xt76125q966n https://exploreuk.uky.edu/dips/xt76125q966n/data/mets.xml   Agricultural Experiment Station, Department of Agricultural Economics, University of Kentucky 1978 journals kaes_research_rprts_30 English University of Kentucky Contact the Special Collections Research Center for information regarding rights and use of this collection. Kentucky Agricultural Experiment Station Research Report 30 : August 1978 text Research Report 30 : August 1978 1978 2014 true xt76125q966n section xt76125q966n COSTS AND RETURNS ASSOCIATED WITH ON-FARM :
STORAGE OF CORN, WHEAT AND SOYBEANS
By
jerry Skees, joe T. Davis, Russell H. Brannon
Otto  Loewer, and D. Milton Shuffett I
c Research Report 30
August 1978
University of Kentucky :: College of Agriculture
Agricultural Experiment Station
Department of Agricultural Economics I
Lexington

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’

 CONTENTS
Page
List of Tables ....................... 3
Introduction ........................ 4
Method of Analysis ..................... 5
Synthetic Cost Analysis .................. 6
Grain Price Patterns .................... 10 ~
Estimating Costs and Returns to Grain Systems ....... ll
Returns ...................... ll
Costs ....................... 18
Calculation of Net Returns ............. 19
Representative Crain Systems ................ 19
The Small Farm ................... 19
The Mid-Size Farm ................. 20
The Large Farm ................... 22
Recommended Grain Systems ................. 23
The Small Farm ................... 23
The Mid—Size Farm ................. 24
The Large Farm ................... 26
Returns to Grain Systems .................. 26
Corn ........................ 27
Wheat .............,......... 27
Soybeans ...................... 29
Returns to Alternative Systems ........... 30
Summary and Conclusions .................. 30
References ......................... 34
Appendix ......................... 36

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 LIST OF TABLES
Table Page
1. Enterprise Characteristics of Representative Farms . . . 7
2. Wheat Price Data .................... 12
3. Yellow Corn Price Data ................. 13
4. Yellow Soybean Price Data ............... 14
5. Fixed, Variable, and Total Annual Cost Associated With
Various Systems for Corn, Wheat, and Soybeans ..... 21
6. Comparison of Fixed and Variable Costs for Representative
and Recommended Systems ................ 25
7. Net Returns to Systems for Corn, Wheat, and Soybeans
(Representative and Recommended Systems) ........ 28
Appendix Tables
1. Allocation of Total Annual Fixed Costs Among Grains . . 36
2. Variable Costs Associated with Various Systems for Corn,
Wheat, and Soybeans .................. 37
3. Costs and Returns Associated with Corn When Utilizing
Alternative Systems .................. 38
4. Costs and Returns Associated with Wheat When Utilizing
Alternative Systems .................. 40
5. Costs and Returns Associated with Soybeans When Utilizing
Alternative Systems .................. 41

 COSTS AND RETURNS ASSOCIATED WITH ON—FARM
STORAGE OF CORN, WHEAT, AND SOYBEANS
By
Jerry Skees, Joe T. Davis, Russell H. Brannon
Otto J. Loewer, and D. Milton Shuffett*
The dramatic increase in the amou t of on—farm grain drying and
storage during the past several years can be attributed to several factors:
(1) the price variability associated with grain production, (2) the
increased market flexibility associated with storage facilities, (3) farmer A
dissatisfaction with crowded market outlets at harvest, (4) the double-
cropping of wheat and soybeans, and (5) the management advantages that
accompany a grain storage system.
Changing demand and supply conditions for grain have historically
led to severe price fluctuations. In 1972, crop failures in various parts
of the world increased the exports of American grain and caused domestic
grain prices to soar. More recently, there has been a period of excess
supply and reduced prices. This instability in grain prices has prompted
policy makers and farmers to consider on-farm storage as one means of
reducing price fluctuations. Individual farmers also view storage
facilities as a means of increasing their market flexibility in responding
to seasonal price changes and as being complementary to livestock enterprises.
Interest in on—farm storage has also been enhanced by changing
production practices and crowded market conditions. Double—cropping
*The authors are respectively, former Research Associate, Assistant
Professor of Agricultural Economics; Professor of Agricultural Economics,
Associate Extension Professor of Agricultural Engineering, and Professor
of Agricultural Economics. 4

