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Arkansas

A R K A N S A S A G R I C U L T U R A L E X P E R I M E N T S T A T I O NDivision of Agriculture University of Arkansas SystemDecember 2007 Research Series 553

Zelpha B. JohnsonD. Wayne Kellogg

Editors

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Technical editing, layout, and cover design by Camilla Crone

This publication is available on the Internet at: http://arkansasagnews.uark.edu/408.htm

Arkansas Agricultural Experiment Station, University of Arkansas Division of Agriculture, Fayetteville. Milo J. Shult, Vice President forAgriculture. Mark J. Cochran, AAES Director and Associate Vice President for Agriculture–Research. TS675QX6.52.The University of Arkansas Division of Agriculture follows a nondiscriminatory policy in programs and employment.ISSN:1051-3140 CODEN:AKAMA6

Cover photo by Peggy Greb, USDA/ARS Image Gallery

ARKANSAS ANIMAL SCIENCE DEPARTMENT REPORT 2007

Edited by

Zelpha B. JohnsonProfessor

and

D. Wayne KelloggProfessor

Department of Animal ScienceUniversity of Arkansas

University of Arkansas Division of AgricultureArkansas Agricultural Experiment Station

Fayetteville, Arkansas 72701

DisclaimerNo findings, conclusions, or reports regarding any product or any process that is contained in any article published in this report

should imply endorsement or non-endorsement of any such product or process.

Blank page to even printer page count in p

INTRODUCTION

It is hard to believe that this is the 10th edition of Arkansas Animal Science. We owe a great debt to Drs. Zelpha Johnson and WayneKellogg who devote valuable time to making this a quality publication. They have edited this publication since 1999; a year after Dr. StaceyGunter designed the format and edited the first edition in 1998.

We believe that Arkansas Animal Science is an essential publication for our program. While peer-reviewed journals are the ultimategoal for publication of quality research, the time-lines for publication and the frequent necessity to combine several trials limit the utili-ty of journals for early dissemination of results. Stakeholders, other researchers, extension faculty, and industry professionals need resultsas quickly as the data are analyzed statistically and prepared in a professional publication such as Arkansas Animal Science. The capacityto present this publication in both hard copy and electronic format on our website further increases its impact.

The research described in this report was conducted at the four main experiment stations used by the Department of Animal Science,including the Arkansas Research and Extension Center at Fayetteville, the Southwest Research and Extension Center at Hope, theSoutheast Research and Extension Center at Monticello, and the Livestock and Forestry Branch Station at Batesville. Other valuableresearch and extension work was conducted at numerous private farms across the state. In the modern world of animal science, the tra-ditional lines between research and extension programs are increasingly disappearing. This should be apparent as one looks at the author-ship of the articles in this publication.

Readers are invited to view all programs of the Department of Animal Science at the departmental website at animalscience.uark.eduand the Livestock and Forestry Branch Station website at www.Batesvillestation.org.

Finally, we want to thank the many supporters of our teaching, research, and extension programs. Whether providing grants forresearch and extension, funds for scholarships, supporting educational and extension programs, donating facilities or horses and livestock,these friends are essential to maintaining a quality animal science program. We thank each and every one of you on behalf of our faculty,staff, students, and stakeholders. We hope you find the research, extension, and educational programs reported herein to be timely, use-ful, and making a contribution to the field of animal science.

Sincerely,

Keith LusbyDepartment Head

INTERPRETING STATISTICS

Scientists use statistics as a tool to determine which differencesamong treatments are real (and therefore biologically meaningful)and which differences are probably due to random occurrence(chance) or some other factors not related to the treatment.

Most data will be presented as means or averages of a specificgroup (usually the treatment). Statements of probability that treat-ment means differ will be found in most papers in this publication,in tables as well as in the text. These will look like (P < 0.05); (P <0.01); or (P < 0.001) and mean that the probability (P) that any twotreatment means differ entirely due to chance is less than 5, 1, or0.1%, respectively. Using the example of P < 0.05, there is less thana 5% chance that two treatment averages are really the same.Statistical differences among means are often indicated in tables byuse of superscript letters. Treatments with any letter in common arenot different, while treatments with no letters in common are.Another way to report means is as mean ± standard error (e.g. 9.1± 1.2). The standard error of the mean (designated SE or SEM) is ameasure of the amount of variation present in the data—the largerthe SE, the more variation. If the difference between two means isless than two times the SE, then the treatments are usually not sta-tistically different from one another. Other authors may report anLSD (least significant difference) value. When the differencebetween any two means is greater than or equal to the LSD value,then they are statistically different from one another. Another esti-mate of the amount of variation in a data set that may be used isthe coefficient of variation (CV), which is the standard errorexpressed as a percentage of the mean. Orthogonal contrasts maybe used when the interest is in reporting differences between spe-cific combinations of treatments or to determine the type ofresponse to the treatment (i.e. linear, quadratic, cubic, etc.).

Some experiments may report a correlation coefficient (r),which is a measure of the degree of association between two vari-ables. Values can range from –1 to +1. A strong positive correlation

(close to +1) between two variables indicates that if one variablehas a high value then the other variable is likely to have a high valuealso. Similarly, low values of one variable tend to be associated withlow values of the other variable. In contrast, a strong negative cor-relation coefficient (close to –1) indicates that high values of onevariable tend to be associated with low values of the other variable.A correlation coefficient close to zero indicates that there is notmuch association between values of the two variables (i.e. the vari-ables are independent). Correlation is merely a measure of associa-tion between two variables and does not imply cause and effect.

Other experiments may use similar procedures known asregression analysis to determine treatment differences. The regres-sion coefficient (usually denoted as b) indicates the amount ofchange in a variable Y for each one unit increase in a variable X. Inits simplest form (i.e. linear regression), the regression coefficient issimply the slope of a straight line. A regression equation can beused to predict the value of the dependent variable Y (e.g. perform-ance) given a value of the independent variable X (e.g. treatment).A more complicated procedure, known as multiple regression, canbe used to derive an equation that uses several independent vari-ables to predict a single dependent variable. Associated statistics arer2, the simple coefficient of determination, and R2, the multiplecoefficient of determination. These statistics indicate the propor-tion of the variation in the dependent variable that can be account-ed for by the independent variables. Some authors may report thesquare root of the Mean Square for Error (RMSE) as an estimate ofthe standard deviation of the dependent variable.

Genetic studies may report estimates of heritability (h2) orgenetic correlation (rg). Heritability estimates refer to that portion

of the phenotypic variance in a population that is due to heredity.A genetic correlation is a measure of whether or not the same genesare affecting two traits and may vary from –1 to +1.

LIST OF COMMON ABBREVIATIONS

Abbreviation Term

Physical Units

cal Calorie

cc cubic centimeter

cm centimeteroC Degrees CelsiusoF Degrees Fahrenheit

ft Foot or feet

g Grams(s)

gal Gallon(s)

in Inch(es)

IU International unit(s)

kcal Kilocalories(s)

kg Kilograms(s)

lb Pound(s)

L Liter(s)

m Meter(s)

mg Milligram(s)

Meq Milliequivalent(s)

Mcg Microgram(s)

mm Millimeter(s)

ng Nanogram(s)

oz ounce

ppb Parts per billion

ppm Parts per million

Units of Time

d Days(s)

h Hour(s)

min Minute(s)

mo Month(s)

s Second(s)

wk Week(s)

yr Year(s)

Others

ADF Acid detergent fiber

ADFI Average daily feed intake

ADG Average daily gain

avg Average

BCS Body condition score

BW Body weight

CP Crude protein

CV Coefficient of variation

cwt 100 pounds

DM Dry matter

DNA Deoxyribonucleic acid

EPD Expected progeny difference

F/G Feed:gain ratio

FSH Follicle stimulating hormone

LH Lutenizing hormone

N Nitrogen

NDF Neutral detergent fiber

NS Not significant

r Correlation coefficient

r2 Simple coefficient of

determination

R2 Multiple coefficient of

determination

SD Standard deviation

SE Standard error

SEM Standard error of the mean

TDN Total digestible nutrients

wt Weight

COMMON ABBREVIATIONS

A Comparison of Weaning Ratio in Five Breeds of CattleZ.B. Johnson, A.H. Brown, Jr., and S.T. Dewey..................................................................................................................................................10

Relationship of Lactate Dehydrogenase Activity with Body Measurements of Angus x Charolais Cows and CalvesM.L. Looper, T.P. Neidecker, C.W. Wall, S.T. Reiter, R. Flores, A.H. Brown, Jr., Z.B. Johnson, and C.F. Rosenkrans, Jr. ..............................13

Supplemental Trace Minerals (Zn, Cu, Mn, And Co) as Availa®4 or Inorganic Sources for Shipping-Stressed CattleM.R. Pass, E.B. Kegley, and C.K. Larson ............................................................................................................................................................16

Arkansas Steer Feedout Program 2005-2006B. Barham, S. Gadberry, J. Richeson, and S. Cline ............................................................................................................................................22

Regression of Feed Intake on Selected Environmental Factors for Beef Bulls During Post-Weaning Feedlot Performance Tests

G.T. Tabler, Jr., A.H. Brown, Jr., E.E. Gbur, Jr., I.L. Berry, Z.B. Johnson D.W. Kellogg, and K.C. Thompson................................................25

Effects of Selected Weather Factors on Feed Intake of Angus, Polled Hereford, and Simmental Beef Bulls During Feedlot Performance Tests

G.T. Tabler, Jr., A.H. Brown, Jr., E.E. Gbur, Jr., I.L. Berry, Z.B. Johnson, D.W. Kellogg, and K.C. Thompson ..............................................29

Influence of Sanitizing Feedlot Pens on Microbial Populations and Cattle Performance M.S. Lee, J.K. Apple, J.S. Yancey, J.T. Sawyer, M.M. Brashears, and TP. Stephens ............................................................................................34

Influence of Reproductive Tract Score on Pregnancy in Angus HeifersJ.G. Powell, A.H. Brown, T.A. Yazwinski, R.A. Rorie, Z.B. Johnson, J.L. Reynolds ..........................................................................................39

Reproductive Performance, Blood Urea Nitrogen, and Blood Glucose Concentration in Beef Heifers Grazing Annual Ryegrass in the Spring and Supplemented at Different Intervals Prior to Timed AI

