THE 3.3311? 8"}: SQPL MANAfiEMENT GROU‘PS AND
REM-J35?) fiPiFOM‘ufi‘HON éN DETERMEMNG
AGRFCULTUME LAND VALUES I‘N
OBCEOLA CC’UNT‘I", . MICHIGAN

Thesis fix the Dew” cf M. S.
is‘flCiflGAN STATE UNWERSITY
Stephen G. Shanon
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LIBRARY

Michigan State
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THE USE OF SOIL MANAGENENT GROUPS AND
RELATED INFORMATION IN DETERMINING AGRICULTURAL LAND

VALUES IN OSCEOLA COUNTY, MICHIGAN

By

Stephen G. Shetron

A THESIS

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
MASTER OF SCIENCE
Soil Science Department

1961

Approved 77K L.C.Ev/<

 

8

ABSTRACT

THE USE OF SOIL MANAGEMENT GROUPS AND
RELATED INFORMATION IN DETERMINING AGRICULTURAL
LAND VALUES IN OSCEOLA COUNTY MICHIGAN

by Stephen G. Shetron

The valuation of land, in.the past, has been primarily

by three methods. These are the Income-Capitalization,

Market-Comparison and Replacement-Cost approach. These systems

appear to be adequate for obtaining approximate indications of

land values. Investigation of these methods show that soil

capabilities are considered to a lesser degree in.the Market-

comparison.and Replacement-Cost approach than in.the Income-
Capitalization approach.
This study was conducted to evaluate land based on

principles of the above three methods with emphasis on soil

through the use of soil management groups. The basic steps

used in this study are as follows:
1. Selection er farms and information about them.
2. Collection of soil data.

3. Determining land use.
A. Assigning the various soils to management groups.

5. Measuring the soil and land use areas.
6. Determination of expected net income.
A. Estimation of prices recieved for each crop.

B. Estimation of yields for each crap per
management unit.

C. Calculating the gross income per management unit
when used for crOpland, woodland and pasture.

D. Estimating the cost associated with each crOp,
per management unit.

E. Calculating the net income per management unit
when.used for cropland, pasture and woodland.

F. Estimation of improvement values.

G. Comparison of expected net income with sale values
minus improvement values.

H. Estimating cropland, woodland and permanent
pasture values from the above process.
Determined capitalization rates are 22.5%'for cropland,

8.9% for pasture and 5.7% for woodland. Investigation of data

shows that the capitalization.rate for crOpland is high due to

the lower determined machinery costs from custom rate data

than for the actual farming conditions. It is felt that there

First-- Farm units are too small

Second-- The Farmer

are two reasons for this.

for the amounts of machinery present.
has overstocked as insurance against not being able to obtain

desired.machinery services. Thus there is inefficient use of

machinery.
Results show that the more productive and highly deveIOped

land is being under-assessed and under valued. The poorer

land in crOpland, pasture and woodland is being over-assessed.

It was found that approximately sisty per cent of the

farm pperators were working off their farms. The farm has

thus become a dual purpose unit; a place to live while earning
am.income off the farm and also a source of income.

Through the use of soil management units and related soil
survey information, it is possible to realistically

evaluate cr0pland, pasture and woodland.

Page I.

THE USE OF SOIL LANAGELENT GROUPS AND
RELATED INFCRKATION IN DETERMINING AGRICULfiURAL LAND

VALUES IN OSCEOLA COINTY, NICIIGAN

BY

Stephen G. Shetron

A THESIS

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
EASTER OF SCIENCE
Soil Science Department

1961

Approved

 

Acknowledgments

The author wishes to acknowledge his sincerest
gratitude to Dr. E. P. Whiteside for his encouragement,

counsel and understanding during all phases in preparation

of this manuscript. Special thanks are due to W. H.

Heneberry for his willingness to discuss problems in

agricultural economics, on Which advice was needed. Credit

is also due the Soil Conservation Service which enabled me

to take the necessary time for class study and the use of

data for this study. I am especially indebted to my wife

Ruth, for her understanding, help and patience through all

phases in the preparation of the manuscript.

Table Of Contents

. Page
1. Abscract Q
2. Table of Contents iii
3. List of Tables v
u. List of Figures vi
5. Purpose 1
6. Review of Literature 2
7. Procedure: 1A
A. Selection of farm properties and information about
them.
3. Collection of field data.
C. Assigning the various soils to management units.
D. Intermining land use.
E. heasurenent of soil mapping units and land use areas.
F. Determination of net income:
(a) Estimation of prices received for each crop.
(bl. Estimating yields of each crop per manage-
ment unit.
(0) Analysis of major crops grown in Osceola
County and on each management unit.
(6) Estimating the gross income per management
unit When used for cropland, woodland and
pasture.
(e) Estimating the cost associated with each
crop per management unit.
(f) Estimating the net income for cropland,
woodland and pasture per management unit.
G. Estimating improvement values.
H. Comparison of expected net income with sale
values minus improvement values.
I. Estimating cropland, woodland and pasture values

from the above process.

8. Discussion. 53

9.
10.
11.

Table Of Contents

Additional Research Needs.
Bibliography

Appendix A and B

(Cont.)

1.

2.
3.

9.

10.

ll.

12.

13.

1h.

15.

List of Tables
Esthmated Per Acre Yield of Principle Crops Grown
by Soil Management Groups.
Price of Products Used in Computing Net Income .

Estimated Costs of Seeds for Major Crops Used in
Computing Production Costs.

Use of Each Soil Management Group as Shown by Conser-
vation Needs Data.

Estimated Proportion of CrOpland Used for Different
Creps in Osceola County on Each Soil Management Groups

Estimated Acreages of Crops Grown in Usceola County

Based on Acreages of Soil Management Groups Plus Tables

Page
27

28
29

30

36

37

h and S and Averages of Michigan Agricultural Statistics

19h9 to 1958.

Estimated Gross Annual Income Per Acre From Cropland
in Usceola County by Soil Management Groups and Crops

Estimated Average Cost of Production for the Common
CrOps Grown in Osceola County.

Estimated Average Cost of Production for “ay and
Pasture in Osceola County. '

Estimated Annual Costs Per Acre of Cropland in 0sceela
County by Soil Management Groups and Crops.

Estimated Annual Net Income Per Acre of Cropland in
Osceola County by Soil Management Groups and Uses.

Estimated Net Income Per Acre df Crops by Soil
Management Groups in Osceola County.

Estimating Net Income Per Acre From Alternatives of
uses of Cropland in Osceola County By Soil Management

Groups.

Estimated Stumpage Values Used for Standing Timber
Values.

Mean Stumpage Values Used in Estimating Net Income
of Woodland in Osceola County.

39

no

1,2
#3

he

h8

Le

1.

2.

3.

h.

6.

7.

9.
10.

11.
12.

13.
11:-

List of Figures

Map of Michigan Showing the Location of Osceola
County.

map of Osceola County Showing the Location of Each
891111310 Unit.

Illustration of the Method Used in Determining the
Number of Acres in Each Soil Management Unit by Kinds
of Land Use.

Trends in Yields, Acreages and Prices of Corn in
Osceola County from l9h9 to 1958.

Trends in Yields, Acreages and Prices if Oats in
Osceola County from 19h9 to 1958-

Trends in Yields, Acreages and Prices of Wheat in
Osceola County from 19h9 to 1958.

Trends in Yields, Acreages and Prices of Hay in
Osceola County form l9h9 to 1958-

Trends in.Number of Cattle and Calves, Cows Milked
Two Tbmes a Day and Prices for Milk from l9h9 to 1958

Relation of computed Net Income to Sale Price.

Relation of Computed Net Income to Sale Price After
Capitalization of Estimated Net Income.

Relation of Sale Price to Estdmated Land Values by
Soil Management Groups and Land Use.

Relation of Sale Price to Assessed Value in Osceola
COunty .

Relation of Equalized Values to Sale Price.
Relation of Equalized Values to Estimated Net Income.

vi

Page
16
18

25

31
32
33
3h
35

56
57

52
58

S9
60

THE USE OF SOIL MANAGENENT GROUPS AND
RELATED INFORMATION IN DETERKINING AGE CULTURAL LAND

VALUES IN OSCEOLA COUNTY, NICHIGAN

Purpose

The purpose of this paper is to demonstrate a method
that would be applicable to the valuation of land as an
investment whether it be for cropland, forestland, pasture
or other agricultural uses. With an understanding of the
proposed method, an individual would be able to determine
the relative worth of land as an investment.

The method used was similar to the ones previously
used in Arenac and Eaton Counties, Michigan. Its validity,
adaptation and utility are tested here in the dairy,

potatoes and truck type of farrizg areas in fiichigan.