 Q -  Q T s
E  
2 A *§ involving wheat followed by no—till soybeans is facilitated by on—farm
% ii; grain storage which permits earlier harvest of high-moisture wheat, thus
i i§i extending the soybean growing season and increasing soybean yields.
E iii A Western Kentucky has traditionally been a grain surplus region, and grain
é ip production has expanded more rapidly than have local market outlets. The
é nil; result has been long delays for farmers at local facilities during the
' Q i harvest season. These delays are costly since the time required for
E TSW harvesting is extended, thus increasing harvest losses and reducing the
? ;w, efficiency of machinery and labor.
i jh Producers contemplating the establishment of on-farm storage
i ya facilities, or expanding present facilities, need information regarding
Q i. the probable costs and returns that will be associated with such long—term
2 ii; investments. Recommendations concerning the type of system suited to
{ I p various sizes of farms and various farming practices are also needed. It
, E
‘ C is the purpose of this report to provide these cost and return estimates
i f for various sizes of farms under alternative management conditions.
i Method of Analysis
% A random sample of 202 farms was drawn from the population of all
l j farms in Christian County, Kentucky. This county was selected as being
, E A fairly representative of grain farming in Western Kentucky and contiguous
i .
i . areas. Early results indicated that farms with less than lOO tillable
l L acres had little or no on—farm storage; thus, those farms were deleted
g from the survey. This resulted in 70 completed and usable questionnaires.
It was determined that this did not constitute an adequate sample size
since, for purposes of the study, it was considered desirable to develop
1

 6
three representative farms. Therefore, an additional 19 farms were
randomly selected from a list of 100 larger grain producers provided by
the Christian County Extension agent for agriculture, bringing the total
usable sample to 89 farms. '
Three representative farms were subsequently developed on the basis
of tillable acres, thus permitting analysis of a range in farm size and
operational procedures. The three representative farms were: (1) The ·
small farm, 100-175 tillable acres; (2) the mid—size farm, 176-450 tillable
acres; and (3) the large farm, more than 450 tillable acres. These ranges
were defined on the basis of the sample distribution and through inspection
of the raw data.
After stratifying the farms according to tillable acres, the means,
medians, modes, and frequencies were computed for the revelant characteristics
within each stratum. These statistics were used to assign relative values
to each characteristic defined in the three representative farms. A summary
of the representative farm data is presented in Table l.
Synthetic Cost Analysis
Using the representative farm data obtained from the survey, two
grain storage systems were developed for each of the three representative
farms. The first system represents current practices and will be referred
to throughout this report as the "representative system". The second
system was developed on the basis of engineering recommendations, with the
objective of designing a least-cost system that would meet harvest
requirements and accommodate storage of all grain produced. This latter
system is referred to as the "recommended system".

