STUDIES ON THE FEASIBILITY OF PREDICTING FEEDLOT PERFORMANCE FROM CERTAIN LABORATORY GRAIN ANALYSES

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University f Nebraska - Lincln DigitalCmmns@University f Nebraska - Lincln Faculty Papers and Publicatins in Animal Science Animal Science Department January 1978 STUDIES ON THE FEASIBILITY OF

1 University f Nebraska - Lincln DigitalCmmns@University f Nebraska - Lincln Faculty Papers and Publicatins in Animal Science Animal Science Department January 1978 STUDIES ON THE FEASIBILITY OF PREDICTING FEEDLOT PERFORMANCE FROM CERTAIN LABORATORY GRAIN ANALYSES M. L. Galyean Oklahma State University, Stillwater D. G. Wagner Oklahma State University, Stillwater R. K. Jhnsn University f Nebraska-Lincln, rjhnsn5@unl.edu Fllw this and additinal wrks at: Part f the Animal Sciences Cmmns Galyean, M. L.; Wagner, D. G.; and Jhnsn, R. K., "STUDIES ON THE FEASIBILITY OF PREDICTING FEEDLOT PERFORMANCE FROM CERTAIN LABORATORY GRAIN ANALYSES" (1978). Faculty Papers and Publicatins in Animal Science This Article is brught t yu fr free and pen access by the Animal Science Department at DigitalCmmns@University f Nebraska - Lincln. It has been accepted fr inclusin in Faculty Papers and Publicatins in Animal Science by an authrized administratr f DigitalCmmns@University f Nebraska - Lincln.

2 STUDIES ON THE FEASIBILITY OF PREDICTING FEEDLOT PERFORMANCE FROM CERTAIN LABORATORY GRAIN ANALYSES I,2 M. L. Galyean 3, D. G. Wagner and R. K. Jhnsn Oklahma State University 4, Stillwater SUMMARY Data frm 14 cattle feeding trials were utilized t study the relatinship between several labratry analyses and animal feed intake (INTAKE), gain (ADG) and feed efficiency (F/G). Labratry analyses cnsidered were 6, 12 and 24 hr in vitr dry matter disappearance (IV6, IV12, IV24, respectively); in vitr gas prductin in 1 hr and 6 hr (GP1 and GP6, respectively); and degree f gelatinizatin (GEL). A multiple regressin equatin with variables fr treatment and trial classificatin, initial weight and the quadratic effect f initial weight was fit t the data. The effect f initial weight was significant fr all three perfrmance variables, and the quadratic effect was significant fr ADG and F/G. A secnd mdel was fit excluding the treatment classificatin, and the maximum R 2 prcedure was utilized t examine hw well labratry analyses accunted fr variatin amng residuals frm this secnd mdel. Mre variatin was accunted fr in the dependent variables F/G (34.96%) and INTAKE (17.81%) than ADG (5.16%) when a cmbinatin f all labratry analyses except GEL was included in the mdel. Mrever, crrelatins between residuals f the secnd mdel and the labratry analyses were higher fr INTAKE and F/G than ADG and were all negative fr INTAKE and F/G, suggesting a negative respnse in intake and an imprved F/G rati as starch alteratin increases. Crrelatins between the labratry analyses were generally quite high. This study suggests that n single labratry analysis cn- t Jurnal Article 3282 f the Agricultural Experiment Statin, Oklahma State University, Stillwater The assistance f Drs. M. A. Brwn and L. D. Yung in statistical analyses is greatly appreciated. 3Department f Animal and Range Science, New Mexic State University. 4 Animal Science Department. sidered wuld be useful fr the develpment f accurate, reliable equatins fr the predictin f feedlt perfrmance, and cmbinatins appear t have value nly in the case f FIG and INTAKE. (Key WOrds: Multiple Regressin, Feedlt Perfrmance, Grain AnalySes, Beef Cattle.) INTRODUCTION Numerus studies invlving the feeding value f prcessed grains in high energy diets fr finishing cattle have included labratry evaluatins f the grain. While it appears that labratry evaluatins such as in vitr gas prductin and degree f gelatinizatln yield valuable infrmatin with respect t the effect f prcessing n the starch fractin Of the grain, little infrmatin exists n the relatinship between labratry analyses f grain and animal perfrmance. Albin et al. (1966) cmpared in vitr dry matter digestibility (IVDMD) f all cncentrate diets with perfrmance f feedlt steers receiving the same diets. Crrelatin cefficients f.88 and.99 were btained between IVDMD and feedlt gain and efficiency, respectively. Klett and Ralsn (1967) bserved significant crrelatins between 12 and 24 hr IVDMD and in vitr digestin f ether extract, dry matter, energy and crude fiber. Kumen et al. (1967) evaluated diets cntaining cncentrates in varying prprtins up t 75% f the ttal diet by a 48 hr IVDMD technique and simultaneus in viv ttal tract evaluatin in sheep. The crrelatin between IVDMD and in viv DMD (.85) was highly significant. Trei et al. (1970) cmpared in vitr gas prductin by rumen micrrganisms and IVDMD in prcessed grains. A crrelatin cefficient f.95 was fund between gas prductin and IVDMD. In this study, multiple regressin and crrelatin analyses invlving data frm 14 feedlt trials were used in an effrt t further investigate the relatinship between animal perfrm- JOURNAL OF ANIMAL science, Vl. 46, N. 1 (1978)