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Land appraisal begins with an understanding of value
and different kinds of value. A dictionary (27) definition
of value is, "The quality or fact of being excellent, useful,
or desirable; worth in a thing," or "The estimate which an
individual places upon some of his possessions as compared
with others." A more liberal definition of value would be
the ability to satisfy a need of an individual. We must
remember that there are as many kinds of values as there are
needs.

An illustration, Barlowe (l), of economic value as
applied to land value would be the example of a land owner
who buys a parcel of land for four thousand dollars and
erects a sixteen thousand dollar house on it. At this
point he has invested twenty thousand dollars in his property,
a sum which may be considered as an economic value. When
the property is appraised for a mortgage loan, it may be
appraised at seventeen thousand collars. A tax assessor
may assess it for property-taxation purposes at twelve
thousand dollars. Upon a decision to sell his property,

a real estate broker might list it at twenty-one thousand
dollars. Iowever, before selling the owner discovers that
the property is needed for a public project and its con-
demnation appraisal value is twenty-four thousand dollars.
This paragraph is an illustration of the difference among

different kinds of economic value.

2.

Concepts of Land Value

Gaddis (S) states that the value of property may be
expressed as its worth in terms of money to the individual.
This may be affected by terms and conditions of the sale
and what the buyer is willing to pay under the existing
conditions.

As cited by Black, et al (2), land value may have a
three fold concept. First a market value, this is based
on experience and actual transactions. This can be refined
by collecting data on selling prices and on the major
facts about a considerable number of comparable farm sales
in an area within the last few years. Their data reflected
the differences in yields, types of roads, land tillage and
distance from towns. Secondly, value may be an assessed
value, which is determined as an estimate of property
value for taxation. This is usually lower than the market
value. It will probably remain stable from year to year
accerding to the persons assessing the properties. Thirdly,
a loan value, which is considered as a normal value based on
average production and normal prices of farm.products. Loan
values are partially determined by regular income from year
to year based on income and operating statements prepared by
the farm Operator.

Another concept of value may be the value of land to
the owner. This is determined by its ability to perform
particular services for the owner, either as a source of

financial income, or as security and as a home. Smith (23)

3.

states that value in this sense could differ from sale
price, if the price is more of a statement of sacrifice
involved in the sale of property. Smith continues by
saying that "value is often confused with price." Many
people say a farm is worth a certain amount of money or it
has been sold for some sum of money. So in discussing

the value of a farm, they are discussing what is generally
known as the price set on the farm.

KcNicheal (10) contends that it is possible to have
a normal agricultural value associated with the land. This
is based on the amount a typical purchaser would, under
usual conditions, be willing to pay and be justified in
paying for the prOpcrty for customary agricultural pur-
poses, with expectation of receiving normal net earnings
from the farm. This is based on the agricultural assets
only.

There is a relationship that exists between "value"
and "price". Price is an indicator of value to the
individual, while "value" by itself is an estimate of
what property might be worth, on the average, to a large

number of individuals.

Principles of Appraisal

According to Davis (3), appraisal procedure logically
divides itself into an inventory of resources and the
conversion of these factors into dollar values. Estimates
are determined by physical productivity of the farm, its
location and its use as a home.

Wagner (26) expresses the appraisal of farm land as
the estimation of worth which is determined in part by the
production of the farm. The land is the chief unit of
production. Inquiry into those factors that constitute
and affect value is an important segment of land appraisal.

Land value, in appraisal procedures, may be and usually
is determined by one of three methods. The first of these
is Income Capitalization. This is the concept that the
present value of property should always equal the present
worth of all its future incomes. Evaluation should equal
the sum of its future flow of income rents discounted back
to the present. Mathematically expressed V = 5/3, when V
is the property value Which is equal to A, the estimated
average annual net return and R, the rate of interest
used in the capitalization process. The advantage of this
method is that it places emphasis of the future income
producing capacities of individual properties. A disadvantage
is the difficulty of setting of a proper rate at whidh to
capitalize net income. One has to avoid making a very
conservative estimate of net income on poor land and then
capitalizing at a high rate.

5.

e.

The second method is the Market Comparison approach.
This is determined by the conditions and prices associated
with the sales of similar and comparable properties and
the price which the property will bring in use current
market. This method provides a definite bridge between the
theoretical Income Capitalization approach of economic
value and the actual exchange values of the market. A
disadvantage is often the lack of current market data.

A third approach is the Replacement or Reproduction
Cost approach. This is the assumption that properties
should be worth their present replacement cost or the
cost of providing an acceptable substitute less an allow-
ance for depreciation and obsolescence that has occured.
This method has the advantage of easyppplication and a
tendency to treat all properties on a comparable basis.

his method does not take into consideration the earning
capacity of land except as it is reflected in its replace-
ment cost.

These three methods of land valuation are used in the
American Rural Appraisal System. (10, 1)

When determining value it is important to keep various
principles in mind. Smith (23) lists these Principles as:
(l) The highest and best use; that is, the use which will
preserve the land and bring to the operator the largest
net return over a long period of time. 'Eighest and best
use varies with time, economic and technological changes

and while it represents a top value in a particular time

‘\J

for a particular use this perfect market condition is

never attained in

’U

ractice. (2) Increasing and decreas-

Ho

ing returns; that s, the response of land to conti ing

nu
increased utilization. (3) Balance and preportionality;
such as rotation of crops and the efficiency of labor
and equipment. When these are out of proportion to each
other;then.conditions are not conducive to highest ami
best use. (L) Conformity; agreement with other members
of society of which the operator is a part, i.e., a dairy
farmer in a cash frain district would be an unconformity.

(S) Substitution; replacement of one unit for another in
case one unit should fail. This represents the upper limit
of valuation. (6) The Law of Contribution; additional values
due to the erection of additional features on the land,
i.e., buildings, fences, electricity and telephone.

(7) Competition; concept of supply and demand. (8) Agents
of production; these would be labor, coordination or
management, capital and natural resources. All of these
eight principles are to be kept in mind when using any of
the three methods of appraisal.

In the appraisal of land, various factors are encount-
ered. The productivity of the soil is a function of soil
management and soil differences, buildings which may add to
the income of the family, (or contribute directly to farm
family income), and location or distances to markets, towns,
schools, etc. In Nebraska (18) it was found that through

the lack of recognition of these factors owners of low

8:
value land carried a proportionally heavier burden of taxes
than the owner of higher valued, more productive land.

Another factor that should be considered is the type
and use of crop rotations or crop sequences. This is an
aid in determining the value of specific soil types which
will give an indication of worth of soil and thus affect
the appraisal of the farming unit. Crop sequence is used
to connotate the different patterns of crops Which reflect
three situations, (1) Ho crop interaction; (2) Negative
crop interaction; (3) Positive crop interaction.

In theory no crop interaction would exist When no crop
in the sequence had an affect on any other crop and the
soil fertility is in a stable condition. Negative crop in-
teraction is when some crops are detrimental to others in
the rotation and basically affect soil fertility. Positive
crop interaction can be considered as the beneficial effects
some crops have on others in the rotation. Each one of
these basic relationships may affect net income.

Henry (7) states two relationships. The first of
these refers to factors no farmer can control. These would
be soils and location. Soils are the very foundation of
the farm and cannot be changed or altered except through

he use of fertilizers and other amendments. Soil types
clearly place the farm in its perspective high, medium or
low bracket. Location refers to the subsequent mass devel-
opment such as the construction of rail-roads and highways

which may enhance location and market value. Location is

 

important for it is tied in closely with adaptibility. A
farm may have value for other than agricultural purposes
such as sub-division and owner urban uses.

The second relationship of Henry are the factors that
the farmer can control. These would be adaption of the
farm and size of use unit. The adaption of the farm would
embrace a knowledge of soil types, landscapes and workability
of soil. Every community has its "Happy Enterprise". This
would be an individual who pursues his immediate interest
rather than What should be practiced in the management of the
soil and thus depreciates the value of the land. Thus the
adoption of enterprise to the area is the most difficult
factor confronting the appraiser and buyer.

An exception to adoption is specialization such as a
livestock feeder or turkeys, which may achieve considerable
success even with the poorer soils. This is more the re-
flection of the individual‘s ability rather than.the soil.
This tends to over value some of the poorer soils.

The second factor of farmer control is size of the
unit. The operating unit must be large enough to
efficiently utilize the land, maintain efficient control
of labor and still be within the management ability and

capacity of the operator.

Techniques of Land Valuation in Other States

One of the first attempts at developing a system to
evaluate land in the Central United States was based on
kinds of soil by Kellogg and Ableiter (9). The objective
was to group soils into "Natural Land Types" which may be
defined as land having particular combinations of physical
features - principally climate, soil, topoSraohy and stoni-
ness which define its natural productivity for plants.