D.L. Kreider, K.P. Coffey, J.D. Caldwell, W.A. Whitworth, T.G. Montgomery, R. Rorie, R.W. McNew,W. Coblentz, and R.K. Ogden ..........................................................................................................................................................................41

Effect of Bovine Somatotropin Treatment on AI Pregnancy Rate in Dairy HeifersR.W. Rorie and T.D. Lester ..................................................................................................................................................................................45

Effects of Penicillamine, Hypotaurine and Epinephrine (PHE) on Post-Thaw Bovine Sperm Parameters, as Measured by Computer-Assisted Sperm Analysis

C.N. Person, T.D. Lester, M.D. Person, and R.W. Rorie ....................................................................................................................................47

Computer-Assisted Analysis of Sperm Parameters after Selection of Motile Sperm by Either Percoll Gradient,Filtration, or Swim-up Procedures

C.N. Person, T.D. Lester, M.D. Person, and R.W. Rorie ....................................................................................................................................51

Effects of Milk Antimicrobial Proteins on Incidence of Mastitis in Dairy CattleM.D. Person, C.N. Person, T.D. Lester, and R.W. Rorie ....................................................................................................................................54

DairyMetrics for Arkansas Herds in May, 2007J.A. Pennington ....................................................................................................................................................................................................56

Glycerol as a Supplemental Energy Source for Meat GoatsK.R. Hampy, DW. Kellogg, K.P. Coffey, E.B, Kegley, J.D. Caldwell, M.S. Lee, MS. Akins, J.L. Reynolds,

J.C. Moore, and K.D. Southern ........................................................................................................................................................................63

In Vitro DM Digestibility of Crabgrass, Bermudagrass, and Wheat Forages Supplemented with Four Levels of Glycerol1

K.R. Hampy, D.W. Kellogg, K.P. Coffey, and K. Anschutz ................................................................................................................................65

Cow and Calf Performance While Grazing Tall Fescue Pastures with Either the Wild-Type Toxic Endophyte or a Non-Toxic Novel Endophyte

K.P. Coffey, W.K. Coblentz, J.D. Caldwell, C.P. West, R.K. Ogden, T. Hess, D.S. Hubbell, III, M.S. Akins,and C.F. Rosenkrans, Jr. ....................................................................................................................................................................................67

Growth Performance and Immune Function of Fall-Born Beef Calves Weaned from Endophyte-Infected Tall Fescue Pastures on Different Dates in the Spring

J.D. Caldwell, K.P. Coffey, W.K. Coblentz, R. K. Ogden, J. A. Jennings, D.S. Hubbell, III, D.L. Kreider, and C.F. Rosenkrans, Jr. ..............70

TABLE OF CONTENTS

Nutritive Value of Fall-Grown Cereal-Grain Forages over TimeM.S. Akins, E.B. Kegley, J.L. Gunsaulis, W.K. Coblentz, K.S. Lusby, R.K. Ogden, J.D. Caldwell,

R.K. Bacon, and K.P. Coffey ..............................................................................................................................................................................73

Effect of Surface Decontamination Using Antimicrobial Agents on Microbiological Quality of Beef SteaksF.W. Pohlman, P.N. Dias-Morse, C.W. Rowe, and S.R. De Silva ......................................................................................................................78

Effect of Salt, Trisodium Phosphate, Synthetic Antioxidants, and Conjugated Linoleic Acid on Sensory and Quality Characteristics of Beef Striploins

C.W. Rowe, F.W. Pohlman, A.H. Brown, Jr., and Z.B. Johnson ........................................................................................................................81

Effect of Salt, Trisodium Phosphate, Synthetic Antioxidants, and Conjugated Linoleic Acid on Instrumental Color Characteristics and Physical Characteristics of Beef Striploins of Different Quality Grades

C.W. Rowe, F.W. Pohlman, A.H. Brown, Jr., and Z.B. Johnson ........................................................................................................................84

Color Stability of Dark-cutting Beef Enhanced with Lactic AcidJ.T. Sawyer, J.K. Apple, Z.B. Johnson, R.T. Baublits, and J.W.S. Yancey ............................................................................................................87

The Impact of Acidic Marination Concentration and Sodium Chloride on Sensory and Instrumental Color Characteristics of Dark-cutting Beef

J.T. Sawyer, J.K. Apple, and Z.B. Johnson ..........................................................................................................................................................92

Impact of Stressing a Pen Mate on Physiological Responses of Growing PigsJ.B. Koonce, E.B. Kegley, D.L. Galloway, Sr., and J.K. Apple..............................................................................................................................96

Effect of Weaning Age on Nursery Pig Growth PerformanceB.E. Bass, C.L. Bradley, J.W. Frank, and C.V. Maxwell ....................................................................................................................................100

Effect of Feeding Alfalfa on Nursery Pig Growth PerformanceC.L. Martin, J.W. Frank, Z.B. Johnson, G.M. Weiss, and C.V. Maxwell..........................................................................................................103

Characterization of Claw Lesions Associated with Lameness in the University of Arkansas Sow HerdC.L. Bradley, J.W. Frank, C.V. Maxwell, Z.B. Johnson, J.G. Powell, S.R. Van Amstel, and T.L. Ward ..........................................................106

10

Introduction

The ratio of calf weight to cow weight at calf weaning(WnRatio) is utilized in some performance testing programs as ameasure of gross biological or economic efficiency in cow-calf pro-duction. Generally, cows that have a high ratio (> 0.50) are moreefficient and profitable than cows that have a low ratio (< 0.50). AsWnRatio goes down, calf break-even cost goes up. Kress et al.(2001) reported that calf weight at weaning divided by cow weightat weaning was an accurate indicator of cow-calf biological effi-ciency. However, Dinkel and Brown (1978) and MacNeil (2005)showed that the WnRatio had little advantage over calf weaningweight alone in estimating efficiency in cow-calf production.Despite differences in the aforementioned reports, there exists aneed for further evaluation of this ratio, because of interest in usingthe ratio as a selection trait and because of the need to improve effi-ciency of cow-calf production. Thus, the objectives of this studywere to estimate genetic parameters for calf weaning weight, cowweight at calf weaning, and WnRatio, and to compare ratios amongsamples of five breeds of beef cattle managed on Ozark nativerange.

Experimental Procedures

Data for this study came from purebred beef cattle popula-tions reared on the University of Arkansas Experiment StationFarm near Savoy. Five breeds were represented: Angus (years 1965through 1995), Hereford (years 1965 through 1998); Charolais(years 1970 through 1988), Red Poll (years 1978 through 1995), andChianina (years 1985 through 1995). Description of the establish-ment and management of these herds was given by Johnson et al.(1990). Calves were born in the Spring and birth weights (Brwt)

recorded within 24 h of birth. Both cow and calf weights wererecorded when calves were weaned in the Fall (usually October).Calf weights were adjusted to 205 d of age by linear regression.Weaning ratio was calculated as calf weight at 205 d of age (Wt205)divided by cow weight (CowWt) at weaning of her calf.

Heritabilities for each of these four traits (Brwt, Wt205,CowWt, and WnRatio) for each breed (except Chianina where thesmall sample size prevented estimation of genetic parameters) wereestimated using the MTDFREML program of Boldman et al.(1993) and Boldman and Van Vleck (1991). Multiple-trait analyseswere conducted with Brwt included in each analysis because thistrait was available for all records. The model included fixed effectsfor year and sex. Age of dam (at birth of the calf) was included as acovariate for Brwt, Wt205, and WnRatio. For CowWt, this covari-ate would be interpreted as age of the cow at the birth of her calf.Both direct and maternal heritabilities were obtained for all traitsexcept CowWt, where maternal effects were not included in themodel. Approximate standard errors were obtained from a singletrait analysis of each trait. Breed differences for each trait wereexamined using PROC MIXED of SAS (SAS Inst., Inc., Cary, N.C.).The model included breed, year, sex, and breed by sex interaction asfixed effects. Age of dam was a covariate, and sire within breed wasa random effect used to test for breed differences. Mean separationwas accomplished using the PDIFF option of LSMEANS in PROCMIXED.

Results and Discussion

Number of observations for each trait and breed, along withmean, standard deviation, minimum and maximum values, is givenin Table 1. Most of the observations were from Angus and Herefordbreeds, with fewer Charolais and Red Poll, and only a few Chianina.

Estimates of heritabilities for direct and maternal effects for

Story in Brief

The objectives of this study were to estimate genetic parameters for calf weaning weight (Wt205), cow weight at calf weaning(CowWt), and ratio of calf weight to cow weight at calf weaning (WnRatio), and to compare ratios among samples of five breedsof beef cattle. Data for this study came from purebred beef cattle populations reared on the University of Arkansas ExperimentStation Farm and included Angus, Hereford, Charolais , Red Poll, and Chianina. Heritabilities for each trait for each breed (exceptChianina which did not have enough numbers) were estimated. Multiple-trait analyses were conducted with birth weight includ-ed in each analysis because this trait was available for all records. Year of birth and sex of calf were included as fixed effects and ageof dam was a covariate. Heritability estimates for direct effects of Wt205 were 0.38, 0.21, 0.30 and 0.10 for Angus, Hereford,Charolais, and Red Poll, respectively. Heritability estimates for maternal effects for Wt205 were 0.19, 0.25, 0.23, and 0.44 for Angus,Hereford, Charolais, and Red Poll, respectively. Estimates of heritability for direct effects for CowWt were similar for Angus,Hereford, and Charolais (0.62 and 0.63) and somewhat higher for Red Poll (0.89). For WnRatio, heritabilities for direct effects werelow, ranging from an estimate of zero for Red Poll to 0.15 for Angus; whereas, heritabilities for maternal effects were higher, rang-ing from 0.39 for Charolais to 0.70 for Red Poll. The Chianina breed did not differ (P > 0.05) from the Hereford breed for WnRatio;however, all other breeds differed (P < 0.05) from each other for this trait.

