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University of Nebraska Cooperative Extension MP74-A

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Dairy Report

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Acknowledgments ......................................................................................... 2

Effect of Soyhull:Soy Lecithin:Soapstock Mixture onReproduction in Early Lactation Dairy Cows .............................................. 3

Brown Midrib Forage Sorghum for Dairy Cows: Short-TermResponses ...................................................................................................... 5

Brown Midrib Forage Sorghum Improves Fiber Digestibility and MilkProduction in Dairy Cows ............................................................................ 8

Maximal Replacement of Dietary Concentrate and Forage with aNew Wet Corn Milling Feed Product ........................................................... 11

Corn versus Sorghum Distillers Grains for Lactating Dairy Cows ........... 14

1999-2000

Issued in furtherance of Cooperative Extension work, Acts of May 8 and June 30, 1914, in cooperationwith the U.S. Department of Agriculture. Kenneth R. Bolen, Director of Cooperative Extension,

University of Nebraska, Institute of Agriculture and Natural Resources.

University of Nebraska Cooperative Extension educational programs abide with the non-discrimination policies of theUniversity of Nebraska-Lincoln and the United States Department of Agriculture.

Longer Particle Length Alfalfa Improves Use of Wet Corn GlutenFeed by Dairy Cows ..................................................................................... 17

Genetics Research ......................................................................................... 22

Dairy Technician Certification ..................................................................... 24

Land Requirements for Managing Manure Nutrients on DairyOperations ..................................................................................................... 25

The Accuracy of Test Strategies to Classify Herds by Johne’sDisease Status ............................................................................................... 29

Dairy Research Herd Report ......................................................................... 33

Dairy Extension Publications Available from University of Nebraska ........ 35

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ACKNOWLEDGMENTS

Appreciation is expressed to the following for providing support of the dairy program at the Universityof Nebraska.

Archer Daniels Midland, Lincoln, NEBoehringer Ingelheim Animal Health, Inc., St. Joseph, MOCargill Corn Milling, Blair, NECenex/Land O’Lakes, Lincoln, NEChurch & Dwight Co., Inc., Princeton, NJDairy Farmers of America, Kansas City, MOFats and Proteins Research Foundation, Chicago, ILGarrison & Townsend, Inc., Hereford, TXHoffman-LaRoche, Inc., Nutley, NJHomestead Dairy Equipment, Inc., Beatrice, NEHuskerland, Geneva, NELignotech, U.S.A., Inc., Rothchild, WIMidwest Laboratories, Inc., Omaha, NENational Association of Animal Breeders, Columbia, MONational Byproducts, Des Moines, IANebraska State Dairymen’s AssociationNebraska Harvestore Systems, Inc., Norfolk, NENebraska Grain Sorghum Development, Utilization and Marketing Board, Lincoln, NENebraska Soybean Development, Utilization and Marketing Board, Lincoln, NENovartis Seeds, Golden Valley, MNNutrivet, Inc., Lincoln, NEPlatte Valley Dairy Equipment, Lincoln, NESoutheastern Poultry & Egg Association, Tucker, GA21st Century Genetics, Shawano, WIUniversity of Nebraska Foundation, Lincoln, NEWill Forbes Fund

To simplify technical terminology, trade names of products or equipment sometimes are used.No endorsement of product is intended nor is criticism implied of products not mentioned.

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Effect of Soyhull:Soy Lecithin:SoapstockMixture on Reproduction in Early Lactation

Dairy CowsWilliam Chapman

Larry LarsonRick Grant1

Summary

An experiment was conducted overthe first 14 weeks of lactation to deter-mine the effect of a soybean hull, soylecithin, and soapstock mixture on lac-tational and reproductive performance.Thirty-seven Holstein cows weregrouped by parity and assigned ran-domly to one of two diets at three weekspostpartum. Diets consisted of 45%forage, 17.1% soybean hulls, and 1) noadded lipid (control) or 2) soy lecithinand soapstock in a 1:1 ratio to supply3% of dietary dry matter (DM). Lacta-tion performance was reported in the1997-98 Dairy Report. Soy lecithin andsoapstock are economical lipidcoproducts of soybean processing thateffectively increased milk productionand energy balance, although repro-ductive performance was not changed.

Introduction

As milk production has increased,postpartum reproductive problems alsohave increased. Reproductive failure isthe second major reason for cullinganimals from the milking herd follow-ing mastitis. During the early post-partum period, milk productionincreases at a faster rate than DMIresulting in negative energy balance.

Energy balance is correlated posi-tively with serum progesterone and IGF-I in early lactation Holstein cows. Cowswith greater concentrations of plasmaIGF-1 for the first two weeks postpar-tum are more likely to ovulate the domi-

nant follicle. Energy balance during theearly postpartum period also appears toplay an important role in determiningwhen postpartum cyclic ovarian activ-ity is initiated. There is a high correla-tion between days to lowest negativeenergy balance and days to first ovula-tion. Early re-establishment of ovula-tory cycles following parturition shouldimprove reproductive performance. Toimprove reproductive performance, theperiod of negative energy balance needsto be minimized without compromisingmilk production.

Lipid supplementation is one methodto increase the energy density of the dietwhile avoiding metabolic problems suchas acidosis caused by high amounts ofconcentrates in the diet. Soy lecithinand soapstock are two lipid coproductsof the soybean oil refining process. Thesetwo lipid sources are widely availableand are approximately one-half asexpensive as tallow, making them eco-nomical sources of dietary lipid. How-ever, there is limited research on thesetwo products in diets for dairy cows.

Therefore, the following experimentwas conducted to investigate the use ofa mixture of soybean hulls, soy lecithin,and soapstock (SLS) as a supplementallipid source during early lactation andto evaluate the response of DMI, milkproduction, energy balance, and repro-ductive performance.

Procedures

Thirty-seven early lactation Holsteindairy cows were grouped by parity andassigned randomly to two dietary regi-mens at three week postpartum: 1) con-trol diet with no supplemental lipid, or2) SLS added to provide 3% lipid (DMbasis; Table 1). Diets were isoitrogenous

(17.6% CP) with similar NDF contents.Soybean hulls, lecithin, and soapstockwere mixed in a ratio of 85:7.5:7.5 (DMbasis). The 1:1 ratio of lecithin andsoapstock was shown previously toresult in the greatest degree of ruminallipid protection. Soybean hulls are an

Table 1. Dietary ingredients and chemicalcomposition of the experimentaldiets.

Control SLS1

----(% of DM)----

IngredientAlfalfa silage2 18.0 18.0Corn silage3 22.5 22.5Alfalfa hay, chopped4 4.5 4.5Corn, rolled 22.4 18.5Soybean hulls 17.1 —SLS — 20.1SoyPass®5 4.7 4.7Soybean meal 8.8 9.7Vitamin and mineral mix6 2.0 2.0

CompositionDM, % 67.3 66.8CP 17.6 17.7ADF 27.6 27.4NDF 41.2 40.5Ether extract 2.9 5.7Nonfiber carbohydrate 28.9 26.8NEL, Mcal/kg 1.61 1.70

1Soybean hulls, soy lecithin, and soapstock(85:7.5:7.5, DM basis).2Alfalfa silage contained (DM basis) 45.0% DM,20.8% CP, 38.0% ADF, and 44.6% NDF.3Corn silage contained (DM basis) 35.0% DM,8.2% CP, 32.9% ADF, and 55.3% NDF.4Alfalfa hay contained (DM basis) 89.0% DM,17.7% CP, 38.1% ADF, and 47.7% NDF.5Manufactured by Lignotech USA (Rothschild,WI). A nonenzymatically browned soybean mealwith 70% RUP.6Supplement contained 15.2% Ca, 7.2% P, 4.1%Mg, 4.0% Na, 3000 ppm of Zn, 1750 ppm of Mn,400 ppm of Ca, 200,000 IU/kg of vitamin A,36,000 IU/kg of vitamin D3, and 585 IU/kg ofvitamin E.

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excellent source of digestible fiber andserve as a good carrier for the lecithinand soapstock. The resulting producthas good flow and handling character-istics. The control diet contained thesame amount of soybean hulls, alfalfa,and corn silage as the treatment diet toallow animals equal amounts of fiberfrom similar sources. Both diets werefed for ad libitum intake as TMR oncedaily.

All cows were fed a common diet forthe first three weeks of lactation as anadaptation period. At the end of theadaptation period, cows were started ontreatment regimens and remained ontreatment until 14 weeks postpartum.Cows were milked twice daily with milkyield being recorded electronically. Netenergy balance (NEB) was calculatedweekly.

The breeding program was initiatedat eight weeks postpartum. A timed AIprotocol was used for all cows as fol-lows: cows received GnRH intramus-cularly (Cystorelin®; Sanofi AnimalHealth, Inc., Overland Park, KS; 100µg per dose) at 63+3 DIM, followed 7days later with PGF2α intramuscularly(Estrumate®; Miles Inc., ShawneeMission, KS; 500 µg per dose). At 48hours after PGF2α, cows received asecond GnRH injection and wereinseminated 16 to 18 hours later. Repeatservices were based on detected estrus.Conception rate was defined as thepercentage of inseminated cowsdiagnosed as pregnant. Ovulation wasconsidered to have occurred whenconcentrations of progesterone were>1 ng/ml for at least two consecutivedays of blood sampling. Concentrationsof progesterone during the luteal phasewere determined from blood samplescollected between day 8 to 16 followingovulation. Ovulation was defined as thesample day prior to serum progesteroneconcentrations >1 ng/ml.

Blood samples were collected once at1 to 2 weeks prepartum and twice weeklyfrom 2 weeks postpartum to 4 weeks

after first insemination for determina-tions of serum concentrations of pro-gesterone and IGF-I. Reproductivemeasures were analyzed by the GeneralLinear Model of SAS using Least SquareMeans.

Results

Lactation performance was pre-viously reported in the 1997-98 DairyReport. Briefly, production of 4% fat-corrected milk and DM intake wereincreased by the incorporation of soylecithin and soapstock into the diet.

Reproductive performance did notdiffer between treatment groupsalthough NEB was increased by feed-ing the lipid (Table 2). There was noparity or treatment effect on days tofirst ovulation, or on luteal phase serumprogesterone concentrations or peakprogesterone during the first ovulatorycycle or the cycle following the timed AI

Table 2. Effect of soy lecithin and soapstock on reproductive measures and IGF-I.

Parity

Primiparous Multiparous

Item Control SLS1 Control SLS

No. of animals 7 8 11 11

NEB,2 Mcal/d 7.59d 9.10c 11.70b 15.39a

First ovulation cyclePeak progesterone, ng/ml 4.28 2.03 2.81 3.31

Luteal phaseprogesterone, ng/ml 2.31 1.66 2.16 2.40

Timed AI cyclePeak progesterone, ng/ml 3.22 3.03 2.54 3.18

Luteal phase 3.97 4.23 3.36 4.37progesterone, ng/ml

Postpartum interval to 59.1 40.9 41.9 39.4first ovulation, d

Conception rate to 2/7 2/8 4/11 5/11timed AI protocol

IGF-I, ng/ml 63.0 74.2 58.4 68.8

1Soybean hulls, soy lecithin and soapstock (85:7.5:7.5, DM basis).2Net energy balance.abcdMeans within a row with different superscripts differ (P<0.05) among parity and treatment withinparity.

protocol. There was no effect of treat-ment on conception rate. Although therewas no effect of diet on IGF-I concen-tration in serum (Table 2), concentra-tion of IGF-I was correlated positivelyto week of first ovulation.

In summary, the combination of soy-bean hulls, soy lecithin, and soapstockis an economical source of lipid toincrease the energy density of the dietavailable to the dairy industry as acoproduct of soybean processing. Thepreviously reported positive milk pro-duction response to these soy coprod-ucts appeared to be at the expense of anymeasurable benefit to reproductive per-formance.

1William Chapman, former graduate student;Larry Larson, Associate Professor, Animal Science,Lincoln; Rick Grant, Associate Professor andExtension Dairy Specialist, Animal Science,Lincoln.

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Brown Midrib Forage Sorghum for Dairy Cows:Short-Term Responses

Nebraska alone, over 300,000 acres ofsorghum were harvested for silage in1995. Forage sorghum can be plantedlater than corn, uses water much moreefficiently, and when exposed to sum-mer drought still produces acceptableyields.

Brown midrib forage sorghums con-tain less lignin than standard sorghumhybrids and the fiber is much moredigestible. A previous study at Nebraskaindicated that cows fed BMR versusstandard forage sorghum at 65% of thedietary DM produced 18 more poundsof milk daily. To date, this has been theonly reported comparison of BMR ver-sus standard forage sorghums for lactat-ing dairy cows.

The purpose of this study was tocompare silage made from BMR sor-ghum with an isogenic standard sor-ghum silage, corn silage, and alfalfasilage for their effect on short-term (4weeks) milk production and fiber di-gestibility.

Procedures

Sixteen Holstein cows (4 primipa-rous) were assigned randomly withinparity to one of four diets in replicated 4× 4 Latin squares with 4-wk periods.Three rumen-fistulated cows wereassigned randomly to the same diets in

Gokalp AydinRick Grant1

Summary

Sixteen Holstein cows were assignedto one of four diets in replicated 4 × 4Latin squares with 4-wk periods tomeasure dietary effect on short-termperformance. Additionally, 3 fistulatedcows were assigned to the same diets ina 3 × 4 Youden square with 4-wk periodsto measure rumen fiber fermentation.Diets comprised 65% of either brownmidrib (BMR) forage sorghum, stan-dard forage sorghum, alfalfa, or cornsilages and 35% concentrate. Dry mat-ter intake (DMI), milk and milk compo-nents were greater for cows fed theBMR versus the standard forage sor-ghum. Efficiency of 4% fat-correctedmilk (FCM) was greatest for the cornsilage diet, equivalent for the alfalfaand BMR sorghum diets, and least forthe standard forage sorghum diet.Rumination and eating activities weresimilar for standard and BMR sorghumsilages, as was rumen pH and acetateto propionate ratio. Ruminal and totaltract digestibility of NDF was greaterfor the BMR versus the standard foragesorghum. Feeding dairy cows BMR for-age sorghum silage resulted in greaterDMI, fiber digestibility, and milk pro-duction versus a standard forage sor-ghum hybrid in this short-term study.