The laws of California (2h) require all lands, if
similar in quality and quantity to be valued at the same
rate for tax purposes whether cropped or not. In order to
accomplish this they have turned to the rating of soil by
the Storie Index Method. This method strives to evaluate
soil for general agricultural purposes, regardless of
location within the state. This rating is based on
characteristics and condition of the soils, such as profile
development, drainage, alkalinity, erosion and fertility.

From the study conducted by Scholtes and Riecken (22)
in Taylor County, Iowa, it was found through the use of
soil survey informiion that many tracts had already been
equitably assessed by the county assessor. Some plus and
minus valuation of tracts resulted from he application of
survey information. This was thought to give a more
equitable valuation of these tracts.

Workers in Nebraska (18) used a method based on soil
survey information and building values. Economic ratings

of soils were prepared for cropland, pasture and rangeland.

. lO.

11.

Building evaluation was according to a rating system that
considers condition, adequacy and location. These values
were converted into net incomes and then into land values.

In Central Illinois (17) (2S) efforts have been made to
determine the productivity of the soils. This was accomplish-
ed with soil survey information and production records of
farms in Central Illinois. These two were correlated and
differences were determined. From the knowledge of the
foregoing material, technicians in Central Illinois were
able to find the influence of soil types on farming, rel-
ative long range earnings and capacity of farms and extent
to which earnings on various soil tyees are influenced by
soil management. With these data the relative value of the
soils, and thus the farm units, were determined.

In hichigan land value studies (A) (20) (21) a method
was used based on expected net income. Soil nanagerent
groups and related information on their use and productiv-
ity in addition to production costs and prices of products,
were used to calculate the expected net incomes. These
were then compared with sale prices of land to detennine
dollar values of the land. Priest (20) found that cal-
culated land values compare favorably with those assigned
by tax commission appraisers and farmers, but that the
total appraised farm values were about 2!fl higher than the
actual sale values. Schairer (21) found that in comparing

calculated and sale values, dairy farms are commonly over

12.

valued compared to cash crOp farms. Even though dairy
farms are worth more because of the costs of buildings
required, according to replacement values, buyers do not
recognize or are not willing to pay the premium for such
property. Results of diese studies also show that farms
selling for high prices are commonly assessed at a lower
proportion of their sale value than those selling at lower
prices.

The technique being used in Montana for tax assess-
ment (1h) (16), in the reclassification of rural lands,
is a method using information from technicians, crop data,
services of agricultural agencies and information from

ls is rated according to

Ho

farmers. Productivity of the so
yields of crops drown and the number of animal units pro-
duced as a measure of grazing on pastureland. This provides
a relative basis for the assigning of dollar values for

tax assessments. This system is not used unless county
commissioners find too many inequalities resulting from
existing methods of appraisal and tax assessments.

Perry (19) in a recent article cites the Soil Survey
Report as a new and useful tool for many diversified
interests. These would range from studies on land utiliza-
tion and planning, industrial and urban development,
engineering, woodland development and land appraisal. An
example was cited from Polk County, Iowa where 2,569 protests
were registered after reassessment in 19h9. Of these, 60%

were farmers. In lQSh a soil survey was completed at the

request of the county. The information was translated
into earning power through a system of crop suitability
ratings. Only one farmer protested after use of this
revised base in l95h. Soil surveys are an aid when
appraising land for it does not penalize the efficient
farmer since ratings are based on the production expected

from average or normal management and not on how well the

farm looks.

Procedure

The procedure used here is similar to the ones used

in Eaton County (20) and Arenac County (A). The basic

steps in this procedure are as follows:

1.
2.
3.
L.

r!
)0

Selection of area for study.

Selection of farms and collection of data.

“nina the various soils to soil management groups.

Measurement of soil grOUps by land use.

Determination of net income:

A.

B.

C.

F.

Estimation of yields per management group for each
crop.

Estimating prices received for each crop.

Estimating proportions of crops grown on each
management group.

Estimating the gross income from each crop and
cropland per management group.

Estimating the cost associated with each crop and
cropland per management group.

Estimating the net income from each crop, cropland,
pasture and woodland.

Estimating values of standing timber and improvement
values.

Comparison of expected net income with sale values minus
values of improvement and standing timber.

Estimating land values from the above process.

Description Of Area For Study

The area under consideration was Osceola County,

Michi

Y

Qan. Osceola County is located in the northwest}
central part of Michigan, figure (1). The types of farm-
ing have been described as dairying, hay and truck crops (8).
Census data show that during the last twenty years the
acreages of potatoes has dropped seventy to eighty percent.
Truck crops, at present, seem to play only a minor role on
cropland. Minor acreages of potatoes, field beans and
cucumbers exist on farms Where conditions are favorable.
Most of the cropland acreages are used for feed crops of
hay, pasture, corn and oats. Wheat is grown as the major
cash grain crop.

The growing season ranges from 110 to 130 days on the
upland soils. Depressional areas may have temperatures
near freezing during the growing season. This tends to
limit the use of these areas mainly to hay and pasture with
some small grain.

The reasons for the selection of Osceola County were
the availability of a recent detailed soil survey, the
amount of available data on land use; the need for inform-
ation on farm appraisal in this particular area of Kichigan

and the personal eXperiences of the author.

15

\.

Figure 1 Map of Michigan Showing the Location of Osceola County.

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Selection of Farm Properties and Collection of Data

The first step was to collect information on the farms
over eighty acres in size, sold between 1952 and 1958 from
the Register of Deeds in Reed City, Michigan. This consist—
ed of tabulating the liber, page, transfer date, names of
the grantor and grantee, and legal description of the farm
units location. Also tabulated was the amount of the revenue
stamps and the estimated market price. (55 cents in revenue
stamps are required per $500 of sale price for each prOperty).
Tax and assessment information for each property was obtained
from the Office of the County Treasurer, Court house, Reed
City, Michigan.

Tracts of land eighty acres in size or larger were used
to insure adequate coverage of the soil management groups
and to avoid part time farming. Those areas that were felt
to have been transferred for purposes other than agriculture
were also eliminated from this study.

Each deed was checked for any restrictions and consider-
ations that would add or subtract from the value of the unit.
As a check against the location in the deeds, each sample
unit was located on the county plat book. This was to avoid
any errors during future investigation of the units.

Their distribution is shown in figure (2).

After the farms were definitely located and the bound-
aries fixed, it was necessary to picture What lay within the
boundaries. Items that were included for inventory were
soils, land use, homesteads, drainage patterns, rivers,

streams, gravel pits, roads and railroads.

17.

 

1L

 

 

 

 

RQW RBW.

2 Map of Osceola County Showingmthmeu Llocation of Sample Units.

2

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Soil Management Groups

Soil management groups are interpretative soil group-
ings based on similar soil properties to a depth of three
to five and one-half feet. These management groups can be
further subdivided into units on the basis of slope, degree
of erosion and stoniness. The management groupings are
useful for fertilizer and lime recommendations when used in
conjunction with tests of the plow layer and for the design
of management practice recommendations When used in con-
junction with information on slope, degree of erosion and
stoniness.

The numbers used in this system indicate the relative
coarseness and fineness of the primary materials from which
the soils were formed: 0 is for the finest clays and S
for the coarse textured sands. Associated with these numbers
is a small letter indicating the natural drainage under
Which the soil has developed; a--for well drained, b——fcr
imperfectly drained, c--for poorly drained soils. Thus,
the management group description for a well drained, sand
soil would be 5a.

When one soil is formed from one kind of material over
another, a fraction is ised. The number in the numerator
stands for the texture of the upper material to a depth of
lS-hZ or hE-éb inches. The denominator refers to the
material in the lower story. For example 3/2 a is for
well drained, sandy loams lE-hZ inches thick over loams to

silty clay loams.

20.

On the basis of these principles it is possible to
designate the groups of soils with similar characteristics
so as to show the relationships among them. The following
table shows the relationship of tje soils in Osceola

County to these management groups. (5)

Soil Series Name

Alcona
Allendale
Au Gres
Bentley
Blue Lake
Bohemian
Breckenridge
Brevort
Erimley
Bruce
Butternut
Carbondale
Coral
Dighton
Emmet
Ensley
Epoufette
Gladwin
Graycalm
Grayling
Greenwood
Houghton
Ingalls
Iosco

Isabella

Kalkaska

Soil Type Number
& Surface Texture

 

325
758
7&0
262
223
272
826
8M7
636
895
897
020
66k
u86
310
859
822
696
116
118
Odo
03o

s.L.

L.S. 76o s.L.
s. 7A1 L.s.
L.S.

L.S.

L.F.S. h2h Si.L.
s.L.

L.S.

L.F.S.

L.F.S.

