.
Analysis of the data showed that of eleven sources listed farmers ranked
Cooperative Extension Service Personnel, Product Company Representatives and other
farmers, both Family and Non-Family Members, at the top. Sources ranking at or near
the bottom were Farmers Home Administration Personnel and Vocational Agriculture

Teachers.

Ranking at the top of the 18 channels listed, were farm magazines,

Agricultural Bulletins from Michigan State University and other universities, and Weekly
or Monthly Newsletters.

Channels that were seldom or never used for receiving

information included Video Tape and Microcomputer Communications.
It was concluded that respondents were similar in personal and farming
characteristics.

Respondents used traditional sources and channels of information

delivery. Young farmers and farmers with their main income from the farm, used a
larger number of sources and channels.
It was implied that Michigan State University should continue to support field
positions in fruit and vegetables, and these positions increase their writing and submitting
of articles to farm magazines.

Also recommended was that agricultural educators

continue to improve agricultural bulletins containing agricultural information, and be
responsive to new technologies, such as video tape and microcomputer communications.

ACKNOWLEDGMENTS
Appreciation and gratitude is extended to Dr. John "Frank" Bobbitt who served
as advisor during the many years of duration of this study and course work.
Thanks are also extended to the sincere support of the other three members of the
committee: Dr. Harrison Gardner, Dr. Eddie Moore, and Dr. J. Allen Beegle. Each
of the five members provided professional advice and training during the preparation of
course work and implementation of this study.
A special thanks is extended to Jerri Pursley for her skills at the word processor
and her support for completion of this study.
The author would like to thank Morari Savadi for his assistance with the statistical
application, and to the entire Van Buren Cooperative Extension office staff, for their
support while the author was on study leave.
Finally, a very special thank you to the author’s wife, Sheri, for her
understanding, encouragement, patience and love that made the completion of this study
possible.
The author dedicates this study to his mother and father for their love and belief
in education for their son.

TABLE OF CONTENTS
Page
LIST OF TABLES

............................................................................................................ viii

LIST OF F IG U R E S ...............................................................................................................xi

Chapter
I.
IN T R O D U C T IO N ................................................................................................. 1
Purpose and Objectives of the study ...................................................................3
Research Q uestions..................................................................................................5
Definitions o f T e rm s ...............................................................................................6
Survey D esig n .......................................................................................................... 7
Assumptions and Limitations of the S tu d y .......................................................... 8
Overview of the D issertation.................................................................................9
S um m ary................................................................................................................. 10
Chapter
II. PRECEDENTS IN THE LITERATURE............................................................ 11
Adoption of Practices .......................................................................................... 11
The 1950’s .............................................................................................................. 13
The 1960’s .............................................................................................................. 16
The 1970’s ..............................................................................................................20
The 1980’s ..............................................................................................................23
Conclusions and Directions from L iteratu re..................................................... 24
Hypothesis to be T e s te d ....................................................................................... 25
S um m ary................................................................................................................ 27

v

Table of Contents (cont’d)
Page
Chapter
m . METHODOLOGY AND STUDY D ESIG N .....................................................28
Population and Sample .......................................................................................29
Development of Instrum ent................................................................................. 29
Validity and Reliability .......................................................................................30
Distribution and Data Collection.........................................................................32
S u m m ary ................................................................................................................ 35
Chapter
IV. STUDY F IN D IN G S ............................................................................................ 36
Description of Respondents................................................................................. 37
Frequency o f Use by Respondents ................................................................... 43
Testing of Null Hypothesis Using C orrelations................................................50
Non R espondents.................................................................................................. 86
S u m m ary ................................................................................................................ 86
Chapter
V. SUMMARY, CONCLUSIONS AND RECOMMENDATIONS...................88
S u m m ary................................................................................................................ 88
C o n clu sio n s...........................................................................................................94
Im p licatio n s.........................................................................................................104
Recommendations for Further Studies ............................................................105
Personal O bservations........................................................................................106
APPENDICES...................................................................................................................... 110
A.
B.
C.
D.
E.
F.
G.

Farm Survey Instrum ent............................................................................. 112
First Cover L e tte r..........................................................................................117
Return Postcards ..........................................................................................119
Second Cover L e tt e r .................................................................................... 121
Postcard Reminder.......................................................................................... 123
Survey and Postcard R e tu r n s ......................................................................125
Reasons Why People DidNot Fill Out S u r v e y ......................................... 127

Table of Contents (cont’d)
(Appendices cont.)
Page
H. Results of t-test Analysis of Respondents Versus
N on-R espondents...........................................................................................129
I. ANOVA Means and Standard Deviations Between Sources
o f Information and Levels of Formal Education ..................................... 131
J. ANOVA Means and Standard Deviations Between Channels of
Information and Levels of Formal E d u c atio n ........................................... 133
K. ANOVA Means and Standard Deviations Between Sources of
Information and Types of Farm O w n e rsh ip ..............................................136
L. ANOVA Means and Standard Deviations Between Channels of
Information and Types of Farm O w n e rsh ip ..............................................138
M. ANOVA Means and Standard Deviations Between Sources of
Information and Gross Farm I n c o m e ......................................................... 141
N. ANOVA Means and Standard Deviations Between Channels of
Information and Gross Farm I n c o m e .........................................................144
LIST OF REFERENCES

.................................................................................................148

vii

LIST OF TABLES

labte

Page

1. Number and Percent o f Male and Female Fruit and Vegetable Farmers . . . . 37
2. Number and Percent of Fruit and Vegetable Farmers by Four
Educational Levels ....................................................................................................38
3. Number and Percent of Fruit and Vegetable Farmers by Type
of Farm O w n ersh ip ..................................................................................................... 39
4. Number and Percent of Fruit and Vegetable Farmers Farming Full-Time
and P a rt-T im e ..............................................................................................................40
5. Number and Percent of Fruit and Vegetable Farmers in Seven
Income G ro u p s..............................................................................................................41
6. Selected Personal and Farm Characteristics of Farmers ....................................... 43
7. Frequencies of Sources of Information Used by Fruit and Vegetable
Farmers
......................................................................................................................44
8. Ranked Means of Sources of Information Used by Fruit and Vegetable
Farmers ......................................................................................................................46
9. Frequencies o f Channels of Information Used by Fruit and Vegetable
Farmers
......................................................................................................................48
10. Ranked Means of Channels of Information Used by Fruit and Vegetable
Farmers
......................................................................................................................50
11. Correlation of Sources of Information and Selected Characteristics
of R espondents............................................................................................................. 52
12. Correlation o f Channels of Information and Selected Characteristics
of Respondents............................................................................................................. 53

List of Tables (cont’d)

Table

Page

13.

Results o f t-test for Differences of Gender on Sources of Information for
New Agricultural Practices ....................................................................................... 60

14.

Results o f t-test for Differences of Gender on Channels of Information for
Agricultural P ractices.................................................................................................. 62

15.

Results o f t-test for Differences Between Part-Time and FullTime Farmers for Sources of Information U s e d ..................................................... 65

16.

Results o f t-test for Differences Between Part-Time and Full-Time
Farmers for Channels of Information U s e d ..............................................................67

17.

One-Way Analysis of Variance of Sources When Considering Type
o f Formal Eduction o f F a rm e rs ..................................................................................69

18.

One-Way Analysis o f Variance of Channels When Considering Type
of Formal Education of F a r m e r s ...............................................................................71

19.

One-Way Analysis of Variance of Sources When Considering Type
of Ownership of F a rm s ................................................................................................74

20.

One-Way Analysis o f Variance of Channels When Considering Type
of Ownership of Farmers ..........................................................................................76

21.

One-Way Analysis o f Variance of Sources When Considering Gross
Earnings o f F a rm s ........................................................................................................ 79

22.

One-Way Analysis of Variance of Channels When Considering Gross
Earnings o f Farmers ...................................................................................................82

23.

Results of t-test Analysis of Respondents Versus N on-Respondents................129

24.

ANOVA Means and Standard Deviations Between Sources of Information
and Levels of Formal Education .............................................................................131

List of Tables (cont’d)

Table

Page

25. ANOVA Means and Standard Deviations Between Channels of Information
and Levels of Formal E d u c a tio n .............................................................................133
26. ANOVA Means and Standard Deviations Between Sources of Information
and Types of Farm O w n e rsh ip ................................................................................136
27. ANOVA Means and Standard Deviations Between Channels of Information
and Types o f Farm O w n e rsh ip ................................................................................138
28. ANOVA Means and Standard Deviations Between Sources of Information
and Gross Farm I n c o m e ........................................................................................... 141
29. ANOVA Means and Standard Deviations Between Channels of Information
and Gross Farm I n c o m e ........................................................................................... 144

x

LIST OF FIGURES
Figure
1. Gender of Respondents

Page
...............................................................................................37

2. Educational Levels of Sample Population...................................................................38
3. Type of Farm Ownership o f Sample Population

.....................................................39

4. Full-Time and Part-Time F a rm e rs ..............................................................................40
5. Gross Income Characteristics of Sample P o p u latio n ...............................................42

xi

CHAPTER I

INTRODUCTION
In 1990, farmers had many sources and channels of information which influenced
their agricultural education and farming operations. Previous studies showed that farmers
locked on to one or two major types of sources and channels, because profitability
depended on accurate, concise and understandable information. Farm population in the
1980’s was declining and among this population the number of part-time farmers was
increasing. These farmers had less time than their full-time counterparts to gather the
information they needed to increase productivity. It, therefore, became necessary for
both formal and non-formal educators to understand better, the sources and channels
these farmers used to receive information about new agricultural practices. They needed
a wider knowledge of the basics of delivery methods. They also needed to keep up with
the changing technology in order to effectively market information to their changing farm
clientele.
In 1990, increased costs of delivering current and up-to-date educational
information was primarily due to increases in postage.

The Cooperative Extension

Service, especially the County Extension Director, had to utilize the most economical and
accessible methods of reaching clientele with educational information on new agricultural
practices. County Extension Directors and Agents were using a multitude of delivery

1

2
channels. Channels included local radio, newsletters, direct mailings, local newspapers
and agricultural bulletins.

Popular channels such as farm magazines, video tapes,

television and computer programs were expensive. Few of these channels were available
for county-wide programming of educational information. Radio and television could not
afford to provide public service or broadcast information on new agricultural practices
at low cost because agricultural populations had dwindled over the past decades (Census
of Agriculture Untied States 1989).

Small broadcast news stations that previously

provided these sources, had enlarged to cover increased cost, and changing audiences.
Without the use o f biased commercials or sponsorships, popular channels were financially
out o f range of agricultural educators.
During the review of the literature, the author found patterns which began as early
as 1958. Farmers were often confused between sources of information and channels of
information. They often mistook the channels as the source of information. This was
evident when they decided where they received information on new agricultural practices.
In most all the literature, neighboring farmers and farm magazines were rated at or near
the top, as a source or channel of information. Another pattern was, the more educated
the farmer or more profitable the farm, the greater the number of sources or channels
were used in gaining new agricultural information. Cooperative Extension agents ranked
below other channels or sources, usually second to sixth on a rating scale of usefulness
in determining new agricultural information. Most of the information shared through
channels, such as radio programs and farm magazines, were either written by Extension
agents or University specialists working for Extension.

3
It was a challenge for County Extension Directors to further utilize these channels
of farm magazines and farm journals to effectively distribute information on new
agricultural practices to farmers. They needed to better understand which sources and
which channels farmers used to gain information on farming practices and techniques.

Purpose and Objectives of the Study
The educational value of this study was to help both formal and non-formal
agricultural educators in contacting the fruit and vegetable farm clientele of Southwest
Michigan.

It was designed to assist Cooperative Extension Agents, Vocational

Agricultural Teachers and other groups of educators, in identifying which sources and
through what different channels farmers received information on new agricultural
practices.

The purpose of this study was:
1.

To determine the use of sources and channels to gain information on new
agricultural practices by fruit and vegetable farmers in Southwest
Michigan.

2.

To determine if selected personal and demographic characteristics had an
effect on sources or channels of information farmers used in gaining
information on new agricultural practices.

The objectives of the study were:
1.

To determine which sources of information, fruit and vegetable farmers
in selected Southwest Michigan counties used, to receive information on
agricultural practices.

2.

To determine what channels of information, fruit and vegetable farmers
in selected Southwest Michigan counties used, to receive information on
agricultural practices.

4
3.

To determine if part-time farmers differ from full-time farmers in their
selection of sources or channels of information concerning new
agricultural practices of fruit and vegetable farming in Southwest
Michigan.

4.

To determine if there is any relationship between the age of a farmer and
the sources or channels used, by fruit and vegetable farmers of Southwest
Michigan to receive information concerning new agricultural practices.

5.

To determine if the size, in number of acres, of a farming operation
governed which sources or channels fruit and vegetable farmers of
Southwest Michigan used to receive information on new agricultural
practices.

6.

To determine if the number of years a person has been in fruit and
vegetable farming had a relationship to the source or channel for receiving
information on new agricultural practices.

7.

To determine if the number of years of formal education had a relationship
to the source or channel used by fruit and vegetable farmers to receive
information about new agricultural practices.

8.

To determine if the gross dollar earnings from the fruit and vegetable farm
affected which sources or channels farmers selected to receive information
concerning new agricultural practices.

Research Questions

The primary purpose of this study was to identify use of sources and channels of
information by fruit and vegetable growers in Southwest Michigan. The second purpose
was to determine if selected personal and demographic characteristics had an effect on
which sources and channels of information farmers used in gaining information on new
agricultural practices.

It was expected by the researcher that certain patterns be

identified when tabulating data. Specific research questions to be answered by this study
were as follows:

5
1.

What was the frequency of use of selected sources and selected channels of
information, by fruit and vegetable farmers selected from five selected counties
in Southwest Michigan, to gain information on new agricultural practices?

2.

Does the size o f the farm in acres affect the use of sources or channels for
gaining information on new agricultural practices used by fruit and vegetable
farmers in five selected counties in Southwest Michigan?

3.

Does the gross dollar earnings of the farm influence a farmer’s use of sources or
channels for gaining information on new agricultural practices used by fruit and
vegetable farmers of five selected counties in Southwest Michigan?

4.

Does the time a farmer spends working off the farm, make a difference in the use
of sources or channels for gaining information on new agricultural practices used
by fruit and vegetable farmers of five selected counties in Southwest Michigan?

5.

Does the age of a farmer have an effect on use of sources or channels for gaining
information on new agricultural practices used by fruit and vegetable farmers of
five selected counties in Southwest Michigan?

6.

Does the amount or level of formal education a farmer has, have an effect on use
of sources or channels for gaining information on new agricultural practices used
by fruit and vegetable farmers of five selected counties in Southwest Michigan?

7.

Does the number of years a person has been farming have an effect on the use
of sources or channels for gaining information on new agricultural practices used
by fruit and vegetable farmers of five selected counties in Southwest Michigan?

8.

Does gender have an effect on use of sources or channels for gaining information
on new agricultural practices by fruit and vegetable farmers of five selected
counties in Southwest Michigan?

9.

Does type of farm ownership affect the use of sources or channels for gaining
information on new agricultural practices used by fruit and vegetable farmers of
selected five counties in Southwest Michigan?

Definitions of Terms Used in the Study

Agricultural Practices - A technique a farmer uses to enhance or maintain profitability
of a farm by using a machine, concept, cultural practice, or behavior, such as no-till

farming methods, irrigation, selective weed control, forward price contracting, etc.
Farm Operator - The owner/operator of agribusiness ventures with intent of raising for
profit, field crops, livestock, greenhouse, fruit or vegetable material.
Agricultural Educators - Those individuals who give formal or non-formal agricultural
education to farm operators or other individuals.
Agricultural Education - The process of learning competencies in the area of agriculture,
through formal or non-formal methods.
Formal Education - Public school or education programs designed for those who have
declared an interest in a specific educational subject matter area and have
registered for class. Those enrolled pay an enrollment fee and agree to abide by a set
of rules o f an institution. Those who complete these programs usually receive some type
of certificate or degree.
Non-formal Education - The selection of information and competencies, developed by an
individual in a non-structured manner, with use of books, articles, newspapers, or
magazines, or by attending specialized seminars or informational meetings. Usually not
taken for credit or certification.
Part-time Farmer - An individual who works more than one hundred days off the farm
in a non agricultural job.
Source of Information - The person or institution which provides information based on
research or first-hand experience with agricultural practices.
Channels of Information - The method of delivery information, such as a type of written
media or video.
ASCS - Agricultural Stabilization Conservation Service

7
CES - Cooperative Extension Service
FmHA - Farmers Home Administration of Michigan
SCS - Soil Conservation Service

Survey Design
The survey was completed by a randomly selected group of farm operators.
Random selection means each farmer had an equal chance of being selected to take part
in the study. This kind of selection ensured reliability of the study.
Farmers selected for this study represented a cross section of fruit and vegetable
farmers in selected Southwest Michigan counties who were on the mailing lists of
Cooperative Extension Service offices of Allegan, Berrien, Cass, Kalamazoo and Van
Buren counties. These Southwest Michigan farms represented one fourth of all fruit and
vegetable farmers in the State of Michigan (Census of Agriculture Unites States 1989).
From these five counties a list of farmers, was produced. From this list of 970 farmers,
275 names were randomly selected and were sent the surveying instrument, along with
a cover letter explaining the survey and instructions for completion (see Appendix A and
B). Research was based on the responses to the survey.
Reasons for selecting 275 names are explained in Statistical Methods In Education
and Psychology (Borg and Gall 1983) and in course work of CEP 904 and CEP 905.
With correct random selection high validity would be achieved.

Two hundred and

seventy-five names were selected to account for surveys that would not be returned or
returned partially answered.
The instrument was divided into two sections. Section one asked farmers to rate

8
frequency o f use of eleven sources from which they received information on new
agricultural practices. It also asked farmers to rate frequency of use of channels from
which they received information on new agricultural practices.
The second section of the survey instrument collected background information on
each farmer and the farm he or she operates. Information included age, gender of the
farmer, size of operation in acres, gross dollar earnings of the farm, number of days
worked off the farm in the past year, number of years of formal education of the farmer,
number o f years in farming, and type of farm ownership. Patterns and differences in
primary and secondary questions were analyzed statistically using the computer software
SPSS P C + . Each major area was described statistically and commonalties or differences
were shown and reported through tables, figures and narratives.

Assumptions and Limitations of the Study
Focus of this study was the frequency of use of sources and channels of
information for receiving information on new agricultural practices by Southwest
Michigan fruit and vegetable farmers.

An assumption was made that farmers who

responded to the questionnaire were sincere in answering their questions.

Another

assumption was that there was no difference between farmers who had been selected and
those who had not been selected by the random sampling method.
Southwest Michigan had a wide variety of farm operations because of its diverse
resources of soils, water and climate. Fruit and vegetable farmers were chosen because
they represented varied marketing and management strategies used in farming, and for
their varied size and potential dollar earnings.

As with other investigations limitations foreseen and unforseen, are recognized
and listed. Following is a list of limitations:
1) This study was based on a population which was drawn from names that were
on mailing lists of the county Cooperative Extension Service in five counties in
Southwest Michigan. This study may have populations of early adopters which used
fewer adoption stages. Clientele had to actively place their names on these list.
2) Other sources and channels could have been used by farm clientele, but space,
funding and practicality required that choices of sources and channels be narrowed.
3) It is difficult to determine the exact number of fruit and vegetable farmers in
Southwest Michigan. The State of Michigan statistical service did have lists which were
more complete.

These lists are protected from anyone outside the United States

Statistical Service.

Overview of the Dissertation
A background and relevance of the study was developed in Chapter I.
Introduction to need, problems and objectives are presented. Research questions are
explained to identify certain factors, followed by a definition of terms used by the author.
An explanation or overview of research design, and limitations to the study are given.
In Chapter II, related literature was presented.

These studies gave both

foundation and history to the study, with specifics on the farmer’s sources and channels
of information on new agricultural practices.
Chapter III contains information on how the study was designed and implemented.
This included the population description, sample description, instrumentation, validity
and reliability measures, distribution and collection of the questionnaire and framework

10
of data analysis.
Each question from the survey instrument was explained in Chapter IV by using
charts, tables, and narrative formats.

Chapter V contained a summary of the study,

conclusions and observations of the study by the author,

implications and

recommendations for further research.

Summary
The challenge of delivery of information to farmers by agricultural educators was
explained in the introduction.

Purpose and objectives were developed along with

research questions to be reviewed in the literature. Definitions of terms unfamiliar to
readers were given.
overview were stated.

Survey design, assumptions, limitations and the dissertation

CHAPTER n
PRECEDENTS IN THE LITERATURE
The use of selected sources and selected channels by farmers to gain information
about agricultural practices was documented in various dissertations, articles in journals
and bulletins. This study was completed by a review of the literature from available
sources.

Summaries o f like studies were reviewed for key words.

A computer

bibliography search using these key words was done at the Michigan State University
Library.

The sources searched were from Eric and Eric on Compact Disk Rom,

dissertation abstracts, Summary of Studies in Agricultural Education and Summaries of
Studies in Extension Education.

Adoption of Practices
in his ”Adoption of New Ideas and Practices", Herbert F. Loinberger of the
Department of Sociology at the University of Missouri, Columbus, Missouri presented
a summary of research, explaining the acceptance of technological advances in
agriculture with implications for facilitating change. This work was a review of studies
completed prior to 1960 on the subject of communications and adoption of ideas, by
farmers in many communities in rural states.
Lionberger stated that the decision to adopt new practices, usually takes time.
"People normally do not adopt a new practice or idea as soon as they hear about it"

12
(P.3).

For many practices, people appear to go through a series of distinguishable

stages: awareness, interest, evaluation, trial, final adoption. Lionberger states that final
adoption was not always permanent. He discussed information sources and how they
varied their position in the adoption cycle.
Lionberger continued with the awareness stage, stating that mass media,
newspapers, magazines, radio and television were the most frequent channels of
information about new ideas and practices. There was one exception, the late adopter.
He was more likely to first learn about a practice from other farmers. Lionberger also
stated that in the second stage, various agricultural agencies were likely to be important
particularly for early adopters. Well-regarded farmers become a useful source during
the evaluation stage. For the trial stage or, "How do I apply it stage?”, frequent sources
were salesmen and dealers (P. 6).

They commonly supply answers to questions

concerning commercial products. Other farmers continue to be important during this
stage. For complex practices, the county agent, vocational agricultural teacher and other
professionals, who are not specialists, were used.
In the final adoption stage, the farmer looks towards government personnel,
industry, and other successful farmers to help reinforce decisions he has made.
Lionberger concluded by stating that mass media was used as a quick and efficient means
of notifying farmers o f new developments. Lionberger recommended mass media be
used by universities to disseminate information. Often a resourceful farmer was directly
linked to information sources and becomes a pass-through. As a pass through, a farmer
passed information from agricultural agents, Vocational Agriculture teachers and
experiment stations to other farmers.