Introduction

Sorghum has become an increas-ingly important forage crop for dairyproducers in the Midwestern and plainsregions of the U.S. Additionally, foragesorghum can serve as an effective “res-cue crop” in other regions of the U.S.when weather conditions preclude suc-cessful corn planting. In Kansas and

a 3 × 4 Youden square. Alfalfa silage,corn silage, standard sorghum silage,and BMR sorghum silage were used asthe dietary treatments. All diets con-tained 65% silage and 35% of a concen-trate mixture comprised of soybean meal,dry-rolled corn, and a mineral and vita-min premix. Nutrient composition ofthe silages and the diets are given inTables 1 and 2.

Cows were milked twice daily andproduction was recorded electronically.A daily composite of milk samples froma.m. and p.m. milkings were takenweekly and analyzed for fat, protein,and lactose. Samples of rumen fluid forpH and acetate to propionate ratio werecollected during week 4 at 4-h intervalsfor 24 h. Fiber digestion of each silagewas measured in situ using dacron bagsto estimate rumen NDF digestion, andacid insoluble ash was used as an inter-nal marker to estimate total tract NDFdigestion.

Results

The BMR forage sorghum contained21% less lignin than the standard for-age sorghum, but similar NDF (Table1). The diets were all equal in CP andrumen undegradable protein, but dif-fered in content of lignin and NDF that

Table 1. Nutrient composition of silages as percentage of DM.

Normal BMR1

Item sorghum sorghum Alfalfa Corn

DM 30.6 31.2 45.0 39.7

CP 6.8 7.3 20.6 7.4ADF 34.7 36.5 33.0 26.4NDF 51.7 50.4 39.4 41.0Lignin 9.5 7.5 6.8 4.4Particles > 1.18 mm2, % 71.4 71.3 62.8 70.1pH 3.89 3.93 4.81 3.87

1Brown midrib.2Forage particles retained on the 1.18-mm screen or greater following wet sieving as a percentage of totalsample.

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reflected the source of the silage (Table2).

DM matter intake among diets wasnot different, but when expressed as apercentage of BW, it was highest forcows fed the corn silage diet and leastfor cows fed the standard sorghum si-lage diet, with cows fed alfalfa andBMR sorghum silages being intermedi-ate (Table 3).

Milk production and 4% FCM were13% greater for cows fed the BMRsorghum diet than for those fed thestandard sorghum diet (Table 4). Al-falfa and BMR sorghum silage dietsresulted in similar milk production, butmilk production was greatest for cowsfed the corn silage diet. The percentageof milk fat was not different among thediets, but production of milk fat wasgreater for the BMR sorghum versus thestandard sorghum diets, which reflectedthe responses observed in milk produc-tion. Milk protein percentage was simi-lar for cows fed BMR sorghum, stan-dard sorghum, and alfalfa silage, butwas highest for cows fed the corn silagediet. Production of milk protein wasgreater for the BMR than for the stan-dard sorghum silage diet. Because ofdifferences in DMI and FCM amongdiets, the efficiency of FCM productionwas greatest for the corn silage diet,similar for the BMR and alfalfa silagediets, and lowest for the standard sor-ghum silage diet (Table 4). There wasno effect of treatment on BW or bodycondition score in this short-term ex-periment. The diet containing standardforage sorghum was clearly inferior formilk production, DMI, and efficiency ofFCM production, which agrees withearlier research at Nebraska usingmidlactation dairy cows.

There were no differences betweenstandard and BMR sorghum in eatingor ruminating activities (Table 5). Cowsfed the corn silage diets spent the leastamount of time eating and ruminating.Averaged over 24 h, ruminal pH, totalvolatile fatty acid concentration, andacetate to propionate ratio were notdifferent among diets (Table 6). Themean pH was greater than 6.2 for all

Table 2. Ingredient and chemical composition of diets.

Normal BMR1

Item sorghum sorghum Alfalfa Corn

Ingredients, % DMNormal sorghum silage 65.0 — — —BMR sorghum silage — 65.0 — —Alfalfa silage — — 65.0 —Corn silage — — — 65.0Soybean meal 21.5 21.5 — 20.8Corn, rolled 10.7 10.7 32.2 11.4Mineral and vitamin mix2 2.8 2.8 2.8 2.8

Composition,3 % of DMDM, % 51.2 51.0 61.0 62.0CP 16.5 16.9 16.3 16.8RUP4 5.3 5.3 5.1 5.2ADF 27.6 25.2 20.3 21.8NDF 39.7 40.3 29.1 34.3Lignin 6.4 5.2 4.7 3.3

1Brown midrib.2A mineral and vitamin supplement was added to all diets to meet or slightly exceed the nutrientrequirements of NRC (1989).3Dietary composition determined using analytical values for individual ingredients.4Rumen undegradable protein; calculated using values reported by NRC (1989).

Table 3. Dry matter and fiber intake as influenced by forage source.

Normal BMR1

Item sorghum sorghum Alfalfa Corn SE

DMIlb/d 47.4 50.0 52.9 55.8 0.8% of BW 3.5c 3.7b 4.0ab 4.2a <0.1

ADFlb/d 13.0a 12.6a 10.6b 11.2ab 0.2% of BW 0.9a 0.9a 0.8b 0.8b <0.1

NDFlb/d 19.4ab 20.5a 15.4c 19.2b 0.4% of BW 1.4b 1.5a 1.2c 1.4b <0.1

a,b,cMeans within a row with different superscripts differ (P < 0.05).1Brown midrib.

Table 4. Lactation performance as influenced by forage source.

Normal BMR1

Item sorghum sorghum Alfalfa Corn SE

Milk, lb/d 47.3c 53.5b 55.4b 65.0a 1.1Milk fat

% 3.73 3.73 3.78 3.82 0.08lb/d 1.74c 1.96b 2.09b 2.47a 0.06

Milk protein% 3.21b 3.23b 3.14b 3.36a 0.03lb/d 1.50c 1.72b 1.74b 2.17a 0.02

Lactose% 4.85 4.88 4.86 4.90 0.02lb/d 2.29c 2.62b 2.69b 3.17a 0.02

4% FCM, lb/d 45.6c 52.3b 54.0b 63.9a 1.3FCM/DMI, lb/lb 0.94c 1.05b 1.05b 1.15a 0.03BW, lb 1333 1316 1316 1313 7BW change, lb/28 d 8.1 2.9 2.6 25.9 9.5BCS2 3.29 3.26 3.23 3.26 0.02BCS change, /28 d -0.06 -0.03 -0.05 -0.01 0.05a,b,cMeans within a row with different superscripts differ (P < 0.05).1Brown midrib.2Body condition score (1 = thin to 5 = fat).

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diets, and all diets resulted in acetate topropionate ratios in excess of 2.0. Frac-tional passage rate from the rumen esti-mated using rare earth marker did notdiffer significantly among the silages(Table 7) and averaged 0.038 h-1. In situlag time and rate of silage NDF diges-tion were not different between stan-dard and BMR sorghum silages (Table7). Fractional rate of NDF digestion washighest for alfalfa and similar for stan-dard sorghum, BMR sorghum, and cornsilage. Potential extent of ruminal NDFdigestion was lowest for alfalfa andhighest for corn silage; it was not sig-nificantly different for standard andBMR sorghum silages. However, BMRsorghum tended to have a greater poten-tial extent of digestion than the stan-dard counterpart, and the apparent ex-tent of ruminal digestion, whichintegrates passage and digestion, wasgreater for BMR than for standard sor-ghum silage.

Total tract digestibilities of NDF andADF for BMR sorghum were 10 and22% greater, respectively, than stan-dard sorghum. Digestibilities of ADFand NDF were 20 and 14% greater,respectively, for corn silage than foralfalfa silage. All of these data indicatethat even though the fiber digestion rateand ruminal VFA were not differentbetween BMR sorghum and standardsorghum, apparent extent of fiber diges-tion for BMR was higher than for stan-dard sorghum and the increased extentof total tract NDF digestion resulted ingreater milk production.

This short-term trial clearly indi-cated that BMR forage sorghum hy-brids result in greatly enhanced NDFdigestibility, dry matter intake, and milkproduction when fed to lactating dairycows. These hybrids are especially suit-able for dairy producers in the Midwest-ern and plains states where corn silageis not always the most suitable cropfrom an agronomic perspective.

1Gokalp Aydin, former Graduate Student; andRick Grant, Associate Professor and ExtensionDairy Specialist, Animal Science, Lincoln.

Table 5. Chewing activity as influenced by forage source.

Normal BMR1

Item sorghum sorghum Alfalfa Corn SE

Eating, min/d 277a 271a 291a 235b 7

Ruminating, min/d 459a 446ab 421bc 388c 11

Total chewing, min/d 730a 717a 712a 623b 13

a,b,cMeans within a row with different superscripts differ (P < 0.05).1Brown midrib.

Table 6. Ruminal pH and volatile fatty acids as influenced by forage source.1

Normal BMR2

Item sorghum sorghum Alfalfa Corn SE

Ruminal pH 6.43 6.48 6.18 6.21 0.07Total VFA, mM 109.6 109.2 107.7 107.2 1.3

VFA, mol/100 molAcetate (A) 62.6 60.6 62.2 62.3 0.9Propionate (P) 30.6 29.3 28.6 30.1 1.2n-Butyrate (B) 2.8b 4.1a 4.0a 3.7a 0.1Isobutyrate 0.8 1.0 0.8 0.7 <0.1n-Valerate 1.5 2.5 2.3 1.5 0.2Isovalerate 1.4c 2.3a 1.9b 1.4c <0.1

A:P 2.0 2.1 2.1 2.1 0.1A+B/P 2.1 2.2 2.3 2.2 0.1

a,b,cMeans within a row with different superscripts differ (P < 0.05).1Data represent means over a 24-h period from samples collected every 4 h.2Brown midrib.

Table 7. In situ digestion kinetics of forage NDF and total tract fiber digestibility.

Normal BMR1

Item2 sorghum sorghum Alfalfa Corn SE

Kp h-1 0.041 0.034 0.046 0.031 0.009

Lag, h 1.29b 0b 2.58ab 4.90a 0.77

Kd, h-1 0.033b 0.049ab 0.103a 0.031b 0.013

PED, % 56.5bc 64.6ab 48.0c 68.6a 2.5

AED, % 24.1c 38.3a 29.4bc 29.6b 1.1

Total tract digestibilityNDF, % 38.8b 42.8ab 45.6ab 51.8a 2.6

ADF, % 32.02c 39.1b 40.3b 48.5a 1.8

a,b,cMeans within a row with different superscripts differ (P < 0.05).1Brown midrib.2Kp = Fractional rate of passage from rumen; Kd = fractional rate of digestion in the rumen; PED = potentialextent of ruminal fiber digestion calculated using equations by Grant (1994); AED = apparent extent ofruminal fiber digestion = PED x Kd/(Kd + Kp) x e-KpL.

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Brown Midrib Forage Sorghum Improves FiberDigestibility and Milk Production in Dairy Cows

Gokalp AydinRick Grant1

Summary

Thirty Holstein dairy cows in earlylactation were fed diets containing35.3% (DM basis) standard foragesorghum silage, brown midrib (BMR)sorghum silage, or corn silage in a 10-wk lactation trial. In vitro extent offiber digestion was significantly higherfor BMR sorghum than for standardsorghum silage. Dry matter intake(DMI) and body condition score werenot different between cows fed BMRand standard forage sorghum, but cowsfed BMR sorghum diets had greaterlong-term milk production than cowsfed standard forage sorghum with milkproduction similar to cows fed cornsilage. The BMR forage sorghumappears to be a viable alternative tocorn silage as a source of highlydigestible forage fiber and it is clearlysuperior to standard forage sorghumhybrids.

Introduction

Climatic conditions in the Midwest-ern and plains region of the U.S., suchas frequent drought and high summertemperatures, introduce considerablerisk into corn production for silage, thusmany producers consider raising silage-type sorghums because of high biomassyields, drought tolerance, and adapt-ability to late planting after winter crops.However, the DM digestibility of cornsilage is typically greater than for forage

sorghum. Lignin, the primary indigest-ible component of plant cell walls,inhibits digestion of cell wall carbohy-drates in the rumen. Usually the cornplant contains less lignin than standardforage sorghum hybrids as well as agreater content of grain. Because highlignin content reduces the potentialextent of fiber digestion, it may result inincreased gut fill, reduced DMI, andless milk production.

Chemical and genetic approacheshave been used to improve forage fiberdigestibility by reducing lignification.Brown midrib forage genotypes usuallycontain less lignin and the chemicalcomposition of the lignin is altered.Genetic control of the lignificationprocess through manipulation of theBMR trait has offered the most directapproach to reducing lignin concentra-tion and increasing digestibility of for-age sorghum. In situ and in vitro NDFdigestion studies have shown that BMRforages have greater extent of NDFdigestion than their standard counter-parts. In most lactation and feedingtrials involving corn silage, BMR cornsilage improved milk production, DMI,and BW gain.

Most previous studies that comparedstandard sorghum genotypes with cornsilage have shown that milk productionand DMI were consistently higher forcows fed corn silage than those fedsorghum silage. Few experiments havecompared BMR sorghum to other com-mon forages fed to lactating dairy cattle.Only one previous study, conducted atNebraska, has compared BMR sorghumsilage with corn and alfalfa silages; weobserved that milk production was not

significantly different for cows fedalfalfa, corn, or BMR sorghum silageswhen the diets contained 65% silage(DM basis).

The earlier study showed that moreexperiments are needed to compareBMR forage sorghum hybrids with othercommon forages to measure the impacton ruminal function and lactational per-formance. It is essential to begin devel-opment of forage systems that optimizethe use of alternatives to corn silage inregions where corn is less agronomi-cally suitable.

Therefore, the objective of thisresearch was to compare a BMR sor-ghum silage with an isogenic standardsorghum silage and corn silage in aration that also contained alfalfa silagein a 10-wk lactation study for theireffect on milk production, DMI andbody condition score.

Procedures

Thirty Holstein cows (15 primipa-rous) in early lactation were grouped byage and previous milk production andassigned randomly to one of threeexperimental diets in a continuous 10-wk lactation trial to measure DMI, milkproduction, rumination activity, andbody condition score. A 2-wk covariateperiod was used during which all cowswere fed a common diet containingalfalfa as the sole forage (50% of dietaryDM).