Loam

buck or peat
P.S.L.

s.L.

s.L.

Loam

s.L.

s.L.

Sand

Sand

Peat

Ruck

L.s. Lu3 s.L.

21.

Soil Kanagement Group

 

3a
h/lb
Sb
ha
'a
2a
3/2c

h/Zc

3b

3c
20

kc

h/Zb

2a
5.0a

Kawkawlin
Kerston
Kinross
Linwood
Lupton
Mancelona
Manistee
Narkey
McBride
Melita
Menominee
Montcalm

Nester

Newaygo
Ocqueoc
Ogemaw
Pinconning
Richter
Ronald
Roscommon
Rousseau
Rubicon
Saugatuok
Sigma

Sims

Tawas

Tonkey

216
23

Leo

u82
320
202
Bob
651
670
836
833
270
120
830
702

903
907

060

L.
iiuclc

S.

652 Si.L.
or loam

Huck or peat

laluck OI' peat

/ S.

L.S.
huck
s.L.
S.

S.

L.S.

L.
s.L.

S.L.
L.S.
S.
L.S.
S.L.
L.
S.
F.S.
S.
S.

.L.

(1‘)

F.S.
L.

260 L.S.

or peat
L66 L.S.
21; L.S.
217 L.S.
36S s.L.
#79 L.S.

313.3 s.L.

805 L.S.

83h L.S.
271 L.F.S.

832 L.S.

L. 90h Si.L.
906 s.L.

Ruck or peat

8151 s.L. 8152 L.S.

2a
3a
ha
Sb-h
M/lc
3b
30

ha
5.3a
Sb-h
uh
2c
m/hc
3c

22.

Twining
Ubly

Wallace

6L2 L.

335 S.L.
105 So

6&9 L.S.

2b

3/2a
Sa-h

23.

heasurements of the Sample Units.

The distribution of the soils and land use were shown
on aerial photos. Through the use of a transparent over-
lay, information concerning the farms was traced nd
analyzed as shown in figure 3. A sample of the sheet
used in summarizing the acreage by soil groups and land
use is shown as form 1 in Appendix R.

The planimeter, a dot counter and a small plastic
grid (8” to a mile) were used for the measurement of
land use, soil mapping units, size of homesteads, lakes
and roads. All of the methods proved to be sufficiently

accurate, but the last was more efficient, due to the

small areas which were encountered.

25.

Figure 3. Illustration of the Kethod Used in Determining

The Amount of Soil Napping Units In Acres.

Sample Unit Outline

 

 

 

 

 

 

 

T 20 N a 7 w Sec. 22 s.%, S.E.%

Location
Size of Unit 80 Acres
Scale h Inches/Mile

Mapping Unit Boundary

Land Use Boundary

 

 

Soil Land Use
Management
Soil Mapping Unit Group‘_ L P F X H
hSO/B-l 2a to 3 1 1 1
653/3-1 2b 13 10 2
907/A-o 2. 3
217/c-1 u/2a 2 A

Total Acres 55 16 S 1 3 = 80 Ac.

Determinina Net Income for Cropland

O

For the determination of expected net income, it is

necessary to estimate the expected yields and prices for

the crops. From the product of these, the expected costs

of production are then deducted to give the expected net

income. The procedure is as follows:

A). From the Michigan Agricultural Statistics for l9h9
to 1958, Types of Farming in Michigan (8) and data from the

National Plant Food Institute (13) yields for each manage-

ment unit were estimated, these were recorded in table 1.

Discussion with the count a ent and personal observations
y 8

substantiated these relative values.
B). In calculating the prices the farmers received,

average yearly prices were used. The source of this inform-

ation was the Michigan Agricultural Statistics for 1952 to

1959. The prices used are recorded in table 2. Seed costs

were obtained from the Michigan Farm Bureau and the Okemos
Elevator. These are recorded in table 3.
C). Initial data on land use by management groups was

obtained from the Osceola County Inventory of Soil and Water

Conservation Needs. This information showed each management

unit and acres of land use as cropland, pasture, forest or
idle land as shown in table A. The determination of percent-

ages of each crop grown on the cropland in each management

group, was estimated by the following procedure. From the
data of the Michigan Agricultural Statistics for Osceola
County, 1950-1959, charts h-B were constructed to give an

estimate of total acreage.(Continued on Page 37)

2b.

27.

Table 1. Estimated Per Acre Yield of Principal Crops

Grown on Each Soil Management Group

Soil Corn Oats Wheat Alfalfa All Hay Pasture Perm
Group bu. bu. bu. Hay-T. T. per Rotation Pasture

 

 

 

 

& per per P8P per acre Tons per cow

Slope acre. acre acre acre acre days
2a-A-B 87 to 30 2.3 1.3 1.2 90
2a-C-D 3o 33 21 1.7
2b 50 to 32 2.5 1.3 1.25 90
2c 52 A 35 2.5 l-h 1.3 90
£55-38 37 3o 23 1.9 1.1 1.0 75
3/2-3a
C-D 30 27 18 1.6
3c-3/2b 81 to 25 2.u 1.2 1.2 85
3c-3/2c A3 to 25 2.i 1.2 1.2 90
u/2a 3o 27 17 1.7 1.0 .9 72
h/Zc 37 35 21 2.1 1.1 1.0 65
La-A-B 35 25 21 1.5 1.0 .8 60
ha-C—D 2o 21 17 1.8
ib-(ub-L) 37 27 23 1.7 1.0 .9 65
hc-(hc-L) to 30 25 1.8 1.1 .9 7o
5/2a 2o 21 13 1.2 1.0 .7 55
5-0a-5.3a
A-B 15 17 11 .9 .8 .5 3o
5.0a-5.3a
C-D 10 15 10 .9
5b 18 2o 12 1.0 1.0 .7 35

So 22 22 13 1.2 1.0 .7 55

Table 2. Price of Products Used in Computing Net Income

Corn

Oats

Wheat

Alfalfa (Baled)
All Hay (Baled)

Pasture (Permanent)

1.29 per bushel
.70 per bushel
1.68 per bushel
22.53 per ton
19.90 per ton
.088 per cow day

28.

Table 3.

Crop

Corn

Winter

Wheat

Oats

Alfalfa

Clover

Cost per

 

(Pioneer)

(Ranger)

(Vernal)
(June-Pennscott)
(Pennscott)

(June a Sweet
Mixture)

approximately

Estimated Costs of Seeds for Major Crepe

Used in Computing Production Costs

Seeding
rate per
acre

Field
lO#/ac.

Silage
1 #/ac-

l%-2 bu.
8.00

2 bu./ac.
6-10#/ac.

6'10'fi4/a0 o
6-10#/ac.

6-10,:7/30.

10-12#/aco

12-15#/300

unless shown, for non-certified seed are
20% less than certified seed.

Certified
seed costs
per acre

 

29.

Non-Certi-

fied seed

costs per
acre

 

re

am

{a

{a
:53:

ea

.4"
.. -
~. .

we

.-
:1“:
z

1.60

Table 8. Estimation of Land Use in Conservation Needs

Survey for Each Soil Management Group

 

 

Management Cropland Permanent Idle Woodland
Group Pasture
2a 60.25% 15% 8.25% 16.5%
2b 88.2 35 3.8 17.0
20 39.6 18 7.9 38.5
3a-3/2a 82.1 21 12.3 28.6
3b-3/2b 56.9 8 10.0 25.1
3c-3/2c 88.0 7 9.0 80.0
8/2a 19.6 20 7.8 53.0
u/Zb 9.0 58 8.7 29.3
h/2c
8a 32.3 2; 17.1 :7.6
Lb (LE-l) 30.“ 15 20.5 8.8
8t-(\-_1) 82.: r 15 9 10.0
f/fh ;.3 ‘F ’1 3 55.2
5.0a—5.3a 12.5 ll 35.5 81.0
5b 55,5 3 12.0 29.5
56 89.3 2 8-7 80-0

31
Figure 8. Trend in Yields, Acreages and Prices of Corn in
Osceola County from 1989 to 1958.

1101
35 i

30 ‘

Bushels / Acre

‘25"-

 

 

“9 56:1 six". 5'2 0'53 5'58 5'5 5'6: 57»: 5'8

Years
12
ll-

101

Acres in Thousands

 

 

89 50 51 52 53 58 55 56 57 58

Years

 

Price / Bushel
H
N
\R

 

 

89 5b 51 52 53 58 SS 56 57 58I

Vanna

32

Figure 5. Trend in Acreage, Yields and Prices of Oats
in Osceola County from 1989 to 1958.
35.
Q)
8
<5 ‘30 '
\\
U)
5:25
2
m
20 ‘

 

 

1+9
12 7

ll -

lO 2

Acres in 1housands

 

Peices Recieved

 

50 5'1 5'2 53 58 55 56 57 58

Ybars

 

50 51 52 53 58 55 56 57 58

Years

 

5b 51 52 53 58 55 55 57 58

Years

Bushels / Acre

Acres in Thousands

Prices Recieved

33
Figure 6. Trends in Yiekds, Acreages and Prices for Wheat

in Osceola County from 1989 to 1958.