3 10 GALYEAN, WAGNER AND JOHNSON ance and labratry analyses f prcessed grains. Crrelatins between the varius labratry analyses were als investigated9 EXPERIMENTAL PROCEDURES Data frm 14 cattle feeding trials invlving the evaluatin f prcessed grain were utilized t study the relatinship between several labratry analyses f grains and the feed intake (INTAKE), average daily gain (ADG) and feed efficiency (F/G) f cattle receiving the same grains. INTAKE, ADG and F/G were all expressed as pen averages. The grains, prcessing -< methds and ther variables invlved in the 14 trials are shwn in table 1. Labratry analyses f the grains cnsidered in this study were ttal in vitr dry matter disappearance after 6, 12 and 24 hr (IV6, IV12 and IV24, respectively) ua incubatin perids;in vitr gas prductin after ~. 1 hr and 6 hr (GP1 and GP6, respectively) and ~ < degree f gelatinizatin (GEL). Methds f labratry analyses have been reprted previ- Z~ usly by Crka and Wagner (1975b). Labra- ~ try data were cllected ver a number f years O ~a by different individuals using the same prce- ~ < dures at ne lcatin9 References regarding the ~ data fr the 14 feeding trials are as fllws:,~ ~ m Aimne (1975), Aimne and Wagner (1977a,b), ~ Z Crka and Wagner (1975a,b,c), Christiansen ~ and Wagner (1974a,b), Martin (1973), and Z >, Schneider, (1971). ~ O One hundred and sixty-tw pens f cattle Z varying frm three t five animals per pen were m used in this study. Infrmatin n GEL was available fr nly 72 pens. One hundred and thirty pens had infrmatin pertaining t IV6, IV12, GP1 and GP6. All pens had data available fr IV24. In an effrt t remve as much variatin as D pssible due t such factrs as trial differences and pen differences in initial weight n test, measures f feedlt perfrmance were first subjected t a regressin analysis where the fllwing mdel was fit: Y = /JO + O/i + IW~l + IW2~32 + e mmm mmmmm m~ NN ~ OOOO ~,~ ~ N Where: Y -- INTAKE (kg), ADG (kg) r F/G /30 = y intercept a i = Treatment-trial classificatin variable, i = 1, 2,..., 45 (14 trials, 45 ttal treatments) IW = Initial weight n test in kg "Ts = IW.7 s kg, - ~ O O