Diets were prepared as typical lac-tation TMR fed to an early lactationdairy cow. All diets contained 53% for-age and 47% of a concentrate mixturecomprised of soybean meal, SoyPass®

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(a nonenzymatically browned soybeanmeal to increase the escape protein con-tent; Lignotech USA, Rothschild, WI),dry-rolled corn, and whole cottonseed(Tables 1 and 2). The sorghum and cornsilages made up 67% of the forage DMin each diet with alfalfa silage compris-ing the remainder. Diets were formu-lated to be isonitrogenous (17.5% CP)and the rumen undegradable proteinrequirements for early lactation werecalculated to be met by all diets. Alldiets were fed as TMR twice daily inamounts to ensure 10% feed refusals.Cows were housed in a tie-stall barnequipped with individual feed boxesand were removed twice daily for milk-ing.

Dietary and animal measurementswere forage physical form and chemicalcomposition of forage and other dietaryingredients measured weekly, rumina-tion activity (measured once during wk5), DMI and milk production measureddaily, milk composition measured onceweekly, and BW measured weekly. Bodycondition score was measured weeklyusing a 1 to 5 scale where 1 was a thincow and 5 was a fat cow.

Results

Chemical composition of experimen-tal silages is presented in Table 1. TheBMR sorghum and standard sorghumhad similar NDF and ADF concentra-tions, but lignin concentration was lessfor BMR than for standard sorghumsilage. Standard sorghum, BMR sor-ghum, and corn silage had similaramounts of forage particles retained ona 3/4-inch screen.

Lactational performance data areshown in Table 3. This study is the onlyreport of the long-term response of lac-tating dairy cows to diets containingBMR forage sorghum, standard foragesorghum, or corn silage. The DMI wasnot significantly different among diets.Milk production and 4% fat-correctedmilk (FCM) were higher for the BMRsorghum diet than for the standardsorghum diet. Milk composition was

Table 1. Chemical composition of experimental silages as percentage of DM.

Normal BMR1

Item sorghum sorghum Corn Alfalfa

DM, % 36.8 34.8 35.5 47.6CP 9.1 9.7 9.5 20.5ADF 33.2 32.0 28.1 36.2NDF 49.9 47.9 48.6 43.0Lignin 7.1 6.1 5.8 7.7

Particle distribution2

>3/4 inch 2.3 5.2 3.8 20.03/4 inch to 5/16 inch 30.1 29.2 22.3 37.0<5/16 inch 67.6 65.6 73.9 43.0

1Brown midrib.2Particle distribution (% of as-is silage) determined using the Penn State Forage Particle Separator.

Table 2. Ingredient and chemical composition of experimental diets.

Normal BMR1 CornItem sorghum sorghum silage

Ingredients, % of DMAlfalfa silage 17.5 17.5 17.5Normal sorghum silage 35.3 — —BMR sorghum silage — 35.3 —Corn silage — — 35.3Corn, rolled 22.8 22.8 22.8Soybean meal 6.6 6.6 6.6Soy Pass®2 8.3 8.3 8.3Whole cottonseed 6.6 6.6 6.6Mineral and vitamin mix3 2.9 2.9 2.9

Chemical composition, % of DMDM, % 64.3 65.1 66.5CP 17.5 17.7 17.6RUP4 6.5 6.9 6.6ADF 24.1 23.6 22.3NDF 32.3 31.6 31.9Lignin 4.9 4.5 4.5

1Brown midrib.2Nonenzymatically browned soybean meal to increase rumen undegradable protein content (LignotechUSA, Rothschild, WI).3Mineral and vitamin mix added to meet or slightly exceed the requirements of NRC (1989).4Rumen undegradable protein; calculated using values reported by NRC (1989).

Table 3. Effect of diet on lactational performance of dairy cows fed experimental diets for 10 wk.

Normal BMR1 CornItem sorghum sorghum silage SE

DMIlb/d 52.3 55.3 54.7 2.2% of BW 4.10 4.20 4.30 0.08

Milk production, lb/d 74.5b 79.4a 76.3ab 1.5Milk composition, %

Fat 3.54 3.59 3.57 0.14Protein 2.99 3.08 3.01 0.04Lactose 4.97 5.04 5.04 0.05

4% FCM, lb/d 69.0b 74.5a 71.4ab 1.5FCM/DMI, lb/lb 1.30b 1.36a 1.31b 0.05

BW, lb 1254 1294 1239 11BW change, lb from 1 to 10 wk 24.9 22.0 33.9 1.8BCS2 3.3 3.4 3.2 0.3BCS change from 1 to 10 wk 0.04 0.09 0.03 0.04a,bMeans within a row with different superscripts differ (P<0.05).1Brown midrib.2Body condition score (1 = thin to 5 = fat).

(Continued on next page)

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unaffected by diet. Efficiency of FCMproduction was greater for BMR sor-ghum than for the standard sorghumdiet. The production of FCM was simi-lar for cows fed either the BMR sor-ghum or the corn silage diet. Dietaryforage had no effect on body weight orbody condition score.

Eating, ruminating, and total chew-ing times were not different among thediets (Table 4). The similar chewingactivity reflects the similar NDF con-tent of each diet and the similar particledistribution of the silages comprisingthese diets. These rumination resultsindicate that the physically effectiveNDF content of standard and BMR sor-ghum was similar, despite the lowerlignin content of the BMR sorghum.

In vitro digestion kinetics showedthat fractional rate of NDF digestionand lag time were not affected by silagesource (Table 5). However, extent ofNDF digestion was significantly greaterfor BMR sorghum than for standardsorghum. In addition, the 30-h in vitrodigestibility of NDF was 23% greaterfor the BMR versus the standard sor-ghum silage, which would be applicableto the typical mean retention time ob-served for lactating dairy cows. Oba andAllen (1998) reported that higher NDFdigestibility would result in higherenergy intake, even if DMI was notaffected. Greater milk production withBMR sorghum than standard sorghumwas likely due to a greater energy avail-ability caused by greater extent of NDFdigestibility for BMR sorghum, eventhough the DMI was not significantlydifferent from the standard sorghum.

Lignin is a primary factor that limitsthe degradability of forage cell wall

Table 4. Effect of diet on chewing activity of lactating dairy cows.

Normal BMR1 CornItem sorghum sorghum silage SE

Eatingmin/d 170 183 161 14

Ruminatingmin/d 327 320 316 19

Total chewingmin/d 497 503 477 26

1Brown midrib.

Table 5. In vitro digestion kinetics of NDF from experimental silages.

NormalItem sorghum BMR1 Corn Alfalfa SE

Lag, h 5.7a 3.6a,b 2.6b 1.8b 1.7

Kd,2 h-1 0.057 0.061 0.050 0.070 0.006

Potential extent ofdigestion, % 55.8e 60.6d 66.1c 55.7e 0.7

r2 0.95 0.97 0.99 0.94

30-h digestion, % 40.1d 49.2c 51.6c 47.8c 0.5

a,bMeans within a row with different superscripts differ (P < 0.10).c,d,eMeans within a row with different superscripts differ (P<0.05).1Brown midrib.2Fractional rate of digestion in the rumen.

carbohydrates. The BMR mutant offorage sorghum contains substantiallyless lignin than standard forage sor-ghum genotypes, and consequently hasgreater potential as a source of digest-ible fiber for lactating dairy cows. TheBMR sorghum resulted in greater fiberdigestion, milk production, and effi-ciency of FCM production versus thestandard sorghum. In our longer-termtrial that included a combination ofalfalfa plus the test silage, the BMRsorghum resulted in milk productionsimilar to corn silage. Our data indi-cates that BMR sorghum silage issuperior to standard sorghum silage,

and because of its agronomic character-istics, BMR sorghum has the potentialto replace corn silage in diets fed tolactating dairy cows in drier regions ofthe U.S. such as the Midwestern andplains states. Future research will needto compare the economics of BMRsorghum versus alternative sources offorage fiber in complete dairy-foragesystems.

1Gokalp Aydin, former Graduate Student; andRick Grant, Associate Professor and ExtensionDairy Specialist, Animal Science, Lincoln.

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Maximal Replacement of DietaryConcentrate and Forage with a New

Wet Corn Milling Feed ProductKrishna Boddugari

Rick GrantRick Stock

Mike Lewis1

Summary

The objectives of these two experi-ments were to determine the maximalamount of dietary concentrate andforage that could be replaced with anew feed product based on ingredientsproduced by the wet corn millingindustry. Experiment 1 evaluated thereplacement of concentrate with thewet corn milling feed (CMF). The fourdiets contained 54.3% forage with CMFreplacing 0, 50, 75, or 100% of theconcentrate portion of the diet (DMbasis). The concentrate mixture com-prised soybean meal and ground corn.The NDF content of the diets rangedfrom 28.2% (0% replacement) to 41.6%(100% replacement). Milk production,milk fat, and milk fat production werenot affected by diet. The diets contain-ing CMF resulted in lower dry matterintake (DMI) than diets without theproduct. There was a significant linearreduction in milk protein as CMFreplaced concentrate despite thepredicted adequate metabolizableprotein content of the diets. Efficiencyof 4% fat-corrected milk (FCM) washigher for diets containing CMF.

In Experiment 2, the CMF replaced0, 15, 30, or 45% of dietary forage; theconcentrate portion of all diets wasentirely replaced with CMF. Dry mat-ter intake was unaffected by diet. Milkproduction increased as CMF replaced

forage, but milk fat percentage wassimultaneously depressed. Milk pro-tein synthesis was unaffected by diet.Overall, efficiency of 4% FCM produc-tion was unaffected by diet. Results ofboth experiments indicate that a newfeed product based on wet corn millingingredients has the potential to effec-tively replace all of the concentrateand a substantial portion of the foragein the diet for lactating dairy cows.

Introduction

In a summary of beef feedlot researchconducted at the University of Nebraska,efficiency of gain was improved 5.1%when diets containing wet corn glutenfeed (Sweet Bran®; Cargill Corn Mill-ing, Blair, NE) were compared withdry-rolled corn diets. Feedlot perfor-mance was similar when Sweet Bran®was fed in the range of 20 to 50% of theration dry matter. When fed in beefgrowing diets, the energy value of wetcorn gluten feed (CGF; Minnesota CornProcessors, Columbus, NE) was greaterthan when fed in finishing diets. Thisperformance response is likely due to areduction in negative associative effectsof rumen fermentable starch on fiberdigestion. The energy value of wet CGFshould be as high, or higher, in diets forlactating dairy cows, which rely onoptimal rumen fiber digestion in thepresence of substantial amounts ofconcentrate feeds.

Rumen acidosis is a significant con-cern in dairy feeding programs due to alarge consumption of concentrates. Cornbran is rapidly and highly digested inthe rumen. Research at the University of

Nebraska showed that the in situ rate ofNDF digestion for CGF was 6.8%/h. Incontrast, the rate of starch digestion inthe rumen ranges between 10 and 35%/h. Consequently, dilution of nonfibercarbohydrates with fiber from CGFshould result in slower rates of fermen-tation, reduced acid load on the rumenper unit of fermentation time, and theability to feed a highly digestible dietwith minimal risk of rumen acidosis. Inpractical terms, energy consumptionshould be maximized, rumen functionshould be normal, and solids-correctedmilk production should be optimal.

In fact, research at the University ofNebraska has shown that the effective-ness of NDF from wet CGF is approxi-mately 74% that of alfalfa silage formaintaining 4% fat-corrected milk pro-duction. But, the effectiveness of wetcorn gluten feed at stimulating rumina-tion is only 11% that of alfalfa silage.These results suggest that the primaryeffect of wet CGF is on reduction of acidload in the rumen, not on stimulation ofsalivary buffering. Finally, by increas-ing the particle length of the dietarysilage, the passage rate of CGF fromthe rumen can be reduced from 6.4 to4.3%/h. Consequently, the extent ofgluten feed NDF digestion in the rumenincreases substantially. All of this infor-mation suggests that a properly formu-lated wet corn milling feed product(CMF) could be fed at much higheramounts than currently practiced in thedairy industry.

One problem with the design of someprevious dairy research evaluating wetCGF has been that diets were balanced

(Continued on next page)

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for crude protein, but not for metaboliz-able protein. Wet corn gluten feed con-tains twice as much crude protein ascorn, but less metabolizable protein.Thus, corn control diets, using soybeanmeal or distillers grains to balance forcrude protein, may contain similar crudeprotein concentrations as wet CGFdiets, but these control diets also con-tain significantly greater amounts ofmetabolizable protein. If metabolizableprotein is not adequate with wet CGFdiets, erroneous conclusions may bemade concerning the feeding value ofthe wet corn gluten feed. Recently, NorthDakota researchers evaluated 0, 15, 30,or 45% wet corn gluten feed in isonitro-genous diets and concluded that 19%(dry basis) gluten feed was optimal formilk production. But, no attempt wasmade to balance the diets for metaboliz-able protein.

A wet corn milling feed product wasdeveloped that may improve efficiencyof milk production and lower costs ofproduction for the dairy producer.Research is needed to determine theeffects of this product on ruminal andtotal tract nutrient digestion, ruminalpH and acid production versus buffer-ing, nutrient intake, and milk compo-nent production particularly during earlylactation when dairy cows are most sus-ceptible to metabolic disorders relatedto feeding highly digestible diets.

Procedures

The research approach entailed twometabolism lactation studies to mea-sure the effect of CMF (produced byCargill Corn Milling, Blair, NE) onrumen fermentation and fiber diges-tion, plus obtain a “snapshot” of theeffect on lactational performance. Theoptimum level(s) will be evaluated in alonger-term lactation study designed tomeasure intake, milk production, bodycondition, incidence of health problems,and economics of feeding CMF.

In Experiment 1, all diets containedapproximately 27% alfalfa silage and

Table 1. Ingredient and chemical composition of diets for Experiment 1.

