1986-08 Spring 1986

SOUTHERN METHODIST UNIX Back-Grounding Operation

Ty K. Roberts

SENiOR DES RN PKQjECT

r!)P P

DEPARTMENT OF OPERATIONS RESEARCH AND ENGINEERING MANAGEMENT

SCHOOL OF ENGINEERING AND APPLIED SCIENCE

DALLAS, TEXAS 75275

SENIOR DESIGN PROJECT

MACKGROUNDING ©1PT1I©

Prepared for Richard S. Barr

May 8,1986

Prepared by Ty K. Roberts

ABSTRACT

After conducting on-site interviews and gathering data from the Lincoln County agent, I found an application for a linear programming model in my uncles cattle operation. I formulated several LP models and evaluated their outputs in order to make recommendations for improving his current feedmix rations.

MANAGEMENT SUMMARY

On my visit to the ranch, I saw that there was some room for improvement,

in the hacgrounding operation.

Although the feed mix currently in use was designed for the cattle's nutrional

needs and growth, its creators neglected to consider the costs involved with

providing that mixure.

After meeting with the general manager of the ranch and the Local county

I agent, I took all the data 1 had collected and formulated three linear programming

Imodels. The models were designed to minimize the cost of the feedmix while

providing for the cattle's needs for nutrition and growth.

I analyzed the outputs from these models and arrived at a recommendation.

I recommend that the ranch make use of feedmix U I found in Table 1 at the end of

this report. This feed mix meets the objectives of the ranch and is 2500 less than

the feedmix currently in use.

11

TABLE OF CONTENTS

ManagementSummary..........................................................................................................ii

Introduction.................. ..................................................................................................... ......... I

BackgroundInformation ................................... ..................................... ................................ 2

Backgrounding............................................................................................................................2

ManagementObjectives .................................................................................................. .......3

Current, Operation .................................................. .................................................... ...... ......... 4

GatheringData............................................................................................................................ 4

Analysisof Situation................................................................................................................ 6

Technical Description of the Models.................................................................................. 7

Constaints ............................................................................................................ .............7

Model l .... ....................................... ..... ..... .. .................... . ... . ...... .............. .... .. ...... ......... .... 8

Model2............................................................................................................................. 8

Model3 ................................... . ...... . ....... ... ........... .... .................... . ........................ . ......... .. 9

UNDO ............................................................................................................................... Jo

ComparisonOf Models ............................................................................................................ 10

Assumptionsand Limitations ............................................................................................. 11

Conclusion/Recommendation .............................................................................................. 1 2

111

I I Subject

IThis report is my Senior Design project. The subject of my project is the

backgrounding operation run by my uncle on a ranch owned by my grandfather in I Kansas.

Pur pose

M y goal for this project was to identify a "real world" situation where an

operatons research technique could be applied. My hope was that by applying an

OR technique, I could somehow improve the operation of that situation. This report

is the result of my efforts and the realization of my goat.

TLack

My major field of study is engineering management with an emphasis in

operations research. I have developed many OR skills from the classes I've taken.

This project required the formulation and evaluation of LP modeling, atechnique

with which I am very familiar.

Scope

I limited my study to the backgrounding operation on my uncle's ranch. My

objective was for a 600 pound steer to gain 2 pounds a day for 60 days at the

I cheapest cost.

BACKGROUND INFORMATION

My uncle runs a cash crop and beef cattle operation. Most of his crops are

sold under a government subsidy program. But, he does maintain a surplus of

milo, aiphalfa, sileage, and wheat hay to he used as feed for his cattle.

He raises cattle to be sold for slaughter. He currently has a total of 415 head

of cattle of which 160 are newborn calves that he will sell to the slaughter houses.

Up until this year, my uncle would sell these calves to a broker as soon as

they were wened off their mothers. At that time, the calves generally weighed

550 to 600 pounds. But this method hasn't proved very profitable. So my uncle

has begun shipping his cattle to feedlots and paying the lots to fatten up the cattle

in the hope they will gain enough weight to be sold at a profit.