4 PREDICTING FEEDLOT PERFORMANCE 11 I I I I O.9 v v v v ~ v v v v v v v.9 Z ~ ~ ~ ~ ~,q. 0. tt~ tt~ ~ ~ ~ ~ ~ "~'x~ u u "~ ~ ~ ~ ~ ~ ~ 9 c? 0J

12 GALYEAN, WAGNER AND JOHNSON IW 2 = Quadratic effect f IW -75 = 75 2 kg (IW'kg) fll,f12 ---- Partial regressin cefficients e - Randm errrs The treatment-trial classificatin variable (ai) served t

5 12 GALYEAN, WAGNER AND JOHNSON IW 2 = Quadratic effect f IW -75 = 75 2 kg (IW'kg) fll,f Partial regressin cefficients e - Randm errrs The treatment-trial classificatin variable (ai) served t accunt fr variatin in trials due t grains, prcessing methd, sex, length f trial, et cetera. Of interest was the effect that differences in initial weight (IW) n test had n measures f perfrmance. Pen average initial weights ranged frm 172 t 342 kg which crrespnds t 47.4 and 79.4 kg.75, respectively. Imprtance f the treatment-trial classificatin variable, initial weight and the quadratic effect f initial weight was verified with the mdel abve fr INTAKE, ADG and F/G. The treatment classificatin was then eliminated frm the mdel resulting in a secnd mdel with a trial classificatin (T i, i = 1, 2,..., 14), IW and IW 2 as fllws: Where: Y=/3 +T i+ IW/31 + IW2132 +c Y = INTAKE (kg), ADG (kg) r F/G fl = Y intercept T i = Trial classificatin variable, i = 1, 2,.,., 14 IW = Initial weight n test in kg'~ = IW 2 = Quadratic effect f IW "Ts -- kg 2 ~1, ~2 = Partial regressin cefficients e = Randm errrs Thus, this secnd mdel differs frm the first ne nly in that T i represents the trial classificatin variable; whereas, 0q represented the trial and treatment classificatin variable in the first mdel. The data were subjected t multiple regressin prcedures t determine hw well labratry analyses f grain wuld substitute fr the treatment classificatin variable in predicting perfrmance fr INTAKE, ADG and F/G. These are referred t as predicted values. This was accmplished by fitting the data t the secnd mdel and using the maximum R 2 prcedure (Service, 1972) with labratry analyses as independent variables and INTAKE, ADG and F/G residuals as dependent variables. The maximum R 2 prcedure lks fr the "best" ne variable mdel, the "best" tw variable mdel and s frth. It first finds the ne variable mdel prducing the highest R 2 statistic. It then adds the next variable which wuld yield the greatest increase in R 2. Each f the variables in the mdel is cmpared t each variable nt in the mdel. The prcedure determines if remving the variable in the mdel and replacing it with the presently excluded variable wuld result in an increased R 2. After all cmparisns are made, the switch which prduces the greatest increase in R 2 is made. Cmparisns are made again, and the prcedure cntinues until it finds n switch which will increase R 2. This is cnsidered the "best" tw-variable mdel. A third variable is added, and the prcess cntinues. Residuals (the differences between predicted and bserved values) were btained fr the mdel including Ti, IW and IW 2, and crrelatins between the residuals and the varius labratry analyses were btained. Crrelatins btained in this manner, therefre, represented crrelatins between adjusted dependent variables and labratry analyses f the grains. RESULTS AND DISCUSSION Relatinships between Initial Weight and PerJbrmance. Multiple regressin equatins with INTAKE, ADG and F/G as dependent variables and treatment-trial classificatin (ai), IW and IW 2 as independent variables are shwn in table 2. These equatins are based n all 162 pens f cattle. It shuld be pinted ut that thse equatins are nt designed as predictin equatins since slpe and intercept cefficients may vary amng treatment-trial classificatins. Rather, the equatins describe the average respnse bserved ver all pens f cattle. The equatin fr the dependent variable INTAKE suggests that as IW (recall this is n metablic bdy weight basis) increases IN- TAKE increases in an apparent linear fashin. The regressin f INTAKE n IW, IW 2 and 0q accunted fr 91.38% f the variatin bserved in INTAKE in these data. Hwever, the R 2 f the simple linear regressin mdel with a i (treatment-trial classificatin variable) alne was 89.47%, indicating its imprtance relative t the initial weight cmpnents. The effect f IW after adjusting fr a i was significant, hwever (P(.0001). As bserved with INTAKE, ADG (table 2) increased with increasing IW; hwever, the quadratic effect f initial weight (IW 2) was significant (P<~.0109) after adjustment fr a i and IW. This suggests that cattle f