 I ~; . 7
; _i Table 1. Enterprise Characteristics of Representative Farms
2 1 if Item Farm 1 Farm 2 Farm 3 _
  1
Q S Total Acres 207 357 1,089
i 1, Tillable Acres 135 290 904
E p General Rented Grain Acres 25 68 304
Q K Variables Acres Double-Cropped 0 76 250
Y ` Bushels Storage Capacity 3,334 10,723 32,844
g if Beef Cattle 53 55 160
I g 0 Swine 160 380 700
2 Q Acres 43 110 375
? ?; Effective Yields (Bu/Ac) 88 95 95
Y °’ Total Bushels 3,784 10,450 35,625
0 Yellow Bushels Sold From Field 454 3,135 14,250
A Corn Bushels Stored On—Farm 3,330 7,315 21,375
j if Bushels Fed From Storage 946 2,195 4,275
? 9 Months Sold Jan-Feb Jan-May Jan—May
€ 0 » Stored Bushels Sold—Pennyrile 2,384 5,120 17,100
Y X p Stored Bushels Sold—Ohio Valley O O 0
1
z _ _ Acres 21 76 250
_ F Effective Yield (Bu/Ac) 34 37 40
` - Total Bushels 714 2,812 10,000
» , Wheat Bushels Sold From Field 0 562 0
Bushels Stored On-Farm 714 2,250 10,000
Months Sold Sep Sep Sep p
` Stored Bushels Sold-Pennyrile 714 2,250 7,500
Stored Bushels Sold—Ohio Valley 0 0 2,500
= ' Acres 63 127 475 ·
f Effective Yields (Bu/Ac) 33 32 32 ~
Q - Total Bushels 2,079 4,064 15,200 A
; E Soybeans Bushels Sold From Field 2,079 1,219 4,560
’ ` Bushels Stored On-Farm 0 2,845 10,640
· Months Sold 0 Jan-May Jan—July
L Stored Bushels Sold—Pennyrile 0 813 3,040
Stored Bushels Sold-Ohio Valley 0 2,032 7,600
L  

 8
s Fixed and variable costs for each system were computed to provide
T an estimate of the total annual cost of each system. Annual fixed
, costs for both types of systems were developed form the University of I
1 Kentucky's Department of Agricultural Engineering computer simulation
‘ program, BNDZN (Bin design).1
” Representative systems were developed by providing BNDZN with the
design requirements derived from the respective representative farm data.
V Recommended systems were developed by providing the appropriate design
requirements obtained from the computer simulation program CHASE (Corn
Handling and Storage Evaluator). CHASE is a computer simulation model
designed to provide management information to farmers considering
construction of grain systems. The farmer provides the program with the
specific parameters of his operation, including: acres, expected yield,
1 width of rows, harvest days, hours in a harvest day, hauling distance to
A the facility, desired beginning and selling moisture contents, labor wage
` rate, drying fuel cost, and electricity cost. The program has built-in
equipment costs, equipment types, and design data.
{ CHASE utilizes the data supplied by the producer in the examination
of 60 alternative systems, changing first the types of hauling vehicle,
i then the type of handling system used (either a portable or a transport
7 auger) and, finally, the drying and storage options. Three drying
S alternatives are examined, including layer, batch—in—bin, and portable or
A IBNDZN has built in updated prices of various items needed in construction
j of grain systems. Layer, batch—in—bin or portable dryers may be chosen.
` Each item has an assumed life and annual repair requirement. Straightline
depreciation is assumed, with a zero salvage value. Other assumptions
p include a charge of 1% for taxes and insurance on each item, and an 8 l/2%
E interest charge on borrowed money which is repaid evenly over the life of
A each item, thus resulting in an effective annual interest charge of 4.25%

     i 9
% 6 Q continuous flow. A no-storage option for the batch—in—bin and portable
i A i dryer is also investigated. After comparing the 60 feasible alternative
i M1 systems, CHASE ranks them according to purchase and annual costs, including
Q ‘l|d labor and basic equipment requirements for each feasible system.
é q A system developed by CHASE was chosen on the basis of cost,
E p flexibility, and individual farm requirements. Although both BNDZN and
y E a e CHASE are designed for handling corn, it was determined that no extra
i Yi requirements would be involved in handling wheat and soybeans with the
E é same system.
3 T After developing fixed costs for each system with the use of BNDZN,
i variable costs were then estimated. Labor requirements were first obtained
2 . for each system from CHASE, and then modified by adjusting for a labor
3 6 i savings coefficient related to having an on—farm grain system. This
i coefficient was developed u der the assu ption that farmers without storage
, é i would incur an extra hour's delay for each trip to the elevator during the
" p busy harvest season.
_ Thompson's fan models (Thompson, Peart, and Foster; 1968) were
’ used to estimate fuel and electrical requirements. When furnished data on
é p atmospheric conditions, grain moisture contents, dryer specifications, bin
j diameter, and grain depth, the fan models calculated running time and a Btu
j 2 requirement for removing a pound of water from a bushel of corn.
E Electricity costs were calculated by multiplying running time by the horse-
’ power of the dryer to obtain horsepower hours, which were then converted
Q to kilowatt-hours with the use of standard conversion factors. Use of
other electrical devices in each system was also estimated on the basis of i
the hours required to handle specified amou ts of grain and the horsepower `