Feedlots are costly, and fattening up cattle as an investment is risky.

Therefore, my uncle has decided to do some of the fattening up on his own ranch.

Since he has a surplus of crops for feed, and available space, he believes he can put.

some weight on the cattle cheaper than the feeddlot can.

There is a name given to this type of feedlot operation--backgrounding. I

found it to he an interesting process and decided to focus in on it for my Senior

Design project.

BACKGROUNDING

Six to nine months after birth, the calves are weed off their mothers. At

that time, the calves generally weigh between 550 to 600 pounds, but are still

Ideveloping physically. When these steers go to the slaughter houses, they will

- weigh between 1100 to 1300 pounds and be about. a year old,

In order for the steers to gain that much weight in such a short time, they

must develop a strong frame to support. it all. The development of that frame is

known as backgrounding.

The primary objective of backgrounding is to put 100 to 120 pounds of bone

and muscle on the steer and to instill good eating habits. Hopefully, the steer will

weigh around 700 pounds when it is shipped to the feedlots in eastern Kansas.

MANAGEMENT OBJECTIVES

My uncle made it quite clear to me that his main objective was to put as

much weight on the steers as possible at the cheapest cost. Of course, he pays

careful attention to their nutrional requirements because he knows a healthy steer

will ultimately gain more weight (bringing in more revenue) than a less healthy

steer.

Another objective he had was to complete the backgrounding process in a

60-day period so he can quickly get the steers out to the feedlots where they can

• start putting on the "big" weight.

ILastly, I learned that my uncle would like to use his milo and alphall'a

sparingly because he can sell them for cash if he has any left over after

I backgrounding the steer-s.

4

CURRENT OPERATION

Not only does my uncle have to feed 160 calves for backgrounding, but also

he has to feed the other 255 head with the same surplus of crops. But those 255

head are full-grown cattle and are fed only enough to maintain life until the next

calving season.

Knowing what crops he has on-hand and which he wants set aside for the

hackgrounding operation, my uncle employs the services of the county agent to

determine a feed mix for his steers. The county agent as access to all of the studies

done on cattle by the state university. He knows, or can find out, everything the

ranchers need to know about their cattle.

The county agent finds out which crops my uncle has on-hand, what breed of

cattle are in question (a cross between seminal and hereford in my uncle's case),

and how much weight gain is desired. With this information, the county agent

looks through several books of charts and statistics to find the nutritional needs of

the cattle and the nutritional wealth of the crops. He then offers a few feedmix

suggestions to my uncle.

Although the county agent doesnt give much thought to the costs involved

with each crop, he is aware that any surplus of milo or aiphalfa can be sold for

cash.

GATHERING DATA

I went to the ranch one weekend to learn more about my uncle's operation.

The night I arrived my uncle and I sat down to discuss my objectives. I explained

5

the purpose and goal of my project. and asked him to describe the different. types

of ranch operations he was responsible for. During that. first meeting, I decided I

would fOCUS my attention on his cattle operation..

The next morning 'I went with my uncle on his daily rounds. Along the way,

with note pad and pen in hand, I asked him a multitude of questions. I wanted to

learn as much as I could about all of the tangible and intangible factors involved

with the cattle business. By noon that day, I had a good understanding of his cattle

operation and had decided to focus in on the backgrounding process.

Although my uncle did a good job of explaining the backgrounding process to

me, he was unable to give me any details about. how the feed mix was derived.

Therefore, I set, up an appointment with the county agent to determine how he

arrived at. a feed mix solution.

I had already gotten the costs and quantities on--hand from my uncle. So

from the county agent I hoped to learn which nutrional requirements he tried to

meet when making a feedmix. .1 also needed to know the upper and lower limits

for those requirements.