In some cases they did not pass on complete

13
information and in turn corrupted and evaluated what they were communicating. They
become

. .influences and innovators and gain status within the community as

information gate keepers" (P.9).
Lionberger also discovered that individual farmers acted as sources of information
to other farmers. They were able to pass on what they read, heard or had seen others
do.

Farmers who were late adopters in farm practices were often willing to accept

advice from these fellow farm producers.

The 1950s
As a part of his dissertation Russell G. Mawby published his findings, entitled
"Types and Sources of Information Used by Farmers in Michigan with Implications for
Extension Programming" in 1959 at Michigan State University. Data for this dissertation
was collected from 199 southern Michigan farms in the summer of 1954.

In his

introduction, Mawby stated that farmers in different positions employed different patterns
of sources of communications when securing a given type of information. Variations and
patterns in sources employed were associated with the amount of formal education,
background experiences, personal situations, scale of the operation, type of farm and
number of educational meetings attended. Farmers with higher educational degrees and
farming experience sought Michigan State University Cooperative Extension personnel
and research specialists. Mawby stated that farmers with different personal and farm
characteristics used a given source of information in the same pattern.
Mawby was looking at ways in which farmers received information useful in
solving problems. He hoped that the Cooperative Extension Service of Michigan would

14
be better able to determine programs and delivery channels based on his study. The
study concerned itself with types of information considered important by farmers and
sources of communication o f information.
In his study, Mawby used data from the Interstate Managerial Survey, a
cooperative interdisciplinary regional study. Agricultural economists and sociologists
from the seven states of Indiana, Iowa, Kansas, Kentucky, Michigan, North Dakota and
Ohio were involved. Farmers surveyed managed farms producing a minimum of $2,500
worth of farm products. Mawby’s sample involved counties south of a line from Bay
City to Muskegon.

Information requested was based on five categories: 1) prices

revealed for products, 2) production factors, 3) new developments, 4) human factors,
political, social and 5) institutional factors (P.50,51).

Mawby measured the use of

information against these five categories.
Mawby stated that individuals receiving information for "maximizing profits,
desire different patterns than do those who receive it to maximize family satisfactions"
(P. 14, 15). He concluded that different communicative sources of information were
used in differing degrees to securing five types of information, by employing eight
communicative sources in sub-groupings established for each different variable in the
study.

Mawby determined groupings to be farm organizations, land grant systems,

commercial people, professional counselors, neighbors, relatives, farm magazines,
newspapers, radio and television. He concluded that farmers, ranked the various sources
differently when a selection was available based on their education, size of their
operation, their background, and personal situation.
A summary, of the sources of production information indicated by respondents,

15
showed that the University Land Grant System was the most useful. Farm magazines
were a strong second.
relatives.

Radio and television were next, followed by neighbors and

Mawby stated that commercial people, professional counselors and farm

organizations were relatively unimportant sources of production information.
Another study in the 1950s included John David Todd’s thesis at the University
of Tennessee in 1959, entitled "The Attitude of Adult Farmers Toward Adult Education
in Vocational Agriculture in the Eagleville School area of Rutherford County,
Tennessee." Todd presented data showing the status of farmers, their background and
attitude toward adult education programs. Sources of information were used for changes
or trends in agriculture. Todd found that farmers used adult education classes, visits by
an agricultural teacher, visits by County Extension Agents and visits to the County
Extension Office, magazines, newspapers, seed and fertilizer dealers, radio and television
and other farmers as sources o f information. Todd measured these sources against the
number o f years farmers had been in agriculture, their age, size of their operation and
number o f classes they attended for formal agricultural adult education.
Todd’s results stated that magazines and other farmers were leading sources of
information. Farmers used these sources of information to make changes in farming
practices or to look at trends in agriculture. Twenty-six percent of the farmers reported
using both adult classes and seed and fertilizer dealers as sources of information. Radio
and television reports were highly ranked. Only six percent used County Agricultural
Agents as a source of information. A small number of farmers said they used their own
judgement in agricultural practices (P. 10).

16
The 1960s
Progress report 111 "Trends in use of Recommended Farm Practices and of Farm
Information Sources in 12 Kentucky Neighborhoods" by C. Milton Cougheuour and N.B.
Patel in 1962 was a summary and an interpretation of findings of surveys conducted in
1950, 1955, and 1960. It examined the use of 14 farming practices by farm operators
in twelve Kentucky neighborhoods. Farmers were broken down by educational levels.
Farmers were to select several practices gained and sources of information used in their
farming operations. Coughenour and Patel reported an increase in use of all sources of
information from 1950 to 1955. After 1955 all sources, except radio and television
which were introduced in 1955, declined as a source of information. Coughenour and
Patle suggested that influential factors causing this shift were of a general nature rather
than specific to certain groups of farmers (P. 7).
Four reasons were given for this shift in use of sources of information; shift of
agricultural agencies from personal contact to using the radio and television; a change
in the leadership of agricultural agencies; depressed conditions reduced motivation to use
agencies and diminishing local leadership of the organizations.
Farmers were asked to state whether they received any farm information from a
list of 14 sources.

The sources investigated were Cooperative Extension Service

personnel, Soil Conservation Service, Agricultural Stabilization Conservation programs,
vocational agricultural teachers, Kentucky Agricultural Experiment Station, newspapers,
magazines, radio, television, farm meetings, Extension letters, farm bulletins and dealers
and salesmen. It was noted that there was a general overall decline in the use of various
sources except radio and television. Radio scored very high as a media or channel of

17
information. Farm magazines ranked second and county agricultural letters ranked third.
The tables within the study showed that as land useability increased for different
types of farming, use of media and agricultural agencies for information also increased.
This was also true when the value of crops was broken down in neighborhoods. High
income neighborhoods utilized sources of information at an increased level. Findings
were taken from four studies completed within five years. The report was completed by
the Extension Editorial staff in 1963. The report stated that farmers did not differentiate
clearly between information sources and information channels.

For example, ". . .

neighbors and friends may have got their information from farm magazines in which case
the magazine is identified as a source, however, farm magazines may have gotten the
information from commercial firms or the College of Agriculture, in which case the
magazine is identified as a channel" (P .l).
The studies showed that farm magazines ranked very high as a source of farm
news. Also friends and neighbors and the farm advisor from Cooperative Extension
Service ranked very high. Those sources at the bottom were Vocational Agricultural
Teachers. These studies looked at specific types of information. Ranking also depended
on the types of information needed. For instance, if a source of information was on
typical small grain varieties, a neighbor or county farm advisor ranked at the top. For
sources of information on income tax experience, lawyers and certified public
accountants ranked at the top. For pasture improvement and saving on planting time,
county farm advisors and the farmer’s experience made up the top two percent reporting.
One of the four studies did differentiate between channels of communications and
asked growers to rank the most important channels. The top three channels were talking

18
with neighbors and friends, reading farm magazines and talking with a farm advisor.
Those which received no rank and were at the bottom of the list, were attending meetings
at the University of Illinois, attending meetings of farm organizations, or listening to
farm news and information on radio.
The final table given in the bulletin ranked the summary of information sources
from each of the four studies. Ranking in the top four were neighbors and friends, farm
magazines, the College o f Agriculture and farm advisors. The bottom four included
personal experience, radio, television and special services.
In a study by Richard Leslie Lee, PhD, University of Iowa in 1967, entitled "The
Flow of Information to Disadvantaged Farmers", it was observed that disadvantaged
farmers from 204 farms in two southern Missouri counties had ten commonly available
sources of farm information. Sources most often selected were, farm newspapers, farm
magazines, farm radio shows, television shows, County Extension Agents, Vocational
Agriculture Teachers, friends and neighbors, farm dealers and salesmen, college bulletins
and almanacs.
A Chi-square analysis of systematic differential data indicated that there were
significant differences between middle class and economically disadvantaged farmers in
using these sources of information. Lee stated that disadvantaged farmers, less than 40
years old, had significantly less positive judgments of friends and neighbors, dealers,
salesman, and collective personnel sources than older economically disadvantaged
farmers. The better educated, economically disadvantaged farmers with more than eight
years of education, had a more positive view of collective mass media, Vocational
Agriculture Teachers and collective personnel sources. However, they had a less positive

19
view of radio, friends and neighbors, dealers, salesmen and almanacs than did the less
educated economically disadvantaged farmer.
Lee’s data also indicated that middle-class farmers made far greater use of mass
media information sources and other additional sources of farm information. They had
larger farms and had been farming longer. They were aware of, and used recommended
farm practices at an increased rate. These farmers were active in more organizations,
were better educated, and had increasingly more optimistic views of farming than their
low income counterparts.
In a study by Jerry Lee Webb, "An Analysis of Delaware Farmers’ Sources of
Farm News and Information" completed in 1968, the goal was to find uses of media by
farmers. His survey instrument included various kinds of farm news and information,
this would help determine specific messages that could be used to develop
recommendations for improving the flow of farm news and information by the
Cooperative Extension Service.
Webb reported that farmers in Delaware received an average of 3.62 farm
magazines and newspapers, 1.5 daily newspapers and 1.35 weekly newspapers (P.24-32).
They had access to both radio and television. Farm magazines were rated high as a
source of information, followed by University of Delaware specialists, county agents,
other farmers, newspapers, sales representatives and dealers. Both weekly and daily
newspapers received by farmers did not contain enough farm information and were not
considered by farmers as important except as sources for farm market information.
Webb also reported, "one of the serious questions facing the Cooperative Extension
Service is how it can continue to serve a declining farm population that demands more

20
sophisticated services and programs, and at the same time serve a growing
non-agricultural audience" (P.2).

The 1970s
In 1979, Calvin Jones, Paul B. Sheatsley and Arthur L. Stinchcombe completed
a report on the "Dakota Farmers and Ranchers Evaluate Crop and Livestock Surveys"
for the National Opinion Research Center. This research involved telephone interview
surveys in 1978, o f 1,681 farmers of North and South Dakota. These farmers divided
into those who produce crops, and those who raise livestock and also by the size and
scale of their operation, large versus small. The questionnaires were divided in two
major sections. One dealt with the information gathering strategies of operators. The
other was their attitudes and beliefs about the quality of USDA crop and livestock
information. Farmers reported they received most of their crop and livestock information
from magazines, journals or newsletters (35%), mass media including newspapers, radio
or television (20%), agricultural agents including university, ASCS, and Extension
(16%), government documents including USDA publications and reports (13%), personal
contacts including business or friends (6%) and all other sources of information (3%).
"In general periodicals, other media and agricultural agents are each more commonly
named as primary sources than our government publications" (P. 16).
In their study "The Iowa Adult Farmer Perceptions and Value of Educational
Programs", Kenneth L. Smith and Allyn Kahler (1982) attempted to determine the level
of participation in educational programs by Iowa farmers. Smith and Kahler assessed the
perception of the value o f selected educational factors. They related these factors to the

21
agricultural-economic conditions of the group of Iowa farmers.
The population included 219 producers from a previous study by Crawford in
1968. They looked at perceived value of sources of technical information which ranked
on a scale from 1 to 9 with 1 being of no value and 9 being of great value. Farm
magazines received a rank o f 6.4, commercial companies-5.7, radio for agriculture-5.6,
agriculture bulletins-5.1, County Agricultural Stabilization and Conservation Service
personnel-5.0, County Cooperative Extension Service personnel-4.6, Soil Conservation
Service personnel-4.6, daily newspaper-4.6, television for agriculture-4.5, vocational
agriculture teachers-2.9 Land Grant College personnel-2.9 and Farmers Home
Administration personnel a ranking of 2.4 (P.46).
Smith and Kahler stated that farmers should be exposed more to services provided
by Cooperative Extension, Vocational Agriculture teachers and other segments of Land
Grant Colleges. Information could be delivered through media, such as farm magazine
since farmers continued to perceive publications as valuable sources of information.
A study on "Information Needs and Sources of Alabama Farmers", was conducted
in 1979 by James L. Stallings and George L. Harrison and published in the Journal of
Alabama Academy of Sciences. At the time, there was an interest in Alabama in the
kind o f information farmers needed for operating their farm business and where they
received this information from. Objectives for determining sources of information used
by farmers, were listed by several categories, including frequency of use, kind of
information needed, commodity groups, gross farm income level, years of formal
education and age of operator. A questionnaire was mailed to a sample of 1,335 farmers
in Alabama in April of 1977. Eighty-five percent of Alabama farmers reported that farm

22
magazines were used as a source for some of the information needed running their farm
business (P. 136). Other farmers or key farmers, were a source for 78% of the farmers
(P. 136).
The authors listed these sources as print media, electronic media and personal
sources. O f print media, besides farm magazines, crop and livestock reporting service
showed a 60% use and newspapers a 59% use. Radio programs and television programs
showed more than 50% use. Personal sources, other farmers, farm supply stores and
cooperatives, county ASCS offices and county Extension offices along with fertilizer
dealers and salesmen and experiment station specialists, showed over 50% use.
Vocational agricultural teachers and meetings at the university were very low, with 22%
use or lower.
Depending on the kind of information, other sources showed higher percentages.
If the kind of information was for fertilizer, insecticide or herbicide, then fertilizer and
chemical dealers or sales representatives showed a higher frequency of use. If prices of
crops and livestock were needed, radio was the most reported source. Newspapers and
television ranked within the top three. When identifying new farm practices in crop and
livestock enterprises, farm magazines were the number one source for these kinds of
information. Other farmers and county Extension offices ranked second or third for all
information of this type (P. 140).
Generalizations were made by sources and by farm income levels.

Use of

different sources of information goes up as the level of gross farm income level rises (P.
144). Different sources of information were used more, as education levels rose. The
relationship was true for most sources requiring reading, such as farm magazines and

23
newspapers but less for radio and television (P. 144).

Stallings and Harrison state,

"there was no consistent relationship between age and use of different specific sources
of information" (P. 144).

The 1980s
Richard L. Farnsworth and L. Joe Moffitt conducted a study entitled "Farmer
Perceptions and Information Resources:

A Quantitative Analysis for Agriculture

Economics Research" (winter, 1984). Their purpose was to investigate the role of public
and private information sources for informing farmers of yields of cotton plantations in
the California San Quinton Valley. Farnsworth and Moffitt stated that farmers frequently
sought information from multiple sources.
Farnsworth and Moffitt concluded that growers used publications to learn about
new products or practices.

Most farmers relied on other sources to learn about

applications of new products and ideas than ones which Farnsworth and Moffitt listed it
in their surveys. Results were inconclusive for Cooperative Extension Service research
personnel and other agricultural scientists. In their conclusions, they stated, "information
occupies an important position in the uncertain work environment, with which farmers
are involved" (P. 11).
In his study "Delivery of Agricultural Information to Small Farmers" completed
at the University of Missouri, Columbia, Milton N. Okai (1986) states that his purpose
was to look at how the farmer perceived the importance of agricultural information and
that of various program delivery systems. Farmers were grouped on the basis of age,
educational level, years of farming, gross income from the farm, size of the farm,

24
enterprises produced, prices received and types of farm businesses.

Sources and

channels that Okai considered were newspapers, magazines, radio and television,
vocational agriculture teachers, Cooperative Extension Service publications, friends and
neighbors, commercial dealers and area Cooperative Extension Service assistants.
Okai’s study consisted of 200 small farm families enrolled in the Small Farm
programming in Southeastern Missouri. Forty farmers were selected randomly. Data
was collected by personal interviews. He found the more educated the farmers, the more
they sought professional information. Farmers ranked Cooperative Extension Service
educational assistants, Cooperative Extension Service publications, friends and neighbors,
radio and television, newspapers and magazines, commercial dealers, area Extension
specialists and Vocational Agriculture instructors in that order. Farmers who had large
farms relied on newspapers and magazines more than farmers who had fewer acres to
farm.

Conclusions and Directions From Literature
A review of the literature and research studies through the 1950’s and early
1960’s revealed that many farmers reported receiving information primarily from other
farmers and secondly from farm magazines along with other sources. (Lionberger 1960
and Mawby 1959). As the decade changed, studies conducted in the 1970’s by Webb,
using Delaware farmers, found farm magazines moving to the top of the list. In the
study by Calvin C. Jones (1979), agriculture agents and university personnel rated higher
than the sources listed in the studies completed of 1950s and 1960s.
One of the important points brought out in most studies was the more educated

25
the farmer, the more he sought additional information sources.

Another underlying

theme was the higher the gross earnings, the more diverse the source of agricultural
information used.

Many traditional sources used, were other farmers and farm

magazines (Stallings and Harrison, 1979). Studies found farmers continued to perceive
publications as valuable sources of information (Smith and Kahler, 1982).

Hypotheses to be Tested
The literature reviewed by the researcher revealed many ways in which the study
objectives of the study and research questions could be tested. The hypotheses stated
were determined after reviewing past studies and from the research questions given in
Chapter I.
Hypothesis 1: There is a significant relationship between the age of the farmer
and the identified sources of information, used by fruit and vegetable farmers of
Southwest Michigan, for new agricultural practices.
Hypothesis 2; There is a significant relationship between the age of the farmer
and the identified channels of information, used by fruit and vegetable farmers of
Southwest Michigan, for new agricultural practices.
Hypothesis 3: There is a significant relationship between the number of years in
farming and identified sources of information, used by fruit and vegetable farmers
of Southwest Michigan, for new agricultural practices.
Hypothesis 4: There is a significant relationship between the number of years in
farming and identified channels of information, used by fruit and vegetable
farmers of Southwest Michigan, for new agricultural practices.
Hypothesis 5; There is a significant relationship between the size of the farm in
acres and identified sources of information, used by fruit and vegetable farmers
of Southwest Michigan, for new agricultural practices.
Hypothesis 6: There is a significant relationship between the size of the farm in
acres and identified channels of information, used by fruit and vegetable farmers
of Southwest Michigan, for new agricultural practices.

26
Hypothesis 7: There is a significant difference between male farmers and female
farmers, with regard to the use of identified sources of information for new
agricultural practices, among the fruit and vegetable farmers of Southwest
Michigan.
Hypothesis 8: There is a significant difference between male farmers and female
farmers, with regard to the use of identified channels of information for new
agricultural practices, among the fruit and vegetable farmers of Southwest
Michigan.
Hypothesis 9: There is a significant difference between full-time farmers and
part-time farmers, with regard to the use of identified sources of information for
new agricultural practices, among the fruit and vegetable farmers of Southwest
Michigan.
Hypothesis 10: There is a significant difference between full-time and part-time
farmers, with regard to the use of identified channels of information for new
agricultural practices, among the fruit and vegetable farmers of Southwest
Michigan.
Hypothesis 11: There is a significant difference between the levels of formal
education of farmers, with regard to the use of the identified sources of
information for new agricultural practices by fruit and vegetable farmers of
Southwest Michigan.
Hypothesis 12: There is a significant difference between the levels of formal
education of farmers, with regard to the use of the identified channels of
information for new agricultural practices by fruit and vegetable farmers of
Southwest Michigan.
Hypothesis 13: There is a significant difference between the types of farm
ownership, with regard to the use of identified sources of information by fruit and
vegetable farmers of Southwest Michigan, for new agricultural practices.
Hypothesis 14: There is a significant difference between the types of farm
ownership with regard to the use of the identified channels of information by fruit
and vegetable farmers of Southwest Michigan, for new agricultural practices.
Hypothesis 15: There is a significant difference between gross farm income, with
regard to the use of the identified sources of information by fruit and vegetable
farmers o f Southwest Michigan, for new agricultural practices.
Hypothesis 16: There is a significant difference between gross farm income, with
regard to the use of the identified channels by fruit and vegetable farmers of
Southwest Michigan, for new agricultural practices.

27
Summary
A search of past literature was reviewed by the author.

Over the past few

decades researchers have written various dissertations and journal articles on sources and
channels used by farmers to gain information on new agricultural practices. Sources and
channels used by farmers depended on various personal and farm characteristics. Sixteen
hypotheses were formulated from the objectives in Chapter I and the literature review of
Chapter II.

CHAPTER HI
METHODS AND PROCEDURES
The primary purpose o f this study was to determine and examine what sources
and channels fruit and vegetable growers of Southwest Michigan used in gaining
information on new agricultural practices. Other questions would determine if size, gross
dollar earnings, the amount of time farmers worked off the farm, age of the farmer,
amount of formal education and the number of years the person had been in farming, had
an effect on the use of sources or channels.
This chapter includes a description of the sample population, development of an
instrument, procedures used for data collection and a discussion of validity and
reliability. The response rate, data analysis types and procedures used are outlined for
each process.
The study was a survey research effort. Data was collected by maii through a
questionnaire, and information was analyzed and described using a computer software
program, SPSS P C + . The questionnaire mailed to the sample population, along with
a cover letter and postcard, was reviewed by the University Committee on Research
Involving Human Subjects.

28

29
Population and Sample
The population of this study included farmers from Southwest Michigan who were
on the Michigan State University Cooperative Extension Service office mailing list and
were identified as having requested fruit and vegetable information at least once. They
come from the counties of Allegan, Berrien, Cass, Kalamazoo and Van Buren.

To

control internal validity, the researcher asked individual counties to send the entire list.
The researcher then purged the lists of non farmer names, prior to random sampling.
From the five counties, using the microcomputer software SPSS P C + , a sample of 275
farmers were randomly drawn from 970 names.
Census figures for the five counties in Southwest Michigan indicated that there
were a total o f 2010 fruit and vegetable growers. Of these 1,446 were fruit growers
(Michigan Orchard Survey, 1986) and 564 were vegetable growers (Michigan
Commercial Vegetable Survey 1987).

Seventy-five percent of farms in Southwest

Michigan may have produced both fruits and vegetables.
The population of 970 fruit and vegetable growers on the mailing list of the five
counties of Allegan, Berrien, Cass, Kalamazoo and Van Buren represented 61 % of the
fruit and vegetable farm population.

Development of Instrument
The mail questionnaire was designed after specific research questions were
developed when considering the objectives of the study. The instrument was divided into
two parts (Appendix A). Part I asked farmers to identify their use of sources on a 5
point scale: 4 = Always Use, 3 = Usually Use, 2 = Sometimes Use, 1 = Seldom Use

30
and 0=N ever Use. The rating scale of 4 = Always Use, 3=Usually Use, 2=Sometimes
Use, 1 = Seldom Use and 0=N ever Use was repeated for question 2 for selected channels
in Part I o f the Survey.

Questions in Part II of the survey asked for background

information on their farm, and personal characteristics. Farm background and personal
characteristics included number of acres owned and rented, number of days the farmer
may have worked off the farm, current age of the farmer, extent of formal education,
number of years in farming, gender, type of farm ownership and gross dollar earnings
from the farming operation.
A cover letter was written describing the importance of the survey and giving
instructions on the completion of the survey (Appendix B). A postcard was also included
with the questionnaire and cover letter (Appendix C). The cover letter instructed the
farmers to fill out the entire questionnaire and to return the questionnaire and postcard
together. This process is used by the United States Census of Agriculture to maintain
confidentiality of respondents.