 l0
of each item used. Finally, an allowance for miscellaneous kilowatt-hours
was added to each total electrical use since the margin of error associated
with estimating electrical use was relatively large. >
Fuel costs were calculated using the Btu/lb of water requirement
obtained from the Thompson models for each system and a procedure for
calculating fuel requirements developed by Loewer, White, and Overhults
(1975). The first step in these calculations involved determining the
total pounds of water removed from each bushel dried. Pounds of water
i removed times the Btu's required to remove a pound of water equaled the
Btu requirement for each bushel of grain. Drying with LP gas was assu ed
to be 80% efficient, and a gallon of LP gas supplies approximately 73,000
Btu's at the 80% efficiency level. Therefore, the Btu's required to dry
one bushel, divided by the 73,000 Btu's supplied by a gallon of fuel,
‘ yielded the portion of a gallon of LP gas required to dry one bushel.
A final variable cost item calculated for each system was the
» chemical requirements for insect control. Calculations were based upon
the use of a mixture of 57 percent malathion, and Gregory's (1973)
recommendation that each bin be sprayed with a half—pint of malathion per
_ 1,000 square feet prior to placing grain into the bin, plus an additional
pint for each 1,000 bushels of grain as it is stored.
p Grain Price Patterns
To assess the profitability of alternative grain storage and drying
0 systems, it is first necessary to determine patterns of cash grain prices
A in major market areas——the Pennyrile and the Ohio Valley. Cash grain
. prices for No. 2 yellow corn, No. l yellow soybeans, and soft winter wheat

   ‘   V M
E 1, E were gathered for these markets from the weekly "Grain Market News"
¥ Tw
é .,; C (1969-76). Monthly prices were computed from the weekly prices, and these
é i ii; prices were used to construct a seasonal index. This index was calculated i
E i »§‘ on a crop—year basis by dividing the average price for each month by the p
é dip j overall average of the monthly prices for the crop—year. The index was
i iép then used to generate prices by taking the mean of the harvest month prices
I E ivjii for the years 1972-76 for each grain and using that price as a base to
i pii· compute expected monthly prices for a harvest year. Harvest months were
i ili considered to be October, June, and November for corn, wheat and soybeans,
é ii respectively. Q
f 3 Tables 2, 3 and 4 present price data for corn, wheat and soybeans, _ _
E i respectively. Each table compares the indexes for the Pennyrile and Ohio i
i { ,’ Valley and the expected prices for these two regions. The tables provide E
Q a quick reference for gross returns to storage for a Christian County
1 i ` producer selling grain in either region. These tables also include
3 estimates of the gross returns for transporting grain grown in the Pennyrile
1 i region to markets in the Ohio Valley region.
A Estimating Costs and Returns to Grain Systems
i { Returns. Many factors affect returns to a farm grain drying and V
A C storage system. In this study, returns were calculated for (l) decreases l
L g in harvest losses associated with the drying capability, (2) returns
E associated with drying yellow corn, (3) returns associated with seasonal
prices, and (4) increases in double—cropped soybean yields associated with U (
L earlier harvest of high moisture wheat. These returns were compared with Z
the total annual fixed and variable costs associated with the physical E