The county agent told me that the most important factors to consider were

moisture content, dry matter, rufage, and protein. Moisture content refers to the

percentage of a crop that is moisture. If 25% of the milo is moisture, then a steer

eating four pounds of milo will only be able to digest three pounds of it, because

the other pound is moisture and will, pass directly through the steer's system. It is

important for the ranchers to know the moisture content of their crops so they can

calculate the dry matter. Dry matter is the amount of the crop left over when the

moisture is taken out. In the example mentioned, the dry matter is three pounds.

The dry matter contains all of the nutrients and fibers, the most important to

I 6

growth being protein. Protein is the catalyst needed for gaining weight and

I building strength. Rufage is synonymous with fiber. Fiber is necessary in the

formation of healthy muscles and tendons..

The county agent told me that there are other mineral and vitamin

I

requirements, but he said if I met the protein and dry matter requirements, I

would also meet these other nutritional requirements. So I had him give me the

Irecommended daily allowances for dry matter and protein which would enable a

600-pound steer to gain an average of two pounds a day. I also had him give me

the average moisture and protein content percentages per pound for milo, alphalfa,

sileage, and wheat hay.

With the nutritional requirements .1 got from the county agent and the costs

I and quantities on-hand from my uncle, I was able to formulate an LP model to

arrive at an optimal feedmix solution at a. minimal cost.

I.ANALYSIS OF SITUATION

After evaluating all of the information I had gathered, I decided to focus my

project on the backgrounding operation with the objective of maximizing weight

I

gain at a minimal cost while meeting the nutritional needs of the cattle.

The technique best suited to solve this type of problem was a Linear

.Programming (LP) model. The first few constraints would represent the upper and

I

lower limits for the recommended dry matter and protein intake per day for each

steer. The other constraints would be the upper limits for the amount of crops on-

hand.

VA

I first formulated an LP model to minimize the cost of the feed mix. My

objective variables were milo, aiphalfa, sileage, and wheat hay. But then I decided

to run some additional models to approach the problem from different angles.

These other models used the same constraints but with different objective

functions.

The second model has an objective function that maximizes revenue. Not

only did I include the cost of crops on-hand, but also I added the revenue gained

from selling the milo and aiphalfa on-hand for cash and buying back only enough

milo and aiphalfa as was needed in the feed mix.

IThe third mode.( is exactly like the second with one exception. In its

objective function, all of the costs assigned to the crops on-hand are considered

"sunk" costs. "Sunk" cost means the costs of the crops are assumed to be zero

• because the crops are leftovers from those already sold to market.

TECHNICAL DESCRIPTION OF THE MODELS

Each of the three LP models has the same constaint.s. The difference

between the models is in their objective functions. The three models are shown on

the pages following this section.

Const.aints

The primary constaints involved with this feedmix problem are the amounts

of protein and dry matter the steer digests each day. According to the county

agent, each steer should consume between 17 to 18 pounds of dry matter each day

along with 1.7 to 1.86 pounds of protein. I determined the moisture content per

8

pound for each crop and formulated an equation to calculate the amount of dry

matter. Constraint 2 is the upper limit, for the daily dry matter consumption and

const.aint 3 is the lower, I also formulated an equation to calculate the amount of

protein per pound in each crop. Const.aint.s 4 and 5 represent. the upper and lower

limit, for port.ein consumption each day. Constaint.s 6, 7, 8, and 9 represent. the

quantity of each crop available per head per day. 1 calculated this from the total

quantity on-hand for each crop.

Model I

This model's objective function minimizes the cost of the feed mix. its

variables represent the pounds of milo, aiphalfa, sileage, and wheat hay used in the

daily feedmix. Their respective coefficients represent the Cost per pound for 60

mixes (representative of the 60-day feeding period).

The optimal solution yielded a cost of $26.82. That is the cost of feeding

each steer for 60 days with the hope that the steer will gain 100 to 120 pounds.

The most critical constaint for this model .is the lower limit on the protein, as

shown by the dual price in Model 1.

Model 2

This models objective function attempts to maximize revenue from the sale

of the milo and aiphalfa on-hand. The four variables from the minimization model

are used here along with four others. The first two new variables represent the

pounds of milo and aiphalfa on-hand that are sold for cash. Their coefficients are

the revenue they would bring per pound for the 60-day period. The last two new

'variables represent the pounds of milo and afphaffa bought from the marketplace

to he used in the feedmix.