By checking the list of individuals who had returned

postcards, against the initial list of 275 farmers, the researcher was able to send a second
questionnaire, cover letter (Appendix D) and postcard for them to complete and return
as before. A third postcard was sent to non-respondents. This postcard explained the
importance of their response, to the project (Appendix E).

Surveys and postcards

returned were recorded daily (Appendix F).

Validity and Reliability
A jury of four experts were selected to establish validity of the instrument. Jury
members were a district horticulture agent, a fruit and vegetable specialist, an experiment

31
station coordinator and an agriculture education professor. They were selected on the
basis of academic background, knowledge of fruit and vegetable farmers and a
understanding of how farmers learn about new agricultural practices.

A copy of the

instrument was delivered to each judge and the researcher scheduled a meeting with each
member to evaluate the instrument. Jury members were asked to evaluate each question
of the instrument to determine if it could be understood, and would appropriately answer
the research questions.
After meeting with the judges and reviewing their concerns, the question about
the amount o f gross dollars earned on the farm was changed. It was moved to the end
of the survey. Members felt that some respondents would be uninclined to answer the
question and this would discourage them early in completing the instrument. The experts
provided assistance in addressing all three types of validity concerns, content-construct,
and face validity.
Reliability of the instrument was achieved through a number of techniques.
Randomness o f selection of the sample population was used.

Reliability was also

increased through selecting a large sample from the population and receiving a high
percentage o f responses from this sample population.

A reliability coefficient,

Cronbach’s Alpha, was completed by using SPSS P C + . An alpha coefficient of .72
"sources of information," and .86 for "channels of information" was computed.
Reliability has been defined in Educational Research an Introduction by Borg and Gall
(1983).

"The reliability of standardized tests is usually expressed as a reliability

coefficient that varies between values of .00 and 1.00, with 1.00 indicating perfect
reliability, which is never attained in practice, and .00 indicating no reliability. The

32
more closely a reliability coefficient is to the value of 1.00, the more the test is free of
error variance and is a measure of the true differences among persons in the dimension
assessed by the test" (Borg and Gall, 1983, p. 283). Alpha coefficients of .72 and .86
shows that the questions o f the survey instrument were reliable.
Copies of the instrument, cover letter and postcards were submitted to the
University Committee on Research Involving Human Subjects. The committee approved
the instrument and cover letters as submitted.

The author then proceeded with the

distribution of the survey instrument and process of data collection.

Distribution and Data Collection
After the computer selected 275 names, they were placed on a word processing
file to be merged with a cover letter. Each cover letter and follow up postcard included
the name of the potential respondent and an appropriate salutation. This allowed for
personalization of cover letters, postcards and envelopes.

All letters, surveys, and

postcards were printed on a laser printer which ensured letter quality printing.
individual identification number was written on each of the postcards.

An

Thisnumber was

the same as the one assigned to each name on the mailing list.
The cover letter assured respondents that their responses would be kept
confidential. It was printed on Cooperative Extension Service letterhead and co-signed
by the researcher and district horticulture agent, T. Mike Thomas. The survey consisted
of four printed pages compiled in magazine type 8 1/2" by 11" pages, then organized in
a fashion that made sure that none of the four pages would get separated. This made
reading easy by the respondents.

33
The entire package was mailed using first class postage with a return self
addressed and postage paid return envelope provided by the researcher, along with the
self addressed, postage paid postcard. The survey and postcard were to be returned
together to the researcher. This process allowed the researcher to determine who had
completed the survey, and keep the confidentiality of respondents.
The survey, cover letter and return postcard with its identifying number, was
mailed on Thursday, June 14, 1990. The author requested that the survey be completed
and returned with in three days. This allowed respondents Friday, Saturday and Sunday
to review their questionnaire, make appropriate selections, and return the survey. On
the following Monday and Tuesday, 90 surveys were returned. At the end of the week
the number of surveys received per day dropped off, along with postcard responses. As
surveys and postcards were returned and received in the Extension office, both were
stamped with the date, and their numbers were recorded.

Individual’s names were

checked off as having returned their questionnaire.
After a three week period, a second cover letter, a second survey identical to the
first, and postcard were sent on Thursday, July 5, 1990. A different colored pen was
used to write the assigned number on the second postcard, to determine the different
respondent periods. These individuals were given a two week period to respond. After
two weeks, individuals who had not returned postcards were sent a third mailing on July
19, 1990. This was a postcard reminding them of the importance of the survey and
requesting that they fill out one of the first prior surveys, and send them in immediately.
The cut off date for the last survey was July 30. Of the 275 surveys mailed, 210 were
returned, 190 (69%) were useable, 20 were unsatisfactory for use, or were blank.

34
Reasons people did not fill out the survey are in Appendix G.
Sixteen names were randomly selected from the list of 65 non-respondents. These
individuals were telephoned and only questions regarding selected background
information of part two of the survey instrument, were asked. This data was analyzed
to determine the differences between the sample population of farmers who returned their
surveys and the sample population of farmers, who had not returned their surveys
(Appendix H).

The results o f the telephone survey showed that their personal and

farming characteristics were the same as the people who had returned the survey.
However, the non-respondents were not asked to rate the selected sources of channels.
After receiving the 190 questionnaires, information on them was typed into the
microcomputer software package SPSS P C + for data analysis. The alpha level was set
in all cases at .05 level of significance, to achieve a 95% confidence level.

The

following statistical procedures were used to analyze the data. The first program selected
the frequencies of variables for descriptive statistics. Frequency counts, percents, valid
percents, and accumulative percents were determined for sources and channels of
information. Frequencies and comparisons were calculated with part two of the survey,
for questions regarding number of days worked off the farm, level of education, gender
of respondent, type of farm ownership and gross dollar earnings from the farm over the
past five years. Also completed were means, standard deviations and range, on Part II
of the survey for age of the farmer, number of years in farming, number of acres owned,
number of acres rented and farm size in acres.
Correlations were used to test the null hypotheses of independent variables, of age
of the farmer, number of years in farming and the size of the farm. Statistical t-tests

35
were performed on independent variables of the null hypotheses, stating differences of
gender and full-time versus part-time farmers, between any two group mean scores.
One-way Analysis of Variance (ANOVA) tests were used to test significant differences
of the null hypotheses determining sources and channels of information used, with more
than two means of independent variables, between types of formal education, types of
farm ownership and gross farm income. Scheffee or Tukey procedures as a post hoc
multiple comparison analysis were preformed at a .05 level of significance, with an
accompanying 95% confidence level for each F-Probability.

Summary
This chapter has outlined the methods and procedures used to implement the
study. A sample of 275 names was drawn from 970 fruit and vegetable growers in
Southwest Michigan on the Cooperative Extension Service mailing list in July of 1990.
The total return rate o f the survey instrument was, 190 surveys usable, 20 surveys not
usable or blank. This is a 69% usable rate of the 275 farmers selected randomly by the
computer software SPSS P C -k

Procedures used to statistically analyze data included

frequencies, percentages, means, standard deviations, correlations, t-test and ANOVAs.
Post hock comparisons were performed using Scheffee and Tukey tests at a 95%
confidence level.

CHAPTER IV
STUDY FINDINGS
The purpose o f the study was to determine the use of sources and channels by
fruit and vegetable farmers in five counties of southwest Michigan to gain information
on new agriculture practices. Also, to determine if selected personal and demographic
characteristics have an effect on sources or channels of information farmers used to gain
this information.

This chapter will describe the respondents of the survey statistically,

with tables and narratives, frequency of use of sources and channels selected by the
respondents and ranking of sources and channels.

Null hypotheses were tested of

respondents’ personal characteristics and the use of sources and channels of agricultural
information and the variables of 1) age, 2) number of years in farming, 3) farm size, 4)
gender, 5) time spent on or off the farm, 6) type of formal education 7) type of farm
ownership and 8) gross farm income. In addition a summary of the study findings was
presented.
As reported in Chapter III, 190 useable questionnaires were returned of 275
questionnaires mailed to farmers in five Southwest Michigan counties. This represented
a 69% return rate.

36

37
Description of Respondents
The respondents of the survey were fruit and vegetable farmers of five counties,
Allegan, Berrien, Cass, Kalamazoo and Van Buren, in Southwest Michigan. Selected
characteristics of a personal nature and also of their farms are displayed in Tables 1.
through 6. Of survey respondents 177 (94.7%) were male and 10 (5.3%) were female.
(See Table 1 and Figure 1) These percentages were identical to those reported in the
1987 Census of Agriculture for the United States, for these types of farms.

Table 1. N um ber and Percent of Male and Female F ruit and Vegetable F anners
Fruit and Vegetable Farmers
Characteristics__________ Number
Percent______________________________
Male
Female
Total

177
_1Q
187

94.7
5.3
100

Gender of Respondents

Males N-177
94.7%
Fem ales N-10
5.3%

Figure of 1. Gender of Respondents

38
As reported in Table 2 and Figure 2, 21 (11.2%) of the farmers had less than a
high school diploma, 95 (50.8%) had a high school diploma, 26 (13.9%) had a two year
degree and 45 (24.1 % had a four year degree or more.

Table 2.

N um ber an d Percent of Fruit and Vegetable Farm ers by F our
Educational Levels
F ruit and Vegetable Farm ers
Num ber
Percent

Characteristics

21
95
26

Less than High School
High School
Two Year Degree
Four Year Degree or more

A1
Total

187

11.2
50.8
13.9
24.1
100

Fruit & Vegetable Farms
Education Level

<hlgh school diploma
high school diploma
61%
L

^

11%

four year d e g r e e
24%

two year d e g re e
14%

Figure 2. Educational Levels of Sample Population

39
The number of owner operators, shown in Table 3 and Figure 3, was 146
(78.9%); 25 (13.5%) farms were partnerships and 14 (7.6%) farm corporations. These
number were very close to what was reported in the Census of Agriculture of the United
States for 1987.

Table 3.
N um ber and Percent of Fruit and Vegetable F anners by Type of
____________ Farm Ownership____________________________________________
F ruit and Vegetable Farm ers
Characteristics
Num ber
Percent
Owner operation
Partnership
Corporation
Total

146
25
_14
185

78.9
13.5

1A
100

Fruit & Vegetable Farms
Type of Farm Ownership

Owner Operator
78.9%
/

C orporation
7.6%

Partnership
13.5%
Figure 3. Type of Farm Ownership of Sample Population

40
The survey results showed 128 full-time farmers (69.99%) and 55 (30.19%) parttime farmers which are reported in Table 4 and Figure 4. These findings were different
from state averages which show almost an even 50/50 distribution in full-time and parttime farming (Michigan Agricultural Statistics 1987).

Table 4.
N um ber and Percent of F ruit and Vegetable F anners Farm ing
____________Full-Time and Part-Tim e__________________________________
F ruit and Vegetable Farm ers
Num ber
Percent

Characteristics

55
128
183

Part-Time
Full-Time
Total

30.1
69.9
100

Fruit & Vegetable Farms
Full Time & Part Time Farmers

^

II

ru n

T" ♦ _ _ _

i lino

I. •

^ /“■* />

i n= i ^ o

69.9%

A

P art Time
30.1%

Figure 4. Full-Time and Part-Time Farmers

41
When grouping the sample population by income, the responses showed an even
distribution among the income groups. Analysis of the income groups are revealed in
Table 5 and Figure 5, revealed that 34 farmers (19.54%) had incomes less than $5,000,
19 farmers (10.92%) had incomes of $5,001 to $10,000, 32 farmers (18.39%) had
incomes o f $10,001 to $25,000, 21 farmers (12.07%) had incomes of $25,001 to
$50,000, 26 farmers (14.94%) had incomes of $50,001 to $100,000, 24 farmers
(13.79%) had incomes of $100,001 to $250,000 and 18 farmers (10.35%) had incomes
over $250,000.
The typical farmer in this study can be described as 1) male, 2) works on his own
operation, 3) has a minimum o f a high school diploma or better, and 4) was a full-time
farmer.

Table 5.

Number and Percent of Fruit and Vegetable Farmers
in Seven Income Groups

Characteristics

F ruit and Vegetable Farm ers
Num ber
Percent

Income G roup
less than $5,000
$5,001 to $10,000
$10,001 to $25,000
$25,001 to $50,000
$50,001 to $100,000
$100,001 to $250,000
greater then $250,000
Total

34
19
32
21
26
24
M
174

19.54
10.92
18.39
12.07
14.94
13.79
10.35
100.00

42

Fruit & Vegetable Farms
Gross Income

Dollars
< $5000
$5001 to $10,000
$10,001 to $25,000
$25,001 to $50,000
$50,001 to $100,000
$100,001 to $250,000
> $250,000
15

20

25

30

35

40

Number of Farms

Figure 5. Gross Income Characteristics of Sample Population

The data in Table 6 showed the average age of the 188 farmers as 54 years old
(S.D. 14.59) with a range from 25 to 80 years of age. Michigan statistics shows the
average farmer age at 52 years (Michigan Statistical Analysis 1987). The 181 individuals
who responded, had been in farming 29 years (S.D. 14.38), with a minimum of 1 year
to a maximum of 60 years. This was higher than the national average of 18 years, found
by the Census of Agriculture United States 1987. The average size of 179 farms were
198 acres (S.D. 76.39), with a minimum of 1 acre to a maximum of 14,000 acres. This
was very close to the Michigan average of 202 acres per farm reported in the Census of
Agriculture United States 1987. The average number of acres owned by the 176 farmers
reporting was 177.2 acres (S.D. 762.32) with a minimum of 0 acres and a maximum of
14,000 acres.

Eighty-six of the respondents rented an average of 71.97 acres (S.D.

233.63). The range of rental land was from 0 acres to as many as 2,000 acres.

43
Table vt—
6. Selected
-*wv«v
mvivv^vu

Personal and F arm Characteristics of Farm ers

Characteristics

N um ber

M ean

Age
Years in Farming
Size o f Farm
Acres Owned
Acres Rented

188
181
179
176
86

54.17
28.97
197.65
177.20
71.97

S.D.

M IN

14.59
14.38
763.39
762.32
233.63

25
1
1
0
0

MAX
80
60
14,000
14,000
2,000

Overall, characteristics of the sample population answering the questionnaire were very
close to the characteristics of populations of the 1987 Census of Agriculture of the United
States and the Michigan Statistical Analysis of 1987.
Research Question 1: What was the frequency of use of selected sources and selected
channels o f information, by fruit and vegetable farmers selected from five counties in
Southwest Michigan, to gain information on new agricultural practices?

Frequency of Use by Respondents
The first objective was to determine the use of twelve selected sources by farmers
to gain information on new agricultural practices. The survey population was asked to
rate how frequently they used twelve sources, on a 5 point scale. The categories were
4 = Always Use, 3 = Usually Use, 2 = Sometimes Use, 1 = Seldom Use and 0 =
Never Use. The frequencies and percentages are listed in Table 7.
The researcher grouped the sources according to categories. He combined the
scores of the responses in the categories of Always Use and Usually Use, to determine
the number of farmers who used a specific source of information. The data displayed
in Table 7 showed that 77 farmers (41.6%), used Cooperative Extension Service
personnel, 65 farmers (35.7%) used Product Company Representatives, 61 Farmers
(33.7%) used

Farmers who were family members, and 52 farmers (28.2%) used

Farmers who were not family members. Vocational Agriculture Teachers were used by

Table 7 - Frequencies of Sources of Informa tion Used by Fruit and Vegetable Farmers
Sources of Information

Agricultural Stabilization Conservation
Service
County Cooperative Extension Service
Farmers Home Administration
Farmers who are family members
Farmers who are not family members
Local Sales people
Michigan State University Specialist
Private Consultants
Product Company Representatives
Soil Conservation Service
Vocational Agriculture Teacher
Other Sources

4 = Always Use
Frequency (Percent)

17
23
1
22
10
4
9
18
22
5
•*
4

(9.3% )
(12.4%)
( .6%)
(12.2%)
(5.4%)
( 2.2%)
(5.0% )
(10.1%)
(12.1%)
(2.7% )
( 2.9%)

3 = Usually Use
Frequency (Percent)

Combined
4 and 3
(Percent)

26
54
8
39
42
40
31
21
43
20
1
4

43 (23.5%)
77(41.6%)
9 ( 5.2%)
61 (33.7%)
52 (28.2%)
44(24.5%)
40(22.1%)
39(21.8%)
65 (35.7%)
25 (13.7%)
1 ( .5%)
8 (5.8%)

(14.2%)
(29.2%)
( 4.6%)
(21.5%)
(22.8%)
(22.3%)
(17.1%)
(11.7%)
(23.6%)
(11.0%)
( -5%)
( 2.9%)

2 = Sometimes Use
1 = Seldom Use
Frequency (Percent) Frequency (Percent)

55
74
13
52
70
75
65
25
69
55
7
37

Respondents were asked how frequently they used sources on a 5 point scale (4 Always U se.............. 0 never use)
**None Reported

(30.1%)
(40.0%)
(7.4%)
(28.7%)
(38.0%)
(41.9%)
(35.9%)
(14.0%)
(37.9%)
(30.2%)
(3.7%)
(26.6%)

51
21
40
24
32
32
37
27
25
46
23
19

(27.9%)
(11.4%)
(22.9%)
(13.3%)
(17.4%)
(17.9%)
(20.4%)
(15.1%)
(13.7%)
(25.3%)
(12.8%)
(13.7%)

0 = Never Use
Frequency (Percent)

34
13
113
44
30
28
39
88
23
56
149
75

(18.5%)
(7.0%)
(64.5%)
(24.3%)
(16.4%)
(15.7%)
(21.6%)
(49.1%)
(12.7%)
(30.8%)
(83.0%)
(54.0%)

Combined
1 and 2
(Percent)

85 (46.4%)
34 (18.4%)
153 (18.4%)
68 (37.6%)
62 (33.8%)
60(33.6%)
76 (42.0%)
115 (64.2%)
58 (26.4%)
102(56.1%)
172 (95.8%)
94(67.6%)

45
1 fanner (.5%), 8 farmers (5.8%) used Other Sources and 25 fanners (13.7%) used Soil
Conservation Service personnel and placed on the Seldom Use or Never Use end of the
scale.
The ranked, means and standard deviations in Table 8 of the sources of
information, revealed similar results. Farmers sources of information, ranked means and
standard deviations were Cooperative Extension Service Personnel, (2.29, 1.05) first and
second Product Company Representatives (2.09, 1.17). Those sources of information
with a ranked means and standard deviations of Farmers who are family members (1.84,
1.34) and Farmers who are not family members (1.84, 1.12) tied for third, fourth, Local
Sales People (1.78, 1.04), fifth Agricultural Stabilization Conservation Service (ASCS)
Personnel (1.68, 1.20), sixth Michigan State University Specialist (1.64, 1.14), seventh
Soil Conservation Service (SCS) Personnel (1.30, 1.10) and eighth Private Consultants
(1.18, 1.41).

Sources of information of ranked means and standard deviations were

Other Sources (.87, 1.08) ninth, Farmers Home Administration (FmHA) personnel (.54,
.86) tenth and Vocational Agricultural Teachers (.22, .53) eleventh. These results were
consistent with past studies (Stallings and Harrison, 1980), mentioned in Chapter II.

46
Table 8.

Ranked M eans of Sources of Inform ation Use by F ruit and
Vegetable Farm ers

Sources of Inform ation

Rank

M ean

Std. Dev.

County Cooperative Extension Service
Product Company Representatives
Farmers who grg family members
Farmers who are not family members
Local Sales people
Agricultural Stabilization Conservation Service
Michigan State University Specialist
Soil Conservation Service
Private Consultants
Other Sources
Farmers Home Administration
Vocational Agriculture Teacher

1
2
3
3
5
6
7
8
9
10
11
12

2.29
2.09
1.84
1.84
1.78
1.68
1.64
1.30
1.18
.87
.54
.22

1.05
1.17
1.34
1.12
1.04
1.20
1.14
1.10
1.41
1.08
.86
.53

The second part of Research question one asked how frequently selected channels
were used by fruit and vegetables farmers for information on new agricultural practices.
Farmers were given 18 choices of categories for channels. The data in Table 9 shows
the frequencies and percentages of use of channels of information by the 190 farmers
who completed the survey. The data in Table 9 shows selected channels having high
percentages in the categories o f Always Use or Usually Use, the researcher combined
the categories. The combined data revealed 104 (56%) farmers selected farm magazines
as the most used channel of information. Agricultural bulletins from Michigan State
University and other universities were second; 93 farmers (50%) selected the top two
categories.

Weekly or Monthly Agricultural Newsletters were used by 88 farmers

(49%). Word of mouth from other farmers as a channel of information was chosen by
75 farmers (41%) of these combined categories.
Those at the opposite end of the rating scale with large percentages in the Seldom
Use and Never Use categories were led by Video Tape reported by 160 farmers (90%).

47
One hundred and fifty-nine farmers (87%) selected Seldom Use and Never Use for the
channel o f Microcomputer Communications and 93 farmers (51%) selected Seldom Use
and Never Use for the channel of Field Days and Twilight Tours.

Table 9.