A Comparison of Weaning Ratio in Five Breeds of Cattle

Z.B. Johnson, A.H. Brown, Jr., and S.T. Dewey1

1 All authors are associated with the Department of Animal Science, Fayetteville.

Arkansas Animal Science Department Report 2007

11

each trait and breed are given in Table 2. Estimates of heritabilityfor Brwt were obtained from each of the three analyses and rangedfrom 0.55 to 0.59 in Angus, from 0.31 to 0.36 in Hereford, from0.52 to 0.63 in Charolais, and from 0.33 to 0.40 in Red Poll fordirect effects. Estimates of heritability of maternal effects for Brwtranged from 0.12 to 0.16 in Angus, from 0.16 to 0.21 in Hereford,from 0.08 to 0.16 in Charolais, and all estimates were 0.05 in RedPoll. Standard errors in Red Poll were larger than the estimateimplying that none of these estimates were different from zero.MacNeil (2005) reported heritability estimates of direct effects of0.46 ± 0.04, 0.48 ± 0.03, 0.76 ± 0.02, and 0.20 ± 0.03 for birthweight, 200-day weight, cow weight, and weaning ratio, respective-ly, in a composite population of beef cattle developed by USDA-ARS at Fort Keogh Livestock and Range Research Laboratory inMontana. He also reported heritability estimates of maternal effectsof 0.10 ± 0.02, 0.13 ± 0.02, and 0.58 ± 0.05 for birth weight, 200-day weight, and weaning ratio, respectively.

Heritability estimates for direct effects for Wt205 were 0.38,0.21, 0.30, and 0.10 for Angus, Hereford, Charolais, and Red Poll,respectively. Heritability estimates for maternal effects for Wt205were 0.19, 0.25, 0.23, and 0.44 for Angus, Hereford, Charolais, andRed Poll, respectively. These estimates are slightly lower for directeffects and slightly higher for maternal effects than those reportedby MacNeil (2005) (0.48 ± 0.03 for direct effects and 0.13 ± 0.02 formaternal effects).

Estimates of heritability for direct effects for CowWt were sim-ilar for Angus, Hereford, and Charolais (0.62 and 0.63), and some-what higher for Red Poll (0.89).These estimates are comparable tothe 0.76 ± 0.02 reported by MacNeil (2005) for this trait. ForWnRatio, heritabilities for direct effects were low ranging from anestimate of zero for Red Poll to 0.15 for Angus, and would not bedifferent from zero for any breed except Angus. These estimates arelower than the 0.20 ± 0.03 reported by MacNeil (2005). The directeffect is the dam’s genes on her performance in producing weaningweight and any direct effect of the calf genes on its performance toweaning. Although estimates of the coefficient of heritability forthe direct component of WnRatio in this study were low, this traitis so important economically that it deserves to be selected fordespite low heritability.

Milk production and mothering ability comprise the maternalcomponents of weaning weight. These components are determinedby the mother’s genes as well as by her environment. The dam’sgenes for these traits do not affect offspring’s growth rate directly,but they do affect the environment provided for the calf by thedam. They also relate to the dam’s ability to protect her calf.Heritabilities for maternal effects for WnRatio were higher than fordirect effects, ranging from 0.39 for Charolais to 0.70 for Red Poll.MacNeil (2005) also reported higher estimates for maternal effects(0.58 ± 0.05). Because of the high estimates of heritability for thematernal component, the WnRatio could be used in selection toimprove both biological and economic efficiency in cow-calfproduction.

Management systems emphasize the best combination of bio-logical and economic efficiency. Although the two types of efficien-cy are interrelated, they are different. Biological efficiency is theamount of beef produced relative to the amount of feed consumed.Economic efficiency is the dollars returned for each dollar spent.

The number of calves weaned and the weight of each calf atweaning are the two most important factors in cow-calf produc-tion. The weaning weight is important because it represents thepounds of production per cow per year. This trait depends on themilk production of the cow, and to a lesser extent, on the ability ofthe calf to grow. The numerator of the WnRatio measures outputof the cow-calf unit and the denominator indicates input througha commonly accepted relationship of cow weight and nutrientrequirements. For the cow, these requirements are affected by hersize and by the demand for milk production by her calf. A cow ofintermediate size will more likely have a higher WnRatio than alarge cow, all else being equal. Most of the time as cow size increases,the WnRatio declines. Davis et al. (1983) found cow weight to becorrelated to efficiency, with smaller cows being more efficient inproduction of weaning weight of calf. The extent to which this ratiorepresents gross efficiency and economic efficiency is only esti-mated.

Least-squares means for breed are presented in Table 3. Aswould be expected Brwt was lowest (P < 0.05) in the Angus breedand highest in Chianina (P < 0.05). Weight at 205 d of age rangedfrom a low of approximately 383 lb for Angus and Hereford breeds(which did not differ, P > 0.05) to a high of 469 lb for Charolais,with Red Poll being intermediate. Charolais calves did not differ(P > 0.05) from Chianina calves for this trait. Chianina cowsweighed the most, followed by Charolais, and Hereford. Angus andRed Poll cows were the lightest and did not differ from each other(P > 0.05). The Chianina breed did not differ (P > 0.05) from theHereford breed for WnRatio; however, all other breeds were differ-ent from each other (P < 0.05). Breed differences for WnRatio pri-marily reflect differences in cow size and milk production amongthe breed groups compared.

Literature Cited

Boldman, K.G., et al. 1993. A manual for use of MTDFREML-A setof programs to obtain estimates of variances and covariances.ARS, USDA, Washington, D.C.

Boldman, K.G., and L.D. Van Vleck. 1991. J. Dairy Sci. 74:4337-4343.

Davis, M.E., et al. 1983. J. Anim. Sci. 57:852-866.Dinkel, C.A., and M.A. Brown. 1978. J. Anim. Sci. 46:614-617.Johnson, Z.B., et al. 1990. Ark. Agric. Exp. Station Bulletin 923.Kress, D.D. 2001. Calf weight/cow weight ratio of weaning as a pre-

dictor of beef cow efficiency. Proceedings, Western Section,ASAS. Vol. 52.

MacNeil, M.D. 2005. J. Anim. Sci. 83:794-802.

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AAES Research Series 553

Table 1. Descriptive statistics for each purebred population.Traita N Mean SD Minimum Maximum

Angus Birth wt, lb 3,872 62.88 11.19 27.00 118.00 Wt205, lb 3,341 387.49 53.66 162.00 605.00 CowWt, lb 2,907 913.92 125.91 554.00 1575.00 WnRatio 2,611 0.43 0.06 0.18 0.73

HerefordBirth wt, lb 2,445 69.46 10.97 29.00 104.00 Wt205, lb 2,106 384.33 57.12 184.00 573.00 CowWt, lb 1,964 999.64 124.10 645.00 1548.00 WnRatio 1,767 0.39 0.06 0.19 0.60

Charolais

Birth wt, lb 575 91.34 15.44 38.00 152.00 Wt205, lb 489 473.92 81.67 193.00 692.00 CowWt, lb 376 1220.29 164.35 800.00 1660.00 WnRatio 316 0.40 0.06 0.20 0.63

Red Poll Birth wt, lb 349 78.50 11.10 50.00 105.00 Wt205, lb 301 430.01 64.88 245.00 620.00 CowWt, lb 246 971.56 135.06 700.00 1472.00 WnRatio 217 0.45 0.06 0.29 0.63

Chianina Birth wt, lb 98 106.39 12.17 80.00 138.00 Wt205, lb 73 473.66 77.57 318.00 708.00 CowWt, lb 94 1318.03 146.37 1010.00 1711.00 WnRatio 71 0.36 0.06 0.23 0.50 aBirth and 205-d weight (Wt205) of calf, cow weight (CowWt) at weaning of her calf and the ratio of calf weight at 205 d of age to cow weight at weaning (WnRatio).

Table 2. Estimates of direct and maternal heritability coefficients (± approximate standard error) for each breed.

Heritability (h2) Traita Angus Hereford Charolais Red Poll Analyses with Brwt and Wt205

Direct Brwt 0.59 ± 0.04 0.36 ± 0.05 0.63 ± 0.12 0.37 ± 0.19 Maternal Brwt 0.12 ± 0.02 0.16 ± 0.03 0.08 ± 0.06 0.05 ± 0.10 Direct Wt205 0.38 ± 0.05 0.21 ± 0.05 0.30 ± 0.13 0.10 ± 0.12 Maternal Wt205 0.19 ± 0.03 0.25 ± 0.03 0.23 ± 0.07 0.44 ± 0.08

Analyses with Brwt and CowWtDirect Brwt 0.55 ± 0.04 0.34 ± 0.05 0.52 ± 0.12 0.33 ± 0.19 Maternal Brwt 0.14 ± 0.02 0.17 ± 0.03 0.08 ± 0.06 0.05 ± 0.10 Direct CowWt 0.62 ± 0.03 0.62 ± 0.04 0.63 ± 0.10 0.89 ± 0.09

Analyses with Brwt and WnRatio Direct Brwt 0.59 ± 0.04 0.31 ± 0.05 0.52 ± 0.12 0.40 ± 0.12 Maternal Brwt 0.16 ± 0.02 0.21 ± 0.03 0.16 ± 0.06 0.05 ± 0.10 Direct WnRatio 0.15 ± 0.04 0.03 ± 0.03 0.09 ± 0.13 0.00 ± 0.12 Maternal WnRatio 0.46 ± 0.03 0.56 ± 0.03 0.39 ± 0.09 0.70 ± 0.08 aBirth (Brwt) and 205-d weight (Wt205) of calf, cow weight (CowWt) at weaning of her calf and the ratio of calf weight at 205 d of age to cow weight at weaning (WnRatio).

Table 3. Least-squares means (± SE) by breed for weight of calf at birth and 205 days of age, cow weight at weaning and weaning ratio.

Traita

Breed Birth wt, lb Wt205, lb CowWt, lb WnRatio Angus 63.6 ± 0.7 f 384.5 ± 3.3 d 918 ± 6 e 0.427 ± 0.003 c

Hereford 70.5 ± 0.7 e 383.3 ± 3.6 d 1,012 ± 6 d 0.383 ± 0.003 e

Charolais 87.2 ± 1.1 c 468.9 ± 5.7 b 1,196 ± 12 c 0.407 ± 0.006 d

Red Poll 74.6 ± 1.9 d 420.9 ± 9.3 c 932 ± 18 e 0.469 ± 0.008 b

Chianina 98.9 ± 2.9 b 456.1 ± 14.2 bc 1,250 ± 23 b 0.375 ± 0.011 eaBirth wt and 205-d weight (Wt205) of calf, cow weight (CowWt) at weaning of her calf and the ratio of calf weight at 205 d of age to cow weight at weaning of her calf (WnRatio). b,c,d,,e,f Within a column, least-squares means without a common superscript differ (P < 0.05).