The const.aint.s are essentially the same with the exception of one or two

additional variables to be found in all the constaints except S and 9. These new

variables represent. the milo and aiphalfa that is to be sold or bought.

The optimal solution is $0.965. This means that by selling all of the milo and

aiphalfa on-hand, and buying back aiphalfa for the feedmix, my uncle can earn

almost one dollar per head, in other words, he would make money while fattening

up the cattle.

Again, the most critical constaint is the lower limit on the protein, as shown

by the dual price in Model 2.

Model 3

The objective function for this model maximizes revenue like that of model

2's. However, in this model I assumed the costs for the crops on-hand to be sunk

costs (assumed zero). The first two variables in the objective function represent

the revenue for selling the milo and aiphatfa on-hand. The last two variables

represent the costs of buying milo and alphalfa for use in the feedmi.

The optimal solution is $16.66. That means that by selling all the milo and

alphalfa on-hand, and buying back milo to use in the feedmix, my uncle will earn

$16.66 per head at the end of the 60-day feeding period. However, we must

remember this is because I assumed zero cost for the crops on-hand. But the truth

is we did incur costs in the production and storage of those crops on-hand.

Like models 1 and2, the most critical constaint for this model is the lower

limit. for the protein requirement.

FILE: FILE FT02F001 A VM/SP(CMS) R3.l612/85 PUT8502

MIN 2.46 MILO 4- 0.54 SIL 1.8 ALFA + 0.45 WH SUBJECT TO

3) 0.89 MILO + 0.35 SIL 4- 0.89 ALFA 4- 0.86 WH > 17 4) 0.15219 MILO 4 0.02555 SIL + 0.11036 ALFA 4- 0.0645 WH

> 1.7 _5).0.15219MLLO0.02555...SI1_+_0.11O36 ALFA...+ .0.0645 WH

< 1.86.

6) SIL <= 26.04099

71 WH <= 5.083 __8).__MIL0_<=_8...208_________________________

91 ALFA < 4.04 END

OBJECTIVE FUNCTION VALUE

._1 ).. ___26... 821,6400

VARIABLE VALUE REDUCED COST

MILO 3.059870 0.000000 SIL._ 18.027817 0..000000

ALFA 4.040000 0.000000

WH 5.082999 0.000000

ROW SLACK OR SURPLUS DUAL PRICES 2) ' 1.000000 0.000000 3) 0.000000 -0.633198

- _.t)__ 0.00.0000 i2..461O92' 5) 0.160000 0.000000 6) 8.013163 0.000000 7) 0.000000 0.898290

._8).. _5.148129 . 0.00000 __• ____ 9) 0.000000 0.138752

NO. ITERATIONS= 6

RANGES IN WHICH THE BASIS IS UNCHANGED

_ ___.....OBJ.....COEFFiCI.ENT..RAN.GES____ VARIABLE CURRENT ALLOWABLE ALLOWABLE

COEF INCREASE DECREASE MILO ' 2.459999 0.756541 0.266622 SIL ., _,__0.540000___.0.427.415__._0.113775

ALFA 1.799999 0.138752 INFINITY WH 0.450000 0.898290 INFINITY

.......................... IGH.THANO_S [DEA.NGES.._.._ ROW CURRENT ALLOWABLE ALLOWABLE

RHS INCREASE DECREASE 2 18.000000 INFINITY 1.000000

3 17.000000 1.000000 0.160000

.616104 8:266 82 4 1.700000

5 . 1.860000 INFINITY 0.160000 6 26.040985__INFI,NITV._.._- 8.013163

5.082999 7.489752 3.329110 8 8.207999 . INFINITY 5.148129 9 4.040000 5.879750 4.040000

fr1Ot1 11

1 FILE: FILE 'FTO3FOOUA 'VM/SP1CMS)R3.i.6f12/85PUT8502 - MAX 2.4 MS + 1.8 AS - 2.46 MM - 1.8 AM - 0.45 HM - 0.54 SM

- 2.22 MB - 1.8 AB _SUBJECT..T O ._._ ...-.--.--..--.-..---..---._---. ___----..--.