Frequencies of Channels of Information Used by Fruit and Vegetable Farmers

Channels of Information

Agricultural bulletins from MSU
and other universities
Agricultural Newsletters
Agricultural Trade Shows
Daily Newspapers
Demonstration plots on trials on farms
Direct Mailings
Farm Magazines
Field Days and Twilight Tours
Microcomputers
Office visits to ASCS, CES, FmHA, SCS
Radio Advertisements and programs
Television Advertisements and programs
Telephone recordings
Using the telephone to contact ASCS,
CES, FmHA, SCS
Video Tapes
Weekly or monthly ag newsletters
Word of mouth from other farmers
Other

4 = Always Use
Frequency (Percent)

3 = Usually Use
Frerpiency (Percent)

Combined
4 and 3
(Percent)

2 = Sometimes Use
1 = Seldom Use
Frequency (Percent) Frequency (Percent)

0 = Never Use
Frequency (Percent)

Combined
1 and 2
(Percent)

23
10
20
27
4
20
42
3
3
11
12
5
8

(12.5%)
(5.5%)
(11.2%)
(14.6%)
(2.2%)
(11.0%)
(22.7%)
( 1-7%)
( 1.7%)
(6.1%)
(6.5%)
(2.7%)
(4.5%)

70
40
41
46
21
48
62
14
5
29
19
5
20

(38.0%)
(22.1%)
(22.9%)
(24.9%)
(11.5%)
(26.4%)
(33.5%)
( 7.7%)
( 2.8%)
(16.0%)
(10.3%)
( 2.7%)
(11.2%)

93 (50.5%)
50(27.6%)
61 (34.1%)
73(39.5%)
25 (13.7%)
68 (37.4%)
104 (56.2%)
17(9.4%)
8 ( 4.5%)
40(22.1%)
31 (16.8%)
10(5.4%)
28(15.7%)

69
56
55
54
72
67
54
71
14
63
62
50
34

(37.6%)
(30.9%)
(30.7%)
(29.2%)
(39.6%)
(36.8%)
(29.2%)
(39.2%)
(7.7%)
(34.8%)
(33.7%)
(27.2%)
(19.1%)

17
41
27
42
49
24
12
46
31
48
45
59
30

( 9.2%)
(22.7%)
(15.1%)
(22.7%)
(26.9%)
(13.2%)
(6.5%)
(25.4%)
(17.1%)
(26.5%)
(24.3%)
(32.1%)
(16.9%)

5
34
36
16
36
23
15
47
128
30
46
65
86

(2.7%)
(18.8%)
(20.1%)
( 8.6%)
(19.8%)
(12.6%)
(8.1%)
(26.0%)
(70.7%)
(16.6%)
(25.2%)
(35.3%)
(48.3%)

22(11.9%)
75 (41.5%)
33 (35.2%)
58(31.6%)
85 (46.7%)
47(25.8%)
27 (14.6%)
93(51.4%)
159 (87.8%)
78(43.1%)
91 (49.5%)
124(67.4%)
116(65.2%)

24
1
39
21
3

(13.1%)
( -6%)
(21.5%)
(11.5%)
(2.5%)

45
5
49
54
8

(24.6%)
(2.8%)
(27.1%)
(29.5%)
( 6.6%)

69 (37.7%)
6(3.4% )
88 (48.6%)
75(41.0%)
11 (9.1%)

51
12
55
85
37

(27.9%)
(6.7%)
(30.4%)
(46.5%)
(30.6%)

32
47
16
16
26

(17.5%)
(26.4%)
(8.8%)
( 8.7%)
(21.5%)

31
113
22
7
47

(16.9%)
(63.5%)
(12.2%)
(3.8%)
(38.8%)

63 (34.4%)
160(89.9%)
38(21.0%)
23 (12.5%)
73 (60.3%)

"Respondents were asked how frequently they used on a S point scale (4 Always Use

0 never use)

■P*.
oo

49
The channels o f information were ranked using means computed from the farmer
responses. The data in Table 10 shows the ranking, means, and standard deviations.
The ranking of each channel's means and standard deviations revealed those at
the top, were Farm Magazines (2.56, 1.15) first, Agricultural Bulletins from Michigan
State University and other universities second, Weekly or Monthly agriculture newsletters
(2.37, 1.26) came third, Word of mouth from other farmers (2.26, .93) fourth, Daily
Newspapers (2.14, 1.18) fifth and Direct Mailings (2.10, 1.16) sixth. Channels with a
mean and standard deviation of Using the telephone to contact ASCS, CES, FmHA and
SCS and Agricultural Trade Shows (1.90, 1.28) tied for seventh, Agricultural
Newsletters (1.73,1.16) ninth, Office visits to ASCS, CES, FmHA and SCS (1.69,1.11)
tenth. Tied for eleventh in the ranking, were Demonstration plots for trials on farms
(1.49, 1.01) and Radio advertisements and programs (1.49, 1.16).

Field Days and

Twilight Tours (1.34, 1.00) ranked thirteenth, Other Channels (1.12, 1.08) ranked
fourteenth, Telephone recordings (1.07,

1.24) ranked fifteenth and Television

Advertisements and programs (1.05, .99) ranked sixteenth. Those with ranked means
and standard deviations at the bottom of the categories were Video Tape (.51, .79) at
seventeenth and Microcomputer Communications (.48, .88) at eighteenth.
Farm Magazines, Agricultural bulletins and Weekly and monthly agricultural
newsletters have been used by farmers for many years.

Literature shows Farm

Magazines ranking first in many of the past surveys (Agricultural Communications
Research Report -14, 1963). Sources and channels of information categorized as Other
were given by respondents and are displayed in Appendix H.

50
Table 10.
Ranked M eans of Channels of Inform ation Used by Fruit and
____________ Vegetable Farm ers_____________________________________________
Channels of Inform ation

R ank

1
Farm Magazines
2
Agricultural Bulletins
Weekly or monthly Ag Newsletters
3
4
Word of Mouth from other farmers
Daily Newspapers
5
Direct Mailings
6
Using the telephone to contact ASCS, CES, FmHA,
7
and SCS
Agricultural Trade Shows
7
9
Agriculture Newsletters
10
Office visits to ASCS, CES, FmHA, SCS
Demonstration plots or trials on farms
11
11
Radio Advertisements and programs
Field Days and Twilight Tours
13
14
Others Channels
Telephone Recordings
15
16
Television Advertisements and programs
17
Video Tape
Microcomputer Communications
18

M ean

Std. Dev.

2.56
2.48
2.37
2.36
2.14
2.10

1.15
.92
1.26
.93
1.18
1.16

1.99
1.99
1.73
1.69
1.49
1.49
1.34
1.12
1.07
1.05
.51
.48

1.28
1.28
1.16
1.11
1.01
1.16
1.00
1.08
1.24
.99
.79
.88

Testing of Null Hypotheses Using Correlations
The hypotheses reported in Chapter II were investigated. All of the hypotheses
were converted to null hypotheses for statistical analysis. Null hypotheses were tested
based on use of identified sources and channels of information and by the fruit and
vegetable farmers and selected characteristics.

The five point rating scale for testing

was:
4
3
2
1
0

=
=
=
=
=

Always Use
Usually Use
Sometimes Use
Seldom Use
Never Use

A significant P-value was set at .05 to obtain a confidence level of 95%.

51
Null Hypothesis 1: There is no significant relationship between the age of the farmer
and the identified sources of information, used by fruit and vegetable farmers of
Southwest Michigan, for new agricultural practices.
Analysis of the items used to test the hypotheses 1-6 are displayed as correlations
in Table 11. Data revealed that younger farmers used the sources of information of (1)
Farmers who are family members, (corr = -.22, n=180, p= .002), (2) Farmers who are
not family members (corr=-.27, n=183, p= .00), (3) Local Sales People (corr= .32,
n=177, p = .0 0 ), (4) Private Consultants (corr=-.19, n=178, p=.009) and (5) Other
Sources (corr=-.24, n=138, p=.004). These were significantly more than sources used
by older farmers.
Since significant differences were found relationships between the age of the
farmer in years and the identified sources of information the researcher rejected the null
hypothesis. The alternate hypothesis which stated that there is significant relationships
between the age of the farmer and the identified sources of information used by fruit and
vegetable farmers of Southwest Michigan for new agricultural practices was accepted.

Null Hypothesis 2: There is no significant relationship between the age of the farmer
and the identified channels of information used by fruit and vegetable farmers of
Southwest Michigan, for new agricultural practices.
Data shown in Table 12 revealed that older farmers used the following channels
of information significantly more than younger farmers (1) Agricultural Bulletins
(corr=.21, n-183, p=.003), (2) Daily Newspapers (corr=.20, n-184, p= .006), and (3)
Direct Mailings (corr=.17, n=181, p=.018).
Younger farmers used the following channels of information significantly more
than their older counterparts:

(1) Agricultural Trade Shows (corr=-.23, n=178,

p=.002), (2) Microcomputer Communications (corr=.17, n=180, p= .01), (3) Using

52
Table 11.

Correlation Between Sources
Characteristics of Respondents

of

Sources of Information

AGE
Correlation
(Number)
P=value

Agricultural Stabilization Conservation Personnel

-.04

Information

EXPERIENCE
Correlation
(Number)
P=value
.03

t i 82k

and

Selected
FARM SIZE
Correlation
(Number)
P=value
.02
k 1747>3

.01
( 184)
P= .89

-.05

-.09
( 174)
P= .21

-.09
( 170)
P = .21

-.22
( 180)
P= .002*

L
P=m)
.63

-.27
( 183)
P= .00*

-.29
( 177)
P= .00*

-.32
( 177)
P= .00*

-.21
( 172)
P= .005*

P= .73

Michigan State University Specialist

-.04
IP=m.56
x

.00
( 174)
P= .91

-.00
( 172)
P= .96

Private Consultants

-.19
( 178)
P= .009*

-.04
( 172)
P= .59

.21
( 170)
P= .004*

-.08

L
P=18!>
.24

-.00
( 175)
P= .97

.08
( 173)
P= .28

.12
( 181)
P= .09

.15
( 175)
P= .04*

L
P=

Vocational Agriculture Teacher

-.06
( 179)
P= .36

-.01

-.04

Other Sources

-.24
( 138)
P= .004*

-.23
( 133)
P= .007*

.04
( 130)
P= .63

Cooperative Extension Service Personnel

Farmers Home Administration

Farmers who are family members

Farmers who are not family members

Local Sales People

Product Company representatives

Soil Conservation Service Personnel

*P-value of less than .05 shows a correlation.

-.06
k 17? ,

-.03

.04

L
l6V
P= .52
.11
( 172)
P= .11
.02

IP=l75J
.70
-.02

I l69J

.01
.79

53
Table 12.

Correlation Between Channels
Characteristics of Respondents

of Information

and

AGE
Correlation
(Number)
P=value

EXPERIENCE
Correlation
(Number)
P=value

Agricultural Bulletins

.21
( 183)
P= .003+

.11
( 177)
P= .12

iP=17
9
.78

Agricultural Newsletter

-.01
( 180)
P= .85

-.04
179
P = .58

L

.08
( 172)
P = .29

Agricultural Trade Shows

-.23

-.11
( 173)
P= .11

.06
( 170)
P = .39

Demonstration plots or trials on farms

.002*

P= .004*

-.07

-.00

L
7.975l
P=1

.09
( 173)
P= .20

.14
( 175)
P= .06

.00
( 173)
P = .99

i8y
.31

.17
( 181)
P= .01*

Farm Magazines

-.03

.02

Field Day & Twilight Tours

-.05

.06

Microcomputer Communications

-.17

I. 00

Direct Mailings

Office Visits

U17?;

-.00
( 176)
P= .96

.05

U7?,
.03

P= .01*

-.15
( 175)
P= .04*

.13
( 172)
P= .07

-.05
P=18<&
.50

-.01
( 174)
P= .80

.00
( 172)
P= .92

L
Radio Advertisements and programs

.02

.20
( 184)
P= .006*

l
P=

.21

FARM SIZE
Correlation
(Number)
P=value

II

Daily Newspapers

IP=

00

Channels of Information

.06

.06

-.00

L
179
P = .74

.02

.01
( 174)
P= .80

L
P=lllX
.09

-.17
( 172)
P= .02*

.00
( 169)
P= .99

-.14
( 182)
P= .04*

-.14
( 176)
P= .05

.05
( 174)
P= .47

S.i82io
Television advertisements and programs

.02
P= .73

Telephone recordings

Using the Telephone to contact ASCS,
CES,FmHA, SCS

-.12

Selected

54
Table 12 (cont’d)

Channels of Information

ACE
Correlation
(Number)
P=value

EXPERIENCE
Correlation
(Number)
P=value

FARM SIZE
Correlation
(Number)
P=value

Video Tape

-.28

-.22
( 172)
P= .003+

.10
( 169)
P = .16

Weekly or monthly Ag Newsletter

-.15
( 180)
P= .04+

Word of mouth from other farmers

Other Channels

-.03

.02

L m)
P= .60

iP =17?)
.75

iP =18?.00+
L

-.10
( 176)
P= .16

.00
( 174)
P= .93

-.22
( 121)
P = .01*

-.16
( 116)
P= .07

.01
( 115)
P = .85

-.20

*P-value of less than .OS shows a correlation.

55
the telephone to contact ASCS, CES, FmHA and SCS personnel (corr=-.14, n=182,
p = .0 4 ), (4) Video Tape (corr=-.28, n=177, p = .0 0 ), (5) Weekly or monthly
agricultural newsletters (corr=-.15, n=180, p = .0 4 ), (6) Word of mouth from other
farmers (corr=-.20, n=181, p = .0 0 ) and (7) Other Channels (corr=-.22, n=121,
p = .0 1 ).
Because significantly different relationships were found between the age of the
farmer in years and the identified channels of information used, the researcher rejected
the null hypothesis.

The alternate hypothesis which stated that there is a significant

relationship between the age of the farmer and the identified channels of information used
by fruit and vegetable farmers of Southwest Michigan for new agricultural practices was
accepted.

Null Hypothesis 3: There is no significant relationship between the number of years in
farming and the identified sources of information used by fruit and vegetable farmers of
Southwest Michigan, for new agricultural practices.
Data shown in Table 11 revealed that Farmers with less years in farming used
these sources of information:

(1) Farmers who are not family members (corr=.29,

n= 177, p = .0 0 ), (2) Local Sales People (corr=-.21, n=172, p= .005) and (3) Other
Sources (corr=-.23, n=133, p= .007), significantly more than farmers with more
experience in farming.
Farmers with more years in farming used the sources of information of the Soil
Conservation Service personnel (corr=.15, n=175, p= .04) significantly more, than
farmers with less years in farming.
Because significant relationships were found between the number of years in

56
farming and the identified sources o f information used by farmers, the researcher rejected
the null hypothesis.

The alternate hypothesis which stated that there is a significant

relationship between the number of years in farming and the identified sources of
information used by fruit and vegetable farmers of Southwest Michigan for new
agricultural practices was accepted.

Null Hypothesis 4: There is no significant relationship between the number of years in
farming and identified channels of information, used by fruit and vegetable farmers of
Southwest Michigan, for new agricultural practices.
Data shown in Table 12 revealed that farmers with more years in farming used
the channel of information of Daily Newspapers (corr=.21, n=178, p=.004)
significantly more than farmers with fewer years in farming. Also farmers with fewer
years

in farming used the channels of information of (1) Microcomputers

Communications (corr=-.15, n=175, p= .04), (2) Telephone Recordings (corr=-.17,
n-172, p = .0 2 ) and (3) Video Tape (corr=-.22, n = 172, p= .003) significantly more, than
farmers with more years in farming.
Because significant relationships were found between the number of years in
farming and the identified channels of information used by farmers, the researcher
rejected the null hypothesis.

The alternative hypothesis which stated that there is a

significant relationship between the number of years in farming and the identified
channels of information used, by fruit and vegetable farmers of Southwest Michigan for
new agricultural practices, was accepted.

Null Hypothesis 5: There is no significant relationship between the size of the farming
acres and identified sources of information, used by fruit and vegetable farmers of
Southwest Michigan, for new agricultural practices.

57
Data shown in Table 11 revealed a significant relationship between the size of the
farm in acres and the use of individual sources of information. The larger the farm in
acres the more the farmer used Private Consultants (corr=.21, n=170, p= .004) as a
significant source of information.
Because significant relationships were found between the size of the farm in acres
and the identified sources used by farmers, the researcher rejected the null hypothesis.
Table 11 shows numbers, P-values and correlations, between sources of information used
by fanners, their age in number of years, and size of their farm in acres. The alternate
hypothesis, which stated that there is a significant relationship between the size of the
farm in acres and the selected sources of information used, by fruit and vegetable farmers
of Southwest Michigan, for new agricultural practices, was accepted.

Null Hypothesis 6: There is no significant relationship between the size of the farm in
acres and identified channels of information, used by fruit and vegetable farmers of
Southwest Michigan, for new agricultural practices.
Data in Table 12 reveals correlations computed between the size of the farm in
acres and the identified channels of information. No significant differences were found
after computing p-values of the correlations.

The researcher accepted the null

hypothesis. There were no significant relationships between the size of the farm in acres
and the identified channels of information used by fruit and vegetable farmers of
Southwest Michigan for new agricultural practices.
Table 12 shows numbers, p-values and correlations, between channels of
information used by farmers, their Age in number of years, and Size of their farm in
acres.

58
To test the stated null hypotheses of single pairs means, the researcher utilized
t-tests.

Significance was set at 95% confidence level and two-tail probabilities were

identified for significant differences of less than .05. The following null hypotheses were
tested for difference between male farmers and female farmers with regard to the use of
identified sources and channels of information.

Null Hypothesis 7: There is no significant difference between male farmers and female
farmers with regard to the use of identified sources of information for new agricultural
practices, among the fruit and vegetable farmers of Southwest Michigan.
The two-tailed probability of the t-tests were computed on the differences of
means of male farmers and female farmers, with regard to the use of the identified
sources of information. Data in Table 13 showed that 168 male farmers with a mean of
1.82 and standard deviation of 1.34, utilized Local Sales People significantly more than
eight female farmers with means of .75 and a standard deviation of .70. The t-value for
the means was 2.93 and two-tail probability was significant at .004.
One hundred and sixty-seven male farmers with a mean of 1.22 and standard
deviation of 1.41, utilized Private Consultants significantly more than 9 female farmers
with a mean of .22 and a standard deviation of .66. The t-value for these means was
2.12 and the two-tail probability was significant at .03. Table 13 shows all means,
standard deviations, numbers, t-values and two-tail probabilities.
Because significant differences were found in the use of identified sources of
information the researcher rejected the null hypothesis between male farmers and female
farmers.

The alternate hypothesis which stated that there is a significant difference

between male farmers and female farmers with regard to the use of identified sources of

59
information for new agricultural practices by fruit and vegetable farmers of Southwest
Michigan, was accepted.

60
Table 13.

Results of t-test for Differences of Gender on Sources of Information
for New Agricultural Practices

Sources of Information
Agricultural Stabilization Conservation Service
Personnel

Male
Mean
S.D.
(Number)

Female
Mean
S.D.
(Number)

1.69
1.20
(171)

1.33
1.25

t-value

2-Tail
Prob.

.88

.38

-.48

.68

(9)

2.27
1.05
(173)

2.44
1.01

Fanner Home Administration

.54
.87
(164)

.50
.75
(8)

.15

.87

Farmers who are family members

1.84
1.34
(170)

1.77
1.30

.15

.88

(9)

Farmers who are not family members

1.83
1.10
(171)

1.90
1.37
(10)

-.18

.86

Local Sales people

1.82
1.02
(168)

.75
.70
(8)

2.93

.004*

Michigan State University Specialist

1.65
1.11
(169)

1.22
1.39

1.12

.26

2.12

.03*

Cooperative Extension Service Personnel

Private Consultants

(9)

(9)

1.22
1.41
(167)

(9)

Product Company Representatives

2.14
1.16
(170)

1.11
1.05
(9)

2.62

.10

Soil Conservation Service Personnel

1.29
1.08
(171)

1.22
1.39

.19

.85

(9)

Vocational Agriculture Teachers

.23
.54
(169)

.12
.35
(8)

.54

.58

Other Sources

.87
1.06
(129)

.85
1.57
(7)

.04

.96

*Significantly less than .05 level for two-tail probability

.22
.66

61
Null Hypothesis 8: There is no significant difference between male farmers and female
farmers with regard to the use of identified channels of information for new agricultural
practices, by fruit and vegetable farmers of Southwest Michigan.
The two-tail probability of the t-test were computed on the differences in the
means of male farmers and female farmers with regard to the use of the identified
channels o f information. The data in Table 14 revealed that 168 male farmers with a
mean of 1.93 and standard deviation of 1.26, utilized Agriculture Trade Shows
significantly more than 8 Female farmers with a mean of .87 and a standard deviation
of 2.3. The two-tail probability was significant at .02.
Because significant difference were found between male farmers and female
farmers the researcher rejected the null hypothesis. The alternate hypothesis which stated
that there is a significant difference between male farmers and female farmers with
regard to their use of identified channels of information for new agricultural practices
among fruit and vegetable farmers of Southwest Michigan was accepted.

62
Table 14.

Results of t-test for Differences of Gender on Channels of Information
for Agricultural Practices
Male
Mean
S.D.
(Number)

Female
Mean
S.D.
(Number)

2.45
.91
(172)

2.88
1.16
(9)

-1.37

.17

Agricultural Newsletters

1.71
1.15
(170)

2.12
1.35
(8)

-.97

.33

Agricultural Trade Shows

1.93
1.26
(168)

.87
.99
(8)

2.33

.02*

Daily Newspapers

2.16
1.16
(173)

1.44
1.23
(9)

1.81

.07

Demonstration plots on trialson farms

1.49
.96
(170)

1.33
1.65
(9)

.47

.64

Direct Mailings (letters)

2.08
1.14

2.10
1.44

-.03

.97

(1 6 9 )

(1 0 )

Farm Magazines

2.57
1.16
(172)

2.20
.91
(10)

1.00

. 31

Field Days and Twilight Tours

1.35
.98
(170)

.87
1.24
(8)

1.34

.18

Office visits to ASCS, CES,FmHA, SCS

1.70
1.11
(170)

1.44
1.23
(9)

.67

.50

R a d io A d v e rtise m e n ts and n ro o rn m s

1

1^2

67

.5 0

1.16
(172)

1.20
(9)

Television Advertisements and programs

1.05
.97
(172)

.88
1.16
(9)

.49

.62

Telephone recordings

1.10
1.24
(167)

.50
1.06
(8)

1.35

.17

2.01
1.25
(171)

2.00
1.73
(9)

.03

.97

Channels of Information
Agricultural bulletins from MSU
and other universities

Using the telephone to contact ASCS, CES,
FmHA, SCS

Video Tape

2-Tail
t-value Prob.

.53
.00
No variance for independent sample t-test one or more samples had no variance

63
Table 14 (cont’d)
Male
Mean
S.D.
(Number)

Female
Mean
S.D.
(Number)

Weekly or monthly ag newsletters

2.41
1.26
(169)

1.66
1.11
(9)

1.74

.08

Word of mouth from other farmers

2.38
.92
(170)

2.10
1.10
(10)

.95

.34

Other Channels

1.12
1.08
(114)

1.00
1.00
(5)

.25

.80

Channels of Information

"Significantly different at less than .05 for two-tail probability

2-Tail
t-value Prob.

64
To determine if full-time farmers utilized identified sources or channels of
information differently from part-time farmers, t-test were computed to test the following
null hypotheses.

Null Hypothesis 9: There is no significant difference between full-time farmers and parttime farmers, with regard to the use of identified sources of information for new
agricultural practices, among fruit and vegetable farmers of Southwest Michigan.
Table 15 shows the means, standard deviations, numbers, t-values and two-tail
probabilities. Two-tail probabilities of t-tests were computed on the difference in the
means between full-time farmers and part-time farmers with regard to the use of the
identified sources of information.

No significant differences in means were found

between full-time farmers and part-time farmers. Therefore, the researcher must accept
the null hypothesis.