Concentrate replacement (% of DM)

Item 0 50 75 100

-------------------------------- (% of DM) ---------------------------------

IngredientsAlfalfa silage 27.1 27.1 27.1 27.1Corn silage 27.1 27.1 27.1 27.1Corn grain, ground 27.2 14.0 6.8 —Soybean meal, 46.5% CP 15.8 7.6 4.0 —CMF — 22.5 33.8 45.3Mineral and vitamin mix1 2.8 1.7 1.2 0.5

Chemical compositionDM, % 58.8 56.9 56.1 55.2CP 18.1 18.0 18.1 18.1ADF 18.1 19.2 21.4 22.4NDF 28.2 35.4 38.2 41.6

1Mix formulated to provide in total ration DM: Ca, 1.0%; P, 0.52%, Mg, 0.36%; K, 1.4%; 0.23 to 0.31%S; 120,000 IU/d of vitamin A; 24,000 IU/d of vitamin D; 790 IU/d of vitamin E.

Table 2. Effect of concentrate replacement on lactational performance during Experiment 1.

Concentrate replacement (% of DM)

Item 0 50 75 100 SE

DM intake, lb/d 54.3a 49.5b 50.8ab 47.9b 1.9Milk, lb/d 66.9 67.1 67.8 64.9 1.9Milk fat, % 3.54 3.84 3.59 3.82 0.16Milk protein, % 3.13a 3.10a 2.84b 2.87b 0.10Milk lactose, % 4.90 4.58 4.59 4.52 0.144% FCM, lb/d 62.3 65.6 63.6 62.7 1.9FCM/DMI, lb/lb 1.15b 1.32a 1.28ab 1.32a 0.05

abMeans within a row with unlike superscripts differ (P < 0.10).

Table 3. Ingredient and chemical composition of diets for Experiment 2.

Forage replacement (% of DM)

Item 0 15 30 45

------------------------------- (% of DM) ------------------------------

IngredientsAlfalfa silage 27.1 23.1 18.9 15.0Corn silage 27.1 23.1 18.9 15.0CMF 45.2 53.4 61.6 69.6Mineral and vitamin mix1 0.6 0.4 0.6 0.4

Chemical CompositionDM, % 56.3 55.7 53.7 58.2CP 18.3 18.9 19.3 19.9ADF 20.7 19.7 18.6 17.6NDF 41.2 40.9 40.8 40.7

1Mix contained (% of DM): 3.5% Ca; 0.46% S; 336,000 IU/kg of vitamin A; 67,000 IU/kg of vitamin D;1346 IU/kg of vitamin E.

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27% corn silage (DM basis). Theremaining 46% of the diet comprised:

1. corn, soybean meal, minerals,and vitamins,

2. 50% replacement of mix 1 withCMF,

3. 75% replacement of mix 1 withCMF, and

4. 100% replacement of mix 1 withCMF

All diets met the calculated metaboliz-able protein requirement for a cowproducing 34 kg of milk using theCornell Net Carbohydrate and ProteinModel. Also, using the Cornell Model,all diets contained at least 110% of therequirement for the essential aminoacids. All diets met or exceeded theNRC (1989) requirements for mineralsand vitamins. The calculated dietaryNFC content ranged from 29.5% (100%replacement) to 37.1% (50% replace-ment). Based on our best estimates fromprevious research at Nebraska, theeffective NDF requirement was met forall diets. Diets were fed as TMR twicedaily to encourage feed intake.

Sixteen Holstein dairy cows (4rumen fistulated), averaging 34 kg ofmilk per day, were assigned to these 4

diets in a replicated 4 x 4 Latin squaredesign balanced for any possiblecarryover effects. Period length was 4wk with sample and data collectionoccurring during the last 10 d of eachperiod. Cows were housed in a tie-stallbarn equipped with individual feedboxes for measurement of individualdry matter intake.

Daily milk production was recordedelectronically, and milk compositionwas determined weekly on compositea.m. and p.m. milk samples.

Experiment 2 was conducted similarto Experiment 1. The diets containedthe same silage mixture (1:1 alfalfa:cornsilage, DM basis). The dietary treat-ments were:

1. CMF replacing 0% of forage,2. CMF replacing 15% of the

forage,3. CMF replacing 30% of forage,

and4. CMF replacing 45% of forage

For all diets, CMF comprised the entireconcentrate portion of the diet, exceptfor minerals and vitamins. The samenumber of animals and experimentaldesign as Experiment 1 were used inExperiment 2.

Results

The CMF product developed for thesetwo experiments contained 65% DM,23.1% crude protein, 40% escape pro-tein (as a % of CP), 13.7% ADF, and40.3% NDF.

Replacing from 0 to 100% of dietaryconcentrate with CMF reduced DMI,but had no effect on milk or milk fatproduction. Efficiency of FCM produc-tion (FCM/DMI) was increased as CMFreplaced dietary concentrate. Milk pro-tein percentage was depressed forExperiment 1, despite using the CornellModel to formulate based on metaboliz-able protein and amino acids. However,these requirements were barely satis-fied for the 100% replacement diet,which was also the control diet inExperiment 2. In Experiment 2, milkprotein was not depressed, but cowsconsumed more DM and the total rationCP was slightly higher.

In Experiment 2, as CMF replacedforage, DMI was unchanged. But, milkproduction increased while milk fatdecreased. Overall, 4% FCM produc-tion was unchanged.

We were able to successfully replaceup to 70% of the dietary DM with thenew CMF product. Results of bothexperiments indicate tremendouspotential for the new wet corn millingfeed product to replace both forage andconcentrate in diets for lactating dairycows.

1Krisha Boddugari, Graduate Student; RickGrant, Associate Professor and ExtensionDairy Specialist, Animal Science, Lincoln;Rick Stock and Mike Lewis, Cargill CornMilling, Blair, NE.

Table 4. Effect of forage replacement on lactational performance during Experiment 2.

Forage replacement (% of DM)

Item 0 15 30 45 SE

DM intake, lb/d 53.2 54.1 55.7 55.9 1.9Milk, lb/d 64.4b 66.9ab 69.1a 68.4a 2.6Milk fat, % 3.72a 3.53ab 3.53ab 3.22b 0.14Milk protein, % 3.24 3.25 3.28 3.31 0.08Milk lactose, % 4.88 4.89 4.84 4.86 0.024% FCM, lb/d 61.6 62.7 65.1 62.9 1.5FCM/DMI, lb/lb 1.17 1.16 1.17 1.13 0.02

abMeans within a row with unlike superscripts differ (P < 0.10).

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Corn versus Sorghum Distillers Grains forLactating Dairy Cows

compared with corn, and also a reduc-tion in subacute ruminal acidosis due todilution of dietary starch with NDFwhen DG replaces corn grain.

Recently, Nebraska researchersevaluated wet DG produced at a com-mercial ethanol plant from a blend of80% sorghum and 20% corn DG. Simi-lar ADG and feed efficiency wereobserved when finishing beef steers werefed diets of dry-rolled corn or when 40%of the corn was replaced by wet DG.Similar ADG and feed efficiency wereobserved when finishing beef steers werefed diets of dry-rolled corn or when 40%of the corn was replaced by wet DG.These data suggest that the energy con-tent of 80% sorghum DG is similar todry-rolled corn. Additionally, the totaltract organic matter digestibility of cornDG was 5.6% greater than the 80:20mixture of sorghum and corn DG whenfed to lambs.

No analogous research concerningsorghum versus corn DG has beenconducted with lactating dairy cattle.Additionally, dairy cattle routinely arefed DG in either a wet or dry form basedprimarily on herd size and feedingsystem. The lamb NDF digestibility dataindicated an advantage for sorghumover corn DG when fed dry, but notwhen fed as wet DG. Whether this dif-ference in NDF digestibility exists fordairy cattle has not been evaluated.

The objective of this experiment wasto evaluate the effect of the same cornand sorghum DG, in both wet and dryforms, on NDF digestion and short-term lactational performance.

Procedures

Distillers grains were produced at acommercial dry milling plant (ChiefEthanol Fuels, Inc., Hastings, NE) fromone fermentation batch for each sourceof grain. Unlike previous experiments,the DG were produced from fermen-tation of either 100% corn or 100%sorghum. The wet DG were stored inplastic silage bags and the dry DG werestored in metal bins prior to initiation ofthe cattle experiments. As the silagebags and bins were filled, representa-tive DG samples were collected. Thechemical composition of the DGproducts used during the dairy experi-ment is shown in Table 1.

Twelve Holstein cows (4 primipa-rous) were assigned randomly withinparity to one of four diets in replicated 4× 4 Latin squares with 4-wk periods tomeasure DMI and milk production andcomposition. Four ruminally fistulated,multiparous cows were assigned ran-domly to the same diets to measureruminal and total tract NDF digestion,ruminal pH, and VFA concentrations.

Dietary treatments were: 1) dry corn

Shaker Al-SuwaieghRick Grant

Todd MiltonKi Fanning1

Summary

A dairy lactation experiment wasconducted to evaluate the nutritionalvalue of distillers grains (DG) fromsorghum or corn fermentation, in bothwet (35.4% DM) and dry (92.2% DM)form. Twelve early lactation Holsteincows (four ruminally fistulated) wereused in a replicated 4 × 4 Latin squaredesign with 4-wk periods. Corn andsorghum DG were fed at 15% of theration dry matter (DM) in either wet ordry form. Diets were fed as total mixedrations that contained 50% of a 1:1mixture of alfalfa and corn silages,24.3% ground corn, and 9.1% soybeanmeal (DM basis). There was no effect ofsource or form of DG on DMI, ruminalpH and volatile fatty acids (VFA), or insitu digestion kinetics of neutral deter-gent fiber (NDF) from DG, althoughthere was a trend toward lower 4% fat-corrected milk (FCM) production withsorghum DG.

Introduction

Distillers grains from fermentationof sorghum and corn grains are a com-mon component of diets for lactatingdairy cattle, but no direct comparison ofthese two DG has ever been conducted.Replacement of 40% of dry-rolled cornwith wet corn DG increased ADG andfeed efficiency relative to steers fed dry-rolled corn only in Nebraska studies.These experiments suggested that wetcorn DG contains approximately 40%more energy for gain than dry-rolledcorn. The higher energy content couldbe due to higher lipid content in DG

Table 1. Chemical composition of distillers grains.

Corn distillers grains Sorghum distillers grains

Item Dry Wet Dry Wet

DM, % 93.0 35.5 91.4 35.3

------------------------------------- % of DM ------------------------------------

CP 28.9 30.5 32.9 31.2ADF 25.5 25.3 28.4 28.5NDF 42.3 42.6 41.3 45.2

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DG; 2) dry sorghum DG; 3) wet cornDG; and 4) wet sorghum DG. All dietscontained 15% of the DG product and50% of a 1:1 mixture of alfalfa and cornsilages, 24.3% ground corn, 9.1% soy-bean meal, and 1.6% mineral and vita-min supplement (DM basis; Table 2).Diets were formulated to beisonitrogenous (18.5% CP) and fed astotal mixed rations twice daily in

amounts to ensure 10% refusals. Cowswere housed in a tie-stall barn equippedwith individual feed boxes and wereremoved twice daily for milking, exer-cise, and estrus detection for a total of 5to 6 h daily.

Daily milk production was recordedelectronically for all cows. Compositea.m. and p.m. milk samples were col-lected twice during wk 4 of each period

and analyzed for percentage of fat, pro-tein, and lactose. Body weight was mea-sured weekly immediately after the a.m.milking.

Samples of ruminal fluid were col-lected directly beneath the ruminaldigesta mat during wk 4 of each periodfrom ruminally fistulated cows at 4-hintervals for 24 h. The pH of ruminalfluid was measured immediately usinga portable pH meter, and concentrationsof VFA were determined by gas-liquidchromatography.

Fractional rate of NDF digestion ofeach DG product was measured usingthe in situ bag technique in which dacronbags containing 5 g of substrate wereincubated in duplicate within the rumenof each cow for 0, 6, 12, 24, 48, and 72h.

Total tract acid detergent fiber (ADF)and NDF digestibilities were measuredduring wk 4 of each period using theruminally fistulated cows only. Feedsamples and rectal grab samples of feceswere taken daily at the a.m. feeding forindirect estimation of digestibility. Thetotal tract ADF and NDF digestibilitieswere determined using the acid-insolubleash ratio technique.

Results

As analyzed, all diets containedapproximately 50% DM, 18.5% CP,22.7% ADF, and 32.8% NDF (DM basis;Table 2). The DG were added at 15% ofthe ration DM because a previousreview of research with DG in dairyrations indicated that this amount maybe nearly optimal for lactation diets basedon DMI and milk production response.This amount of DG resulted in approxi-mately 21.3 percentage units of dietaryNDF from forage, or about 65% of totalNDF from forage, which has resulted inincreased 4% fat-corrected milk pro-duction and DMI when compared withhigher forage control diets.

Table 3 summarizes the effect of DGon DMI and efficiency of milk produc-tion. Dry matter intake averaged 55.8lb/d or 4.0% of body weight for cows on

Table 2. Ingredient and chemical composition of experimental diets fed to lactating dairy cows.

Corn distillers grains Sorghum distillers grains

Item Dry Wet Dry Wet

Ingredient --------------------------------- % of DM ---------------------------------

Alfalfa silagea 25.0 25.0 25.0 25.0Corn silageb 25.0 25.0 25.0 25.0Corn distillers grains, dry 15.0 — — —Corn distillers grains, wet — 15.0 — —Sorghum distillers grains, dry — — 15.0 —Sorghum distillers grains, wet — — — 15.0Corn, ground 24.3 24.3 24.3 24.3Soybean meal, 46.5% CP 9.1 9.1 9.1 9.1Mineral and vitamin mixturec 1.6 1.6 1.6 1.6

CompositionDM, % 52.6 49.1 53.9 47.2CP 18.2 18.8 18.4 18.7ADF 22.5 23.1 22.4 22.9NDF 32.7 32.6 32.4 33.5

aComposition of alfalfa silage was (% of DM): 19.4% CP, 35.0% ADF, and 43.8% NDF.bComposition of corn silage was (% of DM): 8.9% CP, 24.2% ADF, and 41.4% NDF.cMixture contained 15.2% Ca, 7.2% P, 4.1% Mg, 4% Na, 3000 ppm of Zn, 1,750 ppm of Mn, 400 ppmof Cu, 200,000 IU/kg of vitamin A, 36,000 IU/kg of vitamin D3, and 600 IU/kg of vitamin E.