2) 0.89 MM + 0.89 AM + 0.86 HM + 0.35 SM + 0.89 MB

:I+ 0.89 AB >= 17

3) 0.89 MM + 0.89 AM + 0.86 HM + 0.35 SM + 0.89 MB + 0.89 AB < .:...18 .. .....................

- 4) 0.15219 MM + 0.11036 AM + 0.0645 HM + 0.02555 SM + 0.15219 MB + 0.11036 AB )= 1.7

5)

0.15219 MM + 0.11036. AM + 0.0645 HM + 0.02555 SM 15219 MB ..+O.11036 ....AB<=_1.86

• 6) MS + MM = 8.208 7) AS + AM 4.04 8) SM <= 26.04099

..........9)._HM<._5.083_________________________ .:END

OBJECTIVE FUNCTION VALUE

1) 0.965374529

VARIABLE VALUE REDUCED COST MS 8.207999 0.000000 AS 4.040000 0.000000

__.MM ......_.____o . 0 0 0 0 0 0 2.666622 AM 0.000000 1.799999 HM 5.082999 0.000000 SM 10.857266 0.000000

......-_...0.000000._.__._0.026623 AB 9.919750 0.000000

ROW 0R SURPLUS .. ___DUAL PRICES 2) 0.000000 -0856351 3) 1.000000 . 0.000000 4) 0.000000 -9.404198

-- - - ...... 0.160000 0.000000 6)

. .. 0.000000 2.400000

7) 0.000000 1.799999 - 8) 15. 183718 0.000000

. 9) 0.000000 ._.. .O.8.93033._____

NO. ITERATIONS= 8 . .

RANGES IN WHICH THE BASIS IS UNCHANGED

COEFFICIENTVARIABLE . ...CURRENT ±.. LOABLE ALLOWABLE - ..

COEF INCREASE DECREASE MS 2.400000 INFINITY 2.666622

1AS 1.799999 INFINITY 1.799999

MM -2.459999 2.666622 INFINITY AM

HM

-0.450000 -1.799999 . 1.799999

INFINITYINFINITY

0.893033

I s .......... ..-0.540000 _O.011361 ____ ... 0. 167865 . ...........-MB -2.219999 . 0.026623 INFINITY AB -1.799999 0.426856 0.013855

RIGHTHAND SIDE RANGES_..... ROW CURRENT ALLOWABLE ALLOWABLE

RHS INCREASE DECREASE 217.000000 1.000000 1.562920 .3 18.000000 - ._._.1NFINITY .... ._____1.000000 4 1.700000 0.160000 0.271029 5 1.860000 INFINITY 0.160000 6 8.207999 INFINITY 8.207999 7 4.040000 ..INFINITY 4.040000 8

•.26.040985 INFINITY • 15.183718

9 5.082999 4.599006 5.082999

MDtEL Z

FILE: FILE FT04FOO1 A VM/SP (CMS) R3.1 6/12185 PUT8502

MAX 2.4 MS + 1.8 AS - 2.22 MB - 1.8 AB SUBJECT TO

-----------2) _0.89 _MM + 0.89 --AM +..0.86HM3._0.35 SM. -0.89 MB +O.89A8>= 17

3) 0.89 MM + 0.89 AM 4- 0.86 HM + 0.35 SM + 0.89 P-lB + 0.89 AG <= 18

- ...............4) 0.15219 MM .0.11036..AM +..0.0645...HM...+..0.02555 SM + 0.15219 MB + 0.11036 AB >= 1.7

5) 0.15219 MM + 0.11036 AM + 0.0645 HM + 0.02555 SM f 0.15219 MB + 0.11036 AG < 1.86

6)_.JiS..i-....MM 8.208 ------.-.-

71 AS + AM = 4.04 8) SM <= 26.04099 9) HM <= 5.083

_.END..