65
Table 15.

Results of t-test Results for Differences Between Part-Time and
Full-Time Farmers for Sources of Information Used.
Full-Time
Mean’
S.D.
(Number)

Part-Time
Mean
S.D.
(Number)

1.71
1.22
(126)

1.64
1.14
(53)

.37

.71

2.32
1.04
(126)

2.14
1.06
(55)

1.06

.29

Farmers Home Administration Personnel

.54
.83
(118)

.50
.89
(53)

.23

.81

Farmers you are family members

1.85
1.38
(122)

1.81
1.23
(55)

.16

.87

Farmers you are not family members

1.81
1.11
(124)

1.80
1.11
(55)

.08

.93

Local sale people

1.69
.96
(120)

1.90
1.15
(54)

-1.29

.20

Michigan State University Specialists

1.69
1.09
(123)

1.52
1.09
(54)

.92

.35

Private Consultants

1.18
1.38
(122)

1.16
1.45
(53)

.05

.96

Product Company Representatives

2.00
1.11
(124)

2.27
1.25
(54)

-1.43

.15

Soil Conservation Service

1.29
1.11
(123)

1.32
1.07
(55)

-.19

.84

Vocational Agriculture Teacher

.18
.46
(122)

.29
.66
(54)

-1.23

.22

Other Sources

.94
1.10
(93)

.64
1.00
(42)

1.51

.13

Sources or Information
Agricultural Stabilization Conservation
Service Personnel

County Cooperative Extension Service
Personnel

•Significant at less than .05 level for two-tail probability.

t-value

2-Tail
Prob.

66
To determine if full-time farmers utilized identified channels of information
different from part-time farmers, t-test were computed on the following hypotheses.

Null Hypothesis 10: There is no significant difference between full-time farmers and
part-time farmers, with regard to the use of identified channels of information for new
agricultural practices, among fruit and vegetable farmers of Southwest Michigan.
Two-tail probabilities of the t-tests were computed on the difference in the means,
between full-time and part-time fruit and vegetable farmers of Southwest Michigan, with
regard to the use of the identified channels of information. The data in Table 16 shows
significant differences between 82 full-time farmers with a mean of 1.29 and a standard
deviation of 1.07, and 38 part-time farmers with mean of .78 and standard deviation of
1.04, with regard to their use of, Other channels, of information. The t-value mean was
2.41 and the two-tail probability was significant at .01. Table 16 shows means, standard
deviations, numbers, t-values and two-tail probabilities.
Because significant differences were found between full-time farmers and parttime farmers in their use of, Other Channels, of information, the author rejected the null
hypothesis. The alternate hypothesis which stated that there is a significant difference
between full-time farmers and part-time farmers in their use of identified channels of
information for new agricultural practices, among fruit and vegetable farmers of
Southwest Michigan, was accepted.

67
Table 16.

Results of t-test for Differences Between Part-Time and Full-Time
Farmers for Channels of Information Used
Full-time
Mean
S.D.
(Number)

Part-time
Mean
S.D.
t-value
(Number)

Agricultural Bulletins

2.52
.95
(125)

2.36
.86
(55)

1.09

.27

Agricultural Newsletters

1.60
1.17
(123)

1.96
1.13
(54)

-1.07

.06

Agricultural Trade Shows

1.91
1.27
(121)

1.83
1.27
(54)

.40

.68

Daily Newspapers

2.15
1.22
(125)

2.11
1.11
(53)

.24

.81

Demonstration plots or trials on farms

1.53
1.02
(125)

1.39
.92
(53)

.86

.39

Direct mailings

2.15
1.16
(124)

1.88
1.12
(53)

1.41

.16

Farm Magazines

2.52
1.18
(126)

2.64
1.10
(54)

-.66

.51

Field Days and Twilight Tours

1.40
.96
(123)

1.18
1.04
(54)

1.37

.17

Microcomputer Communications

.52
.91
(123)

.37
.78
(54)

1.04

.29

Office visits to ASCS, CES, FmHA, SCS

1.69
1.10
(123)

1.70
1.14
(54)

-.02

.98

Radio Advertisements

1.57
1.14
(124)

1.23
1.13
(55)

1.81

.07

Television Advertisements

.99
.91
(125)

1.14
1.08
(54)

-.99

.32

Telephone Recordings

1.14
1.23
(122)

.82
1.23
(52)

1.57

.11

Using the telephone to contact ASCS, CES, FmHA, SCS

2.00
1.28
(125)

1.92
1.28
(54)

.35

.72

Channels of Information

2-Tail
Prob.

68
Table 16 (cont’d)

Channels of Information

Full-time
Mean
S.D.
(Number)

Part-time
Mean
S.D.
t-value
(Number)

2-Tail
Prob.

Video tape

.53
.82
(120)

.46
.71
(54)

Weekly or monthly Ag Newsletter

2.37
1.28
(123)

2.33
1.23
(53)

.16

.86

Word of mouth from other farmers

2.39
.96
(124)

2.25
.89
(54)

.89

.37

Other Channels

1.29
1.07
(82)

.78
1.04
(38)

2.41

.01+

*Significant at less than .05 level for two-tail probability

.54

.59

69
One-Way Analysis o f Variance (ANOVA) tests were used to determine
differences in the means of sources and channels of information, when multiple variables
were used.

These variables included four types of education, three types of farm

ownership and seven groups of farm income. The F-Probability was set at a .05 to
achieve a confidence level of 95%.

Null Hypothesis 11: There is no significant difference between the levels of formal
education of farmers with regard to the use of the identified sources of information for
new agricultural practices, by fruit and vegetable farmers of Southwest Michigan.
One-Way Analysis of Variance (ANOVA) tests were computed for educational
levels of less than high school, high school diploma, a two year degree, and a four year
degree or more, with regard to the use of identified sources of information used by fruit
and vegetable farmers of Southwest Michigan. The data shown in Table 17 revealed a
significant difference when farmers used, Other Sources. Table 17 shows all F-Ratios
and F-Probabilities. For numbers, means and standard deviations see Appendix I.

Table 17.

One-Way Analysis of Variance of Sources when Considering Type of
Formal Education of Fanners

Sources of Inform ation

F-Ratio

Agricultural Stabilization Conservation Personnel
County Cooperative Extension Agent
Farmers Home Administration Personnel
Farmers who arg family members
Farmers who are not family members
Local sales people
Michigan State University Specialist
Private Consultants
Product Company Representatives
Soil Conservation Service Personnel
Vocational Agriculture Teacher
Other Sources

1.95
1.19
.68
.51
2.45
2.00
.31
1.70
1.56
.84
1.51
3.09

♦Significant at less than .05 level.

F-Probability
.12
.31
.56
.67
.06
.11
.81
.16
.20
.47
.21
.02*

70
One-Way (ANOVA) tests computed for. Other Sources, and levels of formal
education revealed a F-Probability of .02.

A Tukey post hoc comparison revealed

significant differences between farmers with less than a high school diploma with a mean
of .38 and standard deviation of .76, and farmers with a four year degree or more with
a mean of 1.30 and standard deviation of 1.23. Farmers with a four year degree or more
used, Other Sources more than farmers with less than a high school diploma.
Since significant differences were found between farmers with less than a high
school degree and farmers with a four year degree or more, the researcher rejected the
null hypothesis.

The alternate hypothesis which stated that there is a significant

difference between the levels of formal education of farmers and the identified sources
of information for new agricultural practices by fruit and vegetable farmers of Southwest
Michigan was accepted.

Null Hypothesis 12: There is no significant difference between the levels of formal
education of farmers with regard to the use of the identified channels of information for
new agricultural practices, by fruit and vegetable farmers of Southwest Michigan.
One-Way Analysis of Variance (ANOVA) tests were computed for levels of
education o f less than high school diploma, high school diploma, two year degree, and
four year degree or more, with regard to channels of information used by fruit and
vegetable farmers of Southwest Michigan.

The data shown in Table 18 revealed

significant difference in means calculated for farmers who used the channels of
Agriculture Trade Shows, Office visits to ASCS, CES, FmHA, SCS, Using the telephone
to contact ASCS, CES, FmHA, SCS and Video Tape. Table 18 shows all F-Ratios and
F-Probabilities. For number, means and standard deviations, see Appendix J.

71
Table 18.

One-Way Analysis of Variance of Channels When Considering Type
of Formal Education of Farmers

Channels of Inform ation

F-Ratio

Agricultural Bulletins
Agricultural Newsletters
Agricultural Trade Shows
Daily Newspapers
Demonstration plots or trials on farms
Direct mailings
Farm Magazines
Field Days and Twilight Tours
Microcomputer Communications
Office visits to ASCS, CES, FmHA, SCS
Radio advertisements and programs
Television advertisements and programs
Telephone recordings
Using the telephone to contact ASCS, CES,
FmHA, SCS
Video Tape
Weekly or monthly Ag Newsletters
Word of mouth from other farmers
Other channels

.47
1.69
4.62
.26
1.64
.15
.68
.77
.94
2.86
1.23
1.81
1.49

.70
.16
.003*
.85
.18
.92
.56
.50
.41
.03*
.29
.14
.21

3.65
3.80
2.60
1.30
.32

.01*
.01*
.05
.27
.80

F-Probability

^Significant a t the less th an .05 level

One-Way Analysis of Variance (ANOVA) tests computed for the channel,
Agricultural Trade Shows, and levels of formal education, shows a F-Probability of .003.
A Tukey post hoc comparison revealed significant difference in mean between farmers
with less than a high school diploma (mean of .88 and a standard deviation of .99), and
the other three groups of farmers with a high school diploma (mean of 1.93 and a
standard deviation of 1.30), farmers with a two year degree (mean of 2.04 and standard
deviation of 1.12) and farmers with a four year degree or more (mean of 2.16 and a
standard deviation of 1.21). Farmers with a high school diploma or more, used the
channel of Agricultural Trade Shows significantly more than farmers with less than a

72
high school diploma, for information on new agricultural practices.
An ANOVA computed for the channel of Office visits to ASCS, CES, FmHA and
SCS, and levels of formal education revealed a F-Probability of .03. A Tukey post hoc
comparison reveal significant differences of means between farmers with less than high
school diploma, (mean of 1.36 and standard deviation of 1.11), and farmers with a two
year degree (mean of 2.20 and standard deviation of 1.19). Farmers with a two year
degree used Office visits to USDA agencies as a channel of information, more than
farmers with less than a high school diploma for information on new agricultural
practices.
An ANOVA computed between the channel of Using the telephone to contact
ASCS, CES, FmHA and SCS, and levels of formal education, shows a F-Probability of
.01.

A Tukey post hoc comparison revealed significant difference in mean between

farmers with less than a high school diploma, (mean of 1.45 and standard deviation of
1.50), and farmers with a two year degree (mean of 2.53 and standard deviation of
1.30). Farmers with a two year degree, used the telephone to contact USDA agencies,
as a channel of information more than farmers with less than a high school diploma.
An ANOVA computed between the channel of Video Tape and levels of formal
education, shows a F-Probability of .01.

A Tukey post hoc comparison revealed

significant difference in mean between farmers with less than a high school diploma
(mean of .06 and a standard deviation of .25) and farmers with a two year degree (mean
of .88 and a standard deviation of 1.12). Farmers with a two year degree used Video
Tape as a channel of information more than farmers with less than a high school
diploma.

73
Because significant differences were found for the levels of formal education with
regard to identified channels of information, the null hypothesis was rejected.

The

alternate hypothesis which stated that there is a significant difference between the levels
of formal education o f farmers and the identified channels of information for new
agricultural practices by fruit and vegetable farmers of Southwest Michigan was accepted.

Null Hypothesis 13: There is no significant difference between the types of farm
ownership with regard to the use of identified sources of information by fruit and
vegetable farmers of Southwest Michigan, for new agricultural practices.
One-Way Analysis of Variance (ANOVA) tests were computed for types of farm
ownership, owner operator, partnerships and corporations with regard to sources of
information used by fruit and vegetable farmers of Southwest Michigan for new
agricultural practices. F-Probabilities revealed significant difference in means, between
the types of farm ownership, and the sources of information of Farmers Home
Administration Personnel, Farmers who are family members, Michigan State University
Specialist, Private Consultants and Other Sources. Table 19 shows all F-Ratios and FProbabilities, for numbers, means and standard deviations see Appendix K.

•

74
Table 19.

One-Way Analysis of Variance of Sources when Considering Type of
Ownership of Farmers

Sources of Inform ation

F-Ratio

Agricultural Stabilization Conservation Personnel
County Cooperative Extension Personnel
Farmers Home Administration Personnel
Farmers who a s family members
Farmers who are not family members
Local sales people
Michigan State University Specialist
Private Consultants
Product Company Representatives
Other Sources
Soil Conservation Service Personnel
Vocational Agriculture Teacher

.33
.56
5.9
3.05
.42
.57
4.44
4.94
1.18
4.34
.57
.74

F-Probability

.71
.57
.003*
.04*
.65
.56
.01*
.008*
.30
.01*
.56
.47

‘ Significant at the less th an .05 level.

An ANOVA computed for the source of Farmers Home Administration personnel,
and types of farm ownership revealed a F-Probability of .003.

Tukey post hoc

comparison revealed significant difference in means, between owner operators, (mean
of .44 and standard deviation of .76), and partnerships (mean of 1.08 and standard
deviation of 1.25).

Partnerships used the source of Farmers Home Administration

personnel, significantly more than owner operators for information on new agricultural
practices.
An ANOVA computed for the source of Michigan State University Specialist, and
type o f farm ownership, revealed a F-Probability of .01. A Tukey post hoc comparison
revealed significant difference in means, between owner operators (mean of 1.52 and
standard deviation of 1.13), and corporations, (mean of 2.30 and standard deviation of
1.03).

Corporations used the source of Michigan State University Specialists

75
significantly more than owner operators for information on new agricultural practices.
An ANOVA computed for, Other Sources, of information, and types of farm
ownership, revealed a F-Probability of .01.

A Tukey post hoc comparison revealed

significant difference in means, between owner operators, with a (mean of .72 and
standard deviation of 1.02), and partnerships, with a (mean of 1.44 and standard
deviation o f 1.14). Partnerships used, Other Sources, significantly more than owner
operators for information on new agricultural practices.
The Tukey or Scheffee post hoc comparisons could not find differences of means
scores on sources of information used by Farmers who are family members with a FProbability of .04 and Private Consultants with a F-Probability of .008.

Because

significant differences were found between the types of farm ownership, and identified
sources of information, the null hypothesis was rejected. The alternate hypothesis which
stated that there is a significant difference between the types of farm ownership with
regard to the use of identified sources of information by fruit and vegetable farmers of
Southwest Michigan for new agricultural practices, was accepted.

Null Hypothesis 14: There is no significant difference between the types of farm
ownership with regard to the use of the identified channels of information by fruit and
vegetable farmers, for new agricultural practices.
One-Way Analysis of Variance (ANOVA) tests were computed for types of farm
ownership, owner operators, partnerships, and corporation, with regard to identified
channels of information used by fruit and vegetable farmers. Data shown in Table 20
revealed significant difference in means, between the types of farm ownership and these
channels of information Agriculture Trade Shows, Telephone Recordings, Video Tape

76
and Other Channels. Table 20 shows all F-Ratios and F-Probabilities, for numbers,
means and standard deviations see Appendix L.

Table 20.

One-Way Analysis of Variance of Channels W hen Considering Type
of Ownership of Farm ers

Channels of Inform ation

F-Ratio F-Probability

Agricultural Bulletins from MSU and other Universities
Agricultural Newsletters
Agricultural Trade Shows
Daily Newspapers
Demonstration plots or trials on farms
Direct mailings
Farm Magazines
Field Days and Twilight Tours
Microcomputer Communications
Office visits to ASCS, CES, FmHA, SCS
Radio advertisements and programs
Television advertisements and programs
Telephone recordings
Using the telephone to contact ASCS, CES,
FmHA, SCS
Video Tape
Weekly or monthly Ag Newsletters
Word of mouth from other farmers
Other channels

.68
1.16
7.32
.26
2.67
.10
2.34
2.89
.77
.23
.14
1.26
4.41

.50
.31
.0009*
.76
.07
.89
.09
.05
.46
.78
.86
.28
.01*

1.51
4.19
1.40
2.18
5.33

.22
.01*
.24
.11
.006*

^Significant a t less th an .05.

An ANOVA computed for the channel of Agricultural Trade Shows, and types
of farm ownership, revealed a significant F-Probability of .0009. A Tukey post hoc
comparison revealed significant difference in means between owner operators, with a
(mean of 1.69 and standard deviation of 1.25), and partnerships, with a (mean of 2.52
and standard deviation of 1.15), also corporations, with a (mean of 2.61 and a standard
deviation o f .86). Partnerships and corporations used the channel of Agricultural Trade

77
Shows significantly more than owner operators, for information on new agricultural
practices.
An ANOVA computed for the channel of Telephone recordings, and types of farm
ownership, revealed a significant F-Probability of .01. A Tukey post hoc comparison
revealed significant difference in means, between owner operators, with a (mean of .97
and a standard deviation of 1.23), and partnerships, with a (mean of 1.76 and a standard
deviation of 1.30). Partnerships used the channel of Telephone recordings, significantly
more than owner operators, for information on new agricultural practices.
An ANOVA computed for the channel of Video Tape, and types of farm
ownership, revealed a significant F-Probability of .01. A Tukey post hoc comparison
revealed significant differences of means between owner operators, with a (mean of .44
and standard deviation of .75) and corporations, with a (mean of 1.07 and standard
deviation of 1.11). Corporations used the channel of Video Tape, significantly more than
owner operators, for information on new agricultural practices.
An ANOVA computed for Other Channels, and types of farm ownership revealed
a significant F-Probability of .006. A Tukey post hoc comparison revealed significant
difference in means between owner operators, with a (mean of .93 and standard deviation
of 1.03) and partnerships, with a (mean of 1.68 and standard deviation of 1.05).
Partnerships used the channel of Other Channels, significantly more than owner
operators, for information on new agricultural practices.
The Tukey or Sheffee post hoc comparisons could not find differences of mean
scores of the channel of information of Telephone recordings with an F-Ratio of 4.41 and
an F-Probability of .01.
Because significant differences were found between types of farm ownership with

78
regard to identified channels of information, the null hypothesis was rejected.

The

alternate hypothesis which stated that there is a significant difference between the types
of farm ownership with regard to the use of identified channels of information by fruit
and vegetable farmers of Southwest Michigan for new agricultural practices was
accepted.
To determine if gross farm income had a significant effect on the use of sources
or channels of information used by fruit and vegetable farmers of Southwest Michigan
for new agricultural practices, One-Way Analysis of Variance (ANOVA) tests were
computed on the following null hypotheses.

Null Hypothesis 15: There is no significant difference between gross farm incomes with
regard to the use of identified sources of information by fruit and vegetable farmers of
Southwest Michigan, for new agricultural practices.
One-Way Analysis o f Variance (ANOVA) tests were computed for gross farm
income groups, including:
Group
Group
Group
Group
Group
Group
Group

1
2
3
4
5
6
7

=
=
=
=
=
=
=

less than $5,000
$5,001 to $10,000
$10,001 to $25,000
$25,001 to $50,000
$50,001 to $100,000
$100,001 to $250,000
greater than $250,000

with regard to identified sources of information used by fruit and vegetable farmers.
Data shown in Table 21 revealed significant difference in means, between income
groups, and these sources of information Farmers who are family members, Michigan
State University Specialists, Private Consultants and Other Sources. Data in Table 21
shows all F-Ratios and F-Probabilities, for numbers, means and standard deviations see
Appendix M.

79
Table 21.

One-Way Analysis of Variance of Sources when Considering Gross
Farm Income

Sources of Inform ation

F-Ratio

Agricultural Stabilization Conservation Personnel
County Cooperative Extension Personnel
Farmers Home Administration Personnel
Farmers who ai£ family members
Farmers who are net family members
Local sales people
Michigan State University Specialist
Private Consultants
Product Company Representatives
Soil Conservation Service Personnel
Vocational Agriculture Teacher
Other Sources

1.22
1.21
1.20
4.84
1.66
1.13
4.60
3.47
.76
1.74
.91
3.41

F-Probability
.29
.30
.30
.0001*
.13
.34
.0002*
.003*
.59
.11
.48
.003*

^Significant at the less th an .05 level
An ANOVA computed for the source of Farmers who are family members, and
gross farm income, revealed a significant F-Probability of .0001. A Tukey post hoc
comparison revealed significant difference in means, between group 3, ($10,001 to
$25,000) with a (mean of 1.12 and a standard deviation of 1.31) and other groups,
including group 5 ($50,001 to $100,000) with a (mean of 2.42 and a standard deviation
of 1.27) and group 6, ($100,001 to $250,000) with a (mean of 2.50 and standard
deviation of 1.01). Farmers with farm incomes of $50,001 to $250,000 used the source
of Farmers who are family members, significantly more than farmers with farm income
of $10,001 to $25,000 for information on new agricultural practices.
An ANOVA computed for the source of Michigan State University Specialist and
gross farm income, revealed a significant F-Probability of .0002. A Tukey post hoc
comparison revealed significant difference in means between income group 1, (less than
$5,000) with a (mean of 1.16 and standard deviation of 1.18) and other income groups,

80
including groups 5, ($50,001 to $100,000) with a (mean of 2.15 and standard deviation
of 1.18) and income group 6, ($100,001 to $250,000) with a (mean of 2.04 and a
standard deviation of .70) and income group 7, (greater than $250,000) with a (mean of
2.27 and a standard deviation o f .82). Farmers with farm income of $50,001 to greater
than $250,000, used the source of Michigan State University Specialist, significantly
more than farmers with farm incomes of less than $5,000, for information on new
agricultural practices.
An ANOVA computed for the source, Private Consultants, and gross farm income
revealed a significant F-Probability of .003. A Tukey post hoc comparison revealed
significant difference in means between income group 1, (less than $5,000) with a (mean
of .64 and a standard deviation of 1.11), and income group 7 (greater than $250,000)
with a (mean of 2.11 and a standard deviation of 1.49). Significant difference in means
were found between income group 2, with a (mean of .56 and standard deviation of 1.15)
and income group 7.

Farmers with farm incomes of more than $250,000, used the

source, Private Consultants, significantly more than farmers with farm income less than
$10,000, for information on new agricultural practices.
An ANOVA computed for Other Sources and gross farm income revealed a
significant F-Probability of .003. A Tukey post hoc comparison revealed significant
difference in means, between income group 7, with a (mean of 1.60 and standard
deviation of .73) and other income groups including income group 1, with a (mean of
.53 and standard deviation of 1.10), and income group 2, with a (mean of .30 and
standard deviation of .75). Farmers with farm income more than $250,000 used Other
Sources significantly more than farmers with less than $10,000, for new agricultural
practices.

81
Because significant differences were found in the means between gross farm
income groups, with regard to identified sources, the null hypothesis was rejected. The
alternate hypothesis which stated that there is a significant difference between gross farm
incomes with regard to the use of identified sources of information by fruit and vegetable
farmers of Southwest Michigan for new agricultural practices, was accepted.