6 PREDICTING FEEDLOT PERFORMANCE 13 TABLE 2. MULTIPLE REGRESSION EQUATIONS FOR DEPENDENT VARIABLES, INTAKE, ADG, AND F/G. ADJUSTED FOR TREATMENT-TRIAL CLASSIFICATION AND INITIAL WEIGHT EFFECTS Item Intake ADG F/G Equatin Y = (q) a (IWk'~")'*r (lwi~b)2,tr Sy(x) =.4504 R ~ =.9138 Y = (a i) (lwk~,, a) (lwk~a) 2 Sy(x) =.1096 R 2 =.8393 V = (~i) (lwk~ s) (lwk~'~) 2 Sy(x) =.4388 R 2 =.7872 atreatment-trial Classificatin. b(lwk~5) 2 effect nnsignificant (P>.6561). heavier starting weights gained relatively mre rapidly, n a metablic bdy weight basis, than thse f lighter starting weights in these data. This is likely due t cmpensatry gain effects in cattle which were lder and heavier at the start f the trial. Fr the variable ADG, the regressin n IW, IW 2 and a i accunted fr 83.93% f the bserved variatin, althugh a i alne accunted fr 82.44%. Similar results have been reprted by Luetingh (1963)in terms f increases in intake and gain with cattle fed cncentrate diets at different weights and ages. Fr the variable F/G (table 2), the quadratic effect f initial weight was significant (P<.0014) after adjustment fr a i and IW, suggesting cattle f heavy starting weights tended t be mre efficient than thse f intermediate weights. The reasn fr this trend is nt readily apparent but may be due t cmpensatry gain in heavier, lder cattle. Mrever, such cattle may have shwn a slightly greater dilutin f maintenance resulting in imprved F/G, since heavier, lder cattle als gained relatively mre rapidly. Regressin f F/G n q, IW and IW 2 accunted fr 78.72% f bserved variatin in F/G. Hwever, a i alne accunted fr a large percentage f the variatin (76.18%). Luetingh (1963) bserved a trend fr prer TDN and grss energetic efficiency as cattle increasing in weight and age were fed 2:1, cncentrate: rughage diets. His bservatins were likely related t altered bdy cmpsitinal changes. It shuld be nted that even thugh the effects f IW were significant in all cases and IW 2 in tw f the three, the a i classificatin variable fitted in a simple linear regressin mdel cnsistently accunted fr a large percentage f the ttal variatin. Lab Analyses and Feedlt Perfrmance. The ability f the varius labratry analyses t accunt fr variatin amng residuals in the dependent variables (INTAKE, ADG r F/G), after crrectin fr trial and initial weight effects, is shwn in table 3. Since as nted previusly, GEL data were available n nly 72 pens f cattle, these results are shwn with GEL either allwed r nt allwed as variable fr chice by the maximum R 2 prcedure. Recall that residuals frm the secnd mdel (Ti, lw and IW 2) were the dependent variables fr the prcedure. Labratry analyses accunted fr mre f the variatin amng residuals in INTAKE (17.81%) and F/G (34.96%) than fr ADG (5.16%). This was true whether r nt GEL was included as pssible selectin. When GEL was included as a pssible selectin, the maximum variatin accunted fr was 28.49% fr INTAKE, 28.60% fr F/G and 15.62% fr ADG. Thus, the labratry analyses cnsidered in this study wuld have mre predictive value fr INTAKE and F/G than fr ADG; hwever, the actual percentage f variatin amng residuals accunted fr by the varius labratry analyses was relatively small in all cases. If cattle eat t satisfy energy needs, and thus gain, n high cncentrate diets, it is lgical that the variatin accunted fr in ADG in this prcedure wuld be lwer than fr