.-----_____

OBJECT IVE..FUNCTION.._VALUE_

1) 16.6610870

_VARIABLE ....._.....VALUE . ______REDUCED...COST MS 8.207999 0.000000 AS 4.040000 0.000000 MM 0.000000 0.180001 AM _..0.000000... v.190176 HM 5.082999 0.000000 SM 26.040985 0.000000 MB 4.644192 0.000000

ROW SLACK OR SURPLUS DUAL PRICES ._2) ......0.619054. 0.000000_____

3) 0.380946 0.000000 4) 0.000000 -14.5870284--U 5) 0.160000 0.000000

. 6) ._..0.000000 . .. 2.400000._...... ... .............. 7) 0.000000 1.799999

8)

0.000000 0.372698 9) 0.000000 0.940863

NO. ITERATIONS= 8

RANGES IN .WHICH .THE BASIS IS ..UNCHANGED..___ .. .....................

OBJ COEFFICIENT RANGES VARIABLE . CURRENT ALLOWABLE ALLOWABLE

............... __COEF INCREASE ._.._._DECREASE MS 2.400000 INFINITY 0.180001 AS 1.799995 INFINITY 0.190176 MM 0.000000 0.180001 INFINITY

AM MM

0.000000 0.000000

0190176 INFINITY

INFINITY 0.940863

SM 0.000000 INFINITY 0.372698

MG

72.219999....

.._ ..,__._ .2.219999 0.180001 -.

-.AB-1.799999 0.190176 INFINITY

RIGHTHAND SIDE RANGES ROW CURRENT. _.ALLOWABLE - ......ALLOWABLE

- .. RHS . INCREASE DECREASE U 2 17.000000 0.619054 INFINITY

3 . 18.000000 INFINITY 0.380946 4 1.700000 -- -------,. 0.065142._.....- ......_..0.105858 5 1.860000 INFINITY 0.160000 6 8.207999 INFINITY 8.207999 7 4.040000 INFINITY 4.040000 8 26.040985 .............1.899179 ............... 3.086245 9

5.082999 0.789024 1.282196

MODE 3

IVARIABLES

WI FD CRP

I MS AS MM AM HM SM MB AB MTR CST REV

MODEL

i) MIN COST -- -- .li 44 5.08 n8.03-- -- 3021 # $4,291 $1,483

2) MAX REVENUE IW/O SUNK COST 8.21 4.04 -- •-- -- 2586k $4.161 $4315

I MAX REVENUE W/SUNK COST 8.21 4.04 -- -- 604 464 -- 35J6 $4,265 $4,315

CURRENT MIX -- -- -- -- 3000 # $6,854 ???

IMS: milo on-hand sold to mt-U HM: hay on-hand used in mix

I AS: aiphaifa on-hand sold to mt-U SM: sileage on-hand used in mix

1 MM: milo on-hand used in mix MB: nailo bought for use in mix

AM: aIphalfa on-band used in mix AB: aiphalfa bought for use in mix I WI MTR (wet matter): the actual poundage each animal would consume each day

FD CST (feed cost): total Cost of feed mix for 60 day period

CRP REV (crop revenue): total revenue from sate of crops on-hand not used in mix I I Table 1

Comparison of each model's output to the next including the current mix I I I I I

U10

After I formulated each mode!, I input its objective function, variables, and

constraints into a UNDO program. The outputs from each LINDO program provided

me with the results I needed in order to devise the best feedmix solution for the

ranch. The UNDO outputs for each model are shown on the preceding pages.

COMPARISON OF MODELS

I have taken the relevant outputs from each model and put them into Table

1, shown on the previous page, so you can see how each model relates to the

others. Included in this comparison is the current feedmix used by the ranch.

As shown in. the table, model 1 utilized each crop made available where as

model 2 chose not to use any milo and model 3 chose not to use any alphaifa.