 12
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Q AV p l5 A
i iiigvrl structure of each system, the costs of overdrying yellow corn, transpor— ;
E pi; . tation costs for that grain shipped to the Ohio Valley, and an interest W
E 7ig. charge on foregone investments. 3
é 2i;· A modification of the simulation model, CACHE, was used to estimate »
2 .- AA returns to drying and storage of corn. Representative harvest strategies b
i i p T were derived from farm survey data, and recommended strategies were Q
i p l‘i developed on the basis of engineering data. CACHE was then used to compare Q
/ E fl i corn harvest losses with and without an on—farm grain drying and storage L
  _ O
i `ii system. Estimates of harvest losses were computed on the basis of an m
E S assumed harvester speed, calendar days of harvest, percent moisture decline
· c
Z il per day, and beginning moisture content, as derived from previous studies.
E T Byg (1976) indicated that harvest losses for wheat and soybeans increase V
é p by approximately 0.2 bushel per acre for every day harvest is delayed past U
é   recommended harvest date. This figure was used in the calculations. Gains
a
q i _ C associated with reduced harvest losses were valued at harvest price, since tl
A ; the additional bushels were included in total bushels stored. t
1 . . (
{ ` Returns to drying were calculated only for corn, since it was V
~ . s;
’ determined that drying was more critical for corn than for wheat and tf
i soybeans. There are several reasons for this conclusion. First, drying
; ~ (
; 1 returns are related to dockage for selling wet grain. The equilibrium i ig
Y moisture content of corn is approximately 17.5% during the harvest season, Q
. p si
A i which is 2% above the base moisture selling level. By comparison, wheat b
- e
g and soybeans can actually reach equilibrium moisture contents at levels
i below their respective base moisture selling levels. Furthermore, corn 3*
I dries in the field at a slower rate than do wheat and soybeans. The assumed in _;
field drying rate for corn in this analysis is 0.5% per day, compared with i

 ; 16
i a rate of approximately 1.0% per day for wheat and soybeans (Byg, 1976).
i In addition, corn can be harvested at higher moisture levels than either
R wheat or soybeans, further increasing both the returns and the costs L
associated with drying corn.
Actual calculation of returns associated with drying corn was made
2 by comparing strategies with and without an on—farm grain drying and
storage system. Wet bushels were calculated for a strategy without such
` a system, and discoumts for selling wet grain were estimated on the basis
of shrinkage charts and drying charges used by Christian County's largest
market, the Hopkinsville Elevator (1975). The discounted price was
compared with the price per bushel which would be received if the grain
» were dried.
Returns to storage2 for the various grains were calculated using
the expected prices discussed in the preceding section. Monthly returns
after the respective harvest months were calculated both for grain sold in
the local Pennyrile market and that sold in the Ohio Valley market. Returns
to transporting Pennyrile grain to the Ohio Valley were also calculated;
since returns for corn were less than transportation costs, it was assumed
. that no corn would be shipped for sale on that market. Returns to trans-
h porting wheat and soybeans to the Ohio Valley, however, were sufficiently
high to cover transportation costs. Therefore, data collected in the
survey were used to estimate the amounts of wheat and soybeans which would
1 be sold in each region. lt was assumed that these same percentages would
h 2The term “returns to storage," as used in this paper, refers to the
V changing value of the stored product as a result of monthly price
if fluctuations during the months following harvest. _
w