13

Introduction

Measurement of maternal body condition and (or) bloodmetabolites late in gestation may help predict subsequent calf per-formance. Body condition score (BCS) of cows can be assessed withthe nine point BCS system with 1 being thin and 9 being fat(Wagner et al., 1988). Ultrasonography is a good estimator of sub-cutaneous fat thickness in grazing cattle (Aiken et al., 2004), andrecently, several research groups (Miller et al., 2004; Schröder andStaufenbiel, 2006) have suggested ultrasonography may alleviatesome of the subjectivity of BCS.

Relationships between various prepartum metabolic hor-mones in cows and subsequent calf birth weights have been inves-tigated; however, the relationship between maternal lactate dehy-drogenase (LDH) activity and calf performance has not been exam-ined. Lactate dehydrogenase is the last enzyme of the glycolyticpathway, and catalyzes the reversible conversion of pyruvate to lac-tate. Reduced LDH activity has been associated with increased car-cass quality in steers (Flores et al., 2005) and increased reproductiveperformance of heifers (Looper et al., 2002). Objectives were toexamine 1) relationships between LDH activity and body measure-ments of grazing beef cows, and 2) the association between mater-nal LDH activity in late gestation and subsequent calf birth weight(BRW), hip height (CALFHH) at weaning, and adjusted weaningweight (205-day WW).


Eighty-eight Angus and Charolais cows (age = 5.1 ± 2.6 yr)and their Angus-sired calves (n = 86) from a private farm inCrawford County, Ark., were used. Cattle grazed endophyte-infect-ed tall fescue pastures during the cooler months and commonbermudagrass pastures during the warmer months. At 60 daysbefore calving (mean calving date = January 29), BW, BCS, and cowhip height (COWHH) were recorded, and longissimus muscle area(LMA), intramuscular fat percentage (IMF), and rib fat (RF) weremeasured via ultrasonography using an Aloka SSD-500V with a3.5-MHz linear array transducer. Cross-sections of the LMA werescanned between the 12th and 13th ribs, and RF at 3-quarters thewidth of the LMA. Blood samples were collected into vacutainers(Becton Dickinson, Franklin Lakes, N.J.), allowed to clot for 24 h at40°F, and centrifuged (1500 x g for 25 min). Serum samples werestored at 0°F until analysis.

Lactate dehydrogenase activity was measured via a colorimet-ric assay. Enzyme activity is expressed in IU/L. Concentrations ofLDH activity were ranked into three categories by using the meanconcentration ± 1 SD. The 3 categories with associated concentra-tions of LDH activity are shown in Table 1.

Calves were spring-born, and birth weight and sex of calf wererecorded. Calves remained with dams until weaning, and CALFHHand weight were recorded at weaning. Eleven calves were early-weaned (June 19) while the remaining 75 calves were weaned onAugust 31. Weaning weight was adjusted to a standard 205-dayweaning weight.

1 Names are necessary to report factually on available data; however, the USDA does not guarantee orwarrant the standard of the product, and the use of the name by the USDA implies no approval of theproduct to the exclusion of others that also may be suitable.

2 USDA-ARS, Dale Bumpers Small Farms Research Center, Booneville, Ark.3 Neidecker Farms, Van Buren, Ark.4 University of Arkansas Cooperative Extension Service, Van Buren, Ark.5 Department of Animal Science, University of Arkansas, Fayetteville, Ark.

Story in Brief

Objectives were to examine 1) relationships between lactate dehydrogenase (LDH) activity and body measurements of beefcows, and 2) the association between maternal LDH activity in late gestation and subsequent calf birth weight (BRW), hip height(CALFHH) at weaning, and adjusted weaning weight (205-day WW). At 60 days before calving, BW, body condition score (BCS),and cow hip height (COWHH) were recorded, and longissimus muscle area (LMA), intramuscular fat percentage (IMF), and ribfat (RF) were measured via ultrasonography from Angus x Charolais cows (n = 88). A blood serum sample was collected from eachcow and concentrations of LDH activity were determined and ranked (mean ± 1 SD) into 3 categories. Cows with low reverse LDHactivity had calves with increased (P < 0.05) CALFHH and 205-day WW compared with cows with high LDH activity. Cow LMAwas correlated (P < 0.05) with BW, BCS, and COWHH, and 205-day WW of calves. The canonical correlation between cow for-ward and reverse LDH activity, and 205-day WW and CALFHH of calves tended to be significant (r = 0.30; P = 0.08). Further, thecanonical correlation between cow traits including LMA, IMF, and RF, and calf traits of 205-day WW and CALFHH was signifi-cant (P = 0.02). Cow LMA and reverse LDH activity were correlated (P < 0.01) to 205-d WW and CALFHH (r = 0.38). Decreasedreverse LDH activity in prepartum cows was associated with taller and heavier calves at weaning; increased weaning weights willenhance profitability of Arkansas cow-calf operations.

Relationship of Lactate Dehydrogenase Activity with Body Measurements ofAngus x Charolais Cows and Calves1

M.L. Looper2, T.P. Neidecker3, C.W. Wall4, S.T. Reiter5, R. Flores5, A.H. Brown, Jr.5, Z.B. Johnson5, and C.F. Rosenkrans, Jr.5

14


Statistical analyses. The effect of cow age on LDH forward andreverse activity was analyzed by ANOVA using the MIXED proce-dure of SAS (SAS Inst. Inc., Cary, N.C.). The effects of prepartumLDH forward and reverse activity category (low, medium, or high)on BRW, CALFHH, and 205-day WW also were analyzed byANOVA using the MIXED procedure of SAS. Chi-square analysiswas used to determine the effect of prepartum LDH forward andreverse activity category (low, medium, or high) on gender of calf.Relationships among prepartum cow traits (BW, BCS, COWHH,LMA, IMF, and RF), and between prepartum cow traits and subse-quent calf traits (BRW, CALFHH, and 205-day WW) were exam-ined by Pearson and canonical correlations. Objective of canonicalcorrelation analysis was to find a linear combination of one groupof variables (cow traits) that had a maximal correlation with a lin-ear combination of a second group of variables (calf traits). Theanalysis continues until the number of pairs of canonical variablesequals the number of variables in the smaller group. Three separatecanonical analyses were examined in this experiment. The firstcanonical correlation analysis (Analysis 1) compared cow LDH for-ward and reverse activity (Set 1) with 205-day WW and CALFHHof calves (Set 2). The second canonical correlation analysis(Analysis 2) compared the cow traits of LMA, IMF, and RF (Set 1)with the set of calf traits that included 205-day WW and CALFHH(Set 2). The third canonical correlation analysis (Analysis 3) was acombination of LDH activity and ultrasound measurement withcow reverse LDH activity and LMA (Set 1) with 205-d WW andCALFHH of calves (Set 2).


Relationships among cow measurements. Age of cow did notinfluence prepartum forward (P = 0.19) or reverse (P = 0.46) LDHactivity. Mean concentrations of forward and reverse LDH activitywere 748 ± 48 IU/mL and 227 ± 26 IU/mL, respectively. Sire breedof the cow did not influence (P = 0.82) forward LDH activity(mean = 747± 18 IU/mL); however, Angus-sired cows tended (P =0.07; 242 ± 7 IU/mL) to have greater prepartum reverse LDH activ-ity than Charolais-sired cows (219 ± 11 IU/mL). Prepartum LDHactivity (forward or reverse) was not correlated (P > 0.10) with anycow measurements with the exception of cow BCS and forwardLDH activity (r = 0.21; P = 0.09).

Longissimus muscle area (r = 0.39; P < 0.05) and RF (r = 0.26;P < 0.05) measured with ultrasound were moderately correlated tovisual BCS. Others (Miller et al., 2004; Schröder and Staufenbiel,2006) have suggested that ultrasound provides a more precise esti-mate of body condition than visual BCS.

Relationships between cow prepartum LDH activity and calfmeasurements. Distribution of calf gender was similar (P > 0.10)among the 3 categories of prepartum LDH activity (forward orreverse). Cows with low reverse LDH activity had calves withincreased 205-day WW (P = 0.03; Fig. 1) and CALFHH (P = 0.001;Fig. 2) compared with cows with high LDH activity. Reverse LDHactivity was inversely correlated with CALFHH (r = -0.28; P = 0.01)and 205-day WW (r = -0.21; P = 0.05) of calves. Forward LDHactivity tended (P = 0.11) to be negatively correlated (r = -0.18)with CALFHH. Similarly, reduced LDH activity in steers (Flores etal., 2005) and heifers (Looper et al., 2002) was associated withincreased animal performance.

Cow LMA was correlated (P < 0.05) with BW (r = 0.37), BCS(r = 0.39), and COWHH (r = 0.25) in cows, and with 205-day WWof calves (r = 0.28; P = 0.01). First canonical correlation (Analysis1) between cow forward and reverse LDH activity, and CALFHHand 205-day WW tended to be significant (r = 0.30; P = 0.08; datanot shown). Further, the canonical correlation between the set ofcow traits including LMA, IMF, and RF (Analysis 2) was correlated(r = 0.36; P = 0.02; data not shown) with the set of calf traits thatincluded 205-day WW and CALFHH. Of all 3 canonical correlationanalyses, a linear combination of cow LMA and reverse LDH activ-ity (Analysis 3) had the highest (P < 0.01) canonical correlationwith a linear combination of calf 205-day WW and CALFHH (r =0.38; Table 2). Our data suggest that a combination of both ultra-sonography measurements as well as LDH activity in cows may bea better predictor of calf measurements (hip height and adjustedweaning weight) at weaning than ultrasound or LDH activityalone.

Development of a ‘chute-side’ LDH activity test (enzyme-linked assay) is warranted if threshold concentrations of LDHactivity are substantiated with future research studies using largernumbers of cattle. Ideally, producers would collect a minimalamount of blood from the cow (i.e., skin prick of ear), place bloodin the LDH test cartridge, and wait a short amount of time (i.e., 2-3 minutes) for a positive/negative result. It is estimated that such achute-side test would cost producers $10-15/test. Beef producersare likely to utilize any test that will allow them to make manage-ment decisions about weaned calves much earlier in the productioncycle; however, economic analyses of a chute-side LDH activity testare needed.

Implications

Decreased reverse LDH activity in prepartum cows was associ-ated with taller and heavier calves at weaning. Use of prepartummaternal LDH activity may help in selection of superior calves ear-lier in the production cycle enhancing profitability of cow-calfoperations in Arkansas.