Null Hypothesis 16: There is no significant difference between gross farm income with
regard to the use of the identified channels by fruit and vegetable farmers of Southwest
Michigan, for new agricultural practices.
One-Way Analysis o f Variance (ANOVA) tests were computed for these groups
of gross farm income:
Group
Group
Group
Group
Group
Group
Group

1
2
3
4
5
6
7

=
=
=
=
=
=

less than $5,000
$5,001 to $10,000
$10,001 to $25,000
$25,001 to $50,000
$50,001 to $100,000
$100,001 to $250,000
greater than $250,000

with regard to identified channels of information used by fruit and vegetable farmers of
Southwest Michigan. Data shown in Table 22 revealed significant difference in means,
between the above income groups and these channels of information o f Agriculture Trade
Shows, Farm Magazines, Field Days and Twilight Tours, Using the telephone to contact
ASCS, CES, FmHA and SCS, Video Tape, Weekly and monthly agriculture newsletters
and Other Channels. Table 22 shows all F-Ratios and F-Probabilities, for numbers,
means and standard deviations see Appendix N.

82
Table 22.

One-Way Analysis of Variance of Channels when Considering Gross
Farm Income

Channels of Inform ation

F-Ratio F-Probability

Agricultural Bulletins from MSU and other universities
Agricultural Newsletters
Agricultural Trade Shows
Daily Newspapers
Demonstration plots or trials on farms
Direct mailings
Farm Magazines
Field Days and Twilight Tours
Microcomputer Communications
Office visits to ASCS, CES, FmHA, SCS
Radio advertisements and programs
Television advertisements and programs
Telephone recordings
Using the telephone to contact ASCS, CES,
FmHA, SCS
Video Tape
Weekly or monthly Ag Newsletters
Word of mouth from other farmers
Other channels

.70
1.00
7.31
.74
2.07
1.00
2.31
4.49
1.41
1.21
.74
.83
1.55

.64
.42
.00*
.61
.05
.42
.03*
.0003*
.21
.30
.61
.54
.16

2.55
2.90
5.12
2.02
3.05

.02*
.01*
.0001*
.06
.008*

^Significant at the less th an .05 level
An ANOVA computed for the channel, Agriculture Trade Shows, and gross farm
income, revealed a significant F-Probability of .00.

A Tukey post hoc comparison

revealed significant difference in means, between income group 1, (less than $5,000)
with a (mean of 1.43 and a standard deviation of 1.33), and other income groups
including income group 6 ($100,001 to $250,000) with a (mean of 2.54 and a standard
deviation of .93) and income group 7 (greater than $250,000) with a (mean of 3.05 and
a standard deviation of .80). Farmers with farm income more than $100,001 used the
channel, of Agricultural Trade Shows, significantly more than farmers with farm income
of less than $5,000, for information on new agricultural practices.
A Tukey post hoc comparison detected a significant difference between income

83
group 2, with a (mean of 1.00 and standard deviation of 1.11), and other income groups
including income group 5 with a (mean of 2.15 and standard deviation of 1.15), and
income groups 6 and 7. Farmers with farm incomes of $50,001 to more than $250,000,
used the channel of Agriculture Trade Shows significantly more than farmers with farm
income o f $5,001 to $10,000, for information on new agricultural practices.
A Tukey post hoc comparison detected significant difference in means, of income
groups between income group 3 with a (mean of 1.71 and standard deviation of 1.32),
also income group 4 with a (mean of 1.70 and standard deviation of 1.12), were
significantly different from the mean of income group 7. Farmers with farm incomes
of more than $250,000 used the channel of Agricultural Trade Shows, significantly more
than farmers with farm income of $10,001 to $50,000, for information on new
agricultural practices.
An ANOVA computed for the channel, Field Days and Twilight Tours, and gross
farm income, revealed a significant F-Probability of .0003.

A Tukey post hoc

comparison revealed significant difference in means between income group 1 with a
(mean of 1.06 and a standard deviation of 1.01), and income group 6 with a (mean of
1.83 and standard deviation of .86).

Farmers with farm incomes of $100,001 to

$250,000 used the channel, Field Days and Twilight Tours, significantly more than
farmers with farm income of less than $5,000, for information on new agricultural
practices.
Also found were difference in means, between income group 2 with a (mean of
.70 and standard deviation of .77), and other income groups including income group 6
and 7 with a (mean of 1.77 and standard deviation of .73). Farmers with farm income
of more than $100,001 used the channel, of Field Days and Twilight Tours, significantly

84
more than farmers with farm income of $5,001 to $10,000, for information on new
agricultural practices. Income group 4, with a (mean of .90 and standard deviation of
.85), was significantly different from the mean for income group 6. Farmers with farm
income of $100,001 to $250,000 used the channel, Field Days and Twilight Tours,
significantly more than farmers with farm income of $25,001 to $50,000, for information
on new agricultural practices.
An ANOVA computed for the channel, Using the telephone to contact ASCS,
CES, FmHA and SCS, and gross farm income, revealed a significant F-Probability of
.02. A Tukey post hoc comparison revealed significant difference in means, between
income group 1 with a (mean of 1.45 and a standard deviation of 1.09), and income
group 6 with a (mean of 2.58 and a standard deviation of .97). Farmers with farm
income of $100,001 to $250,000 used the channel, Using the telephone to contact ASCS,
CES, FmHA and SCS, significantly more than farmers with farm income of less than
$5,000, for information on new agricultural practices.
An ANOVA computed for the channel of Video Tape and gross farm income
revealed a significant F-Probability of .01.

A Tukey post hoc comparison revealed

significant difference in means, between income group 1 with a (mean of .20 and
standard deviation of .61), and income group 7 with a (mean of .93 and standard
deviation of .92). Farmers with farm income of more than $250,000, used the channel
of Video Tape significantly more than farmers with farm income of less than $5,000, for
information on new agricultural practices.
An ANOVA computed for the channel, Weekly or monthly agricultural
newsletters, and gross farm income, revealed a significant F-Probability of .0001. A
Tukey post hoc comparison revealed significant difference in means, between income

85
group 1 with a (mean of 1.70 and standard deviation of 1.36), and other income groups
including income group 6 with a (mean 2.91 and standard deviation of .88) and income
group 7 with a (mean o f 3.22 and standard deviation of .94).

Also detected were

difference in means, between income group 2 with a (mean of 1.76 and standard
deviation of 1.30), and income groups 6 and 7. Farmers with farm incomes of more
than $100,001 use the channel, Weekly or monthly agricultural newsletters, significantly
more than farmers with farm income less than $10,000, for information on new
agricultural practices.
An ANOVA computed for the channel of Other Channels and gross farm income,
revealed a significant F-Probability of .008. A Tukey post hoc comparison revealed
significant difference in means between income group 1 with a (mean of .50 and standard
deviation of .80), and income group 7, with a (mean of 1.75 and a standard deviation of
.86). Farmers with farm income greater than $250,000, used the channel Other Channels
significantly more than farmers with farm income of less than $5,000, for information
on new agricultural practices.
Tukey or Scheffee post hoc comparisons were unable to determine the significant
difference between the groups of means computed for farm income, and the identified
channel, Farm Magazines, with a significant F-Probability of .03.
Because significant differences were found between the means computed for gross
farm income groups with regard to identified channels, the null hypothesis was rejected.
The alternate hypothesis which stated that there is a significant difference between gross
farm income with regard to the use of identified channels of information by fruit and
vegetable farmers of Southwest Michigan for new agricultural practices was accepted.

86
Non-Respondents
The researcher sought to determine if there was a significant difference between
respondents to the survey and non-respondents to the survey, after the survey deadline
of July 30, 1990. Sixteen names were randomly selected of the 65 non-respondents.
Sixteen represents approximately 25% of the non-respondent group.

These 16

individuals were telephoned and asked about selected characteristics from Part II of the
survey, including their current age, number of years in farming, total number of acres
farmed, total number of acres owned and the total number of acres rented. It was found
by using t-test on respondents that there was no significant difference between
respondents and non-respondents (Appendix H). It was therefore determined, that there
was no significant difference between the two groups, personal and farm characteristics
and that information received on the respondent would not be different statistically, even
if all 275 surveys had been received.

Summary
Sources used by the respondents were ranked in the following order; Cooperative
Extension personnel followed by Product Company Representatives, Farmers who are
family members, Farmers who are not family members, Local Sales People, Agricultural
Stabilization Conservation Service Personnel, Michigan State University Specialists, Soil
Conservation Service Personnel, Private Consultants, Other Sources, Farmers Home
Administration and Vocational Agricultural Teachers.
Of channels used, the ranking was as follows: Farm Magazines, Agricultural
Bulletins, Weekly or monthly Ag Newsletters, Word of Mouth from other farmers, Daily
Newspapers, Direct Mailings, Using the telephone to contact ASCS, CES, FmHA, SCS,

87
Agricultural Trade Shows, Agriculture News Letters, Office visits to ASCS, CES,
FmHA, SCS, Demonstration plots or trials on farms, Radio Advertisements and
programs, Field Day and Twilight Tours, Others Channels, Telephone Recordings,
Television

Advertisements

Communications.

and

programs,

Video

Tape,

and

Microcomputer

CHAPTER V

SUMMARY
The first part o f Chapter V contains a discussion of the research questions,
procedures used by the researcher, and results from various statistical tests. The second
section includes major conclusions reached from the findings for sources and channels
of information used by farmers to receive new information on agricultural practices.
Implications, based on study findings are discussed in the third section. Limitations that
were encountered in the study are presented in section four. The final section states
recommendations for future research in this important area of dissemination of
information.
As cost of direct mail rises and commercial companies increase their use of
advertising in all forms of media, agricultural educators, both formal and non-formal,
must direct their energies toward the delivery of unbiased agricultural information, iney
must use the most sought after and least costly information channels used by farm
operators. This delivery must be in a form which can be easily accessible to all types
of farmers. Farm types have changed over the past 30 years. According to the Census
of Agricultural for the United States, more of our farm operators are operating part-time.
Farms had become larger in acreage, overall, and farmers had increased access to a
greater variety of channels.

88

89
Agricultural educators faced a challenge to know our audience and their needs for
agricultural information. It was with this challenge in mind that this study was designed.
The focus of the study was to find answers to the questions of farmer use of selected
agricultural information sources and channels.

It was also important to determine if

selected personal and demographic characteristics had an effect on these sources or
channels, by investigating fruit and vegetable farmers from five counties in Southwest
Michigan.
To accomplish the stated purposes the following objectives were established:
1. To determine what sources of information fruit and vegetable farmers, in
selected Southwest Michigan counties used, to receive information on
agricultural practices.
2. To determine what channels of information fruit and vegetable farmers, in
selected Southwest Michigan counties used, to receive information on
agricultural practices.
3. To determine if part-time farmers differ from full time farmers in their
selection of sources or channels of information concerning new agricultural
practices among fruit and vegetable farmers in Southwest Michigan.
4. To determine if there is relationship between the age of the farmers and
sources or channels used by fruit and vegetable farmers of Southwest
Michigan to receive information concerning new agricultural practices.
5. To determine if the size, in number of acres, of a farming operation governs
which sources or channels fruit and vegetable farmers of Southwest Michigan
used to receive information on new agricultural practices.
6. To determine if the number of years the person has been in fruit and vegetable
farming had a relationship to the source or channel for receiving information
on new agricultural practices.
7. To determine if the number of years of formal education had a relationship to
the source or channel that fruit and vegetable farmers used to receive new
agricultural practices.
8. To determine if gross dollar earnings from the fruit and vegetable farm
effected sources or channels farmers used to receive information concerning
new agricultural practices.

90
Based on research questions and the literature review, hypotheses were
formulated.
Research Question 1: What was the frequency of use of selected sources and selected
channels of information, by fruit and vegetable farmers selected from five counties in
Southwest Michigan, to gain information on new agricultural practices?
Research Question 2: Does the size of the farm in acres affect the use of sources or
channels for gaining information on new agricultural practices used by fruit and vegetable
farmers in five selected counties in Southwest Michigan?
Hypothesis 5: There is a significant relationship between the size of the farm in
acres and identified sources of information, used by fruit and vegetable farmers
of Southwest Michigan, for new agricultural practices.
Hypothesis 6: There is a significant relationship between the size of the farm in
acres and identified channels of information, used by fruit and vegetable farmers
of Southwest Michigan, for new agricultural practices.
Research Question 3: Does the gross dollar earnings of the farm influence a farmer’s
use of sources or channels for gaining information on new agricultural practices used by
fruit and vegetable farmers in five selected counties in Southwest Michigan?
Hypothesis 15: There is a significant difference between gross farm incomes with
regard to the use of the identified sources by fruit and vegetable farmers of
Southwest Michigan, for new agricultural practices.
Hypothesis 16: There is a significant difference between gross farm income with
regard to the use of the identified channels by fruit and vegetable farmers of
Southwest Michigan, for new agricultural practices.
Research Question 4: Does the time a farmer spends working off the farm, make a
difference in the use of sources or channels for gaining information on new agricultural
practices used by fruit and vegetable farmers of five selected counties in Southwest
Michigan?
Hypothesis 9: There is a significant difference between full-time farmers and
part-time farmers, with regard to the use of identified sources of information for
new agricultural practices, among fruit and vegetable farmers of Southwest
Michigan.
Hypothesis 10: There is a significant difference between full-time and part-time
farmers with regard to the use of identified channels of information for new
agricultural practices, among fruit and vegetable farmers of Southwest Michigan.

91
Research Question 5: Does the age of a farmer have an effect on the use of sources or
channels for gaining information on new agricultural practices used by fruit and vegetable
farmers of five selected counties in Southwest Michigan?
Hypothesis 1: There is a significant relationship between the age of the farmer
and the identified sources of information, used by fruit and vegetable farmers of
Southwest Michigan, for new agricultural practices.
Hypothesis 2: There is a significant relationship between the age of the farmer
and the identified channels of information, used by fruit and vegetable farmers of
Southwest Michigan, for new agricultural practices.
Research Question 6: Does the amount or level of formal education a farmer has, have
an effect on the use of sources or channels for gaining information on new agricultural
practices used by fruit and vegetable farmers of five selected counties in Southwest
Michigan?
Hypothesis 11: There is a significant difference between the levels of formal
education of farmers with regard to the use of the identified sources of
information for new agricultural practices by fruit and vegetable farmers of
Southwest Michigan.
Hypothesis 12: There is a significant difference between the levels of formal
education of farmers with regard to the use of the identified channels of
information for new agricultural practices by fruit and vegetable farmers of
Southwest Michigan.
Research Question 7: Does the number of years a person has been farming have an
effect on the use of sources or channels for gaining information on new agricultural
practices used by fruit and vegetable farmers in five selected counties in Southwest
Michigan?
Hypothesis 3: There is a significant relationship between the number of years in
farming and identified sources of information, used by fruit and vegetable farmers
of Southwest Michigan, for new agricultural practices.
Hypothesis 4: There is a significant relationship between the number of years in
farming and identified channels of information, used by fruit and vegetable
farmers of Southwest Michigan, for new agricultural practices.
Research Question 8: Does gender have an effect on use of sources or channels for
gaining information on new agricultural practices by fruit and vegetable farmers of five
selected counties in Southwest Michigan.
Hypothesis 7: There is a significant difference between male farmers and female
farmers, with regard to the use of identified sources of information for new
agricultural practices, among fruit and vegetable farmers of Southwest Michigan.

92
Hypothesis 8: There is a significant difference between male farmers and female
farmers, with regard to the use of identified channels of information on new
agricultural practices, among fruit and vegetable farmers of Southwest Michigan.
Research Question 9: Does the type of ownership affect the use of sources or channels
for gaining information on new agricultural practices used by fruit and vegetable farmers
o f selected five counties in Southwest Michigan.
Hypothesis 13: There is a significant difference between the types of farm
ownership with regard to the use of identified sources of information by fruit and
vegetable farmers of Southwest Michigan, for new agricultural practices.
Hypothesis 14: There is a significant difference between the types of farm
ownership with regard to the use of identified channels of information by fruit
and vegetable farmers o f Southwest Michigan, for new agricultural practices.
The survey method was used to determine sources and channels of information
used for receiving information on new agricultural practices by fruit and vegetable
farmers. Personal and farm characteristics were described. A mailed instrument was
used to survey the fruit and vegetable farmers in five counties of Southwest Michigan.
Data was collected using a questionnaire developed by the researcher, and approved by
the University Committee of Research Involving Human Subjects. The questionnaire had
two parts. Part I asked farmers to identify their use of selected sources and channels
using a 5 point scale. Respondents circled 4 if they Always Used the practice, 3 if they
Usually Used the practice, 2 if they Sometimes Used the practice, 1 if they Seldom Used
the practice and 0 if they Never Used the practice.

Part II of the survey requested

personal and demographic characteristics of the farmers, including current age, gender,
formal education, number of years farmers have been involved in farming, number of
days the farmer worked off the farm, current number of acres owned and rented, types
of farm ownership, and gross dollar earnings from the farm on an average over the past
five years.
The population for this study were farmers who were on the Cooperative

93
Extension Service mailing list of the counties of Allegan, Berrien, Cass, Kalamazoo and
Van Buren.

The population included 970 names received from these counties.

Microcomputer software SPSS P C + was used to generate a random sample of 275
farmers.
A cover letter co-signed by the researcher and the district horticulture agent,
Theodore M. Thomas, was included with the questionnaire along with a response
postcard. The cover letter contained instructions on how to complete the questionnaire
and also explaining the importance of the entire research project.
A follow-up questionnaire was mailed after a two week period. Two weeks later
a postcard reminder was mailed. The useable survey response rate was 69% (190 usable
surveys of the 275 surveys mailed). Sixteen farmers, representing 25% of the 65 that
did not respond, were telephoned and asked questions from Part II of the survey to
determine differences o f personal or farm characteristics of respondents versus non­
respondents.

Validity was established through a jury of experts.

Reliability was

established with Cronback’s alfa. A reliability coefficient of .76 and .82 was established
with microcomputer software.
Frequencies were used to describe the sources and channels selected by the fruit
and vegetable farmers. Frequency counts, percentages, means and standard deviations
were calculated on questions of the instrument.

One-way Analysis of Variance

(ANOVAs) and t-tests were used to determine significant differences between respondent
use of sources or channels of information and farmer characteristics. Scheffee or Tukey
tests were used as a post hoc multiple comparison procedures, at a .05 level of
significance, to determine a 95 % confidence level.

94
Conclusions
The research questions and major findings from testing null hypotheses presented
in Chapter IV, are listed here, with conclusions.
Research Questions 1:

What was the frequency of the use of selected sources and

selected channels of information by fruit and vegetable farmers, in five selected counties
of Southwest Michigan, for gaining information on new agricultural practices?
Findings: 1. County Cooperative Extension Service personnel with a mean of 2.29
ranked first as a source of agricultural information. Product Company
Representatives with a mean of 2.09 ranked second. Farmers who are
either family members or not family members with means of 1.84 ranked
third, as a source of agricultural information.
2.

Sources of agricultural information which were lowest ranked by fruit and
vegetable farmers were, Vocational Agricultural Teachers and Farmers
Home Administration Personnel. Farmers Home Administration with a
mean of .54 ranked tenth. Vocational Agriculture Teachers had a mean
ranking of .22 on the 5 point scale of 4 to 0, and were ranked last of
eleven sources.

3.

Farm Magazines, with a mean of 2.56 ranked first as the most used
channel of agricultural information. Agricultural bulletins from Michigan
State University or other universities with a mean of 2.48 ranked second.
Weekly or monthly agricultural newsletters with a mean of 2.37 ranked
as the third most used channel of information.

95
4.

Channels which were least often used by fruit and vegetable farmers, were
Television advertisements and programs, with a mean of 1.05. Television
advertisements and programs ranked 16th out of a possible 18 channels.
Video Tape with a mean of .79 ranked seventeenth.

Microcomputer

Communications with a mean of .48 ranked eighteenth, and the lowest
ranked of all channels of information.
Conclusions:

Traditional sources of agricultural information, such as, Cooperative

Extension Service personnel, Product Company Representatives, and other farmers, both
Family and non family members are used most often by fruit and vegetable farmers of
Southwest Michigan, for information on new agricultural practices. Statistical results
were comparable to past studies on adoption of farming practices. Cooperative Extension
Service personnel may have an inflated mean due to the original population coming from
mailing lists of the Cooperative Extension office in each of the five counties of Southwest
Michigan.
Research Question 2: Does the size of the farm in acres affect the use of sources or
channels for gaining information on new agricultural practices used by fruit and vegetable
farmers in five selected counties of Southwest Michigan?
Hypothesis 5: There is a significant relationship between the size of the farm in
acres and identified sources of information, used by fruit and vegetable farmers
in Southwest Michigan, for new agricultural practices.
Hypothesis 6: There is a significant relationship between the size of the farm in
acres and identified channels of information, used by fruit and vegetable farmers
of Southwest Michigan, for new agricultural practices.

96
Findings: 1. The data indicated that farm size had significant impact on sources, as
farm size increased farmers used Private Consultants significantly more
often as a source of information.
Conclusions:

Farm size was not a major factor when farmers chose the identified

sources or channels of information. However, Private Consultants were used by larger
farms.

Access to sources and channels has more to do with other personal or farm

characteristics than farm size o f acres.
Research Question 3: Does the gross dollar earnings of the farm influence a farmer’s
use of sources or channels for gaining information on new agricultural practices used by
fruit and vegetable farmers in fives selected counties of Southwest Michigan?
Hypothesis 15: There is a significant difference between gross farm incomes with
regard to the use of the identified sources fruit and vegetable farmers of
Southwest Michigan, for new agricultural practices.
Hypothesis 16: There is a significant difference between gross farm income with
regard to the use of the identified channels by fruit and vegetable farmers of
Southwest Michigan, for new agricultural practices.
Gross farm income did influence the use of sources and channels.
Findings: 1. Those farmers whose gross farm earnings were between $50,001 to
$100,000 used Farmers who are family members as a source, more than
those farms that had gross earning of $10,001 to $25,000.
2. As gross dollar earnings increased, the use of Michigan State University
Specialists as a source of information also increased significantly.
3. Farms grossing over $250,000 used Private Consultants as a source,
significantly more than those farms grossing under $5,000.

4. Fanners grossing over $100,000 used Agricultural Trade Shows as a
source of information, significantly more than any of the farmers grossing
under $100,000.
5.

As gross dollars received from the farm increased, the use of Farm
Magazines also increased significantly.

6. Farmers with gross earnings of $100,001 to $250,000 utilized Field Days
and Twilight Tours significantly more than farmers with a gross income
of $5,001 to $10,000.
7.

As the income from gross dollar sales increased farmers used the
telephone significantly more to contact ASCS, CES, FmHA and SCS
offices.