7 14 GALYEAN, WAGNER AND JOHNSON TABLE 3. VARIATION AMONG RESIDUALS FOR DEPENDENT VARIABLES INTAKE, ADG AND F/G ACCOUNTED FOR BY MAXIMUM R 2 SELECTED SINGLE OR COMBINATION LABORATORY ANALYSES AFTER CORRECTION FOR TRIAL AND INITIAL WEIGHT EFFECTSa, b Variable Labratry analyses % Variatin amng residuals accunted fr INTAKE ADG F/G IV24" GPI*, GP6* GPI*, GP6*, IV24" GPI*, GP6*, IV6, IV12* GPI*, GP6, IV6, IV12, IV24 GP6 * GPI*, GP6* GP1, GP6*, IV24 GP1, GP6*, IV12, IV24 GP1, GP6*, IV6, IVl2, IV24 G P6 * GPI*, GP6* GP1 *, GP6*, IV12" GPI *, GP6*, IV6, IV12* GPI*, GP6*, IV6, IV12, IV24 GEL ut f mdel (130 pens f cattle INTAKE ADG F/G GEL in mdel (72 pens f cattle) GEL* 5.03 IV24", GEL* 9.04 GPI*, GP6*, 1V24" GPI*, GP6*, IV6*, IV24" GPI*, GP6*, IV6*, IV24", GEL GPI*, GP6*, IV6, IV12, IV24, GEL GP6* 5.13 GPI*, IV GPI*, IV12, IV24" GPI*, IV6, IV12, IV24" GP1, GP6, IV12, IV24", GEL GP1, GP6, IV6, 1V12, IV24", GEL GP6* GPI*, GP6* GPI*, GP6*, GEL GP1 *, GP6*, IV6, GE]L i GPI*, GP6*, IV6~ Iu GEL GPI*, GP6*, IV6, iv12, IV24, GEL *Significant regressin F (P<.10). amdel frm which residuals were derived. Y = 3 + T i + IW31 + IW232 + e accunted fr 80.51, and 52.64% f Variatin in INTAKE, ADG and F/G, respectively, fr all 162 pens f cattle. bsimple linear regressin mdel with Y = 3 + T i + e accunted fr 78.45, and 49.46% f variatin in INTAKE, ADG and F/G, respectively, fr all 162 pens f cattle. INTAKE and F/G. Since dietary energy intake is nt limited by bulk fill in high-cncentrate diets, ADG wuld be largely a functin f genetic ptential. As labratry analyses tend t measure factrs related t energy values, they might nt be expected t accunt fr as

8 PREDICTING FEEDLOT PERFORMANCE I- z r, > v ip4..k 9 q ;> V ;> I ~ ~, ~u 0 ~ ~ + 0 [-, 0.g ~ I ~ 9,'r "- " I,-e t~ < + l..~ + 4- g- e~ I + ~ I 4..,.-i 4- <J -t- I ~ 4- ~ ~.~ v + + ~ ~ II ~ ~ I1 ~ ~. II I, ~,g i, II I I1" ~ el.,.-1 < z z < ~

16 GALYEAN, WAGNER AND JOHNSON much variatin in ADG as in INTAKE and F/G. Multiple regressin equatins based n the "best" cmbinatin f labratry analyses are shwn in table 4.