Acknowledgment

The technical assistance of Larry Huddleston, Brent Woolley,and Sam Tabler, USDA-ARS, Booneville, Ark., is gratefullyacknowledged.

Literature Cited

Aiken, G. E., et al. 2004. Prof. Anim. Sci. 20:246.Flores, R., et al. 2005. Proc. West. Sec. Am. Soc. Anim. Sci. 56:240.Looper, M. L., et al. 2002. Prof. Anim. Sci. 18:120.Miller, L. R., et al. 2004. Proc. West. Sec. Am. Soc. Anim. Sci. 55:163.Schröder, U. J., and R. Staufenbiel. 2006. J. Dairy Sci. 89:1.Wagner, J. J., et al. 1988. J. Anim. Sci. 66:603.


15

Table 1. Concentrations of maternal lactate dehydrogenase (LDH) activity (forward and reverse) ranked (mean ± 1 SD) into one of three categories.

Category n LDH activity (IU/mL) LDH forward Low 9 592 ± 66

Medium 66 741 ± 56 High 13 920 ± 41

LDH reverse Low 17 164 ± 13 Medium 56 231 ± 27 High 15 327 ± 21

Table 2. Canonical correlations of prepartum cow traits (Set 1) with subsequent calf performance traits (Set 2) (Analysis 3).

Set 1 (cow traits)a V1 V2

LMA 0.67 0.74 LDHr -0.66 0.76

Set 2 (calf traits) W1 W2205-day WW 0.97 0.23 CALFHH 0.73 -0.68

Canonical correlation 0.38* 0.18

*P < 0.01

aLMA is longissimus muscle area; LDHr is lactate dehydrogenase reverse activity; 205-day WW is 205-d weaning weight of

calves; and CALFHH is hip height of calves at weaning.

0

100

200

300

400

500

600

700

Low LDHr Medium LDHr High LDHr

205-

dW

W,l

bin

aa

b

05

101520253035404550

Low LDHr Medium LDHr High LDHr

Hip

heig

ht,i

nche

sin

a bb

Fig. 1. Influence of maternal reverse lactate dehydrogenase (LDHr) activity on 205-day weaning weight (205-d WW) of Angus-sired calves (a,bP = 0.03).

Fig. 2. Influence of maternal reverse lactate dehydrogenase (LDHr) activity on hip height at weaning of Angus-sired calves (a,bP = 0.001).

16

Introduction

Morbidity in receiving cattle is a costly economic problem thatmay, in part, be addressed by nutritional intervention. Previousresearch indicates that not only are there medication costs associat-ed with morbid cattle, but that these cattle usually grow slowerthroughout the feedlot phase, are less efficient in converting feed togain, and their carcasses grade lower after slaughter. Thus, improv-ing health and growth during the receiving period is of interest.Trace minerals are some of the nutrients that impact immune func-tion; therefore, the objective of this study was to compare twosources of zinc, copper, manganese, and cobalt in backgroundingdiets for cattle.


Two hundred and eighty-eight male calves (77 steers and 211bulls) initially averaging 527 lb were obtained from sale barns insouth-central Arkansas or eastern Oklahoma and shipped to theUniversity of Arkansas Beef Cattle Facility at Savoy. Calves arrivedin 3 sets with arrival dates of January 10 (n = 96), January 31 (n =98), and March 8, 2006 (n = 94). Upon arrival, calves were ear-tagged with an individual identification number, weighed, and keptin a common pen with access to hay and water overnight. The fol-lowing morning, calves were given viral (BoviShield Gold 5, Pfizer,New York, N.Y.) and clostridial (Covexin 8, Schering-Plough,Branchburg, N.J.) vaccinations, and were dewormed (Cydectin,Fort Dodge, Madison, N.J.). Bulls were castrated by banding(California Bander, Inosol Co. LLC, El Centro, Calif.), and hornedanimals had their horns tipped. All calves were branded andweighed.

Within each set of calves, calves were allocated randomly with-in 4 weight blocks (using the arrival weight) to pen (2 pens/weightblock; 11 to 13 calves/pen). Pens within block were randomlyassigned to treatment. Calves were housed on 1.1-acre grass pad-docks. All calves were fed grain supplements (Tables 1, 2, and 3)that served as the carrier of each of the 2 treatments. Treatmentsconsisted of supplemental zinc (360 mg/d), copper (125 mg/d),manganese (200 mg/d), and cobalt (12 mg/d) from inorganic ororganic (Availa-4, Zinpro Corp. Eden Prairie, Minn.) sources.Calves were offered 2 lb supplement on the first day. There were 2supplements (one/dietary treatment) formulated for feeding at the2 lb/d rate. When the majority of the calves in each pen were con-suming the supplement, the pen was switched to supplements withthe appropriate mineral treatment that were formulated for feedingat the 3 lb/d rate (d 7, Set 1; d 6, Set 2; d 5, Set 3), and then the 4lb/d rate (d 14, Set 1; d 9, Sets 2 and 3), with the calves receivingthese supplements for the remainder of the 42-d trial. Calves had adlibitum access to bermudagrass hay (10.1% CP, DM basis). Samplesof supplements and the hay were analyzed for DM, CP by totalcombustion, and trace minerals by inductively coupled plasmaspectroscopy (ICP) after wet ashing (Table 3). Booster vaccinationswere given on d 14.

Calves were observed daily for signs of morbidity beginningthe day after processing. Calves were scored by one of the pencheckers and given a clinical illness score of 1 to 5 (Table 4). Calveswith a score > 1 were brought to the chute and a rectal temperaturewas taken. If the rectal temperature was ≥ 104°F, the calf was treat-ed according to a preplanned antibiotic regimen (Table 5). Recordswere kept of all antibiotics given. Sick animals were returned totheir home pen for convalescence.

Weights were taken initially and prior to supplement feedingon d 7, 14, 28, 41, and 42. Average daily gain was calculated, based

1 Department of Animal Science, Fayetteville2 Zinpro Corp., Eden Prairie, Minn.

Story in Brief

Male beef calves (n = 288, avg BW 527 lb) were obtained from sale barns. Within each set (n = 3), calves were allocated ran-domly within 4 weight blocks to pen (2 pens/ block; 11 to 13 calves/pen). Pens within block were randomly assigned to treatment.During the 42-d backgrounding period, calves were on 1.1-acre paddocks, had ad libitum access to bermudagrass hay, and werefed corn-soybean meal supplements that served as the carrier for treatments. Treatments consisted of supplemental zinc (360mg/d), copper (125 mg/d), manganese (200 mg/d), and cobalt (12 mg/d) from inorganic (zinc sulfate, manganese sulfate, coppersulfate, and cobalt carbonate) or organic (zinc amino acid complex, manganese amino acid complex, copper amino acid complex,and cobalt glucoheptonate; Availa®4, Zinpro Corp., Eden Prairie, Minn.) sources. Calves supplemented with organic trace miner-al sources had a greater final weight (598 vs. 588 lb for organic and inorganic, respectively; P = 0.04) and ADG (1.7 vs. 1.5 lb/d fororganic and inorganic, respectively; P = 0.04) than calves supplemented with trace minerals from inorganic sources.Supplementation with organic trace minerals tended (P = 0.09) to reduce the percentage of calves that received a second antibiot-ic treatment. When calves that had initial antibodies to infectious bovine rhinotracheitis virus (IBRV) were removed, there was aneffect of dietary treatment (P = 0.03) in the naïve calves. Calves supplemented with inorganic trace minerals had a greater anti-body response to IBRV vaccination. Organic trace mineral supplementation improved growth performance of shipping stressedcalves compared to those fed equivalent levels of inorganic sources.

Supplemental Trace Minerals (Zn, Cu, Mn, And Co) as Availa®4 or Inorganic Sources for Shipping-Stressed Cattle

M.R. Pass1, E.B. Kegley1, and C.K. Larson2


17

on averages of initial and final weights that were taken on consecu-tive days; and any feed refusals were noted. Calves were bled on d 0,14, and 41. Plasma from d 0 and 41 was analyzed for zinc and cop-per by ICP. Serum from d 0, 14, and 41 was analyzed for antibodytiters for infectious bovine rhinotracheitis virus (IBRV), parain-fluenza virus 3 (PI3), bovine respiratory syncytial virus (BRSV), andbovine viral diarrhea (BVD) at the Oklahoma Animal DiseaseDiagnostic Laboratory (Oklahoma State University, Stillwater, Okla.).

Growth performance, medication costs and number of treat-ments/calf were analyzed using MIXED procedures of SAS (SASInstitute, Inc., Cary, N.C.) as a randomized complete block design.The model included treatment as a fixed effect, and set of calves,and BW block as random effects. Plasma trace mineral concentra-tions and antibody titer responses were analyzed using a repeatedstatement and the covariance structure SP (POW); the subject ofthe repeated statement was pen within set of calves. The modelincluded set, block, treatment, day, and the day by treatment inter-action. Pen was used as the experimental unit for these analyses.Morbidity data (whether calves were treated one, two, or threetimes with antibiotics) were analyzed using Chi-square analyseswith calf as the experimental unit. The LIFETEST procedure wasalso used to compare when calves received their first, second, third,or last antibiotic treatment; with calf as the experimental unit.


Calves supplemented during the receiving period with organ-ic sources of trace minerals had a 10 lb greater final weight (P =0.04) and 0.24 lb greater ADG than calves supplemented with thesame levels of trace minerals from inorganic sources (Table 6).

Sixty three percent of these sale barn calves were treated forbovine respiratory disease, and there was no effect (P = 0.46) ofsupplemental trace mineral source on the percentage of calves thathad to be treated with an initial antibiotic (Table 7). However, sup-plementation with organic trace minerals tended (P = 0.09) toreduce the percentage of calves that received a second antibiotic forbovine respiratory disease. Numerically, 5 calves that were supple-mented with inorganic trace minerals were deemed “chronics” ver-sus 2 calves that were supplemented with organic trace minerals.Cattle considered “chronics” were those that did not show improve-ment after receiving the 3 antibiotic treatments. Supplemental tracemineral source did not affect (P ≥ 0.67) the average number ofantibiotic treatments or the medication costs (Table 7). The day ofthe study that the first or third antibiotic treatment was given wasnot impacted by supplemental trace mineral source (Table 8 andFig. 1). However, calves supplemented with organic trace mineralstended (P = 0.08) to receive the second treatment 1 d later thancalves supplemented with inorganic trace minerals.