25 u
20 ‘

15'

 

89 50 51 52 53 58 55 56 57 58*

Years

0‘

 

 

89 5o 51 52 55 58 55 56 57 58

Years

2.201

N
O

3.4
O

N
o

O
O

H
o
\O
O

1.80-

 

89 50 51 52 53 58 55 55 57 58

Years

Acres in Thousands Tons / Acre

Prices Recieved

38
Figure 7. Trends in Yields, Acreages and Prices for Hay

in Osceola County from 1989 to 1958.

2.0 2[
1.5”
1.0 ‘

89 50 51 52 53 58 55 56 57 58‘

 

 

Years
85.,
noqI/2//N\\\\o112277-~——-““\\\\v////'--“\\\\\
35 ..

 

 

89 50 51 52 53 58 55 58 57 58’
Years

22

21

20

19

 

 

89 5o 51 52 53 58 55 5% 57 58

Years

Number Cattle & Calves

Cows Milked Twice Daily

35

Figure 8. Trend in Number of Cattle and Calves, Cows hilked

30'!
25«

20‘

 

89

121
11*

10‘

 

Two Times a Day, Price of Milk per cwt... Price of
Butterfat per Pound from 1989 to 1958.

58 51 52 53 58 55 58 57 58

Years

 

89
8.50-)

3.50-

 

.80 .'

.70 ~

. 602

 

58 51 52 53 58 55 58 57 58

Pric;;'/cwt
for milk.

Price /lb.
for BOT.

 

89

58 51 52 55-_,58 55 56 57 58

 

36.
Table 5. Estimated Proportion of Crepland Used for
Different Crops on Each Soil Management

Group in Osceola County.

Soil Corn Oats Wheat Alfalfa Other Rotation
Group Ha Pasture
2a 105 12% 55 365 7% 30%
2b 12 12 8 25 10 33

2c 12 15 8 10 15 37
3a-3/2a 12 12 7 37 8 28
3b-3/2b 10 10 10 30 15 25
3SE3£26 12 12 5 15 20 26
8/2a 10 10 8 30 20 26
8/2b—8/lb 10 10 10 25 20 20
8/20

8a 12 12 5 30 20 21
8b-(8b-L) 10 15 5 25 20 25
8c-(8c-L) 15 20 5 15 15 30
S/Za S S 25 2S 35
5.0a-5.3a 3 3O 2O 37
5.0b 10 10 5 15 25 35
5.00 10 10 5 10 3O 35

Table 6.

Soil
Management
Group
2a
2b
2c
3a—3/28
30-3/20

30-3/20
(Bo-L)

h/Za
u/eb-u/lb
h/Zc

ha
hb-(hb-L)
hc-(hc-L)
S/Za
S.Oa-S.3a
5.0b

5.00

Total

Estimated Acreages of Crops Grown in Osceola

County Based on Acreages of Soil Management

Groups, Tables h and S, and lQSh U.S. Census

Data and the Average of Nichigan Agricultural

Statistics for the years 19h? to 1953

37.

 

Av. Mich. Ag.

Stat. 19h?-

1958

U.S. Census

Date IQSA

Corn Oats Wheat Alfalfa Other All Rotation
Hay Hay Pasture

3.131 3,7u0 1,552 11,200 2,190 13,390 9,392
u05 MOS 2L6 8th 338 1,182 1,11u
159 200 10A 132 20 152 ABQ
1,200 1,200 697 3,550 7A3 1,293 2,395
no to to 120 60 180 100

15 15 6 2o 26 u6 3L
259 259 100 865 517 1,382 6L9
73 73 73 18k 1&5 329 1A7
3,005 3,005 1,260 8,376 5,037 13,u13 5,289
78 118 39 180 15h 33k 180
118 156 39 180 15h 33A 100

u u u 25 25 50 35

500 520 300 2,550 1,083 5,239 3,11h
53 53 26 70 1th 21b 110
53 5h 27 53 179 232 525
9,093 9,8t2 b.515 28,355 11,b15 39.770 23,673

9,776 10,000 b,h90 81,600

7,837 9,505 3,700 26,600 11,900 38,500 33,591

38.

trends of different crops, total hay and cropland in the
county. The average figures from Michigan Agricultural
Statistics for 1989 to 1958, were used for the total hay
acreages and proportions of other crops of the total crop-
land area in the county. A summary of the data shows that
86,000 acres of total cropland exists in Osceola County
according to the Conservation Needs data. Nichigan Agricul-
tural Statistics show an estimated 62,900 acres in corn, oats,
wheat and hay. The difference, 23,000 acres, was assumed

as the amount, in acres, of rotation pasture. This was

found to be a valid assumption upon investigation of reporting

methods in Conservation Needs. Idle cropland was not consid-

ered as part of the cropland estimate. Of the major crops
grown, corn occupies 11%, oats 11%, wheat 5%, all hay h6fl,
(of which 70% is alfalfa and 30% is grasses) and rotation
pasture occupied 27%.

On the basis of the above sources of information and
the estimated proportion of the various crops grown on the
various soil groups in Arenac County (A), a cropland use
table for Osceola County was constructed as shown in table 5.

These estimates were checked by multiplying management
group acreages in Osceola County from the recent soil survey
of the county by the proportions of these soil groups used
for cropland, table A, and these by the estimated proportions
of the cropland in each crop, table 5. It was then possible
to compare these estimated acreages of the various crops

with the census data on crops grown in the county as shown

in table 6.

Table 7.

Soil
Groups

2a

2b

20
39-3/20
3b-3/2b
3c-3/2c
h/Za
8/2b
h/Zc

8a
ub-<ub-L>
80-(hc-L)
5/2a
5.0a-5.3a
5b

5c

Corn

06.10
7.78
7.86
5.71
5.28
6.65
3.87
8.38

5.81
8.76
7.72
1.29

Oats

$3.36
3.36
8.51
3.36
2.80
3.36
1.89
2.31

2.10
2.26

Groups and Crops.

Wheat Alfalfa

82.53
8.30
8.70
2.72
8.20
2.10
1.20

3.36

1.78
1.93
2.11
1.09

.92
2.16
2.18

$18.65

18.08

5.85
15.83
16.22

8.11
11.89
15.18

10.13
9.57
6.08
6.75
6.08
3.37
2.70

81.81
2.58
8.17
1.75
3.58
8.77
3.88
3.98

3.98
8.38
3.28
8.97
3.98
5.87
8.58

Estimated Gross Annual Income Per Acre From

Cropland in Osceola County by Soil Management

$8.10
9.29
10.83
5.80
0.75
7.02
5.27
8.32

3.78
5.06
6.08
5.51
8.16
5.51
5.55

39-

All Hay Rotation Total
Pasture

8 2.55

81.35
37.92
38.77
38.83
32.01
27.60
33.53

26.08
28.96
29.87
20.38
16.69
19.53
20.56

Table 8. Estimated Average Cost of Production for the

Cultivated crops Grown in Osceola County.

Labor, machinery,
plowing, disking,
dragging, planting

and cultivation.

Harvesting-loading

hauling and storage.

Fertilizer and seed

costs.

10% risk and

management charge.

Corn

$12.25

8 5.50

Oats

 

s 7.98

he

5.75

$10.10

8 . 8

Wheat

8 9.55

$ 5.75

$13.12

1101

Table 9. Estimated Average Cost of Production for Hay

and Pasture in Osceola County.

Alfalfa Other Rotation Permanent
Hay Pasture Pasture
Yield 2, 3 T/A 1.3 T/A 2/3 of hay 90 days

and alfalfa

Labor, machinery,
plowing, fitting
and planting. 8 1-00 8 1.50

Harvesting, mowing,
raking, baling and

storing. 8 8.25 8 6.50

Fertilizer and

seed costs and

bulk spreading. 810.98 8 9.08 823-50 8 1.50
R1 sks and
management 8 1.92 8 1.61 8 2.80_ 8 .30
‘1 825-90 8 3.30
Costs per acre # fl 9 fi 36
or cow day. 821.15 917.79 9 3.86 a .03 per
cow

day

Table

Soil
Group
2a

2b

3a-3/2a
3b-3/2b
30-3/20
h/Za
h/Zb
1/2c

ha

bb-hb-L

hc-hc-L

5/28
5.0a
5.3a
5b
50

10.