When I plugged the current feedmix numbers into the constaints used in the

models, I found that the current mix violated all but three constaints--6, 7, and 9.

The steers dry matter consumption was 20.22 pounds per day and their protein

consumption was 2.54 pounds per day. With these amounts, the cattle would no

doubt gain more that two pounds a day; however, that extra gain isn't cheap. It is

costing the ranch $42.00 to feed each head for 60 days, far more expensive than

any of the other models.

Model 1 and the current mix have the same wet matter content--30 pounds.

This was recommended by the county agent. Model 2, on the other hand, offers a

feedmix weighing only 25.86 pounds and Model 3 has a feedmix weighing 35.76

pounds. With a light feedmix, the steer's hunger might not be satisfied and the

steer may eat some of the other steer's rations, depriving them of their nutritional

needs. A heavy mix isn't good either because a steer might not be able to consume

that. much wet matter in one day, thus the steer won't be getting the nutrients it

needs to gain the average two pounds a day.

Models 2 and 3 yield the same revenue from the sale of milo and aiphalfa.

But Model 2 has the cheapest feed cost. Although the feed cost. for Model I is more

expensive than Models 2 and 3, it, is, respectively, only 3% and 0.6% more

expensive. On the other hand, the mix currently in use is costing as much as 64.7%

more than the other models.

ASSUMPTIONS AND LIMITATIONS

In formulating these models 1 had to make a few assumptions and use some

theoretical data.

Assumptions:

1) I kept the feedmix constant for the entire 60-day period. In reality, the

feedmix would have to change each time the cattle gained 15 to 25 pounds

because they would need more feed to sustain the heavier weight.

2) 1 used theoretical percentages when figuring out the moisture and

protein content because the actual data wasn't available to me. In reality,

my uncle would send a sample of each crop into a lab to have those contents

tested.

3) The costs involved are taken from current market prices and

historical data from past harvests. However, the revenues used are the

12

Iaverages of the best. and worst. forecasts for the future market prices given

- to me by my uncle.

4) In the models I let the lower limit Of milo be zero because I

couldn't obtain data to justify a non-zero limit. But in reality, milo is a

necessity in a feed mix for several reasons. Milo is high in protein and is

considered candy for cattle. But the cattle can't eat much of it at first

because their system is tc1dUcate to handle it. So the cattle must get

used to eating milo gradually. The reason milo is so important is that it is

vital for fattening cattle up to the 1200 pound benchmark.

5) Weather is critical to the backgrounding process. But it is

intangible and extremely difficult to quantitate. The significance of weather

is that during cold weather, the cattle must consume more feed than usual in

order to retain warmth. During a mild winter, the cattle wont require as

much feed. Since it is very diffecult to predict the weather for the next 60

days, my uncle cannot know exactly how much feed his cattle will require.

If I were to use the percentages from the lab tests and limited myself to a

time period where the cattle gained 15 to 25 pounds, a more accurate model and

solution could be obtained.

CONCLUSION/RECOMMENDATIONS

I

Our goat is to obtain a 100 to 120 pound weight gain in the cattle at a

minimal cost while providing the steer with a healthy diet. We want a healthy diet

Ibecause we know a healthy steer will ultimately gain more wieght than an

unhealthy steer. Each of the crops on-hand have varying degrees of proteins,

I

13

fibers, minerals, and vitamins. But by using each crop on-hand in the feed mix, and

I meeting the daily recommended diet, we can be assured that the steer is getting all

the vitamins, nutrients, and minerals it needs to build a healthy frame. We may be

able to save some money by using feed mix #2 or #3 , but our main goal isn't. to

make money on the backgrounding operaton, it is to build a strong and healthy

Isteer. We will worry about revenue when we try to sell them off at 1300 pounds.

ITherefore, my recommendation is to use feedmix 1 in lieu of the current

feed mix. It utilizes all of the crops on-hand and even has some leftover milo to be

Isold. This feed mix meets all of the nutritional needs of the cattle and can save the

ranch over $2500 during the backgroundIng process.