Antibody response to vaccination was compared in all calves,and was also compared in the subpopulation of calves that did nothave detectable antibodies to the virus of interest on d 0 (naïvecalves). The size of this subpopulation varied by virus (BRSV, n =166; BVD, n = 207; IBR, n = 262; and PI3, n = 95). There was aneffect (P < 0.001) of sampling day in all models; calves did produceantibodies in response to vaccination. There was no effect (P ≥0.12) of dietary treatment or a dietary treatment by sampling dayinteraction on BRSV, BVD, or PI3. A dietary treatment by samplingday interaction for IBRV was detected when all calves were consid-ered (P = 0.05); calves supplemented with inorganic trace mineralshad greater antibody titers to IBRV on d 14 (P = 0.09) and d 41 (P= 0.07) than calves supplemented with organic trace minerals.When calves that initially had antibodies to IBRV were removed,there was a main effect of treatment (P = 0.03) and a tendency fora treatment by sampling day interaction (P = 0.06). Calves supple-mented with inorganic trace minerals had a greater antibodyresponse to IBRV vaccination on d 14 (P = 0.02) and 41 (P = 0.01)than those supplemented with organic trace minerals.

There was no effect (P ≥ 0.24) of supplemental trace mineralsource on the plasma concentrations of zinc or copper (Table 9).Plasma zinc concentrations were increased (P = 0.02) on d 41 com-pared to d 0.

Implications

Supplementation with organic sources of trace mineralsimproved growth performance of shipping stressed cattle for theinitial 42 d as compared to equivalent levels of inorganic sources ofzinc, copper, manganese, and cobalt.

Acknowledgments

The authors wish to express their appreciation to ZinproCorp., Eden Prairie, Minn., for funding this project. P. Hornsby, G.Carte, and S. Behrends are greatly appreciated for their assistancewith this research and care of the cattle.

18


aVitamin ADE premix contains 4,000,000 IU vitamin A, 800,000 IU vitamin D, and 500 IU vitamin E/lb. bVitamin E premix contains 20,000 IU/lb. cTo provide 160 mg monensin/d when supplement fed at 4 lb/d.

Table 1. Ingredient composition of grain supplements. Fed at 2 lb/d Fed at 3 lb/d Fed at 4 lb/d

Ingredient Inorganic Organic Inorganic Organic Inorganic Organic Corn-cracked, % 56.3 56.3 68.9 68.9 75 75 Soybean meal, % 34 34 23.2 23.2 18 18 Molasses, % 2 2 2 2 2 2 Fat, yellow grease, % 1 1 1 1 1 1 Dicalcium phosphate, % 0.9 0.9 0.4 0.4 0.18 0.18 Limestone, % 2.4 2.4 2 2 1.8 1.8 Salt, white, % 2 2 1.5 1.5 1 1 Availa-4, g/ton - 6,982 - 4,667 - 3,500 Zinc sulfate (35.5% Zn), g/ton 1011 - 676 - 507 - Manganese sulfate (32% Mn), g/ton 623.5 - 416.7 - 312.5 - Copper sulfate (25.2% Cu), g/ton 494.7 - 330.7 - 248 - Cobalt carbonate (46% Co), g/ton 25.9 - 17.4 - 13 - Sodium selenite (0.99% Se), g/ton 100.8 100.8 67.3 67.3 50.5 50.5

Vitamin ADE premixa, % 0.2 0.2 0.14 0.14 0.1 0.1 Vitamin E premix b, % 0.1 0.1 0.07 0.07 0.05 0.05 Rumensin mixc, % 0.8 0.8 0.54 0.54 0.4 0.4

Table 2. Calculated nutrient composition of supplements, DM basis. Fed at 2 lb/d Fed at 3 lb/d Fed at 4 lb/d

Nutrient Unit Inorganic Organic Inorganic Organic Inorganic Organic CP % 24.2 24.2 19.4 19.4 17.1 17.1 NEm Mcal/100 lb 95.8 95.8 97.9 97.9 99.2 99.2 NEg Mcal/100 lb 63.8 63.8 64.7 64.7 65.4 65.4 Ca % 1.4 1.4 1.1 1.1 0.9 0.9 P % 0.6 0.6 0.45 0.45 0.39 0.39 Zn mg/d 360 360 360 361 360 360 Mn mg/d 200 200 200 200 200 200 Cu mg/d 125 125 125 125 125 125 Co mg/d 12 12 12 12 12 12 Se mg/d 1 1 1 1 1 1

Table 3. Analyzed nutrient composition of supplements, DM basis. Fed at 2 lb/d Fed at 3 lb/d Fed at 4 lb/d

Nutrient Unit Inorganic Organic Inorganic Organic Inorganic Organic DM % 93.6 94.1 90.6 91.7 91.0 91.0 CP % 23.1 23.1 18.5 18.1 16.6 17.5 Zn mg/kg 410. 438. 312. 303. 243. 259. Mn mg/kg 271. 272. 224. 182. 114. 152. Cu mg/kg 152. 166. 119. 115. 92. 93. Co mg/kg 13.2 13. 9.6 8.6 6.5 6.9


19

Table 4. Clinical illness scores for calvesa.

Score Description Appearance

1 Normal No abnormal signs noted

2 Slightly ill Mild depression, gaunt, +/- ocular/nasal discharge

3 Moderately ill Ocular/nasal discharge, gaunt, lags behind other animals in the group, coughing, labored breathing, moderate depression, +/- rough hair coat, weight loss

4 Severely ill Severe depression, labored breathing, purulent ocular/nasal discharge, not responsive to human approach

5 Moribund Near death aModified from clinical assessment score criteria provided by Dr. Dianne Hellwig, DVM.

Table 5. Treatment schedule for calves treated for BRD.

Therapy 1: Nuflor (Schering-Plough Animal Health, Branchburg, NJ), 6 mL/100 lb BW, subcutaneous in neck x Check in 48 h. If clinical illness score > time 0 score or 2 and rectal temperature is 104ºF,

then consider the treatment a failure and go to Therapy 2, otherwise consider the treatment a success.

Therapy 2: Baytril (Bayer, Shawnee, KS), 5 mL/100 lb BW subcutaneous in neck x Check in 48 h. If clinical illness score > time 0 score or 2 and rectal temperature is 104ºF,

then go to Therapy 3 (treatment failure) otherwise consider the treatment a success.x Also for animals that recovered from Therapy 1 and relapsed at a later date.

Therapy 3: Excede (Pfizer, New York, NY), 1.5 mL/100 lb BW subcutaneous in back of ear x Check on fourth day. If clinical illness score > time 0 score or 2 and rectal temperature is

104ºF, then this is a treatment failure and the calf is identified as a “chronic”, otherwise consider the treatment a success.

x Also for animals that recovered from therapy 2 and relapsed at a later date.

If bovine respiratory disease symptoms occur > 21 d after administering the previous therapy, then considered a new episode andbegin again with Therapy 1.

20


A B

C

Fig. 1. Curves generated with the LIFETEST procedure of SAS for day the calves received their first (A); second (B), P = 0.08; and third (C) antibiotic treatments.


21

012345678

0 14 28 42

Time, d

BV

D,l

ogof

Ab

titer

0

1

2

3

4

5

6

0 14 28 42

Time, d

BR

SV

,log

Ab

titer

InorganicOrganicNaïve -- InorganicNaïve -- Organic

012345678

0 14 28 42

Time, d

PI3

,log

Ab

tite r

-0.50

0.51

1.52

2.53

3.5

0 14 28 42

Time, d

IBR

,log

Ab

titer

A B

C D

Fig. 2. Response to vaccination with modified live vaccine for respiratory viruses, (A) antibodies to bovine respi-ratory syncytial virus (BRSV); (B) antibodies to bovine viral diarrhea (BVD); (C) antibodies to infectious bovinerhinotracheitis virus (IBRV), all calves in model – treatment x day interaction P = 0.05, naïve calves in model –

treatment P = 0.03 and treatment x day interaction P= 0.06; and (D) antibodies to parainfluenza type 3 (PI3).

Introduction

The University of Arkansas Cooperative Extension ServiceSteer Feedout Program provides cow-calf producers the opportuni-ty to acquire information about post-weaning performance andcarcass characteristics of their calves. It also points out factors thatinfluence value beyond the weaned calf phase of beef production.The program is not a contest to compare breeds or breeders or topromote retained ownership. The Feedout Program creates anopportunity for producers to determine how their calf crop fits theneeds of the beef industry. The program also provides the informa-tion needed to determine if changes in genetics and/or manage-ment factors are warranted for producers to be competitive in beefproduction.


On November 10, 2005, 139 steer calves from 16 Arkansas pro-ducers representing 11 counties were placed on feed at WheelerBrothers Feedyard in Watonga, Oklahoma. Producers wererequired to administer 5-way modified live vaccinations to allcalves and were encouraged to precondition the calves for a mini-mum of 30 days prior to shipment. Calves were weighed andprocessed on November 11, 2005. Processing included weight col-lection, deworming, implanting with a growth implant, and eartagging with a feedlot lot tag. All calves were placed in one pen.Management factors such as processing, medical treatments andrations were the same as the other cattle in the feedyard. This wasthe first year that electronic ear tags (EID) were used in the pro-gram. The EID tags helped the feedyard and Extension personnelmanage individual animal medicine costs and weights. The feed-yard manager and Extension personnel selected animals for each ofthe 3 harvest groups when they reached the weight and conditionregarded as acceptable for the industry and market conditions.Cattle were sold on a carcass basis with premiums and discounts forvarious quality grades, yield grades and carcass weights. Feed, pro-cessing and medicine costs were financed by the feedyard. Allexpenses were deducted from the carcass income, and proceedswere sent to the owners. Of the 139 steers that started on feed in thefall, one died (0.99% death loss). One calf suffered from severe

bloat, and was sold to a local packing plant where its carcass wascondemned. These 2 calves were not included in the statisticalanalyses; therefore, 137 steers were used in the analyses.