 i “ wi 17
g Q ig Q be shipped to the Ohio Valley if farmers were using the recommended grain `
i y;§ drying and storage systems. This assumption seems reasonable, given the
% ii; logistical problems associated with transporting larger amounts of grain.
% ,;é~i Returns to storage for the representative systems were calculated by
é i p comparing expected prices at traditional selling times and at recommended
V Q i_ selling times. The returns to recommended systems were calculated on the
g *;·:i basis of a single recommended selling time, after considering the system‘s V
i ii- constraints and optimum selling prices.
3 i Q1 It was assumed that corn used for on—farm livestock feed was fed p
i .§i° at a fairly constant rate over a 10-month period. On the assumption that
§ returns to storage increase at a fairly constant rate, returns at the end
E _. of the 10-month period were divided by 2 to compute the returns to corn
é rpt fed over the entire period. Experienced farmers and extension specialists
R A in the area indicated that if feed grain must be purchased from a local
g g ‘ mill, there is a 10-cent per bushel premium over the price paid farmers by
3 the local elevator; thus, a return of 10 cents per bushel on corn stored
; ` for feed was also included.
i Returns in the form of increased yield of double—cropped soybeans _
§ _ associated with earlier planting were also calculated. Earlier soybean p
A E planting is made possible by early harvest of high moisture wheat and
_ é drying it in on—farm facilities. Ten years of data collected by Egli (1977)
1 2
i Q indicate that soybean yields are reduced by approximately 2% for each day
' that they are planted after June 13. Thus, early planting has a significant _
} impact on total yield.

 18
Costs. Overdrying costs are incurred because of shrinkage associated with
drying corn for storage to moisture levels below those required by the
market. This is necessary, however, if corn is to be stored safely into ,
the spring in Kentucky. In this study, it was assumed that most corn is
dried to 14%, while the base requirement for selling is 15.5%. Losses to
overdrying were valued at the selling price out of storage. Since no loss
in nutritional value is associated with overdrying, fed corn was not charged
an overdrying cost.
Another major cost associated with storing grain is the income
foregone on investments that could have been made had grain been sold at
harvest. An annual return of 6% on short-term investments was assumed,
and a 0.5% charge was added to cover property taxes and insurance on the
stored grain. An effective interest charge was then computed for the period
for which the grain was stored. Since a farmer makes his decision to store
grain at time of harvest, it was assumed that the price prevailing at
harvest times the bushels harvested would represent the income immediately
foregone by the decision to store. Therefore, interest charges were
Q calculated on this amount. Since fed corn is assumed to be fed at a constant
V rate over a lO—month period, one—half of the lO—month effective interest
V rate was charged to fed corn.
A final cost assigned to each system was the cost associated with
L shipping stored grain from the Pennyrile Region to the Ohio Valley.
- Discussions with agricultural extension specialists resulted in a decision
3 to charge 13 cents per bushel for shipping grain to the Ohio Valley.
w

     _, 19
é I gig, Calculation of net returns. Gross returns associated with each grain were
Q liéh i compared with total costs to obtain net returns for each grain for represen- h
§ Eh A tative farm systems selling at traditional times and at recommended times. v
i lll} h Finally, returns associated with each grain were totaled to allow comparison .
E 1‘
A é Qp; of the net returns of each grain system.
5 §‘ `S h
g li} Representative Grain Systems
' E gi y The small farm. ln designing a grain system for representative
% lfiy farm l (the smaller farm), a 3,334-bushel storage bin with a perforated
E Ein- floor and lO—horsepower drying fan were used.3 This system was designed
E T? for use of forced natural air only, with no heating u it built into the
E .. fan. Although variable costs of drying are less for this system, and it
E 1. represents the system com only used on smaller farms in Christian Cou ty,
g h S there is some risk associated with drying grain with natural air alone. lf
Q V _ high—m0isture corn is placed in the structure on top of other corn, a A
{ ¥ p pocket of wet corn can result which may cause loss of all corn in the bin t
l r owing to spoilage. Therefore, such a system requires a high level of
l E management to insure proper conditioning of the grain. i
` ' A related characteristic of this system affects the rate at which
E T grain can be harvested. In this particular case, the system determines
h A the harvest rate. Since the system involves in—bin, layer drying of grain,
l E each layer should be dry before another layer is placed on top. This may A
1 actually require extending the harvest period over a longer time than
would be required in the absence of on—farm storage. To obtain all of the
I p 3For information on the annual fixed costs associated with the alternative
systems, see Appendix Table l. Detailed cost data for individual components
of the various systems (bins, fans, augers, etc.) are available from the
_ authors on request. They are not included in this report because changing
cost