9 16 GALYEAN, WAGNER AND JOHNSON much variatin in ADG as in INTAKE and F/G. Multiple regressin equatins based n the "best" cmbinatin f labratry analyses are shwn in table 4. The best cmbinatin was ne that resulted in maximum imprvement in R 2 with n increase in the regressin errr mean square. These cmbinatins were fit int a mdel which included trial and initial weight effects (Y = fl + T i + IW/31 + IW2~2 + LAi~ 3... LAn~ n + e, where LA i = ith lab analysis). As nted previusly, the greatest R 2 values were btained with the dependent variables INTAKE and F/G. Regressin equatins and R 2 values were similar whether r nt GEL was cnsidered. Nte als that R 2 values resulting frm these mdels are lwer than thse shwn in table 2 when a treatment classificatin was included in the mdel (79.15% vs 91.38% fr INTAKE in table 4 vs table 2). It is ntewrthy, hwever, that the R 2 f 76.68% fr F/G in table 3 (GEL ut f mdel) is similar t the R 2 in table 2 f 78.72%, indicating that these analyses have predictive value fr F/G. It is imprtant t cnsider that, based n infrmatin presented thus far, n single labratry analysis wuld be a gd predictr f animal perfrmance. It wuld appear that cmbinatins f labratry analyses wuld be the mst prmising means f develping predictin equatins. T further investigate the assciatin between perfrmance parameters (INTAKE, ADG, F/G) and varius labratry grain analyses, crrelatin analyses were per- frmed n the data (table 5). Crrelatins f INTAKE with the varius labratry analyses are small (e.g., IV24 = -.36, GEL = --.22) and d nt indicate a strng assciatin, althugh many are significant. The fact that all the crrelatin cefficients are negative, hwever, is in agreement with the general belief that as gelatinizatin, starch availability and digestibility increase, intake shuld decrease as energy availability increases. Similar results were again btained with F/G, with all crrelatin cefficients being rather small and negative (-.22 and -.32 fr IV24 and GEL, respectively). Nevertheless, crrelatins were highly significant (P<.01)fr GP6, IV24 and GEL. The same ratinale fr negative crrelatins with INTAKE wuld apply t F/G. Crrelatin cefficients between ADG and the labratry analyses were all small and nn-significant, thus, reaffirming the lw R 2 values previusly discussed in tables 3 and 4. In general, crrelatins between all dependent variables and labratry analyses are nt f the magnitude necessary fr develpment f accurate, reliable predictin equatins using any single analysis. These results are in cntrast t thse f Albin et al. (1966) wh reprt r values f.88 and.99 between IVDMD and feedlt gain and efficiency, respectively. Crrelatins amng the varius labratry analyses are shwn in table 6. These crrelatins, uncrrected fr trial differences, reveal TABLE 5. CORRELATIONS BETWEEN INT, ADG, AND F/G CORRECTED FOR TRIAL AND INITIAL WEIGHT EFFECTS AND VARIOUS LABORATORY ANALYSES Labratry analyses Variable GPI GP6 IV6 IV12 IV24 GEL INTAKE a b c ADG F/G = acrrelatin cefficients. b Sigmflcance 9 9 level. Cpens f cattle upn which crrelatin is based.