Osceola County by Soil Hana

Corn

$3.01
3.91
3.65
3.91
3.0M
3.9M
3.01
3.0a

3.91
3.01
L.Sé
1.52
1.52

b.)

3 o 0);-

Oats

$3.13

3-13
3.92
3.13
2.60
3.13
2.60
2.60

F-J 1—1 U1 k» k )
o o 0 ¢ 0

\u \1) m \0 H
P: 64 r0 [U x»

2.60
2.60

Wheat

$1.58
2.61
2.61
2.19
3.12
1.58
l.h3
1.13

1.58

1.58

[\3
1"

\FL Lu
\J)
\O

O
in

\p
O
m

l\)
1...!

H
}4

3.58
3.58
2.68
hoh9

3.58

k.h9

5.36

ement Groups.

Rotation
Easture

$1.16
1.27
1.113

-7“
I-
1 \)

Estimated Annual Costs Per Acre of Cropland in

Total

517.92

18.11
16.11
19.52
18.85
16.u3
18.09
17.88

Table 11.

Management
Unit

2a

2b

2c

3a-3/2a

3b-3/2b

30-3/26

h/Za

E/Zb-(hb-L)

1/26-(uc—L)

ha

he

he

S/Za

5.0a-5.3a

Sb

50

Estimated Annual Eet Income Per Acre of

Cropland in Osceola County by Soil Hanage—

ment Groups.

Cropland

$22.63
23.21
21.51
15.25
18.16
111.89
8.5
11.73
10.00
6.57
9.&9
11.06
1.07
.61
2.70
3.76

Permanent
Pasture

$11. 68
b.68
6.68
3.89
both
1.68
3.75
3.75
3.37

Woodland

113.

1:13—-

D). For the estimation of gross annual income from
cropland in each management group the following procedure was
used. The yields per acre of each crop on each group were
multiplied by the price per bushel. Through the use or
percentage of proportion of the crops on each management
group, the gross returns from each crop and the total were
determined and recorded in table 7.

E). Estimated costs per acre per year for each crop and
cropland on each management group was determined. The common
practices in Osceola County in crop proudction are assumed
to be similar to those reported in hiChigan EXperimental
Station Bulletin #72. Costs of these operations were based on
Extension Folder F-l61, Rates for Custom.Work in Kichigan.
These were determined on an acre rate with an averace level
of management. This was calculated by multiplying costs
associated with each crop, table 8 and 9, in each group by the
percentage of that crop on each management group, table 5.

Harvesting costs were assumed to vary with yields, Costs
of hauling and storage of the crops and costs of these
operations were from the custom rate schedule cited above.

Fertilizer use data were taken from the l95h.Census of
Agriculture data and the Michigan Agricultural Statistics.
Average amounts applied were for corn, 209 pounds per acre;
wheat, 251 pounds per acre; oats, 227 pounds per acre; hay
and rotation pasture, 191 pounds per acre, costs per pound
based on a 5-10-5 analysis at $70.00 per ton.

The estimated net income per acre for the cropland by

soil management flroups is then the difference between the
estimated total gross income in table 7 and fine estimated
total cost for the cropland per management group in table 10.
These differences in totals are recorded in table 11 and
similar expected net incomes from each crop on each soil
management unit is also listed in table 12.

F). For permanent pasture, the number of cow days per
acre on each soil management group in table 1 was multiplied
by eight cents and the costs of producing the pasture in

table 9 were deducted, the net income from pasture is shown

in table 11.

Table 12. Esthnated Net Income Per Acre of Crops by Soil

Management Units in Osceola County.

Fanagement Corn Oats Wheat Alfalfa All Rotation
Unit & Hay Hay Pasture
Slope

2a-A-B 130.20 8 1.89 8 19.28 830.67 8 8.08 $23.18
2a-C-D 8.28 -3.01 1.02 17.15

2b 31.08 1.89 22.50 35.18 8.08 21.30
2c 36.66 3.99 27.51 37.13 8.08 25.13
3a-3/2a A-B 17.31 -5.11 7.38 21.66 1.10 18.67
3a-3/2a C-D 7.95 -7.21 -1.02 11.90

3b 22.17 1.89 10.71 32.92 10.19 23.18
30 25.05 1.89 10.71. 32.92 10.19 23.18
1/2a 8.28 -7.21 -2.70 17.15 2.11 16.12
1/26, 1/1b 13.11 -3.01 2.31 19.10 1.10 17.77
1/2c 17.13 -1.61 1.02 26.16 1.10 18.67
1a-A-s 11.73 -8.61 1.02 12.61 2.11 11.18
1a-C-D -1.62 -11.11 -2.70 10.39

16, 1b-L 17.13 ~7.21 7.38 17.15 2.11 16.12
16, 1c-L 21.18 -5.11 10.71 19.10 1.10 16.12
5/2a-A-B -1.62 -11.11 -9.12 5.89 2.11 11.91
i:ga, 5.3a -11.07 -11.21 12.78 -.87 -1.87 7.11
5.3a, 5.3a -17.52 -15.61 -11.16 -.87

Sb -7.20 -12.11 -11.10 1.38 2.11 11.91
Sc -2.01 -10.71 -9.12 5.89 2.11 11.91

Woodland Evaluation

To determine the expected net income for woodland
the expected net returns used in the study conducted by
Heneberry et al (1) were used. Preliminary results gave
indications that another method of capitalizing the expected
net income was needed. Table 11 gives a summary of the
expected net incomes from cropland, permanent pasture and

woodland on the soil management groups in Osceola County.

Stand ing Timber Values

In order to obtain an accurate value for wood products
on the land it was necessary to design a data and check
sheet. This check sheet was a combination of methods used
by the hichigan State Tax Commission and the Michigan De-
partment of Conservation Land Examination Sheet. The data
sheet places emphasis on species and stand density which
is converted to thousands of board feet. This is then
multiplied by the corresponding values in table 13a. Each
sample unit that contained wooded areas was visited in

order to obtain accurate information and data.

17

18.

Table 11. Estimated Stumpage Values Used For

Standing Timber Values.

Saw Timber:

 

Maple $25-30 per Thousand Board Feet
Oak $20-10 n I! n 1!
Beech $10-up " " " "

Mixed Maple, Beech and Oak, $18-25 per Thousand Board Feet

Swamp Elm, Ash, Soft Maple $10-20 " " " "

Pulp:

Aspen, $2.00-3.SO per 1'x1'xlOO' cord.

White Birch, Oak and Hard Maple, $3.00-SOO per
1'x1'xlOO'

These values are from the Michigan State Tax Commission

Manual for 1955.

 

19.

Table 15. Mean Stumpage Values Used in Estimating

Net Income of Woodland in Osceola County.

 

Saw Timber gulp
Specie Kglgg Specie Xalge
Maple 827.50/m bd. ft. Aspen $2.75/cord
Oak $25.00/m " " White birch
Beech $10.00/m " " Oak & Hard Maple $1.00/cord

Mixed Maple
Beech & Oak $21.50/m
Swamp Elm 81:

Ash, Swamp Maple $15.00/m

These values are mean

"

H

N

values from table 11.

Improvement Values

Improvements, as used in this study, refer to the
homestead unit. This would consist of a house and out
buildings. Out buildings usually consist of a barn, silo
and in some instances a corn crib, garage and tool shed.
The values of the homesteads were studies on 50 farms.

The method of obtaining information on these units was
by the use of check sheets patterned after that proposed by
Schairer (21) and data in the Michigan State Tax Commission
Manual. Photographs were taken to show examples of the
homesteads and these are shown in the Appendix A. The
purpose of the check sheets was to systematically collect
enough field data on the buildings to determine any affects
they might have on the sale price of each farm. As with
Arenac and Eaton Counties the observable features of the
houses and out buildings were assigned a number according
to their relative importance. Adaptability was an added
feature for out buildings which was not used in the Arenac
and Eaton County studies. Examples of these check sheets
for the house and out buildings are shown as forms 2 and 3
in Appendix B.

The upper parts of the check sheets are designed to
rate the buildings according to the type and quality of
construction, material and use. Adjustment for depreciation,

location and personal convenience are held as separate items.

50.

Statistical Analysis

From the data compiled on actual sale prices and
estimated land values, a correlation coefficient (r)
was determined. The square of the correlation coefficient
was also calculated and is termed the coefficient of deter-
mination (re). A test for significance was carried out at
the .01 percent level.

A linear equation, Yc = a / bx, was also worked out;

Ye is the computed sale price; a , the point of origin of
the line represented by the equation; b, the change in
estimated land value associated with a given change in the
sale price x, in thousands of dollars.

The statistical analysis carried out for the correlation
coefficient, coefficient of determination and linear equation
was done by the statistical pool of the Department of
Agricultural Economics, and William H. Feneberry, at
Nichigan State University.