Table 3. Performance responses to corn and sorghum distillers grains fed to lactating dairy cows.

Corn distillers grains Sorghum distillers grains

Item Dry Wet Dry Wet SE

DMIlb/d 54.5 56.9 56.9 55.2 2.2% of BW 3.9 4.0 4.1 4.0 0.2

BW, lb 1408 1421 1410 1404 35BW change

per period, lb 22.4 24.6 24.8 33.2 11.2

4% Fat-corrected milk, lb/d 73.3 72.6 70.3 69.0 3.9FCMa/DMI, lb/lb 1.3 1.3 1.3 1.2 0.1

Milk fat% 3.7 3.6 3.5 3.5 0.1lb/d 2.8 2.6 2.6 2.4 0.2

Milk protein% 3.4 3.3 3.2 3.2 0.1lb/d 2.6 2.4 2.4 2.2 0.2

Milk lactose% 4.7 4.6 4.7 4.8 0.1lb/d 3.5 3.5 3.7 3.5 0.2

aFat-corrected milk. (Continued on next page)

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all diets. Neither BW nor change in BWper 4-wk period was affected by diet.Numerically, 4% fat-corrected milk pro-duction was approximately 6% lowerfor the sorghum DG diets; there was atrend (P = 0.15) toward reduced fat-corrected milk production for cows fedthe sorghum DG. Efficiency of 4% fat-corrected milk production was similarfor all diets and averaged 1.28. Milk fatproduction was unaffected by diet andreflected the high ruminal pH observedfor cows consuming all diets (Table 4).

Nearly all previous research withlactating dairy cows has evaluated re-placement of dietary corn or soybeanmeal with DG, rather than comparingsource or form of DG. Early researchwith dry DG (source not specified) indi-cated that DG inclusion in the ration inplace of corn grain or soybean mealoften increased milk fat production.More recently, Nebraska researcherscompared dry corn DG with solvent-extracted soybean meal in diets for earlylactation dairy cows that contained 50%of an alfalfa and corn silage mixture. Inthis experiment, there were no differ-ences in DMI or milk productionbetween the two sources of protein. Inour study, all diets contained soybeanmeal plus DG and supplied adequatemetabolizable protein for cows in earlylactation.

Ruminal pH and acetate to propi-onate ratio indicated that DG from cornor sorghum, whether wet or dry, resultedin ruminal conditions that were optimalfor cell wall fermentation (Table 4). Alldiets resulted in an acetate to propionateration greater than 2.0; ratios below 2.0have been associated with milk fat de-pression. Similarly, the ruminal NDFdigestion rate and extent of DG werehigh, reflecting the high fibrolytic ac-tivity associated with ruminal pH greaterthan 6.2. The fractional rate, lag, andextent of NDF digestion observed forcorn and sorghum DG were within therange observed previously for othernonforage sources of fiber. Apparent

extent of ruminal NDF disappearancefrom DG (assuming a fractional pas-sage rate from the rumen of .050 h-1)ranged between 39 and 46%, with nodifference among treatments (Table 5).Total tract ADF and NDF digestibilitywas unaffected by diet and values weretypical of a highly digestible lactationration containing fibrous coproduct feedssuch as DG.

In summary, the dairy experimentdemonstrated that short-term lactationalperformance of early lactation dairy cowswas similar (P>0.10) for wet versus dryDG. Additionally, supplementing the

Table 4. Effect of corn and sorghum distillers grains on ruminal pH and volatile fatty acidconcentrations.

Corn distillers grain Sorghum distillers grains

Item Dry Wet Dry Wet SE

Rumen pH 6.30 6.50 6.55 6.45 0.11

Total VFA, mM 96.1 98.7 96.9 96.5 0.9Acetate (A) 53.9 54.0 54.4 54.7 0.5Propionate (P) 24.9 24.4 25.2 25.1 0.3Butyrate 16.3 16.4 15.5 15.4 0.4Isobutyrate 1.5 1.4 1.2 1.2 0.1Valerate 1.7 2.0 2.0 1.9 0.1Isovalerate 1.7 1.8 1.6 1.7 0.1

A:P 2.20 2.23 2.18 2.15 0.04

Table 5. Digestibility of corn and sorghum distillers grains and total tract fiber digestion.

Corn distillers grain Sorghum distillers grains

Item Dry Wet Dry Wet SE

In situ NDF digestion ofdistillers grains

Lag, h .6 0 0 0Rate, h-1 .059 .041 .042 .062Extent, % 87.8 86.4 85.1 81.5r2 .96 .93 .93 .99

Apparent extent of NDFdisappearancea 46.1 39.0 38.9 45.2

Total tract digestion, %ADF 62.5 59.7 58.9 57.7 5.7NDF 64.7 59.2 66.3 62.6 6.9

aCalculated using the following equation assuming a fractional passage rate of distillers grains from therumen of .050 h-1: e -kpL x [kd/(kd + kp)] x PED, where kp = fractional passage rate of distillers grain particlesfrom the rumen, kd = fractional rate of ruminal NDF digestion, and PED = potential extent of ruminal NDFdigestion.

ration with DG from either source at15% of the DM had no deleterious effectson ruminal pH, NDF fermentation, ortotal tract NDF digestibility. A longer-term lactation study would clarify thesignificance of the trend observed in 4%fat-corrected milk production.

1Shaker Al-Suwaiegh, Graduate Student; RickGrant, Associate Professor and Extension DairySpecialist; Todd Milton, Assistant Professor andExtension Feedlot Specialist; Ki Fanning, GraduateStudent, Animal Science, Lincoln.

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Longer Particle Length Alfalfa ImprovesUse of Wet Corn Gluten Feed by Dairy Cows

Dana AllenRick Grant1

Summary

Twelve early lactation Holstein cows(4 fistulated) were used in replicated4 × 4 Latin squares with 4-wk periods todetermine the effective neutral deter-gent fiber (NDF) content of wet corngluten feed and to measure the effect offorage particle size on ruminal matconsistency and passage rate of wetcorn gluten feed. Diets were 1) 23.3%NDF (17.4 percentage units NDF fromalfalfa silage), 2) diet 1 plus 11.1 addi-tional percentage units NDF fromalfalfa silage, 3) diet 1 plus 10.7 per-centage units NDF from wet corn glutenfeed, and 4) 8.6 percentage units NDFfrom alfalfa silage plus 8.9 percentageunits NDF from coarsely choppedalfalfa hay with 10.7 percentage unitsNDF from wet corn gluten feed. Thecalculated effective NDF factor for wetcorn gluten feed, using change in milkfat concentration per unit change inNDF, was 0.74 compared with anassumed 1.0 for alfalfa silage. Rumi-nation activity was measured to cal-culate a physically effective NDF factorfor wet corn gluten feed which was only0.11 compared with 1.0 for alfalfasilage. Physically effective NDF alsowas determined for wet corn glutenfeed by wet sieving; 22% of the par-ticles were retained on the 3.35-mmscreen or greater. Ruminal mat consis-tency increased and passage rate ofwet corn gluten feed decreased withadded hay. The inclusion of choppedalfalfa hay to a diet containing wetcorn gluten feed increased ruminal matconsistency, rumination activity, andslowed passage rate resulting in greaterruminal digestion of NDF from wetcorn gluten feed. Depending on the

tively as dietary forage due to theirsmall particle size. Therefore, it isimportant to consider the effective NDFcontent of these fiber sources. EffectiveNDF is defined as the fraction of NDFthat maintains milk fat synthesis andprovides optimal ruminal conditions formaximum fiber fermentation. Physicallyeffective NDF (peNDF) specificallyreflects the ability of the feed to stimu-late chewing and subsequent salivationand ruminal buffering. Effectivenessfactors for feeds have been estimatedusing three approaches 1) change inmilk fat concentration, 2) change inrumination activity, and 3) sieving andparticle size analysis. Ration formula-tion requires that accurate effective NDFvalues be determined for nonforagesources of fiber, but various methods ofdetermining effective NDF have resultedin inconsistent values for the same feed.For example, Wisconsin researchersmeasured effective NDF of CGF, usingmilk fat percentage as the response vari-able, and found that in two separatetrials the values differed by 56%.

The objectives of this research were1) to evaluate the effect of altering for-age particle size on ruminal mat consis-tency, rumination activity, passage rateof WCGF, and milk production, and 2)to determine the effective NDF contentof WCGF relative to a high-fiber con-trol diet based on response in milk fatconcentration, rumination activity, andparticle size distributions.

Procedures

Twelve Holstein dairy cows (8 mul-tiparous including four ruminallyfistulated) were used in a replicated4 × 4 Latin square design with 4-wkperiods. Fiber sources compared werealfalfa silage, alfalfa hay, and WCGF.Chemical composition and particle dis-tribution of dietary fiber sources are

response variable, effectiveness of NDFfrom wet corn gluten feed varied from0.11 to 0.74.

Introduction

A coproduct of wet milling of corn,wet corn gluten feed (WCGF) is prima-rily a mixture of corn bran and fer-mented corn extractives (steep liquor).Although WCGF contains 40 to 45%NDF, it only contains 3% lignin and isa source of highly digestible fiber. Asdairy operations increase in size, theability to use wet coproduct feedsincreases. When incorporating non-forage sources of fiber, such as WCGF,into rations for lactating dairy cows,there are at least two major consider-ations 1) the interaction between forageand nonforage fiber in terms of ruminalpassage and digestion, and 2) the effec-tive NDF content of the nonforage sourceof fiber.

The rumen digesta mat is a highlyeffective first-stage separator. Throughthe processes of filtration and mechani-cal entanglement, the mat selectivelyretains potentially escapable fiber par-ticles, thereby increasing the timeallowed for fermentation. Fine particleswith a mean length of less than 1.0 mmwere found in high concentrations over24 h in the dorsal rumen, which alsocontained the greatest amount of largeparticles. The consistency of the rumi-nal mat (hard or soft packed) eitherpromotes or retards particle passagefrom the reticulorumen. In the onlyprevious study with lactating dairy cows,researchers at Nebraska observed a 16%decrease in fractional passage rate ofsoybean hulls from the rumen of cowsfed coarsely chopped hay to increaseruminal mat consistency of an alfalfaand corn silage blend.

Nonforage sources of fiber do notstimulate rumination activity as effec-

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shown in Table 1. The WCGF wasdelivered and stored in a plastic silagebag prior to the start of this experiment.There was no visual evidence of mold-ing while feeding the product duringthe experiment.

Dietary treatments were 1) basal low-fiber alfalfa silage diet (LF) formulatedto contain 23.3% NDF (17.4 percentageunits of NDF from alfalfa silage), 2)high-fiber alfalfa silage diet (HF) for-mulated to contain 31.9% NDF (LF dietplus an additional 11.1 percentage unitsof NDF from alfalfa silage), 3) WCGFdiet formulated to contain 31.6% NDF(LF diet plus 10.7 percentage units ofNDF from WCGF), and 4) WCGF dietplus coarsely chopped alfalfa hay for-mulated to contain 32.0% NDF (8.6percentage units of NDF from alfalfasilage plus 8.9 percentage units of NDFfrom alfalfa hay plus 10.7 percentageunits of NDF from WCGF). Diets wereformulated to be isonitrogenous (18%CP, DM basis). The calculated RUPrequirements were met by adding SoyPass® (a nonenzymatically brownedsoybean meal containing 70% RUPmanufactured by Lignotech USA,Rothschild, WI) to the diet to achieve5.6 to 6.3% RUP (DM basis, Table 2).With these diets, an increase in milk fatconcentration or rumination activity forcows fed the LF versus the HF dietwould be attributable to additional NDFfrom alfalfa silage. Similarly, an in-crease in milk fat concentration or ru-mination activity for cows fed the LFversus the WCGF diet would be attrib-utable to additional NDF from WCGF.The effect of increasing dietary forageparticle length on ruminal mat consis-tency and passage kinetics of WCGFwould be determined by comparing re-sponses to the WCGF diet with or with-out added chopped hay.

Experimental periods were 28 d; thelast 7 d were used for sample and datacollection. Diets were fed once daily inamounts to ensure 10% refusals. Bodyweight was measured each week imme-diately after a.m. milking. Daily milkproduction was recorded electronicallyfor all cows. Composite a.m. and p.m.

Table 1. Chemical composition and particle distribution of alfalfa silage, alfalfa hay, and wet corngluten feed.

Fiber source

Item Alfalfa silage Alfalfa hay WCGF1

----------------------------- (% of DM) -----------------------------

DM, % 46.3 88.9 62.5CP 21.2 17.6 23.4ADF 31.6 34.7 11.7NDF 43.4 47.3 43.9NEL, Mcal/kg 1.52 1.19 1.98

Particle distribution2

% > 9.5 mm 27.0 44.0 1.03.35 mm < % < 9.5 mm 22.0 24.0 21.01.18 mm < % < 3.35 mm 8.0 15.0 10.00.3 mm < % < 1.18 mm 3.0 3.5 8.00.053 mm < % < 0.3 mm 3.0 1.0 6.5% < 0.053 mm 37.0 12.5 53.5

Physically effective NDF3, %> 1.18 mm 57.0 83.0 32.0> 3.35 mm 49.0 68.0 22.0

1Wet corn gluten feed.2Determined by wet sieving.3Physically effective NDF calculated according to Mertens (1997). Neutral detergent fiber content ofparticles retained on 1.18-mm screen and greater was: alfalfa silage, 53.5%; alfalfa hay, 66.5%; andWCGF, 76.5%.

Table 2. Ingredient and chemical composition of dietary treatments.