10 PREDICTING FEEDLOT PERFORMANCE 17 TABLE 6. CORRELATIONS AMONG VARIOUS LABORATORY ANALYSES Labratry analyses Variable GP1 1V6 1V12 IV24 GEL GP a b c GP IV IV IV acrrelatin cefficients. b 9 Significance level. Cpens f cattle upn which crrelatin is based. strng and generally bvius assciatins amng several f the analyses. The significant crrelatin f.668 between GP6 and GEL supprts the idea that gas prductin values prvide infrmatin similar t gelatinizatin values in regards t the extent f starch alteratin. The high, significant crrelatins between the three IVDMD measures (.9029 fr IV12 and 1V24) are expected as they are cnsecutive measures n the same sample. The crrelatins between GP6 and any f the IVDMD measures were nt as high as that reprted by Trei et al. (1970). Hwever, the gas prductin methd used in ur studies was a amylglucsidase enzyme and yeast utilizatin prcedure; whereas, Trei et al. (1970) used rumen micrrganisms in their gas prductin system. In cnclusin, it appears that n single labratry analysis f grain will predict perfrmance f animals fed that grain with a high degree f accuracy. Cmbinatins f the lab analyses may have been predictive value fr certain perfrmance measures (e.g., F/G); hwever, it wuld seem that these analyses better serve the purpse f describing the effects f prcessing and extent f starch alteratin in grains. LITERATURE CITED Aimne, J. C Feedlt, in vitr and metablism studies with prcessed wheat and barley. M. S. Thesis, Oklahma State University. Aimne, J. C. and D. G. Wagner. 1977a. Micrnized wheat. I. Influence n feedlt perfrmance, digestibility, VFA and lactate levels in cattle. J. Anim. Sci. 44:1088. Aimne, J. C. and D. G. Wagner. 1977b. Micrnized wheat. II. Influence n in vitr digestibility, in vitr gas prductin and gelatinizatin. J. Anim. Sci. 44:1096. Albin, R. C., A. Simnacher and R. M. Durham In vitr digestin f all-cncentrate ratin. Rep. n Texas Technlgical Cllege Research 55. Christiansen, R. R. and D. G. Wagner. 1974a. Recnstituted wheat. I. Influence n feedlt perfrmance f cattle. J. Anita. Sci. 38:456. Christiansen, R. R. and D. G. Wagner. 1974b. Recnstituted wheat. II. Influence f physical frm n in vitr digestibility. J. Anim. Sci. 38:463. Crka, D. C. and D. G. Wagner. 1975a. Micrnized srghum grain. I. Influence n feedlt perfrmance f cattle. J. Anim. Sci. 40:924. Crka, D. C. and D. G. Wagner. 1975b. Micrnized srghum grain. II. Influence f in vitr digestibility, in vitr gas prductin and gelatinizatin. J. Anim. Sci. 40:931. Crka, D. C. and D. G. Wagner. 1975c. Micrnized srghum grain. III. Energetic efficiency fr feedlt cattle. J. Anim. Sci. 40:936. Klett, R. H. and A. T. Raisn A cmparisn f in vitr and in viv digestin techniques. J. Anim.

18 GALYEAN, WAGNER ANDJOHNSON Sci. 26:922. (Abstr.). Kumen, F., B. A. Dehrity and R. R. Jhnsn. 1967.

11 18 GALYEAN, WAGNER ANDJOHNSON Sci. 26:922. (Abstr.). Kumen, F., B. A. Dehrity and R. R. Jhnsn Develpment f an in vitr fermentatin technique fr estimating the nutritive value f high energy mixed ratins fr ruminants. J. Anim. Sci. 26: 867. Leutingh, H. C The efficiency f beef prductin in terms f carcass weight as influenced by the ratin cncentratin and age f steers. J. Agr. Sci. 61:127. Martin, T Feedlt and in vitr studies with prcessed srghum and wheat. M. S. Thesis, Okla- hma State University. Schneider, William In viv and in vitr evaluatin f high misture mil and mil-wheat cmbinatins fr fattening beef cattle. M. S. Thesis, Oklahma State University. Service, Jlayne A user's guide t the statistical analysis system. Nrth Carlina State University. P Trei, J., W. H. Hale and Brent Theurer Effect f grain prcessing n in vitr gas prductin. J. Anim. Sci. 30:825.

M.J. Guthriel, D.G. Wagner2

EFFECT OF SUPPLEMENTAL PROTEIN OR GRAIN ON INTAKE AND UTILIZATION OF MEDIUM QUALITY PRAIRIE HAY BY STEERS M.J. Guthriel, D.G. Wagner2 and D.C. Weakley3 Stry in Brief Sixteen 1,053 lb tw-year-ld Herefrd