8. As gross dollar sales increased on the farm the use of Video Tape as a
channel to receive information also increased significantly.
9.

Growers grossing over $100,000 used Weekly or monthly ag newsletters
significantly more than growers grossing under $10,000 or less as channel
of information on new agricultural practices.

Conclusions: From the testing of the null hypotheses it was determined that as farm
income increased, the use of Michigan State University Specialists, Farm Magazines, Use
of the telephone and Video Tapes also increased as sources or channels of information.
Farms with higher incomes used a wider variety of sources, more than farms receiving
lower gross farm incomes. The differences in the findings were between groups with
under $50,000 and those with gross income of over $50,000.

98
Research Question 4: Does the time the farmer spends working off the farm, make a
difference in the use of sources or channels for gaining information on new agricultural
practices used by fruit and vegetable farmers of five selected counties of Southwest
Michigan?
Hypothesis 9: There is a significant difference between full-time farmers and
part-time farmers, with regard to the use of identified sources of information by
fruit and vegetable farmers of Southwest Michigan, for new agricultural practices.
Hypothesis 10: There is a significant difference between full-time and part-time
farmers, with regard to the use of identified channels of information by fruit and
vegetable farmers of Southwest Michigan, for new agricultural practices.
Findings:

1.

The test completed for the null hypothesis showed a significant
difference between Part-Time or Full-Time farmers in their use of Other
Channels for gaining information on new agricultural practices.

Conclusions:

Part-time farmers and full-time farmers use the identified sources and

identified channels equally except for Other Channels. Time spent off the farm was not
a major factor in using sources or channels of information for new agricultural practices.
Research Question 5: Does the age of the farmer have an effect on the use of sources
or channels for gaining information on new agricultural practices used by fruit and
vegetable farmers of five selected counties of Southwest Michigan?
Hypothesis 1: There is a significant relationship between the age of the farmer
and the identified sources of information, used by fruit and vegetable farmers of
Southwest Michigan, for new agricultural practices.

99
Hypothesis 2: There is a significant relationship between the age of the farmer
and the identified channels of information, used by fruit and vegetable farmers of
Southwest Michigan, for new agricultural practices.
There were significant differences in there use of sources and channels about new
agricultural information, among different age groups.
Findings; 1. Older farmers used Agricultural Bulletins, Daily Newspapers and Direct
mailings significantly more than younger farmers.
2.

Younger

farmers

attended

Agricultural

Trade

Shows,

used

a

Microcomputer Communications, used Video Tapes and used Weekly or
monthly ag newsletters significantly more than older farmers.
3. Younger farmers used the telephone to contact the ASCS, CES, FmHA
and SCS offices and also other farmers, both Family members and non
family members, significantly more than their older counterparts.
Conclusions:

Older farmers used more traditional forms of information than their

younger counterparts. Younger farmers used more recent or newer forms of sources or
channels. Younger farmers also used a greater variety of both sources and channels than
older farmers.
Research Question 6: Does the amount or level of formal education a farmer has, have
an effect on the use of sources or channels for gaining information on new agricultural
practices used by fruit and vegetable farmers of five selected counties of Southwest
Michigan?

100
Hypothesis 11: There is a significant difference between the levels of formal
education of farmers with regard to the use of the identified

sources of

information for new agricultural practices by fruit and vegetable farmers of
Southwest Michigan.
Hypothesis 12: There is a significant difference between the levels of formal
education of farmers with regard to the use of the identified channels of
information for new agricultural practices by fruit and vegetable farmers of
Southwest Michigan.
Analysis showed that there were significant differences in the use of sources and
channels o f agricultural information between farmers with different levels of formal
education.
Findings: 1. Farmers with a high school diploma, two year degree or four degree or
more, utilized Agricultural Trade Shows as a channel of information,
significantly more than farmers with less than a high school diploma.
2.

Farmers having a two year degree above high school used the channels of
Office visits to ASCS, CES, FmHA and SCS and Video Tape significantly
more than farmers who had less than a high school diploma.

Conclusions:

Four of the eighteen channels were used by farmers with a higher

education significantly more than farmers with less than a high school education.
Research Question 7: Does the number of years a person has been farming have an
effect on the use of sources or channels for gaining information on new agricultural
practices used by fruit and vegetable farmers in five selected counties of Southwest
Michigan?

101
Hypothesis 3: There is a significant relationship between the number of years in
farming and identified sources of information, used by fruit and vegetable farmers
of Southwest Michigan, for new agricultural practices.
Hypothesis 4: There is a significant relationship between the number of years in
farming and identified channels of information, used by fruit and vegetable
farmers of Southwest Michigan, for new agricultural practices.
There was a significant difference with farmers in regards to the number of years
they have been involved in farming.
Findings: 1. The fewer years a farmer had been farming, the more they utilized
Farmers who were not family members.

They also used Local Sales

People as a source of information more than farmers with more years in
farming.
2. Farmers

with

fewer

years

in

farming

utilized

Microcomputer

Communications, Telephone recordings and Video Tape as channels of
information, significantly more than farmers who had been in farming for
longer period of time.
3. Farmers with increased experience or years in farming used Daily
Newspapers and the Soil Conservation Service Personnel, significantly
more as sources of information than farmers with less experience.
Conclusions: These findings correlated closely with age. Farmers with less years of
experience used a greater variety of sources and channels than farmers with many years
of experience. To make sure that farmers with more years in farming are receiving
information agricultural educators need to disseminate information through, daily
newspapers.

102
Research Question 8: Does the gender have an effect on the use of sources or channels
for gaining information on new agricultural practices by fruit and vegetable farmers in
five selected counties o f Southwest Michigan?
Hypothesis 7: There is a significant difference between male farmers and female
farmers, with regard to the use of identified sources of information by fruit and
vegetable farmers of Southwest Michigan, for new agricultural practices.
Hypothesis 8; There is a significant difference between male farmers and female
farmers, with regard to the use of identified channels of information by fruit and
vegetable farmers of Southwest Michigan, for new agricultural practices.
The analysis revealed significant differences in the use of sources and channels
of agricultural information between and male farmers and female farmers with two of the
twelve sources, and one of the eighteen channels.
Findings: 1. Male farmers used Local Sales People and Private Consultants
significantly more than female farmers as sources of information to gain
information on new agricultural practices.
2. Male farmers utilized Agriculture Trade Shows as a channel of
information significantly more than female farmers for new agricultural
practices.
Conclusions: There were significant differences between males and females in their use
of two sources and one channel. Local Sale People, Private Consultants and Agriculture
Trade Shows are used more by male farmers than female farmers.
Research Question 9: Does the type of farm ownership affect the use of sources or
channels for gaining information on new agricultural practices used by fruit and vegetable
farmers in five selected counties of Southwest Michigan?

103
Hypothesis 13:

There is a significant difference between the types of farm

ownership with regard to the use of identified sources of information by fruit and
vegetable farmers of Southwest Michigan, for new agricultural practices.
Hypothesis 14:

There is a significant difference between the types of farm

ownership with regard to the use of the identified channels of information by fruit
and vegetable farmers of Southwest Michigan, for new agricultural practices.
Analysis revealed that there were significant differences in the use of sources and
channels of agricultural information between these types of farm ownership, owner
operator, partnerships and corporations.
Findings: 1. Partnerships used Farmers Home Administration Personnel as a source of
information significantly more than owner operators to gain information
on new agricultural practices.
2. Partnerships and corporations utilized Agricultural Trade Shows as a
channel of information for new agricultural practices, significantly more
than owner operators, for new agricultural practices.
3. Partnerships utilized Telephone recordings as a channel of information,
significantly more than Owner operators, as a channel of information for
gaining information on new agricultural practices.
4. Corporate owned farm operations utilized Video Tape, significantly more
frequently as a channel of information than owner operators, for new
agricultural practices.
Conclusions: The more partners involved in the ownership of the farm the greater the
use of Farmers Home Administration Personnel, attendance of Agriculture Trade Shows
and the use of Telephone recordings as sources and channels.

104
Implications
Major implications were stated and discussed by the author concerning use of
sources and channels of information by fruit and vegetable farmers of Southwest
Michigan. The degree to which findings can be generalized exist to the population of
which the random sample population was drawn.
Implication 1: When sources and channels were separated, county Cooperative
Extension Service personnel ranked high as a source of information to clientele for fruit
and vegetable information. As funding of programs becomes a serious problem, ways
to keep agents current with up-to-date information, backed up by specialists able to assist
county staff, must be continually reviewed.
Implication 2: Many Product Company representatives currently assist in delivery
of information and are excellent sources to clientele. Product Company Representatives
have access to funds from their companies that could be used by county Cooperative
Extension Service personnel to disseminate information or to co-sponsor workshops,
radio programs, field days and tours.
Implication 3: As disseminators of information agricultural educators need to
utilize channels which clientele used.

Farm magazines such as Michigan Farmer,

Michigan Prairie Farmer, American Vegetable Grower, American Fruit Grower and
monthly newsletters of Great Lakes Fruit Growers News and Great Lakes Vegetable
Growers News were used as a source of information by clientele in Southwest Michigan.
Cooperative Extension Service personnel need to write and submit articles to these
channels. These are inexpensive ways of delivery information to clientele, providing
both regional and statewide coverage.

105
Implication 4: Agricultural Bulletins were a vital and useful tool for delivering
information to clientele. Michigan State University Cooperative Extension Service must
continue to develop, update and provide agricultural bulletins as channels of information.
The Agricultural Bulletins give farmers a technically concise document without bias of
commercial sales. .
Implication 5: As new channels of information become available, such as Video
Tape and Microcomputer Communications, as educators we must understand the
saturation levels and which type of farmers are using these technologies.

As video

players and computers become common in homes and farms, agricultural educators must
have the software and videos available for farm clientele to use.
Implication 6: Traditional delivery of information by channels must be reviewed
by each agricultural educator to streamline delivery and reduce costs of having numerous
expensive channels not used by farm clientele. With cost of postage increasing the use
of newsletters created, printed and mailed by each educators office must be reviewed for
readership.

Recommendations for Further Studies
As with any study many additional questions and objectives could have been
specified. Listed below are six recommendations that were suggested for future research.
1.

Throughout the research it was noted that "Other Sources" and "Other

Channels" were used by fruit and vegetable farmers.

Future studies could involve

determining which other sources or channels of information farmers use to gain
information on new agricultural practices.

106
2. The study was completed primarily on those farmers who were on Cooperative
Extension Service mailing lists. A study could be accomplished to determine if there is
a difference in the selection of sources or channels by farmers, who are not currently on
mailing lists of the Cooperative Extension Service in the study area.
3. Other populations could be studied, such as field crop or livestock producers,
to determine if they receive information from similar or different sources than fruit and
vegetable farmers in the study area.
4. Conduct a study to determine if different regions of the state use sources or
channels differently than Southwest Michigan.
5. Conduct a study to determine how the stages of adoption make a difference
in the sources or channels o f information used by farmers.
6. Conduct a study using non-traditional Cooperative Extension Service clientele
or home owners as the population, to determine the use of sources and channels for
information delivery.

Personal Observations
The following are personal observations by the author.
Observation 1: It is important that the Michigan State University Cooperative
Extension Service continue to use field staff positions in the area of fruit and vegetables,
to continue their mission of disseminating technical information to clientele of Southwest
Michigan. It is also important that the Michigan State University Cooperative Extension
Service and other agricultural educators continue to have a positive relationship with
product company representatives, as they were a resource used by clientele.

Many

Product Company Representatives currently assist in delivery of information, and are

107
sources to clientele. Product Company Representatives have access to funds from their
companies that could be used to disseminate information or to sponsor workshops, radio
programs, field days and twilight tours with formal agricultural educators.
Disseminators of information must utilize channels which clientele use. Farm
magazines, such as the Michigan Farmer, Michigan Prairie Farmers, American Vegetable
Grower, American Fruit Grower and monthly newsletters of the Great Lakes Fruit
Growers news and Great Lakes Vegetable Growers News were used as a source of
information by clientele in Southwest Michigan. To reach farmers, agricultural educators
should consider writing and submitting articles to these channels. These are inexpensive
ways of delivery of information to clientele providing both regional and statewide
coverage.
Some areas were not used as much as others. Agricultural educators should also
consider trying newer channels of information, especially the use of Video Tape and
Microcomputers. Standards should be recognized so as not to spend an inappropriate
amount o f money for software and videos that may become obsolete. Because of their
basic practice of being classroom teachers of youth, the agricultural teacher’s reputation
may be a hindrance to fully develop their potential. They may consider selecting and
building some type of specialty to gain respect from the farming community in which
they work and live. They also may wish to teach adult education classes during the year
and possibly work with county Cooperative Extension Service offices during the summer
months to enhance their image.
Observation 2: Instructional videos that are available currently to farm producers
may be priced higher than average or below average income farms may be able to afford.
Also the video tape player may still be seen in households as a entertainment item and

108
high debts of lower income farms would prohibit the purchase of this item. Farms with
higher income may have other family members involved in the farming operation.
Observation 3: Older farmers may not be making as many adjustments to their
farming operations and do not need the details of information found in other sources or
channels. Younger farmers may have video tape players in their homes for entertainment
or have purchased them before their older counterparts. Younger farmers may have been
exposed to the use of microcomputers through work off the farm, school or from a
working spouse.
Observation 4:

It was difficult to identify clientele by educational levels for

delivery of information. Agricultural educators needed to know levels of education when
writing and publishing reports, bulletins and newsletters.

The results show that

agricultural educators may write information and deliver information to clientele at high
school level or greater. It is important they do not write or present information too
simplistic or they may loose the attention of their particular audience.
Observation 5:

Farmers with less years in farming most likely are younger

farmers. To keep daily newspapers as a channel, agriculture educators may need to work
with sponsors to keep their information in local papers. Many of the papers have cut
their coverage to one page per week.

Agricultural educators must know their local

newspaper editors and make contact regularly.
Observations 6:

Agricultural educators need to continually renew their

information to exclude the possibility of gender bias, in delivery of agricultural
information so that they do not alienate either sex.

Local sales people and private

consultants may have been predominately male. Agricultural trade shows are also staffed
predominately by males. Their literature and sales delivery is written and presented to

109
a predominant male market-place.
Observation 7: Farmers in partnerships and corporations would need to purchase
additional management through private consultants, as acreage and diversity increase,
creating the need for assistance in areas of marketing, production practices and record
keeping. Partnerships usually involve a father and son relationship requiring additional
capital to allow the son to purchase his way into the operation. With additional risk and
questionable outcomes from new arrangements, Farmers Home Administration had a
history of loaning capital to these types of farms because of their lender of last resort
policy. When farmers borrow money they also consulted with their lender, on approved
practices for which capital could be used.

APPENDICES

APPENDIX A

112
APPENDIX A
Copy of the Survey Instrument

FARM INFORMATION SURVEY
SOUTHWEST MICHIGAN FRUIT AND VEGETABLE
on sources and channels for new agricultural practices

Please read all the questions thoroughly before you give an answer.
PART I .
Note: The questions in Part are asking you to rate how frequently you use direct sources of
inform ation, as well as channels of information. Please read the rating scale before
answering each question.
1.

Please circle the num ber th a t best describes how frequently you use each of the
following sources of information for agricultural practices.
Always
Use

Usually
Use

Agricultural Stabilization Conservation Personnel (ASCS)

4

3

2

1

0

County Cooperative Extension Agent (CES)

4

3

2

1

0

Farmers Home Administration Personnel (FmHA)

4

3

2

1

0

Farmers who are family members

4

3

2

1

0

Farmers who are not family members

4

3

2

1

0

Local sales people

4

3

2

1

0

Michigan State University Specialist (MSU)

4

3

2

1

0

Private Consultants

4

3

2

1

0

3

2

1

0

Product Company Representatives (fertilizer,chemical, seed etc.) 4

Sometimes
Use

Seldom
Use

Never
Use

Soil Conservation Service Personnel (SCS)

4

3

2

1

0

Vocational Agriculture Teacher (Local High School)

4

3

2

1

0

Other

4

3

2

1

0

113
PARTI. CONTINUED:

2.

Please circle the number that best describes how frequently you use each of the
following channels of information for agricultural practices.
Always
Use

Usually
Use

Sometimes
Use

Seldom
Use

Never
Use

Agricultural Bulletins (from Michigan State University and
other universities)

4

3

2

1

0

Agricultural Newsletters (Agri-Talk, The Plowshare, Doanes,
Pro-farmer, etc.)

4

3

2

1

0

Agricultural Trade shows (Horticulture Convention, Vegetable
Growers Annual Meeting, etc.)

4

3

2

1

0

Daily newspapers

4

3

2

1

0

Demonstration plots or trials on farms

4

3

2

1

0

Direct mailings (letters)

4

3

2

1

0

Farm magazines (Michigan Farmer, American Vegetable Grower,
American Fruit Grower and others)
4

3

2

1

0

Field Days and Twilight Tours

4

3

2

1

0

Microcomputer Communications (phone modem or diskettes)

4

3

2

1

0

Office visits to ASCS, CES, FmHA, SCS

4

3

2

1

0

Radio advertisements and programs

4

3

2

1

0

Television advertisements and programs

4

3

2

1

0

Telephone recordings (code-a-phone)

4

3

2

1

0

Using the telephone to contact ASCS, CES, FmHA, SCS

4

3

2

1

0

Video tape

4

3

2

1

0

Weekly or monthly Ag Newsletter (Great Lakes Fruit Grower,
Farmers Advance, Great Lakes Vegetable Grower

4

3

2

1

0

Word of mouth from other fanners

4

3

2

1

0

Other

4

3

2

1

0

114
PARTH.
Note:

Pan II. asks background and cross reference information related to the questions in
Pan I.

1.

Please state the number of acres that you own and/or rent for your fruit and
vegetable production.
_______Acres Owned
Acres Rented

2.

Please put an (x) by the appropriate category for the number of days you worked
off-the-farm last year.
_______No off-the-farm work
Less than 100 days of off-the-farm work
_______More than 100 days of off-the-farm work

3.

Please state your current age.
_______years old

4.

Please put an (x) by the appropriate category which best
education.
_______less than high school diploma or equivalent
_______high school diploma or equivalent
two year college degree (any kind)
_______four year college degree or more (any kind)

5.

Please state the number of years you have been farming.
_______years in farming

describes your formal

115
PART II. CONTINUED:

6.

Please indicate your sex with an (x).
Male
Female

7.

Please put an (x) by the type of farm ownership.
_______Owner operator
_______Partnership
_______Corporation

8.

Please put an (x) by the appropriate range of gross dollar earnings from your fruit
and vegetable operations as averaged over the past 5 years.
less than $5,000
$5,001 to $10,000
$10,001 to $25,000
$25,001 to $50,000
$50,001 to $100,000
$100,001 to $250,000
greater than $250,000

Thank you for completing this survey.
Please return in the envelope provided.
Don’t forget to also return the enclosed postcard at the same time.

APPENDIX B

117
APPENDIX B
Sample o f First Cover Letter

June 14, 1990

1~
2~
3~
Dear 4 ~ :
In order to better serve you, the clientele of the Cooperative Extension Service, the Extension
agents in Southwest Michigan are in the process of determining what sources and channels fruit
and vegetable fanners use to gain information on farming practices. A survey instrument has
been developed. You are one of a few farmers that have been selected to help by providing your
input.
Your responses to the questionnaire will be very beneficial in determining how agricultural
information will be dispersed in the future, and will allow us to formulate plans to meet your
information needs.
The survey takes approximately seven minutes to complete. Please answer all the questions. The
questionnaire should be answered by the person who is most involved in making decisions about
the farming operation.
Enclosed are three items, one survey, one pre-addressed and pre-stamped envelope and one pre­
addressed and pre-stamped postcard. Please put the completed survey into the envelope and mail
both the survey and the postcard at the same time. We would appreciate receiving the completed
survey within the next five days.
All responses are confidential and no personal information is being recorded. We need the
farmer and farm uala to help us define the difference in needs of farmers of all types. You
indicate your voluntary agreement to participate by completing and returning this questionnaire.
We thank you very much for your time and trouble in completing the enclosed questions. If you
have any questions about the survey please contact Pete Vergot at 657-5564.
Sincerely yours,

Pete Vergot, III
County Extension Director
Van Buren County
jP
Enclosure

T. Mike Thomas
District Extension
Horticulture & Marketing
Agent

APPENDIX C

119
APPENDIX C
Sample of Return Postcards

No____
Thank you for your input.
Please mail this postcard when you mail your questionnaire.
Thank you.

Pete Vergot, III
County Extension Director
Van Buren County
657-5564

No. 2____
Thank you for your input.
Please mail this postcard when you mail your questionnaire.
Thank you.

Pete Vergot, III
County Extension Director
\fon
«M
M

657-5564

v o u ti K J

APPENDIX D

121
APPENDIX D
Sample of Second Cover Letter

June 28, 1990

1~
2~
3~
Dear 4 ~ :
At the present time we have not received your survey. We have enclosed another one for you if you have
misplaced or forgotten the first one. You are one of a few farmers that have been selected to help by
providing your input. In order to better serve you, the clientele of the Cooperative Extension Service, the
Extension agents in Southwest Michigan are in the process of determining what sources and channels fruit
and vegetable farmers use to gain information on farming practices. A survey instrument has been
developed.
Your responses to the questionnaire will be very beneficial in determining how agricultural information will
be dispersed in the future, and will allow us to formulate plans to meet your information needs.
The survey takes approximately seven minutes to complete. Please answer all the questions. The
questionnaire should be answered by the person who is most involved in making decisions about the
farming operation.
Enclosed are three items, one survey, one pre-addressed and pre-stamped envelope and one pre-addressed
and pre-stamped postcard. Please put the completed survey into the envelope and mail both the survey and
the postcard at the same time. We would appreciate receiving the completed survey within the next Eve
days.
All responses are confidential and no personal information is being recorded. We need the farmer and
farm data to help us detine the difference in needs of farmers of all types. You indicate your voluntary
agreement to participate by completing and returning this questionnaire.
We thank you very much for your time and trouble in completing the enclosed questions. If you have any
questions about the survey please contact Pete Vergot at 657-SS64.
If you have filled out and mailed back the survey along with the postcard please disregard this letter.
Sincerely yours,
Pete Vergot, III
County Extension Director
Van Buren County
jP
Enclosures

T. Mike Thomas
District Extension
Horticulture & Marketing
Agent

APPENDIX E

123
APPENDIX E
Sample of Postcard Reminder

Dear:

July 16, 1990

It is very important to us that we receive your comments regarding
the Farm Information Survey for Southwest Michigan Fruit and Vegetables
on sources and channels for new agricultural practices.
Please take a few minutes to complete the questionnaire and return it in
the envelope previously provided.
If you need an additional survey or have a question please call, 657-5564.
Sincerely,

Pete Vergot, III
County Extension Director
Van Buren County
jP

APPENDIX F

125
APPENDIX F

SURVEY AND POSTCARD RETURNS

Surreys Received
Complete Incomplete

Postcards Received

18

28

19

31

20

12

1

21

10

1

8

22

11
18

2
2

14
18

25
26
27
28
29

24
30

10

7
3

8
1

3
2

3
4

Jul;
2

21
15

2
3

19
16

6

8
8

1
1

10
6

2

7

3
5
9

6

10
12

1

1

4

2

13

2

2

16

0

1

17

3

3

18

_l

i
195

15

187

APPENDIX G

127
APPENDIX G
Reasons Why People Did Not Fill Out Survey
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.

I retired in 1988 I have leased the farm out.
I am not a grower I sell produce but never grow it.
We no longer raise fruit and vegetables, we are totally grain and cattle and
sunflowers, however a good survey.
I am no longer farming, please take me off the mailing list.
I have not farmed for years, my input would not be helpful to you.
Most o f the farm was sold in 1987, I’m only farming about 5 acres.
We not longer have fruits and vegetables.
My farm is rented out, I ’m not farming anymore.
I no longer farm having sold our farm in 1987. I was a farmer for 55 years.
Our son took over the farm.
My husband passed away June 15, we aren’t farming this year.
To my knowledge Randy Wetzel does not live at this address.
Not farming anymore.
I have too small o f a farm to be included.
We sold our farm last year.
Please be advised that I’m not actively engaged in farming at the present time and
cannot complete this survey.