Diet1

Item LF HF WCGF WCGFH

Ingredient ----------------------------- (% of DM) -----------------------------

Alfalfa silage 40.0 65.7 39.8 19.9Alfalfa hay — — — 18.8WCGF — — 24.4 24.4Ground corn 46.3 29.2 28.6 26.9Soybean meal 6.5 1.7 2.1 4.8Soy Pass®2 3.7 — 1.7 1.7Mineral and Vitamin mix3 3.5 3.5 3.5 3.5

CompositionDM, % 66.0 56.3 62.0 70.1NDF 23.3 31.9 31.6 32.0

Alfalfa silage (% of NDF) 17.4 28.5 17.3 8.6Alfalfa hay (% of NDF) — — — 8.9WCGF (% of NDF) — — 10.7 10.7

ADF 15.8 22.4 17.3 17.5CP 18.1 18.0 18.4 18.5NEL, Mcal/kg 1.78 1.67 1.78 1.73

Particle distribution4 ----------------- (% of DM retained on screen) ------------------

% > 9.5 mm 10.0 9.8 7.3 11.6% > 3.35 mm 58.2 52.2 47.4 45.2% > 1.18 mm 72.3 66.4 60.1 60.30.053 mm <% < 1.18 mm 9.8 12.8 14.0 14.1% < 0.053 mm 17.9 21.1 25.9 25.6

1LF = low fiber, HF = high fiber, H = chopped hay, WCGF = wet corn gluten feed.2Nonenzymatically browned soybean meal (Lignotech USA, Rothschild, WI).3Supplement contained 7.9% Ca, 2.6% P, 1.8% Mg, 2.2% Na, 1,026 ppm of Zn,718 ppm of Mn, 128 ppm of Cu, and 15,358, 3,072, and 94,270 IU per kilogram of Vitamin A, D, and E,respectively.4Determined by wet sieving.

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milk samples were collected twice dur-ing wk 4 of each period and analyzed forpercentage of milk fat, protein and lac-tose.

Forage, concentrate, and TMRsamples were composited daily duringthe last 7 d of each collection period forchemical analysis. Particle size wasdetermined on masticate, ruminaldigesta, and fecal samples collected atapproximately 4 h postfeeding on thelast day of each period using wet siev-ing. Particle size distributions were alsodetermined for composite TMR, forageand WCGF samples during each pe-riod. Additionally, rumens were emp-tied, and digesta was weighed andsampled for DM and NDF analyses todetermine ruminal fill.

Total chewing, eating, and ruminat-ing times were determined during thelast wk of each collection period.Ruminal fluid samples were collectedvia ruminal fistula immediately beneath

the ruminal mat at 4-h intervals for 24h during the last d of each period. Rumi-nal pH was determined immediatelyusing a portable pH meter. Fractionalpassage rate of WCGF fiber from therumen was determined using Er as arare earth marker. To determine frac-tional rate of ruminal NDF digestion ofWCGF, 5-g samples of dried, ungroundWCGF were measured into dacron bagsusing the in situ bag technique.

The effect of increasing dietary par-ticle size on ruminal mat consistencywas determined using a techniqueadapted from Welch (1982) as describedby Weidner and Grant (1992). Ruminalmat consistency was measured at 3 hpostfeeding. A 454-g weight was placedin the ventral rumen 1 h prior to mea-surement to ensure normal mat refor-mation. Upon release of an exterior1500-g weight, ascension of the 454-gweight through the ruminal contentswas recorded every 10 s for 120 s. The

ascension rate, in centimeters per sec-ond, was considered to be an indicationof ruminal mat consistency.

Results

Cows fed the WCGF diets consumedthe greatest amount of DM (Table 3).This higher DMI likely reflected thesmaller particle size of the WCGF dietsand the faster rate of passage for WCGFversus alfalfa silage. Averaged over alldiets, NDF intake was 1.23% of BW,which is typical of cows in this stage oflactation.

Milk yield was numerically increasedby 6.4% versus the LF diet for cows feddiets containing WCGF (Table 4). Cowsfed the HF diet produced the least amountof milk. Production of 4% FCM wasnumerically greater for the WCGF dietwith added chopped hay compared withother treatments. Efficiency of milk pro-duction, calculated as FCM/DMI, washighest for cows fed the HF diet (1.17)and lowest for cows fed the LF diet(1.07); however, no significance amongtreatments was detected.

Milk fat concentration was signifi-cantly less for cows fed the LF dietcompared with cows fed the HF diet.This response can be attributed to inad-equate amount and physical form ofNDF needed for acetate production andmaintenance of milk fat synthesis forcows fed the LF diet. The increase inmilk fat percentage for cows fed the HFdiet can be attributed to additional al-falfa silage and to additional NDF fromWCGF in the WCGF plus hay diet. Thechange in milk fat concentration wasused to calculate an effective NDF fac-tor for WCGF. Milk protein concentra-tion was different among treatments(Table 4). Cows fed the WCGF diet withadded hay produced significantly greatermilk protein than cows fed the HF diet,although the difference was small at0.15 percentage units.

Dairy cattle require fiber of adequateparticle size to maintain a healthy rumi-nal environment. Recently, ruminationactivity has been used as an estimate ofthe physical effectiveness of fiber sources

Table 3. Consumption of DM, NDF, and ADF by cows fed experimental diets.

Diet1

Item LF HF WCGF WCGFH SE

DMIlb/d 53.2ab 49.3b 55.2a 57.4a 2.4% of BW 4.2ab 3.9b 4.4a 4.5a <0.1

NDFlb/d 12.5c 15.6b 17.6a 18.3a 0.7% of BW 0.9c 1.2b 1.4a 1.4a <0.1

ADFlb/d 8.4c 11.0a 9.7b 9.9b 0.4% of BW 0.7c 0.9a 0.8b 0.8b <0.1

a,b,cMeans within row with unlike superscripts differ (P < 0.10).1LF = low fiber, HF = high fiber, H = chopped hay, WCGF = wet corn gluten feed.

Table 4. Lactational performance of cows as influenced by experimental diets.

Diet1

Item LF HF WCGF WCGFH SE

Milk, lb/d 68.6 64.8 72.1 74.3 4.1Fat

% 2.90b 3.25a 3.15ab 3.14ab 0.11lb/d 2.00 2.13 2.16 2.33 0.18

Protein% 2.97ab 2.85b 2.95ab 3.00a 0.06lb/d 2.00ab 1.84b 2.11ab 2.22a 0.13

Lactose% 4.87 4.86 4.89 4.88 0.07lb/d 3.34 3.15 3.52 3.63 0.22

4% FCM, lb/d 57.2 57.6 61.4 64.8 4.14% FCM/DMI, lb/lb 1.07 1.17 1.11 1.13 0.06BW, lb 1285 1261 1254 1255 13.2a,bMeans within a row with unlike superscripts differ (P < 0.10).1LF = low fiber, HF = high fiber, H = chopped hay, WCGF = wet corn gluten feed.

(Continued on next page)

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at stimulating salivary secretion andruminal buffering. Table 5 summarizeschewing activity as influenced by dietarytreatment. Cows fed the HF diet spentsignificantly more time eating andruminating per day compared with theLF diet. Addition of chopped alfalfa hayto the WCGF diet resulted in rumina-tion activity similar to the HF diet (475and 504 min/d, respectively). Byincreasing dietary particle size withreplacement of 47% of the alfalfa silagewith alfalfa hay, chewing activity wasincreased for the WCGF diet with hayversus the same diet without hay.

Ruminal pH was greatest for the HFdiet (6.36; Table 6). Because rumina-tion activity stimulates salivary secre-tion of bicarbonate and phosphate buff-ers, ruminal pH would be expected to behigher for diets that stimulate greaterrumination. Ruminal pH was numeri-cally higher for the WCGF plus hay dietversus the WCGF diet. Furthermore,the pH values for the LF, HF, and WCGFdiets resulted in a calculated effective-ness factor for NDF from WCGF ofapproximately 13%. Michigan Stateresearchers have suggested the use ofruminal pH as an accurate estimate ofthe physical and chemical characteris-tics of fiber from nonforage sources offiber. Ruminal VFA concentrations weredetermined for each dietary treatment(Table 6). Increased dietary NDF for theHF and WCGF diets did not result ingreater acetate to propionate ratios,which averaged 2.15 for all diets.

Specific gravity and particle sizeaccount for 88% of the variation inparticle passage from the rumen.Nonforage sources of fiber often haveboth a high specific gravity and smallparticle size, resulting in decreasedruminal retention time and lowered NDFdigestibility. Therefore, addition ofalfalfa hay to the WCGF diet allowed acomparison of the effects of increasingdietary particle length on ruminal matconsistency, particle retention time, andruminal NDF digestibility. At 3 hpostfeeding, the WCGF diet withchopped hay had a significantly slowerrate of ascension (centimeters per sec-

Table 5. Chewing activity as influenced by diet.

Diet1

Activity LF HF WCGF WCGFH SE

Eatingmin/d 190b 237a 175b 192b 17

Ruminating min/d 339b 504a 356b 475a 23

Total chewingmin/d 529c 740a 531c 667b 23

a,b,c,dMeans within a row with unlike superscripts differ (P < 0.10).1LF = low fiber, HF = high fiber, H = chopped hay, WCGF = wet corn gluten feed.

Table 6. Ruminal pH and VFA as influenced by diet.

Diet1

Item LF HF WCGF WCGFH SE

pH 5.95b 6.36a 6.00b 6.14b 0.08Total VFA, mM/L 104.5 102.7 103.8 104.5 0.9VFA, mol/100 mol

Acetate (A) 57.2 56.0 57.0 56.9 0.6Propionate (P) 25.9 25.4 25.6 25.7 0.3n-Butyrate 16.8 16.9 16.8 17.1 0.4Isobutyrate 1.3 1.2 1.3 1.2 0.1n-Valerate 1.8 1.7 1.6 1.9 0.2Isovalerate 1.6 1.6 1.6 1.7 <0.1

A:P 2.2 2.0 2.2 2.2 <0.1a,bMeans within a row with unlike superscripts differ (P < 0.10).1LF = low fiber, HF = high fiber, H = chopped hay, WCGF = wet corn gluten feed.

Table 7. Ruminal mat consistency as influenced by dietary treatment.

Diet1

Item LF HF WCGF WCGFH SE

Distance traveled, cm10 s 8.3a 3.0b 7.3a 4.0b 1.2120 s 34.0a 17.0c 31.4a 23.4b 1.4

Ascension rate, cm/sec10 s 0.80a 0.30c 0.70ab 0.40bc 0.10120 s 0.28a 0.14c 0.26a 0.19b <0.10

a,bMeans within a row with unlike superscripts differ (P < 0.10).1LF = low fiber, HF = high fiber, H = chopped hay, WCGF = wet corn gluten feed.

ond) than the WCGF diet (Table 7),reflecting a more consistent, hard-packed ruminal mat. The total distancetraveled in 120 s was also greater for theWCGF diet compared with the WCGFdiet plus hay. Adding alfalfa haydecreased ascension rate similar to theHF diet, whereas the WCGF diet wassimilar to the LF diet (0.26 versus 0.28,cm/s, respectively).

Table 8 contains the rate of passageand in situ digestion data for the diets.The HF diet resulted in the greatestamount of ruminal NDF and the LF dietresulted in the least amount of NDF. We

observed that passage of WCGF fromthe rumen was significantly decreasedfor the WCGF diet plus hay comparedwith the WCGF diet (0.042 versus 0.068/h, respectively). Apparent extent ofruminal NDF digestion was calculatedand combines both NDF digestion andpassage. By decreasing ruminal rate ofpassage, addition of alfalfa hay resultedin an increased extent of digestion forthe WCGF diet versus the WCGF dietwithout added hay (47.4 versus 32.4%,respectively).

Three methods have been used todetermine effective NDF 1) change in

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may reflect the chemical and physicalattributes of WCGF as a highly digest-ible fiber which is capable of dilutingdietary NFC and slowing rate of fer-mentation acids production, yet is only11% as effective as alfalfa silage atmaintaining rumination activity due toits small particle size.

Mertens (1997) proposed using thelaboratory technique of particle sieving.In our study, particle distributions weredetermined for each fiber source. Par-ticles retained on the 1.18-mm screenand greater were 57, 83, and 32% foralfalfa silage, alfalfa hay and WCGF,respectively. These larger particles re-quire rumination and reduction in sizefor passage from the reticulorumen tooccur. Particles retained on the 3.35-mm screen and greater are more appli-cable to larger ruminants. Therefore,the peNDF factor for WCGF would be0.22 compared with alfalfa silage at0.49. This suggests that the alfalfa silageused in our experiment was not 100%effective, emphasizing the need to stan-dardize effective NDF values based onone fiber source.

Interactions between forage andnonforage sources of fiber are not clearlyunderstood. Coarsely chopped haydecreased passage rate of WCGF,increased rumination activity, andincreased ruminal extent of NDF diges-tion compared with the WCGF dietwithout hay. Effective NDF values canvary substantially, depending on theresponse variable chosen to calculatethe effectiveness factor. To be conserva-tive, a smaller peNDF value should beused to avoid a situation in which rumi-nal acidosis could occur. More researchis needed to confirm if in fact somenonforage sources of fiber, such asWCGF, have effectiveness factorsgreater than 50%. Quantitating the im-pact of dietary forage on utilization ofnonforage sources of fiber will allow usto define accurately the peNDF require-ment of lactating dairy cows.

1Dana Allen, former Graduate Student; RickGrant, Associate Professor and Extension DairySpecialist, Animal Science, Lincoln.

Table 8. Ruminal content characteristics, passage rate of WCGF fiber, and in situ NDF digestionkinetics of WCGF.

Diet1

Item LF HF WCGF WCGFH SE

Rumen contentsWet weight, lb 403.3 414.3 375.0 405.7 19.6Dry matter, % 18.5 19.5 20.0 20.5Dry weight, lb 74.4 80.7 74.8 83.2 3.9NDF, % 60.0 65.0 67.5 65.0 0.3NDF, lb 44.7c 54.3a 49.3bc 53.5ab 1.7

Rate of passage, %/h 5.20ab 4.20b 6.40a 4.20b 0.60Digestion kinetics

Lag, h 5.80 4.20 5.40 3.50 1.14kd, %/h 5.40ab 6.70a 6.40ab 5.10b 0.50PED2, % 92.8 92.8 92.9 92.7 0.6AED3, % 32.6b 47.4a 32.4b 44.8a 2.3

a,b,cMeans within a row with unlike superscripts differ (P < 0.10).1LF = low fiber, HF = high fiber, H = chopped hay, WCGF = wet corn gluten feed.2Potential extent of ruminal fiber digestion calculated using equations in Grant (1994).3Apparent extent of ruminal fiber digestion calculated using equations in Grant (1994).

Table 9. Calculation of effective NDF and physically effective NDF based on change in milk fatconcentration and rumination activity as influenced by dietary treatment.