Results of this calculation are shown in Figure ll
which shows the "Relation of Estimated Land Values to Sale
Price" less building and timber values. The equation

reads: Y = 5207.50 / 1.058x; r 3 .891

51.

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Discussion

Trends in the agriculture of Osceola County can be
partially understood by consideration of the charts on
the major crops and the data on cattle and calves, cows
milking wo times a day, price of milk and butterfat per
hundred-weight in figures 1 through 8.

As the number of cattle increased or decreased, so
have the corn acreages. We can assume from this comparison
that the corn acreages have fluctuated to meet the demands
of cattle or vice versa, the cattle have been increased to
use the increased corn supply.

Oats data indicate a steady decline in acreage. There
appears to be no relationship to cows, cattle, milk price
or other crOps grown. The use of an average acreage of
oats over the decade from 1919 to 1958 may have over empha-
sized the present importance of oats on Osceola County.

This would tend to lower land values for most of the soils
in oats, as indicated in table 12, which show a negative net
income per acre.

Wheat shows no clear relationship to other crops grown
but the increase since 1955 may irdirfite it is replacing out;
in part. In affr t on depressirg t-reagrs l“f ray rate
3Pflter,ed intrc: ed arrezges a: were ferrers tIIr to vtrat
a a a ras; -rop. Allotments seem to have no effect on the
acreages. Acreage of wheat decreased from 1919 to 1955 even
though wheat allotments were in effect. No correlation

appears to exist between the wheat data and that on cows,

53.

514--

cattle and milk prices.

The data for hay correlates with the increase in
cows, cattle, milking and price data. This increase is
felt to meet the demand of more hay required by the cattle.

We can assume, in Osceola County, that oats and Wheat
play a minor role in the dairy enterprise since there appears
to be no effect on them by the other crops gaown. Corn and
hay acreage trends seem to fluctuate with the amounts of
cattle raised, or vice versa. The amounts of cows milked
twice daily fluctuate with the prices received, or vice versa,
as indicated in figure 8.

It must also be taken into consideration that the numbers
of farmers in the county has also decreased. This will tend
to depress some of the acreages of the crops grown. In-
creases in yields are consistent only with wheat. Other
crops may be affected more by weather. It can therefore be
assumed that the more inefficient farmers are getting out of
the farming business.

Upon comparing the data synthesized from custom rates
for expenses, with farm account records, it was found that
the synthesized costs on a per acre basis were less than
those reported in the farm account records. For example it
was found that the synthesized machinery expense was half
of the farm account figure, and other per acre expenses were
similar. It can.therefore be assumed that the farmers in
Osceola County have over-stocked themselves on machinery as
an insurance against not being able to obtain the necessary

machines when desired, as might be the case when depending

,

 

55.

on custom work. It can also be assumed that they do not have
large enough farms for efficient operation. It may be that
the farmers themselves do not realize how much their own
labor is worth. Thus, the total net income is, under
existing conditions, lower than it might be with more
efficient operation.

When the data are adjusted to take into account these
existing conditions, the capitalization rate is lowered from
22.5% for cropland to approximately 115. This 11% corresp
ponds to similar results found in Eaton and Arenac Counties.
Discussion with some of the land owners and town‘s people
revealed that a 10 to 12% capitalization rate was considered
to be average for cropland. In this study the costs based on
custom work rates and U18 22.5% rate was used for estimating
the land values from the expected net incomes for cropland.
The 22.5? capitalization rate was determined by a process
of comparison which is a percentage relationship that exists
between the annual net returns and going market values of
comparable properties. The capitalization rate in this
study is an average figure of the estimated net income divided
by the sale price in figure 9. Figure 10 ihovs the sample
units after capitalization of data in figure 9.

In the plot of values of sale price in thousands per
farm sampled as opposed to assessed value in thousands per
farm, figure 12, several relationships are apparent. The
higher the sale in thousands of dollars, the less in propor-
tion is the assessed value. Or conversely, the lower the

sale value of a property the higher the percentage that the

56

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61.

assessed value is of the sale price. From other data in
other states and counties in Michigan, this appears to be a
common situation.

When considering this relation of sale price to assessed
value, it is obvious that the more productive and highly de-
veloped land or larger farms are being under assessed and
that the poorer or smaller farms are being relatively over
assessed. This relationship to amounts of improvements on
the land is borne out by the fact that the dots at the higher
end of the curve are more commonly farming units with im-
provements and sold as such. Most of the dots at the lower
end of the curve are units of idle and forested lands,
without improvements.

The assessor in this situation has apparently also
tended to undervalue the more intensively cultivated or
more productive land and over valued the less productive
idle and forested land. The same situation holds true for
each of the individual townships. This also held true for
the Eaton and Arenac County appraisal studies and in other
states such as Nebraska and Iowa. USe of the method tried
in this study would avoid the bias and result in more equit-
able land evaluation.

When comparing the relation of estimated sale price in
thousands to equalized values on sixteen sample units,
figure 13, the following relationships seem to exist. Re-
gardless of land use the improved farms are valued by equal-
ization 15% higher than the sale price. Adjustments made

during the course of study are as follows. All of the

62.

equalized values used multiplied by 2.8 from the Michigan
State Tax Commission, in order to bring the values from

1958 to 1959 dollar values. This was done to bring into
line the equalized values of each sample unit for comparison
with sale values based on 1959 data. The sale prices were
also adjusted for the time of sale to a 1959 base. In-
accuracies in these adjustment factors may tend to show over
equalization of sample units when compared to sale prices or
values based on estimated net income, figure 11. It must

be remembered too that the estimated net income is an average
figure from 1952 to 1959 or centering around 1951-55. On
these farms too it appears that they have been over valued
even when comparing equalized values to estimated values
based on net income or sale prices. Relating the equalized
assessed values to value based on the expected net income
from the soil management groups and the sale price of
properties currently being sold would decrease this over
valuation bias.

During the evaluation of the improvements of the sample
units, it was found by the check sheets that the house and
out buildings values fell into %d and D classes by the Mich-
igan State Tax Commission Manual. This was also found by
Schairier in Arenac County. Personal contact with the local
peOple in Osceola County found a general opinion that the
improvements accounted on the average for approximately half
the value of the sale price, while land was felt to consist

of the other half of the sale price. This corresponds to the

63.

data in Current Developments in the Farm Real Estate Market,
for Michigan, h} to h5% of the value is for improvements.
This helps to explain the over valuation in equalization
for many improvements were rated in a class higher than was
done in this study. On the other hand it was also found
that many of the buildings were improved since the initial
sale and time of valuation. This proved to distort the
data for it was almost impossible to put an original value
on the buildings at the time of the sale. This distortion
would tend to over value the less productive land by giving
an impression of a highly productive unit.

Another point of interest was that a high proportion of
farm operators are working off the farm in small local
industries. This was also found by the Soil Conservation
Service in a survey of their cooperators in Osceola County
Soil Conservation District. Three out of five were not
farming full time. There appears to be a correlation of
size of farming unit to farmers working off the farm. The
smaller the unit the more likely the farmer to be working in
industry. This is also noticeable in the analysis of major
crops grown, acreages of each and the numbers of cattle or
calves and cows milked two times a day. From l9h9 to 1953
there seemed to be a general increase in all of the above
due possibly to the Korean conflict and from 1953 to the
present, there has been a general decrease in the above. It
is believed that the latter is due to the general trend of
farm personel to seek added income by working in the small

industries.

on.

From table 12 several important relationships are to be
observed. Management Units ha, 5a, 5b and 5c show a trend of
higher estimated land value and thus a higher net income for
forestry and pasture than cropland land use. Management units
2a, 2b, 3a and he Show a higher estimated land value when
used for cropland and pasture than for forestry and pasture
combinations. It can therefore be assumed that the most
intensive and economical land use for units 5a, 5b and 5c is
forestry and pasture combinations. For managmnent units 2a,
2b, 3a and he the most economical and intensive land use is
cropland and pasture. When the reverse of these land uses
occurs, the trend is for lower estimated net income and
lower land values.

Results of the statistical analysis conducted by the
statistical pool of the Agriculture Economics Department
at Nichigan State University, found a correlation coefficient
of .9hh between estimated land value and sale price. By
squaring this number, the coefficient of determination is
found. In this case it is .891. This can be interpreted as
the percent, 897, of the sale price of land and estimated
land values that can be attributed to the parameters used
in the method of estimating the land values.

As indicated by the linear equation y = .2075 {_l.058x,
figure 11, where the point of origin of the line represented
by the equation is 207.50 dollars. The amount of change in
estimated land value associated with a change in the sale
price of $100.00 is $105.80.