Carcasses were placed in 2 groups according to industry stan-dards for carcass merit. Carcass groups were 1) fit industry stan-dards (at least USDA Choice, Yield Grade < 3.5, and hot carcassweight between 550 and 950 lb) or 2) did not fit industry standards.The main effect of carcass group and the interaction with depend-ent variables carcass value, average daily gain (ADG), and netreturn were determined using PROC GLM of SAS ( SAS Inst. Inc.,Cary, N.C.). Least-squares means were calculated with the PDIFFoption and reported.

Calves were sorted into categories based upon their feedlotreturn (income minus feedlot direct expenses). Data from calves inthe top 25% and bottom 25% were sorted out for further analysis.Factors affecting feedlot return for the top 25% and the bottom25% were determined using the Stepwise method of PROC REG ofSAS. Independent variables included initial (arrival) weight; per-centage Brahman, English, and Continental breeding; ADG; YieldGrade; Quality Grade; feed cost per pound of gain; hot carcassweight; days on feed; medicine cost; ribeye area; ribeye area per 100lb of hot carcass weight; and dressing percentage. The breeding per-centages were provided by the producer upon delivery.


The financial summary is reported in Table 1. Average grossincome per head was $1,029.17 (range = $504 to $1,315). The feed-lot return averaged $686.76; whereas, the calculated returns,accounting for the initial value of the calf at arrival, averaged$32.99 (range = $-188 to $259).

The sick pull rate was high with 80 calves (56%) treated forsickness. Still, this is a dramatic improvement over last year's 80%pull rate. The pull rate was high for cattle that were all listed asbeing preconditioned. The average medicine cost for the entire penwas $13.39 per head, $30 less than last year's average. The healthstatus of cattle in the feedyard usually has a major impact on per-formance and profit. Healthy steers had numerically higher feedlotnet returns ($703) than steers that became sick ($674) but this dif-ference was not statistically significant. No differences were noted

22

1 Animal Science Section, Cooperative Extension Service, Little Rock.

Story in Brief

The objective of the Arkansas Steer Feedout Program is to provide cow-calf producers information about the post-weaningfeedlot performance and carcass characteristics of their calves. For the 2005-2006 feedout, quality grade, initial weight, hot carcassweight, yield grade and medicine costs were all factors that affected (P < 0.05) the feedlot return over specified costs. Cow calf pro-ducers who participated in the program can use the information to evaluate how their cattle breeding programs fit the needs ofthe beef cattle industry.

Arkansas Steer Feedout Program2005-2006

B. Barham, S. Gadberry, J. Richeson, and S. Cline1

between healthy and sick steers for ADG, hot carcass weight, feedcost per pound of gain, total cost per pound of gain, dressing per-centage, yield grade, ribeye area, and ribeye area per cwt. of carcassweight (P > 0.10). Previous feedout data indicate that health status(healthy vs. sick) negatively impacts feedlot and carcass perform-ance. Given past health issues that cattle in the program have faced,Arkansas producers need to implement a sound health manage-ment plan. Arkansas producers should consult with their veterinar-ian on designing a vaccination program for their herd. By imple-menting a sound vaccination program at the ranch of origin, pre-dictability and consistency of calves increases along with productvalue, and calves have the opportunity to express their geneticpotential.

The performance of the steers in the top 25% and bottom 25%for feedlot return are shown in Table 2. The average steer arrivalweight and final weight were 609 pounds (range = 373 to 889 lb)and 1,284 pounds (1,057 to 1,528 lb), respectively. Average dailygain was 3.47 pounds and ranged from 2.17 to 4.67 pounds. Theaverage number of days on feed was 194 days, and the average totalcost of gain was $0.47. Overall, 40 percent of the steers gradedChoice, which is lower than the national average (56.8%). Onehead graded Prime, and 10 head received a premium for CertifiedAngus Beef or Angus Pride Choice. Carcass standards for the beefcattle industry are Choice quality grade, yield grade of less than 4,and hot carcass weight between 550 and 950 pounds. Thirty-fivepercent of the steers fit these industry standards. The steers thatmet the industry standards averaged $171 per head more thanthose that did not fit the industry standards (P < 0.001). They hadhigher carcass values because they graded Choice, and they werenot discounted for yield grades greater than 4.0 or for carcassesoutside the weight range. Of the steers that were in the top 25%based on feedlot net return, 94% met the industry standards, andfor those in the bottom 25% based on feedlot net return, 100% didnot meet the industry standards.

Listed below are the significant (P < 0.01) factors that affectedfeedlot net return over specified costs for steers in the 2005-2006program. Specified costs include feed, freight, insurance, process-ing, medicine, Beef Check-off dues, and interest. Factors are listedin descending order of importance.

Quality Grade - Cattle that graded Prime, Choice, Select, andNo Roll had feedlot net returns of $835, $782, $621 and $543 perhead, respectively. All feedlot net returns based on quality gradesdiffered (P < 0.001) from each other. Marbling is the primary factorthat affects a calf 's ability to grade Choice. Three main factors thataffect marbling are: (1) the genetic ability to marble; (2) the matu-rity or the physiological age, not the chronological age; and (3)ration. Some cattle breeds report marbling EPD's in their sire sum-maries. Carcass traits such as marbling are highly heritable; there-fore, selecting high marbling EPD bulls can be effective for improv-ing the marbling ability of their calves. Breed can also influence acalf 's ability to grade Choice. Calves with a high percentage ofEnglish breeding usually have an increased ability to grade Choice.

Physiological age influences frame score. Large-frame cattlemust be older (chronologically) to reach the same physiological ageto express marbling as compared to smaller-frame cattle. Steers

should be medium to large frame, and extremes at both ends of thescale (small and extremely large) should be avoided.

Initial Weight - The relationship between initial weight andfeedlot net return was negative indicating that as initial weightincreased feedlot net return decreased. This relationship is slightlymisleading though. The main reason initial weight was present as asignificant factor was due to the market at the time of harvest. Thefirst group of steers harvested received the lowest carcass price ofthe 3 harvest groups. This first harvest group of steers was largelymade up of the calves with heavier initial weight. Generally, theheavier the calf upon entrance to the feedyard the fewer days theytake to reach harvest weight. Nonetheless, in this year’s program,heavier calves were at a disadvantage due to the market. It is notrecommended to change the type and size of calf entering the feed-lot based upon this finding.

Hot Carcass Weight - The relationship between hot carcassweight and feedlot net return was positive; therefore as hot carcassweight increased, so did feedlot net return. The more carcasspounds sold, the greater the gross income and feedlot net return.Table 3 shows the relationship between hot carcass weight, totalcost of gain, average daily gain, feedlot net return, and calculatedreturn.

Factors that affect hot carcass weight include frame size, mus-cle thickness, and backfat. Muscle thickness is a major factor thatrelates to carcass weight. Thickness, depth and fullness of quarter,and width (without excessive fat) of back, loin, and rump are indi-cations of muscling.

Yield Grade - As yield grade increased from 1 to 5, feedlot netreturn changed very little ($630, $657, $714, $712, $742 per headfor yield grades 1, 2, 3, 4 and 5, respectively). There were no differ-ences (P > 0.05) between feedlot net returns for Yield Grades 1 and5, although there appeared to be a trend that the higher yield gradeshowed an increase in feedlot net return. Backfat, ribeye area, hotcarcass weight and percentage of kidney, pelvic and heart fat are thefactors that determine yield grade. As yield grade (1 to 5) increases,the amount of fat increases in relation to the amount of lean mak-ing a lower numerical yield grade more desirable.

Medicine Cost - Healthy calves outperformed sick calves. Agood preconditioning vaccination program will not guarantee ahealthy feedyard calf, but it is the best management tool available.Healthy calves had a higher feedlot net return ($703 vs. $674 perhead) than calves that were treated for illness. A higher percentageof healthy steers graded Choice than did the sick calves.

Implications

Both high and low feedlot returns are affected by calf health(medicine costs), feedlot performance factors, and carcass charac-teristics. Value based or grid marketing is increasing in use and var-ious forms of value based marketing are spreading to all levels ofthe industry. A producer’s goal should be to produce a product thatmeets the demands of all segments of the beef industry and beefconsumers – those who do this will be more competitive in the everchanging marketplace.


23

Table 1. Financial results summary, 2005-2006 Arkansas Steer Feedout Program. Item Average per head ($)a Range ($) Gross income 1,029.17 504 to 1,315 Expenses Feed 275.18 213 to 336 Freight, interest, etc. 61.43 57 to 87 Medicine 13.39 0 to 63.31Total feedlot expenses 342.41 273 to 427 Feedlot net return 686.76 484 to 912 Calf initial valueb 653.77 442 to 889 Calculated return 32.99 -188 to 259 a 137 head b An Arkansas Livestock Market News Reporter placed an arrival value on each calf bases upon arrival weight and frame and muscle scores.

24


Table 2. Performance summary of the bottom 25%, top 25% and average steers based on feedlot net return. Item Bottom 25% Top 25% Average Number of steers Gross Income per head ($) Carcass value per lb ($) Initial value per head ($) Medicine per head ($) Feed cost per head ($) Total expense per head ($) Feedlot net return per head($) Calculated return per head ($) Days on feed Feed cost per lb of gain ($) Total cost per lb of gain ($) Arrival weight (lb) Muscle scoreFrame score Percent large Percent medium Final weight (lb) Average daily gain (lb) Hot carcass weight (lb) Carcass value ($/lb) Dressing percentage Ribeye area (sq in) Backfat (in) REA per 100 lb carcass weight Quality grade Percent Prime Percent Choice Percent Select Percent No roll Yield grade

35890a

1.17a

592a

17.39c

261 a

331 a

559a

-32 a

198 0.38 0.47

543a

1.8

35% 65%

1,256a

3.36a

762a

1.17a

63.1%a

13.6 0.41c

1.77a

0%a

0%a

92%a

8%a

2.32

35 1,184b

1.36b

702b

12.17d

286b

353b

831b

128b

196 0.37 0.47

651b

1.6

42% 58%

1,390b

3.49b

867b

1.36b

65.2%b

13.8 0.58d

1.59b

3%b

91%b

6%b

0%b

2.7

137 1,029

1.25 653

13.00 272 339 686

30.59 194

0.38 0.47

609 1.7

35% 65%

1,284 3.47

825 1.24

64.3% 13.6

0.52 1.65

0.7% 40% 57%

2.2% 2.61

a,b Values within rows with unlike superscripts differ (P < 0.0001). c,d Values within rows with unlike superscripts differ (P < 0.001).

Table 3. Summary of hot carcass weight, total cost of gain, average daily gain, feedlot net return and calculated return.