Fiber source

Item Alfalfa silage WCGF1

Milk fat2

Increase in milk fat %, a 0.35 0.25Added NDF %, b 11.00 10.70Slope, a/b 0.03 0.02eNDF factor3 1.00 0.74Chemical NDF, % 43.40 43.90Effective NDF, % 43.40 32.90

Rumination activity4

peNDF factor 1.00 0.11Physically effective NDF, % 43.40 4.80

Ruminal pH5

eNDF factor 1.00 0.13Effective NDF, % 43.40 5.71

1WCGF = wet corn gluten feed.2Based on data in Table 4.3Effectiveness of alfalfa assumed to be 1.0.4Based on data in Table 5.5Based on data in Table 6.

milk fat concentration, 2) change inrumination activity, and 3) evaluationof particle size distributions. Becausemilk fat is dependant on fiber digestionand production of fermentation acids inthe rumen, it is thought to be the mostcomplete measure of effective NDF. Inour study, an effective NDF value basedon change in milk fat concentration wascalculated using the slope-ratio tech-nique as shown in Table 8. Milk fatincreased in HF and WCGF diets com-pared with the LF diet to yield an effec-

tive NDF factor of 0.74 for WCGF ifalfalfa silage is assumed to be 1.0. There-fore, WCGF contained 32.9% effectiveNDF based on change in milk fat per-centage. Using the same technique tocalculate peNDF based on change inrumination activity, the peNDF factorfor WCGF was 0.11 compared with anassumed value of 1.0 for alfalfa silage.An effective NDF factor based on changein ruminal pH (Table 6) of 0.13 wassimilar to the peNDF value for rumina-tion activity. The large range in values

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Genetics Research

Jeffrey F. Keown1

Summary

Often, producers ask what type ofresearch is being conducted in thegenetics area. This is a legitimatequestion, so I am listing in abstractform six areas that my students haveresearched this past year. The next sixarticles are written in a more formalmode, but I think you will have anunderstanding of the scope of theresearch involved. In the dairy geneticsarea are students from the United States,Saudi Arabia, India, South Korea,Japan, Mexico and Brazil. Most ofour research is conducted using pro-ducers’ records from the Dairy RecordsProcessing Center in Raleigh, NorthCarolina.

New Age-month Correction Factorsfor Milk Production of HolsteinCattle in Mexico

M. Valencia-Posadas1

Correction factors (CF) for milk pro-duction used nationally in Mexico wereestimated 23 years ago using a siremodel with few records and assuming avalue of heritability. Since those CFwere adopted, many changes of man-agement practices have occurred. NewCF are needed to reduce possible biasesin genetic evaluations. The objectives ofthis study were to estimate age-monthCF for milk production by region and tocompare currently used CF and thoseobtained in this study. Records wereprovided from the Mexican HolsteinAssociation. Only 305d milk yields wereconsidered. Records were classified bythree regions. Numbers of records,including all lactations, were 12,062,42,059, and 17,990 for the North (N),Central (C) and South (S) regions,respectively. The base group includedcows calving in January between 70-73months of age. Variance components

and age-month solutions were obtainedby REML using an animal model. Aver-ages of milk production and heritabilityestimates were 8,446, 7,841, and 7,176kg and 0.26, 0.24, and 0.18 for N, C, andS regions, respectively. Deviations ofsolutions from base groups weresmoothed through polynomial regres-sion and then used to obtain the CF.Differences (DIF) between new CF foreach region and current national CFwere obtained. Analysis of variance wasused to test equality between them. Cor-relations between CF also were esti-mated. Correlations between current CFand the new CF by region were only0.89 to 0.92. The new CF was differentbecause group of age and month effectswere significant for DIF. The new CFcould be less biased than current CFbecause an animal model was used withthe most recent records and with spe-cific CF for each region.

Heterogeneity of Variance andInteraction of Genotype byEnvironment for Milk Production inHolstein Cattle in Mexico

M. Valencia-Posadas1

For the establishment of selectionprograms for dairy cattle in Mexico it isimportant to determine if heterogeneityof variance exists for milk productionand to investigate genotype x environ-ment interaction (GxE) among regions.The objectives of this study were 1) toestimate variance components (VC) byregion and periods of time, 2) to esti-mate VC after classifying herd-years bystandard deviation level (SDL), and 3)to investigate GxE between regions.Records were provided from the Mexi-can Holstein Association. Only matureequivalent 305d milk yields were con-sidered. Records were classified by threeregions (North, Central, and South),three periods of time (1973-1983, 1984-1990, and 1991-1997) and herd-yearsdivided in three SDL (high, medium,

and low). Separate analyses were madefor first and all lactations. The VC wereobtained by REML using an animalmodel. To study GxE, genetic correla-tions (rg) were obtained through daugh-ters of sires distributed among regions.The likelihood ratio test was used to testif rg between two regions was differentfrom one. Evidence for heterogeneity ofvariance, principally additive geneticvariance, was found among regions andperiods of time with analyses of first andall lactations. Heritability estimates were0.18 to 0.31 for all lactations and 0.21 to0.31 for first lactations. Even thoughgenetic and phenotypic variances weredifferent for records classified by SDL,heritabilities were similar (0.23, 0.21,and 0.24, for high, medium, and lowSDL, respectively). The rg between theNorth and South regions was statisti-cally different from one (0.38), indicat-ing the presence of GxE. Importantdifferences in ranking of sires by regionswere found in all analyses.

Genetic Parameters for LongevityTraits for Holstein Cattle in Mexico

M. Valencia-Posadas1

The Mexican Holstein Association(MHA) has not until now utilized recordsto estimate genetic parameters or EBVfor longevity traits. Different variablesand methods of analyses have been usedto study longevity and to estimate geneticparameters in dairy cattle. The objec-tive of this study was to estimate herita-bilities (h2) and genetic correlations(rg) between lifetime and stayabilitytraits and milk production of first lacta-tion. Records of Holstein cattle wereprovided from MHA. Only matureequivalent 305d milk yields were con-sidered. Most recent year of birth was1988. Cows were assumed to have beenculled or died after last recorded lacta-tion. Total number of cows was 46,026.Lifetime traits were: number of lacta-

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tions initiated (NLI), total milk produc-tion over all lactations (TMP), and lengthof productive life (LPL). Stayability traitswere: stayability to 36, 48, 60, and 72months of age (S36, S48, S60, and S72,respectively). Milk production for firstlactation (MP1) was used to obtain rgwith lifetime and stayability traits. Vari-ance components were estimated utiliz-ing REML for animal models. Aver-ages for NLI, TMP, LPL, and MP1 were2.63, 18,530 kg, 1,812 days, and 6913kg, respectively. Percentage of live cowsat 36, 48, 60, and 72 months of age was95, 66, 42, and 25%, respectively. Heri-tability estimates for lifetime traits were0.11 to 0.14, for MP1 was 0.30 and forstayability traits were 0.05 to 0.09. Allrg between lifetime and S48, S60, andS72 were greater than 0.85. The NLI,TMP, and LPL are essentially the sametrait because estimates of rg betweenthem were about 0.94. The MP1 andS48 can be used as early indicators oflongevity (i.e., for TMP and LPL)because of high estimates of rg. Thetraits analyzed in this study could beused in selection programs for Holsteincattle in Mexico.

Variance Due to Cytoplasmic Lineand Sire by Herd Interaction Effectsfor Milk Yield Considering REMLBias

P. R. N. Rorato1

A total of 138,869 lactation milkyields (305 d, 2x, ME) from first threeparities of 68,063 New York Holsteincows were used to estimate variancecomponents due to additive directgenetic, cow permanent environmental(cow within sire for sire model), sire byherd interaction, and cytoplasmic lineeffects. The original data (OD) wereassigned to ten random samples whichwere each analyzed using an animalmodel (AM) and a sire model (SM).From each sample of OD, twenty othersamples with levels assigned randomlyto cytoplasmic and interaction effects(data with randomly simulated levels -SL) were analyzed, of which ten wereanalyzed with an AM and ten with a SM.

The models also included fixed effectsof herd-year-seasons. Average fractionsof phenotypic variance and average stan-dard errors were respectively for AMand SM: for additive direct genetic ef-fects, .300 (.029) and .228 (.040) for(OD) and .325 (.025) and .262 (.039) for(SL); for cow permanent environmentaleffects, .242 (.024) and .444 (.014) for(OD) and .235 (.025) and .492 (.016) for(SL); for sire by herd interaction effects,.015 (.008) and .018 (.007) for (OD) and.003 (.007) and .004 (.009) for (SL); andfor cytoplasmic line effects, .011 (.007)and .043 (.008) for (OD) and .003 (.006)and .003 (.007) for (SL). The differ-ences between estimates of variance com-ponents for OD and SL suggest thatestimates of fractions of total variancedue to sire by herd interaction and cyto-plasmic effects estimated with REMLmay be biased upward by .003 to .004.

Parameter Estimates for Direct andMaternal Genetic Effects forYearling, Eighteen-month, andSlaughter Weights of Korean NativeCattle

Ji-Woong Lee1

Data collected by the National Live-stock Research Institute in Rural Devel-opment Administration of Korea wereused to estimate genetic parameters foryearling weight (YWT, n=5,848), 18month weight (WT18, n=4,585), andslaughter weight at about 22 months(SWT, n=2,279) for Korean NativeCattle. Nine animal models were usedto obtain REML estimates of geneticparameters. Model 1 (DP-2) includeddirect genetic, maternal, and residualenvironmental random effects. Model 2(DQ-2) included direct genetic,sirexregionxyear-season (SRYS) inter-action, and residual environmental ran-dom effects. Model 3 (DPQ-2) was basedon Model 2 (DQ-2) but included boththe interaction and maternal effects.Model 4 (DMP-2) was based on Model1 (DP-2) but the maternal effect waspartitioned to include maternal geneticand permanent environmental effects.

Model 5 (DMPQ-2) was based on Model3 (DPQ-2) and included maternal geneticand permanent environmental as well asthe sire interaction effects. Those fivemodels included two fixed factors:regionxyear-season and age of damxsexeffects. Models 6 (DP-3), 7 (DQ-3), 8(DPQ-3) and 9 (DMPQ-3) were basedon Models 1, 2, 3, and 5, respectively butincluded as a third fixed factor whetheror not identification of the sire wasknown. A single-trait animal model wasinitially used to obtain starting values formultiple-trait analyses. Estimates of heri-tability with Model 9 (DMPQ-3) forYWT, with Model 6 (DP-3) for WT18,and with Model 8 (DPQ-3) for SWTwhen analyzed with single-trait analyseswere .14, .11, and .17, respectively andnearly the same with bivariate analyses.Estimate of maternal heritability forYWT from single trait analysis was .04with estimates for the other traits nearzero but for bivariate analyses the esti-mate for YWT was .01. With single traitanalysis, estimate of the direct-maternalgenetic correlation for YWT was stronglynegative (-.81). Estimates of directgenetic correlations between YWT andWT18, YWT and SWT, and WT18 andSWT were large: .99, 1.00, and .97,respectively. Estimates of environmen-tal correlations varied from .60 to .81;the largest was between WT18 and SWT.Inclusion of a fixed factor for whethersire identification was missing or notmissing in the model reduced estimateof direct heritability for slaughter weight.These results suggest that SRYS inter-action is important for yearling weightand may be needed in a model for slaugh-ter weight and that maternal effects maybe of slight importance for yearlingweight but of no importance for WT18and SWT. Models for national cattleevaluations for Korean Native Cattlefor YWT should be considered thatinclude maternal genetic and perma-nent environmental as well as SRYSinteraction effects, but those effects don’tseem to be needed for models for WT18and SWT.

(Continued on next page)

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Use of Records of BovineSomatotropin Treated Cows inGenetic Evaluation

Shogo Tsuruta1

Records from the North CarolinaState Dairy Records Processing Centerwere used to estimate effects of bovinesomatotropin (bST) treatment and(co)variance components and to predictbreeding values on milk productiontraits. The data comprised 5,245 test-day (TD) records of bST treated cowsand 126,223 TD records of untreatedcows in first lactation for milk, fat, andprotein yields. Fixed effects of bST bydays in milk (DIM) interaction and(co)variance components of randomeffects (animal, permanent environment,

random regressions, and residual) wereestimated from TD animal models withherd-year (HY) effects on herd-test-date(HTD) effects using the REMLF90 pro-gram. To assess the potential for bias ingenetic evaluations when some and notall cows are treated with bST, breedingvalues predicted by the animal modelswith and without effects of bST treat-ment were compared for cows and sires.Random regressions for additive geneticand permanent environmental effectswere included in the models. In themodel with HY effects, responses tobST treatment for milk yield increasedwith DIM, suggesting interactionbetween effects of bST and DIM. How-ever, in the model with HTD effects, theinteraction between effects of bST and

DIM was small. Percentages of increasedue to bST treatment were ranging from5 to 8% for TD milk, fat, and proteinyields. Correlations between breedingvalues predicted from the models withand without effects of bST treatmentwere greater than .99. These resultssuggest that bias in genetic evaluationdue to ignoring bST treatment may besmall or that responses to bST andbreeding values may be highly corre-lated.

1Jeffrey F. Keown, Professor and ExtensionDairy Specialist, Lincoln; M. Valencia-Posadas,former graduate student; P. R. N. Rorato, formergraduate student; Ji-Woong Lee, Post-doctoral;Shogo Tsuruta, former graduate student.

Dairy Technician CertificationJeffrey F. Keown1

Summary

This article gives an overall outlineof the Dairy Certification Program thatthe University of Nebraska-LincolnDairy Extension staff has started withthe Beatrice Campus of Southeast Com-munity College. It is hoped that throughthis one-year program of class studyand an internship, students will be pre-pared to assume mid-level manage-ment positions in Midwest dairyoperations.

Purpose

The purpose of the Dairy TechnicianCertification is to train individuals towork on the large number of expandingdairy farms in Nebraska. We anticipatea need for 300 to 400 new dairy employ-ees over the next five years to fill newpositions in the expanding dairy indus-try.

Administration

The program will be jointly adminis-tered by Southeast Community College-Beatrice (SCC) and the CooperativeExtension Service of the University ofNebraska-Lincoln (UNL). A group often individuals consisting of dairy pro-ducers and dairy industry representa-tives has been formed to supervise andwork with the Dairy Certification. Thisgroup will help assure that the gradu-ates of the certification program aretrained to become mid-level manage-ment personnel.