APPENDIX H

APPENDIX H

TABLE 23. Results of t-test Analysis of Respondents Versus Non-Respondents
Selected Characteristics
Respondent
Mean
Current Age of Respondents
Number of Years in Farming
Total Acres farmed
Acres owned
Acres rented

54
29
198
177
72

^Significant at the less than .05 level

Non
Respondent
M ean
51
31
177
146
98

t-value

Two-tail
P rob.

.93
-.53
.11
.16
-.25

.356
.600
.913
.871
.806

APPENDIX I

131
APPENDIX I
Table 24.

ANOVA Means and Standard Deviations Between Sources of Information and Levels of
Formal Education
Level of Formal Education
Less Than
High School
Diploma

High School
Diploma

Two Year
Degree

Four Year
Degree or More

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Agricultural Stabilization Conservation 1.38
1.22
Service Personnel
(18)

1.73
1.15
(94)

2.04
1.13
(25)

1.40
1.20
(44)

Cooperative Extension Service
Personnel

2.15
1.08
(20)

2.17
1.06
(93)

2.46
.81
(26)

2.47
1.30
(44)

Fanners Home Administrative
Personnel

.50
.65
(14)

.45
.71
(91)

.66
1.09
(24)

.63
1.03
(44)

Farmers who are family members

1.55
1.57
(20)

1.83
1.32
(92)

1.80
1.15
(25)

2.00
1.39
(42)

Farmers who are not family members

1.70
1.12
(20)

1.69
1.09
(92)

1.76
1.05
(25)

2.22
1.14
(45)

Local Sales People

1.40
1.18
(15)

1.70
.98
(92)

2.15
1.04
(26)

1.79
1.01
(43)

Y AA
Ai f t

i r .r \
1 i UV

1 HA
A• / 4

V AA
1 • ! L>

1.04
(18)

1.20
(92)

.93
(25)

1.20
(44)

Private Consultants

.58
1.06
(17)

1.14
1.34
(92)

20
l . 38
(24)

1.47
1.60
(44)

Product Company Representatives

1.88
1.13
(18)

2.10
1.13
(93)

2.48
l .08
(25)

1.88
1.27
(44)

Soil Conservation Service
Personnel

1.20
1.15
(20)

1.21
1.05
(92)

l .60
l .08
(25)

1.32
1.20
(43)

Vocational Agriculture Teachers

.05
.24
(17)

.22
.51
(93)

.12
.33
(24)

.34
.71
(44)

Other Sources

.38
.76
(13)

.74
1.01
(75)

.88
1.05
(17)

1.30
1.23
(33)

Sources of Information

iT H W llig U U UMiiW

l .

APPENDIX J

133
APPENDIX J
Table 25.

ANOVA Means and Standard Deviations Between Channels of Information and Levels
of Formal Education
Level of Formal Education
Less Than
High School
Diploma

High School
Diploma

Two Year
Degree

Four Year
Degree or More

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Agricultural Bulletins by Michigan
State and other Universities

2.47
1.07
(19)

2.45
.94
(94)

2.38
.80
(26)

2.62
.87
(43)

Agricultural Newsletters

1.16
.98
(18)

1.78
1.18
(93)

1.92
1.32
(25)

1.72
1.07
(43)

Agricultural Trade Shows

.88
.99
(17)

1.93
1.30
(93)

2.04
1.12
(24)

2.16
1.21
(43)

Daily Newspapers

2.09
1.44
(21)

2.13
1.24
(94)

2.30
.88
(26)

2.04
1.10
(42)

Demonstration Plots or Trials
on Farms

1.15
1.11

1.68
.94
v-v

1.32
1.06

V* " /

1.58
.95
ro,*\
vr -v

Direct Mailings

2.25
1.40
(20)

2.06
1.16
(91)

2.04
.97
(25)

2.09
1.15
(44)

Farm Magazines

2.21
1.47
(19)

2.62
1.09
(94)

2.57
1.17
(26)

2.56
1.12
(44)

Field Days and Twilight Tours

1.00
.90
(18)

1.35
1.05
(93)

1.32
.94
(25)

1.41
.95
(43)

Microcomputer Communications

.27
.75
(18)

.41
.82
(93)

.68
.90
(25)

.53
1.00
(43)

Channels of Information

/A^\

y -v -z y

134
Table 25 (cont’d)

Level of Formal Education
Less Than
High School
Diploma

High School
Diploma

Two Year
Degree

Four Year
Degree or More

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Office Visits to ASCS, CES, FmHA
and SCS

1.36
1.11
(19)

1.67
1.04
(92)

2.20
1.19
(25)

1.48
1.09
(43)

Radio Advertisements and programs

1.35
1.13
(20)

1.60
1.24
(93)

1.44
.82
(25)

1.20
1.05
(43)

Television Advertisements and
programs

.95
.94
(20)

1.07
1.03
(93)

1.28
.73
(25)

.76
.81
(43)

Telephone Recordings

1.00
1.17
(17)

1.00
1.19
(91)

1.52
1.38
(25)

.90
1.19
(43)

Using the Telephone to contact ASCS,
CES, FmHA and SCS

1.45
1.50
(20)

1.85
1.17
(92)

2.53
1.30
(26)

2.20
1.28
(93)

Video Tape

.06
.25
(16)

.52
.73
(92)

.88
1.12
(25)

.44
.73
(43)

Weekly or Monthly Agricultural
Newsletters

1.68
1.33
(19)

2.39
1.30
(91)

2.72
.93
(25)

2.40
1.22
(44)

Word of Mouth from other farmers

2.00
1.16
(20)

2.36
.91
(93)

2.48
.87
(25)

2.46
.88
(43)

Other Channels

1.23
1.30
(13)

1.04
1.05
(66)

1.11
1.26
(17)

1.28
.93
(25)

Channels of Information

APPENDIX K

136
APPENDIX K
Table 26.

ANOVA Means and Standard Deviations Between Sources of Information and Types of
Farm Ownership
Types of Farm Ownership
Owner
Operators

Partnerships

Corporation

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Agricultural Stabilization Conservation Service
Personnel

1.66
1.22
(141)

1.88
1.12
(25)

1.66
1.15
(12)

Cooperative Extension Service Personnel

2.26
1.02
(142)

2.40
1.08
(25)

2.53
1.05
(13)

Farmers Home Administration Personnel

.44
.76
(134)

1.08
1.25
(25)

.58
.66
(12)

Farmers who are family members

1.73
1.39
(139)

2.40
.95
(25)

2.15
.98
(13)

Farmers who are not family members

1.82
1.12
(141)

2.04
.99
(24)

1.92
1.07
(14)

Local Sales People

1.76
1.02
(136)

1.84
1.10
(25)

2.76
.86
(13)

Michigan State University Specialists

1.52
1.13
(138)

2.00
1.00
(25)

2.30
1.03
(13)

Private Consultants

1.00
1.32
(137)

1.70
1.65
(24)

1.92
1.11
(13)

Product Company Representatives

2.01
1.19
(139)

2.32
1.18
(25)

2.38
.86
(13)

Soil Conservation Service Personnel

1.27
1.10
(140)

1.52
1.19
(25)

1.23
.83
(13)

Vocational Agriculture Teachers

.20
.52
(138)

.33
.63
(24)

.30
.48
(13)

Other Sources

.72
1.02
(105)

1.44
1.14
(18)

1.18
.87
(11)

Sources of Information

APPENDIX L

138
APPENDIX L
Table 27.

ANOVA Means and Standard Deviations Between Channels of Information and Types
of Farm Ownership

Types of Farm Ownership
Owner
Operators

Partnerships

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Agricultural Bulletins from Michigan State
University and other Universities

2.48
.95
(142)

2.60
.76
(25)

2.23
.83
(13)

Agricultural Newsletters

1.68
1.16
(138)

1.96
1.20
(25)

2.07
1.03
(13)

Agricultural Trade Shows

1.69
1.25
(136)

2.52
1.15
(25)

2.61
.86
(13)

Daily Newspapers

2.14
1.17
(142)

2.28
1.20
(25)

2.00
1.15
(13)

Demonstration Plots and Trial on Farms

1.40
1.04
(139)

1.76
.87
(25)

1.92
.49
(13)

Direct Mailings

2.11
1.21
(138)

2.00
.86
(25)

2.07
1.07
(14)

Farm Magazines

2.46
1.19
(141)

2.96
.88
(25)

2.78
.89
(14)

Field Days and Twilight Tours

1.23
.99
(138)

1.60
.86
(25)

1.76
.92
(13)

Microcomputer Communications

.45
.90
(130)

.44
.65
(25)

.76
1.01
(13)

Channels of Information

Corporation

Mean
S.D.
(Number)

139
Table 27 (cont’d)
Types of Farm Ownership
Owner
Operators

Partnerships

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Office Visits to ASCS, CES, FmHA
and SCS

1.69
1.08
(139)

1.84
1.21
(25)

1.61
1.19
(13)

Radio Advertisements and programs

1.46
1.15
(141)

1.60
1.22
(25)

1.53
1.19
(13)

Television Advertisements and programs

1.03
.97
(141)

.96
.88
(25)

1.46
1.19
(13)

Telephone Recordings

.97
1.23
(135)

1.76
1.30
(25)

1.07
.86
(13)

Using the Telephone to Contact ASCS, CES,
FmHA and SCS

1.95
1.28
(140)

2.40
1.15
(25)

2.23
1.16
(13)

Video Tape

.44
.75
(136)

.62
.71
(24)

1.07
1.11
(13)

Weekly or Monthly Newsletters

2.30
1.28
(137)

2.76
2.42
(25)

1.23
.75
(14)

Word of Mouth from other farmers

2.33
.92
(139)

2.72
.79
(25)

2.21
.89
(14)

Other Channels

.093
1.03
(89)

1.68
1.05
(19)

1.55
.52
(9)

Channels of Information

Corporation

Mean
S.D.
(Number)

APPENDIX M

APPENDIX M
Table 28.

ANOVA Means and Standard Deviations Between Sources of Information and Gross Farm Income

Gross Farm Income
<$5,000

$5,001
to
$10,000

$10,001
to
$25,000

$25,001
to
$50,000

$50,001
to
$100,000

$100,001
to
$250,000

Greater
than
$250,000

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Agricultural Stabilization Conservation
Personnel

1.28
1.22
(32)

1.55
1.42
(18)

1.45
1.18
(32)

1.57
1.12
(19)

1.84
1.12
(26)

2.00
1.16
(23)

1.83
.98
(18)

Cooperative Extension Service Personnel

1.96
1.09
(32)

2.31
1.05
(19)

2.15
1.16
(32)

2.36
1.38
(19)

2.15
1.08
(26)

2.41
.58
(24)

2.72
.75
(18)

Farmers Home Administration Personnel

.46
.86
(30)

.25
.44
(16)

.61
.91
(31)

.22
.73
(18)

.69
1.01
(26)

.78
.95
(23)

.61
.91
(18)

Farmers who are family members

1.51
1.20
(31)

2.15
1.38
(19)

1.12
1.31
(32)

1.42
1.26
(19)

2.42
1.27
(26)

2.50
1.01
(22)

2.16
1.24
(18)

Farmers who are not family members

1.40
1.21
(32)

1.94
1.12
(19)

1.53
1.10
(32)

2.00
1.02
(20)

1.83
.96
(24)

2.12
1.22
(04)

2.05
.93
(18)

Local Sales People

1.67
1.10
(31)

1.50
1.15
(18)

1.65
1.18
(32)

1.83
1.09
(18)

1.80
.84
(26)

2.17
.77
(23)

2.05
.87
(18)

Michigan State University Specialists

1.16
1.18
(31)

1.38
1.14
(18)

1.37
1.00
(32)

1.31
1.10
(19)

2.15
1.18
(26)

2.04
.70
(23)

2.27
.82
(18)

Sources of Information

Table 28 (cont’d)

Gross Farm Income
<$5,000

$5,001
to
$10,000

$10,001
to
$25,000

$25,001
to
$50,000

$50,001
to
$100,000

$100,001
to
$250,000

Greater
than
$250,000

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Private Consultants

.64
1.11
(312)

.56
1.15
(16)

1.09
1.30
(32)

1.31
1.30
(19)

1.24
1.50
(25)

1.75
1.53
(24)

2.11
1.49
(18)

Product Company Representatives

1.74
1.29
(31)

2.23
1.48
(16)

2.12
1.26
(32)

2.05
1.07
(19)

2.03
1.21
(26)

2.25
.79
(24)

2.38
1.03
(18)

Soil Conservation Service Personnel

1.06
1.09

(31)

1.10
1.14
(19)

.90
1.14
(32)

1.47
.96
(19)

1.42
1.13
(26)

1.69
.82
(23)

1.22
.87
(18)

Vocational Agriculture Teachers

.32
.70
(31)

.05
.24
(17)

.21
.60
(32)

.15
.50
(19)

.28
.54
(25)

.29
.46
(24)

.055
.23
(18)

Other Sources

.53
1.10

.30
.75

.73
1.11

.92
.95

.60
1.12

1.31
.88

1.60
.73

Sources of Information

APPENDIX N

APPENDIX N
Table 29.

ANOVA Means and Standard Deviations Between Channels of Information and Gross Farm Income

Gross Farm Income
<$5,000

$5,001
to
$10,000

$10,001
to
$25,000

$25,001
to
$50,000

$50,001
to
$100,000

$100,001
to
$250,000

Greater
than
$250,000

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.

Agriculture Bulletins from Michigan State
University and other Universities

2.32
1.07
(31)

2.44
1.09
(18)

2.31
.82
(32)

2.40
1.14
(20)

2.69
1.01
(26)

2.62
.71
(24)

2.61
.69
(18)

Agricultural Newsletters

1.70
1.17
(30)

1.33
1.13
(18)

1.59
1.21
(32)

1.75
1.20
(20)

1.92
1.16
(26)

1.87
1.11
(24)

2.16
1.15
(18)

Agriculture Trade Shows

1.43
1.33
(30)

1.00
1.11
(17)

1.71
1.32
(22)

1.70
2.12
(20)

2.15
1.15
(26)

2.54
.83
(24)

3.05
.80
(18)

Daily Newspapers

2.37
1.18
(32)

1.68
1.20
(19)

2.09
1.30
(31)

2.20
1.00
(20)

2.07
1.19
(26)

2.04
.99
(24)

2.22
1.26
(18)

Demonstration Plots and Trials on farms

1.19
.98
(31)

1.33
1.08
(18)

1.25
.99
(31)

1.35
.93
(20)

1.65
.97
(26)

1.91
.88
(24)

1.72
.66
(18)

Direct Mailings

1.76
1.30
(30)

2.05
1.25
(18)

2.16
1.03
(31)

2.38
1.43
(21)

2.20
1.15
(25)

2.33
.70
(24)

1.83
1.04
(18)

Farm Magazines

2.00
1.34
(32)

2.27
1.12
(18)

2.75
1.04
(32)

2.71
1.10
(21)

2.61
1.20
(26)

2.79
.88
(24)

2.94
.87
(18)

Channels of Information

(Number)

Table 29 (cont’d)

Gross Farm Income
<$5,000

$5,001
to
$10,000

$10,001
to
$25,000

$25,001
to
$50,000

$50,001
to
$100,000

$100,001
to
$250,000

Greater
than
$250,000

Mean
Mean
S.D.
S.D.
Channels of Information_________________ (Number)____ (Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D
(Number)

Mean
S.D.
(Number)

Field Days and Twilight Tours

1.06
1.01
(20)

.70
.77
(17)

1.50
1.07
(32)

.90
.85
(20)

1.42
.94
(26)

1.83
.86
(24)

1.77
.73
(18)

Microcomputer Communications

.23
.77
(30)

.23
.43
(17)

.40
.75
(32)

.35
.67
(20)

.76
1.24
(26)

.50
.72
(24)

.66
.97
(18)

Office Visits to ASCS, CES, FmHA
FmHA and SCS

1.26
1.17
(30)

1.72
1.22
(18)

1.56
.98
(32)

1.55
1.09
(20)

1.69
1.19
(26)

2.04
.95
(24)

1.72
1.01
(18)

Radio Advertisements and programs

1.51
1.43
(31)

1.21
1.18
(19)

1.53
1.10
(32)

1.50
1.31
(20)

1.42
1.17
(26)

1.79
.97
(24)

1.11
.96
(18)

Television Advertisements and programs

1.22
1.28
(31)

.72
1.12
(18)

.87
.79
(32)

.95
.94
(20)

1.07
.89
(26)

1.16
1.00
(24)

.83
.61
(18)

Telephone Recordings

.63
1.21
(30)

.93
1.43
(16)

1.48
1.36
(31)

1.40
1.39
(20)

.92
1.09
(26)

1.16
1.12
(24)

1.16
.98
(18)

Using the Telephone to Contact the
ASCS, CES, FmHA and SCS

1.45
1.09
(31)

2.00
1.37
(18)

2.00
1.24
(32)

1.75
1.55
(20)

2.08
1.22
(25)

2.58
.97
(24)

2.50
1.24
(18)

Video Tape

.20
.61
(30)

.23
.56
(17)

.50
.80
(32)

.40
.68
(20)

.69
.83
(26)

.83
.96
(24)

.93
.92
(16)

Weekly or Monthly Agriculture
Newsletters

1.70
1.36
(30)

1.76
1.30
(17)

2.53
1.21
(32)

2.61
1.07
(21)

2.46
1.17
(26)

2.91
.88
(24)

3.22
.94
(18)

Table 29 (cont’d)

Gross Farm Income
<$5,000

$5,001
to
$10,000

$10,001
to
$25,000

$25,001
to
$50,000

$50,001
to
$100,000

$100,001
to
$250,000

Greater
than
$250,000

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.
(Number)

Mean
S.D.

Word of Mouth from other farmers

2.00
.94
(30)

2.15
.89
(19)

2.22
.80
(31)

2.38
.86
(21)

2.56
1.04
(25)

2.70
.90
(24)

2.61
.97
(18)

Other Channels

.50
.80
(22)

.54
.93
(11)

1.22
1.26
(22)

1.33
1.04
(15)

1.23
1.09
(17)

1.30
.75

1.75
.86
(12)

Channels of Information

(Number)

(13)

-t*.

o\

LIST OF REFERENCES

148
List of References

Borg, Walter R. and Meredith Damien Gall. Educational Research An Introduction.
4th ed. New York: 1983.
Coughenour, C. Milton and N.B. Patel. "Trends in Use of Recommended Farm
Practices and Farm Information Sources in 12 Kentucky Neighborhoods Progress
Report III, "University of Kentucky, Lexington, 1962.
Farnsworth, Richard L. and L. Joe Moffitt. "Farmers’ Perceptions and
Sources: A Quantitative Analysis." Agricultural Economics
36.1, (1984): 8-11.
Glass, Gene V., and Kenneth D. Hopkins.
Psychology. New Jersey: 1984.

Information

Statistical Methods in Educational and

Jones, Calvin C. Agricultural Information: Uses. Needs, and USDA Services. U.S.
Department of Agricultural Economics and Statistics National Opinion Research
Center, Chicago Illinois: 1980.
Jones, Calvin C., Paul B. Sheatsley and Arthur L. Stinchcombe. Dakota Farmers and
Ranchers Evaluate Crop and Livestock Surveys. National Opinion Research
Center Report No. 128. Chicago: 1979.
Lee, Richard Leslie. "The Flow of Information to Disadvantaged Farmers."
University of Iowa, 1967.

Diss.

Lionberger, Herbert F. Adoption of New Ideas and Practices. Iowa: 1960.
Mawby, Russell G. "Types and Sources of Information Used by Farmers in Michigan,
with implications for Extension Programming."
Diss.
Michigan State
University, 1959.
Michigan. Michigan Department of Agriculture. 1986 Michigan Orchard and Vineyard
Survey. Lansing: 1987.
Michigan. Michigan Department of Agriculture. 1987 Michigan Commercial Vegetable
Survey. Lansing: 1987
Michigan. Michigan Department of Agriculture.
Development Statistics. Lansing: 1990.

1989 County Food and Agriculture

149
List of References (cont’d)

Obahayujic, Julius and John Hillison. "Now Hear This, Delivery Methods for Farmers."
Journal of Extension. Spring (1988): 21-22.
Okai, Milton N. "Delivery of Agricultural Information to Small Farmers."
Diss. University of Missouri - Columbia, 1986.
Rowntree, Derek. "Statistics Without Tears."
New York: 1981 .

A Primer for Non-Mathematicians,"

Smith, Keith L. and Allen A. Kahler. "Iowa Adult Farmers’ Perception of the Value of
Educational Programs." Journal of the American Association of Teacher
Educators in Agriculture. (1982): 41-50.
Stallings, James L. and George L. Harrison. "Information Needs and Sources of
Alabama Farmers." Journal of Alabama Academy of Science. 51.2 (1980):
131-151.
Todd, John David. "The Attitude of Adult Farmers Toward Adult Education in
Vocational Agriculture in the Eagleville School Area of Rutherford County,
Tennessee." Thesis. University of Tennessee, 1959.
United States. Department o f Commerce, Bureau of the Census.
Agriculture. Vol. 1.51 Washington: 1989.

1987 Census of

Webb, Jerry Lee. "Analysis of Delaware Farmers’ Sources of Farm News and
Information." Thesis. University of Delaware, 1968.
Where Farmers Get Information. Urbana: University of Illinois, College of Agriculture,
1963.