Results of the statistical analysis are similar to the

65.

results found by Tom Priest in a similar study in Baton

County, iichigan.
Conclusion

This study is based on the use of soil management groups
and related information for evaluation of farmland. This

system has the advantage of eliminating bias on the part

K.)

of the assessors. It takes into consideration the differences

in 30113, land use and incomes that can be derived from the

Any individual who uses this system should realize that
adjustments and checks are necessary. As changes occur in
land use and with advancement in technology adjustments
will need to be made in land values. Adjustments are also
necessary for current local variations in productivity such
as yields lost through drought, floods and poor soil conditions.
This can be accomplished by adjusting the net incomes by
soil groups and then an adjusted capitalized value can be
determined.

Soil management groups can be used for purposes other
than land evaluation. They can be used as a basis for
buying and selling land. Banks and other lending institutions
can use these soil management groups to determine the
feasibility of lending money. Finally soil management groups
can be used for improvements in farm management by adjusting
land use or farm sizes to the soil present to get the most
net income consistent with a permanent agric.lture for a

farmer, or farm manager as indicated in tables 11 and 12.

Additional Research Needs

During the course of this study, it became apparent
that more research is needed. In the field of soils and
crops, more accurate data are needed with respect to types
of crops grown on different soils in the various counties.
Yields of the crops grown on different soils with given
management are also needed. Other items that seem to be
lacking are the knowledge of crop sequences, machinery and
practices used, including erosion control measures, and
amounts of fertilizer being applied. This information is
not generally available or specific for any certain soil
and types of farming areas.

In the field of economics, the determination of costs
of each operation, on other than account farms, for the
typical farm operator is lacking. It would also be desirable
to have studies conducted on the effect that industry has
on land values and on the general farm situation in the
various farming areas of Nichigan. As stated in the dis-
cussion, 3/5 of the farm population in Osceola County
have part time work away from the farm. Thus the farm has
arrived at a dual purpose. The farm has remained a place
to live and other industries have become a place of
employment.

Relative price data on farms in relation to location,
tyoes of roads, modern conveniences, school debts and taxes
are lacking but are necessary for a more complete picture
of land values. These may also influence the type of farm

operation.

66.

In the field of Agricultural Engineering there is
limited information on the effect of the soil properties
and soil management on the cost of using machinery. There
are indications that soil texture and drainage have an
effect on the power requirements of machinery. This will
directly affect the costs of using the machines in dollars
and cents. It is known that clayey soils and sod crops
will increase the expenses through increased power necessary
to pull when compared to sandy soils and cultivated crops.
The amount of influence on expenses by soil management groups
cannot be evaluated at this date.

Additional research is needed on more realistic capital-
ization rates. This appears to vary from area to area.

There is also a need of information on woodland values.
This is with respect to species, stand densities and costs
of operation for pulp, maple syrup and other forest products.
More information is needed on costs of the harvesting and
transportation and prices received for wood products.

It has been found during the course of this study,
that in almost every phase adequate information is lacking
for adequate evaluation of lands for agricultural purposes.
It is therefore felt that additional work is needed on
land evaluation for agricultural purposes throughout Michigan.
The method tried here seems to be very satisfactory in the

types of farming areas where it has been tried.

10.

ll.

12.

13.

15.

Bibliography-

Barlowe, Raleigh. Land Resource Economics Prentice Hall
Inc., Englewood Cliffs, N.J. 1953

 

Black, Clawson, Sayre and Wilcox, l9h7. Farm Management
MacNillin Co., New York, N.Y.

 

Davis, W. D., 19L6. Rural Appraisal Procedures, The
Appraisal Journal, Vol. XIV pg. 3&8—360.

 

Heneberry, Wm., Schrirer, 0., & Whiteside, E. P., 1956
Uses of Soil Maps for Improving_Tax Assessments Procedure
for Farm Property in Arenac County, Michigan. Unpublished
Manuscript, Michigan State University.

 

 

Fertilizer Recommendations for Michigan Crops, Extension
Bulletin 159 (revised), 1957. Cooperative Extension
Service, Michigan State University.

Gaddis, P. L., l9h6. Some Fundamentals of Farm Appraisal
The Appraisal Journal, Vol. XIV, pg. 136:1h3.

 

Henry, E. G., l9k6. Appraising Farm Lands. The Appraisal
JOLII‘Ilal, V010 XIV, pg. 33'370

 

Hill, Elton B. & Nawby, Russel G., 195u. Types of Farming
in Michigan. Nichigan Agricultural Experiment Station
Special Bulletin 206.

 

 

Kellogg, Charles E. & Ableiter, Kenneth J., 1935. A Method
of Rural Land Classification, U. S. Dept. of Ag. Tech.
Bulletin No. h59.

 

McKicheal, Stanley, 1951. McNicheals Appraising Manual
Prentice Hall Inc., Englewood Cliffs, New Jersey

 

Mishigan Agricultural Statistics, Michigan Dept. of Agri-
culture, Michigan Crop Reporting Service, Cooperating
with the U.S.D.A., 19L9 to 1958.

Michigan State Tax Commission Assessors Manual, 1958.
Published and distributed by Authority of Act 215, P. A.
19Sh, Second Printing.

Michigan Checklist for Areas 3 and h, 1959. National
Plant Food Institute, Midwest Regional Office, Chicago,
Ill.

Murray, William G., 1958. Appraisal of Farm Real Estate
U. S. Dept. of Agr. Yearbook of Agr. 1958, pg. 190-197.

 

Nielson, James & Bittner, R. F., 1958. Farm Practice
Adoption, Michigan Agr. EXp. Station, Tech. Bulletin 263.

 

68.

16.

17c

18.

19.

20.

21.

22.

23.

2k.

69.

Nunns, Frederick K., 1958. The Classification of Rural
Lands, U. S. Dept. of Agr. Yearbook 1958, pg. 362-370.

Odell, R. T., How Productive Are the Soils of Central
Illinois. Illinois Agricultural Experimental Station.
Bulletin 522. ‘ ’

 

Ottoson, Howard, Aandahl, Andrew a Kristjanson, L.
Burbank, 195A. Valuation of Farm Land for Tax Asspssment.
Nebraska Agricultural EXperiment Station Bulletin E27.

Perry, Robert D., 1960. New Tool Proves Useful. The
Appraisal Journal, Vol. XXVIII, pg. u654fi68.

 

Priest, T. W., 1960, Use of Soil Management Groups and
Related Information in Evaluation of Pamnlands. Thesis
for the Degree of M.S., Soil Science Dept. Michigan
State University.

 

 

Schairer, Dale H., 1959. Rating and Valuing Building on
Their Physical Characteristics, Thesis for the Degree of
M.S., Ag. Eng. Dept., Michigan State University.

 

Scholtes, W. H. & Riecken, F. E. Use of Soil Survey In-
formation for Tax Assessments in Taylor County, Iowa.

 

 

Smith, Glenn 0., 1950. Appraisal of Farms, he Appraisal
Journal Vol. XVII, g. 503-311.

 

Storie, E. & Weir, Walter W. The Use of Soil Maps For
Assessment Pprposes, Soil Science Society of America,
‘4’010 7, pg. Alb-Iklgo

 

 

Thompson, W. N. & Johnston, P. 3., 195h. Row Valuable
are The Soils of Central Illinois. Illinois Ag. Exp.
Station Bulletin 550.

 

 

Wagner, John J., l9h7. Valuation of Farm Laids, The
Appraisal Journal, Vol. XV, pg. 5&53357.

 

Websters New Collegiate Dictionary, l9h9, G. & C-
Merriam 00., Publishers, Springfield, Mass., pg. 1209.

Appendix A

Picture Supplement

The following three pages contain photographs of var-

ious scenes of farm buildings, and associations of soils

and land use with the typical vegetation present. A narrative

follows describing the photographs:

Scenes A & B: A homestead, house and out buildings, located
on Nester and Isabella soils. The topography
is from.moderate to steeply sloping with general
agriculture as the main land use. This unit
typifies the average level of management. It
has modern facilities and is worth approximately
$h,SOO—S,000. This would be a class D home
by the standards of the fichigan State Tax
Commission.

Scenes C h D: A homestead on Isabella soils with moderate to
steep slopes. This unit would be considered
above averave. The main entrrfrior beye ig

geheral faktirffiahd asir“, With a Valhb of
apprbkimateiy $8,000-8,9OO for the buildings.

Scenes E a F: This represents one homestead with house and
barn and the associated fields. TheSe are
1eVel to gently sipping sandy soils. Unit would
be censidered average for the couh*y. If the
owner were to depend pn the land for ah income

this Unit would not appear as it does. The

70-

71.

owner in this case works at a factory ten miles
away. Resources from two incomes have been
placed back into the homestead for improvement;

the i come from the land and from the factors.

 

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