Hot carcass weight (lb)

Total cost of gain ($)

ADG(lb)

Feedlot net return per head ($)

Calculated return per head ($)

600-699 0.52 2.5 545 -33 700-799 0.46 3.3 617 23800-899 0.47 3.5 703 30900-999 0.47 3.8 798 74

Introduction

Weather has a strong impact on feed intake of beef cattle.Understanding effects of environmental variables is of economicimportance because weight gain is dependent on feed intake.However, skin thickness, hair coat, rumen volume, rate of diges-tion, and metabolic efficiency differ among breeds (Kidwell andMcCormick, 1956; Dean et al., 1976), and could affect behavioralresponses among animals to environmental conditions. Conditionsto which cattle are unacclimatized can upset normal feed intakeand adversely affect performance. Duration of adverse conditionsseems important, and because effects caused by environmentalconditions are variable, feed intake in a variable environment is dif-ficult to predict (NRC, 1987). Thermal stress can markedly alterenergetic efficiency of ruminants as evidenced by effects of coldstress on energy utilization by beef cattle (Delfino and Mathison,1991). Other adverse environmental conditions (wind, precipita-tion, humidity, etc.) can accentuate effects of thermal stress.Performance and mortality of fed cattle are heavily influenced byweather conditions cattle are exposed to during feeding periods.Seasonal weather patterns contribute to seasonal intake patternsand performance of cattle. Therefore, our objective was to identifyand quantify impacts of selected environmental variables on feedintake of beef bulls during feedlot performance tests.


Feed intake data originated from bulls (n = 1,874) evaluated in52 individual 140-d University of Arkansas Cooperative Bull Testsat Fayetteville, Hope, and Monticello. On arrival at test stations,bulls were weighed, identified by tattoo or brand and ear-taggedwith a test identification number. Bulls were sorted into groups of10 according to weight, and the groups randomly assigned to exer-

cise lots. Bulls in each of the groups remained together throughoutthe test. Individual animals within groups were assigned to a feed-ing stall prior to the official test. Bulls were given a preliminary 21-d period prior to the 140-d feeding trial to lessen weaning stressand become adjusted to the new surroundings, feeding proceduresand diet. Each bull was provided with approximately 93 ft2 underroof for shade and protection from inclement weather and approx-imately 159 ft2 in an exercise lot. Lots were paved and each con-tained 10 adjacent individual feeding stalls.

Diet, Feeding and Weighing Procedures. Each bull was allowed 2h of eating time in the early morning (0800 to 1000) and 2 h in lateafternoon (1500 to 1700). Individual intake was measured byweighing feed and orts each day. A total mixed ration preparedcommercially from the same formula was fed each year at eachlocation. As formulated, the diet contained 0.8 Mcal NEm, 0.5 Mcal

NEg and 12% CP per lb DM. When not in feeding stalls, bulls had

access to fresh water and commercial mineral mixture containingcalcium, phosphorus and trace-mineralized salt. Weights weretaken at the beginning of each test and at 28-d intervals. All weightswere partially shrunk because calves were weighed immediatelybefore the morning feeding and had not been allowed access towater since the evening feeding of the previous day.

Photoperiod and Weather Data. Photoperiod information wasobtained from sunrise/sunset tables (U.S. Naval Observatory,Washington, D.C.). Weather data for the period Jan. 1977 to Dec.1990 were obtained from the National Climatic Data Center(Asheville, N.C.). Nine environmental variables and 3 productterms were in the initial data set but this number was carefullyreduced to 6 environmental variables in the final analysis. Weathervariables used in the final analysis included: maximum tempera-ture, day length, rainfall, relative humidity, barometric pressure,and wind speed. The arithmetic mean intake and mean environ-mental variables by location of test and period of test are present-ed in Table 1.

1 Department of Animal Science, Fayetteville2 Agricultural Statistics Lab, Fayetteville3 Department of Biological and Agricultural Engineering, Fayetteville

Story in Brief

Weather data were analyzed to identify and quantify effects on feed intake of performance-tested beef bulls. Feed intake dataoriginated from bulls (n = 1,874) in University of Arkansas Cooperative Bull Tests at Fayetteville, Hope, and Monticello during 52trials. Bulls were given a 21-d adjustment period then individually full-fed a total mixed ration twice daily in the same stall for 140d. Photoperiod and climate data were obtained from U.S. Naval Observatory (Washington, D.C.) and National Climatic DataCenter (Asheville, N.C.), respectively. Data were pooled, divided into five 28-d periods with each period analyzed separately usingall animals over all tests. Principal component (PC) analysis was used to reduce number of independent variables in the regressionand overcome collinearity associated with numerous weather variables. Feed intake was influenced by 5 PC representing 6 climatevariables (maximum temperature, day length, rainfall, relative humidity, barometric pressure and wind speed) throughout thestudy. Coefficients for environmental factors ranged from positive to negative during various study periods. No single environ-mental variable had a consistent effect throughout all 5 periods. Results indicated numerous environmental variables influencefeed intake and that effects of individual variables may vary as feeding period progresses, making consistently accurate predictionsdifficult.

Regression of Feed Intake on Selected Environmental Factors for Beef Bulls During Post-Weaning Feedlot Performance Tests

G.T. Tabler, Jr.1, A.H. Brown, Jr.1, E.E. Gbur, Jr.2, I.L. Berry3, Z.B. Johnson1 D.W. Kellogg1, and K.C. Thompson2

25

26


Statistical Analysis. Feed intake data from 52 feedlot perform-ance tests at three Arkansas locations over 13 yr were pooled anddivided into five 28-d periods beginning with the start of each test,with each period analyzed separately, using all animals over all tests.Because each location used different start dates, the 28-d periodswere different calendar dates corresponding to the weigh dates ofanimals. Average starting test dates were Nov 19 at Fayetteville, Nov5 at Monticello, and at Hope, Feb 3 (Hope 1) and Aug 18 (Hope 2).Statistical analyses were performed using SAS Version 8.2 (SASInstitute, Inc., Cary, N.C.).

Distribution of bulls by breed and location of test is presentedin Table 2. Because weather variables tended to be highly collinear,regression of feed intake on them would be problematic. To avoidthese issues, principal components (PCs) were calculated from thestandardized original variables. Each PC is a linear combination ofthe original set of independent variables. There are as many PC asthere are original variables. As a group, they account for all of thevariation in the original variables and are mutually independent.Because some PC will explain only a small percentage of the varia-tion, these PC can be eliminated from the analysis without signifi-cant loss of information, thereby reducing the dimensionality ofthe problem. As a result, 5 PC remained after initial elimination.Each PC was interpreted by considering only those variables whosecoefficients were sufficiently large in magnitude relative to thelargest absolute value of all coefficients in that PC. All interpretedcoefficients (eigenvectors) had a magnitude of at least 0.35. Sixweather variables were dominant influences based on eigenvectorsof the linear equation for each PC.

Principal component 1 (Table 3) was associated with maxi-mum temperature and day length in all 5 feeding periods and wassignificant (P < 0.001) in periods 2 through 5. For PC 2, significant(P ≤ 0.002) in periods 1, 4, and 5, rainfall was prominent in periods1, 2, and 4 while relative humidity appeared in periods 1, 2, 3, and5, with barometric pressure also prominent in period 3. Principalcomponent 3 was significant (P = 0.002) in period 3 and associat-ed with rainfall and relative humidity. Principal component 4 wassignificant (P < 0.001) in periods 1, 4 and 5 and associated withrainfall, and additionally in period 5, relative humidity. The fifthPC was significant (P ≤ 0.012) and associated with wind speed inperiods 2 and 3. Finally, using the PLS procedure of SAS, feedintake was regressed on the initial set of 6 environmental variables(maximum temperature, day length, rainfall, relative humidity,barometric pressure, and wind speed) not eliminated by PC analy-sis. These regression coefficients are reported and discussed.


Coefficients of regression from PROC PLS for the effects ofmaximum temperature, day length, rainfall, relative humidity,barometric pressure, and wind speed on feed intake of individual-ly fed beef bulls in feedlot performance tests are presented in Table4. None of the 6 selected weather variables had a consistently posi-tive or negative effect on feed intake across all 5 periods. The coef-ficients of regression for maximum temperature on feed intake inperiods 1 through 5 were -5.86, -8.11, -23.13, 24.49, and -5.55,respectively. The negative coefficients indicate that as temperatureincreased in periods 1, 2, 3, and 5, feed intake decreased. In con-trast, a positive coefficient in period 4 indicates that, as temperatureincreased, feed intake also increased during this period.

Regression coefficients for the effects of day length on feedintake were -0.80, 52.15, 3.71, -26.55, and -2.61 in periods 1through 5, respectively. Negative coefficients in periods 1, 4, and 5indicate that feed intake decreased as day length increased in theseperiods; while in periods 2 and 3, positive coefficients indicate feedintake increased as day length increased.

Coefficients of regression for the effects of rainfall on feedintake were -8.14, 0.77, -3.02, -0.98, and -1.26 for periods 1 through5, respectively. Similar to maximum temperature, rainfall displayednegative coefficients in 4 of 5 periods. Negative coefficients indicatethat feed intake decreased as rainfall increased in periods 1, 3, 4,and 5. In contrast, a positive coefficient in period 2 indicates feedintake increased as rainfall increased.

Relative humidity and barometric pressure each displayedpositive coefficients in 4 of 5 periods and a negative coefficient in 1period. Regression coefficients for the effects of relative humidityon feed intake were 13.57, 162.95, -9.39, 150.28, and 3.42 for peri-ods 1 through 5, respectively. Positive coefficients in periods 1, 2, 4,and 5 indicate that, as relative humidity increased, feed intakeincreased. In contrast, during period 3, a negative coefficient indi-cates that feed intake decreased as relative humidity increased.

Coefficients of regression for the effects of barometric pressureon feed intake in periods 1 through 5 were: -2.73, 19.20, 4.20, 34.98,and 31.49, respectively. Similar to relative humidity, positive coeffi-cients in four periods (periods 2 through 5) indicate feed intakeincreased as barometric pressure increased. However, during peri-od 1, feed intake decreased as barometric pressure increased as evi-denced by a negative coefficient.

Regression coefficients for the effects of wind speed on feedintake were 8.30, 4.27, 0.62, -0.69, and -2.43 for periods 1 through5, respec

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