Responsibilitiesof Cooperating Groups

Southeast Community College-Beatrice Campus will offer its studentscourses that will give them the basicscientific background to work on morespecialized modules which will be pre-pared by the Cooperative Extension Ser-vice at the University of Nebraska-Lincoln. The Cooperative ExtensionService will also arrange for a two-monthinternship for students to gain hands-on

dairy experience. UNL will also workwith SCC to add dairy emphasis to exist-ing course offerings.

Basic Courses Offered bySCC-Beatrice Campus

The following courses are an essen-tial component of Dairy TechnicianCertification.

CreditCourse # Course Title HoursAGR 131 Crop and Food

Science 4AGR 141 Livestock

Management andSelection 4

AGR 171 Ag Spreadsheets 2AGR 205 Farm Records 3AGR 221 Nutrition 4AGR 223 Feeds 2AGR 231 Animal Breeding 5AGR 241 Range & Forage

Management 4AGR 245 Animal Health 4AGR 281 Agribusiness Coop

Internship 7AGR 285 Seminar II 2

Total Credits 41

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Land Requirements for Managing ManureNutrients On Dairy Operations

ducer with livestock in confined facili-ties should also consider this issue. Thisquestion is fundamental to sound envi-ronmental management of manure.

Current NDEQ permit proceduresfor livestock facilities require producersto document the land base available formanure application. If the owned ormanaged application ground is inad-equate for agronomic application ofmanure based upon nitrogen (N), theproducer must identify sufficient landthrough signed agreements with neigh-boring crop producers.

Phosphorus (P) based managementof manure requires significantly greaterland base than N-based management.Currently, land requirements are notregulated based upon P. NDEQ requiresthat a producer submit soil tests for soilP levels, minimum of one composite per40 acres. For fields where soil P levelsexceed “agronomic levels”, a manage-ment plan for minimizing runoff fromthese sites may be required. No upperlimits for soil P level have been estab-lished to deny future manure applica-tion on a site. However, growing pres-sure exists for greater regulation of

phosphorus buildup in soil.Many factors affect manure nutrient

excretion and eventual land base foragronomic nutrient application. Deci-sions at the feedbunk will play a criticalrole. The purpose of this article is toexamine the impact of feed bunk deci-sions on land needs for manure applica-tion.

Feeding for HighMilk Production Levels

As milk production potential of dairycattle has increased, so has the nutrientrequirements of those cattle and thenutrients they excrete (Table 1). His-torically, a rule of thumb of one acre percow has been used to define manureapplication site requirements for dairycattle.

With higher milk production levels,such rules of thumb are inadequate formanure handling systems designed toconserve nutrients (manure storage andimmediate incorporation of manure).For herds producing between 70 and100 pounds of milk per cow per day, a100-cow herd will require between 140

Rick Koelsch1

Summary

Manure nutrient excretion by cattleand the resulting land requirements formanaging those nutrients are affectedby feed bunk decisions. Increasing aration’s crude protein level from 17.1to 19.5% may increase the land re-quirements of a 100-cow dairy by 25acres. Increasing phosphorus levelsfrom 0.43 to 0.52% may increase landrequirements for a 100-cow dairy bymore than 50 acres. This article willsummarize the impact of feeding pro-gram options on land requirements andintroduce tools for evaluating theseissues for individual farms.

Introduction

Is sufficient land available for man-aging the nutrients in manure? Thisquestion is being asked by the NebraskaDepartment of Environmental Quality(NDEQ) as it reviews permit applica-tions for livestock facilities. Any pro-

Upon completion of the 41 creditslisted under the Basic Courses offeredby SCC-Beatrice Campus, the studentwill participate in a two-month internprogram. The program will be adminis-tered by University of Nebraska Exten-sion and will involve working on a dairyfarm to learn the basic operations of adairy farm.

Dairy Modules

The dairy portion of the courses listedwill be offered via computer modules

from UNL. These four modules willcover the areas of Dairy Rations, DairyGenetics and Sire Evaluation, ForageQuality, and Dairy Herd Health. Thesemodules will be incorporated into thevarious courses listed under BasicCourses.

Specific hands-on modules not of-fered via the computer:

P.C. Dart — dairy record keepingMilkers School — learn how to

properly milk cows and maintain equip-ment

You may access the various dairymodules on the Internet at

http://deal.unl.edu/dairy/Please feel free to send your com-

ments to me at:ANSC407@UNLVM.UNL.EDUThis program began Fall 1999 with

SCC. If you have any questions, pleasegive me a call at (402) 472-6453.

1Jeffrey F. Keown, Professor and ExtensionDairy Specialist, Lincoln.

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and 170 acres to manage the nitrogen inmanure, depending on crop rotationand yield. To manage the nitrogen inmanure and satisfy NDEQ, one shouldplan on at least 1.5 acres per cow. Witha greater focus on environmental prob-lems associated with excess soil phos-phorus levels, access to at least 2.25acres per cow may be necessary.

A smaller land base is required tomanage the nutrients in a system de-signed to “dispose” of nutrients (anaero-bic lagoon and land application withcenter pivot (see Table 1). A significantportion of the nitrogen volatilizes intothe air while P settles with solids andaccumulates in the bottom of the la-goon. Between 0.3 and 0.8 acres percow would be required for this type ofmanure management system, depend-ing upon the milk production level andchoice of N- vs. P-based manure man-agement.

Recognize that the “lost” phospho-rus continues to accumulate in the la-goon. At the time that this sludge mustbe removed, a very large land base maybe required to avoid excessive applica-tion of phosphorus in the sludge.

Systems that “dispose” of nutrientsare under increasing scrutiny. The vola-tilized ammonia eventually returns toearth, often adding to nitrogen loadingof surface waters. Lagoons also experi-ence greater total seepage — due prima-rily to their larger size — than manure

storage. These factors contribute to sur-face water problems, especially in coastalareas, and can create greater risk toground water. The state of North Caro-lina has banned the construction ofanaerobic lagoons. It is important torecognize the uncertain future foranaerobic lagoons.

Impact of Feed NutrientConcentrations

Protein not utilized for milk produc-tion or animal maintenance/growthneeds will be excreted as urea or organicnitrogen in the manure. Typically, 70%of the nitrogen fed to animals as proteinwill be excreted in a diet balanced ac-cording to National Research Councilguidelines. Feeding protein in excess of

these levels adds to the nitrogen in themanure.

Two dairy rations with different pro-tein levels are illustrated in Table 2. Thehigh alfalfa diet (19.5% crude protein)results in about 20% more nitrogen inthe manure as compared to a diet withsupplemental by-pass protein (17.1%crude protein). Twenty percent moreland is needed for manure managementfor the higher protein diet. For a 100-cow herd, an additional 6 to 25 acres isneeded for managing the nitrogen inmanure for the two systems detailed inTable 2.

Commonly observed ranges for phos-phorus levels in dairy rations can havean even greater impact on land require-ments. A ration containing 0.52%

Table 1. Change in land application area needs with change in milk production level.1

Milk Production Manure Nurtient Excretion Available Nutrients after Land Requirements if(lbs./day) (lbs. of nutrient/yr.) Losses (lbs. of nutrient/yr.) Manure is Applied at an:

N P2O5 N P2O5 N Rate P Rate

System That Conserves Nutrients (manure storage and incorporation during application) 2

100 34,800 14,200 28,100 14,200 170 24070 28,900 13,000 23,400 13,000 140 22050 24,300 11,900 19,600 11,900 120 200

Nutrient Disposal System (anaerobic lagoon and pivot irrigation) 3

100 34,800 14,200 6,500 5,000 41 8470 28,900 13,000 5,400 4,500 32 7650 24,300 11,900 4,600 4,200 28 70

1Assumptions:- Feed nutrient concentrations based upon NRC recommendations. Crude protein levels of 17.5, 16.4, 15.3, and 12.0% were assumed for cows producing 100,

70, 50, and dry cows respectively. Phosphorus concentration of 0.5% was assumed for all groups. It was assumed that- 100-cow herd included 83 lactating cows and 17 dry cows.- Nutrient use in crop production assumed a six-year rotation of corn (170 bushels/acre), corn silage (22 tons acre), and alfalfa (5 ton/acre).2Assumes 80% of the nitrogen and 100% of the phosphorus is conserved.3Assumes 20% of the nitrogen and 35% of the phosphorus is conserved in the wastewater to be pumped annually. The remaining P will accumulate in sludge andrequire an additional 400 and 500 acres if removed every 10 years and applied at three times agonomic phosphorus rates.

Table 2. Changes in land application area needs for 100-cow dairy as a result of difference in dietprotein level.

Crude Protein Dietary Options Manure N Excretion Available N after Land Requirement(lbs. N/yr.) Losses (lbs. N/yr.) for Managing N

System That Conserves Nutrients (Manure Storage and Incorporation During Application) 1

High Alfalfa Diet/No AddedEscape Protein ( 19.5% CP) 35,400 28,600 162

Diet Supplemented with EscapeProtein (17.1% CP) 30,000 24,200 137

Nutrient Disposal System (anaerobic lagoon and pivot irrigation) 1

High Alfalfa Diet/No AddedEscape Protein (19.5% CP) 35,400 6,600 39

Diet Supplemented with EscapeProtein (17.1% CP) 29,900 5,600 331See Assumptions used for Table 1 except for crude protein levels.

(Continued on next page)

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phosphorus will result in 30% moreland needed for managing manure phos-phorus than a 0.43% dietary phospho-rus level (Table 3). Both phosphoruslevels should meet the needs of a dairycow producing 75 pounds of milk perday. For a 100-cow herd with a manuremanagement system designed to con-serve nutrients, an additional 50 or moreacres is needed for managing the extraphosphorus.

Estimating Land Requirements

The previous estimates of land appli-cation area needs may vary for indi-vidual farms for a variety of reasons. Todevelop a better understanding of landneeds for an individual situation, a“Manure Nutrient Inventory” spread-sheet has been developed to assist Ne-braska livestock producers. The spread-sheet can be accessed from a homecomputer with Microsoft Excel (version5.0 or later) and Internet access. Thespreadsheet and a set of instructions areavailable at: http://www.ianr.unl.edu/manure/

Many Cooperative Extension andNRCS offices also have access to thistool and would likely be able to assist inreviewing an individual situation.

The purpose of the Manure NutrientInventory Spreadsheet is to estimate theexcretion of nutrients by livestock andpoultry, the quantity of nutrients re-maining after losses, and the land needsfor utilizing those nutrients at agro-nomic rates (see Table 4 for sampleprintout). A producer can evaluate theimpact of the following inputs on therequired land base:

- Herd size,- Feeding program,- Method of storage and/or treat-

ment of manure,- Method of land application, and- Crop selection, rotation, and yield.

The nutrient balance component ofthe spreadsheet is a unique approach toestimating manure nutrient excretion.Typically, book value estimates are usedfor manure nutrient production. Theweakness of this approach is that itassumes all dairy cows are fed the same

Table 3. Changes in land application area needs as a result of differences in diet P level.

Phosphorus manure P Excretion Available P after Land Requirement forDietary Options (lb. P2O5/yr.) Losses (lb. P2O5/yr.) Managing P

System That Conserves Nutrients (Manure Storage and Incorporation During Application) 1

Nebraska IndustryAverage (0.52% P) 13,400 13,400 225

UNL Recommendation(0.43% P) 10,200 10,200 171

Nutrient Disposal System (anaerobic lagoon and pivot irrigation) 1

Nebraska IndustryAverage (0.52% P) 13,400 4,700 792

UNL Recommendation(0.43% P) 10,200 3,600 602

1See Assumptions used for Table 1 except for crude protein levels.2Additional land will be needed for managing the phosphorus accumulating in the sludge. That landrequirement is approximated in Table 1 footnote.

ration and perform the same. The nutri-ent balance approach requires informa-tion on the feeding program (feed con-sumption and feed protein, phosphorus,and potassium concentration) and ani-mal products produced (milk produc-tion for lactating cows and weight gainfor heifers). Manure nutrient excretionis assumed to be the difference betweenfeed nutrient consumption and nutri-ents retained in animal products (Fig-ure 1). Either book value or nutrientbalance methods can be used in thespreadsheet.

Conclusions

Nutrients in manure represent a criti-cal environmental threat if managedimproperly. Dairy producers should haveaccess to at least 1.5 acres of land percow to manage manure in a nutrientconservative manure management sys-

tem (0.4 acres per cow for a nutrientdisposal manure management system).The actual quantity of land is affected bymany decisions including feed bunkdecision. Commonly observed rangesfor ration crude protein and phosphoruslevels resulted in a 20 to 30% change inthe land requirements for managing thenutrients in manure. This amounted to25 to 50 acres of additional land needsfor a 100-cow dairy herd. However,because these estimates require infor-mation specific to individual dairies,producers are encouraged to use the“Manure Nutrient Inventory” spread-sheet or similar tools to evaluate thosesite-specific parameters.

1Rick Koelsch, Associate Professor andExtension Livestock Environmental Engineer,Animal Science and Biological SystemsEngineering, Lincoln.

Feed Nutrients Retained NutrientNutrient — by Animal or = ExcretionIntake Animal Products

Figure 1.

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Table 4. Summary of nutrient excretion, nutrient remaining after storage and field losses, and land requirements for agronomic application.

Producer’s Name: John Doe Address: Box 100 Phone: 402-499-9999Farm Name: Shady Acres Address: Route 1 Fax: 402-499-9998

Town, State, Zip: Anytown, NE 60000 e-mail: jdoe@share.comHerd/Flock Summary:

Portion of Method for EstimatingAverage Average Year Facility Nutrient Excretion

Species and Group ID Capacity Weight Is Occupied

Dairy Hi Group 200 1400 Nutrient Balance

Dairy Low Group 200 1400 Nutrient Balance

Dairy Dry Cows 60 1450 Nutrient Balance

Nutrient Excretion by Livestock Summary

1. Earthen Storage 164,286 lbs. N/yr. 69,393 lbs. P2O5/yr. 77,422 lbs. K2O/yr.2. lbs. N/yr. lbs. P2O5/yr. lbs. K2/yr.3. lbs. N/yr. lbs. P2O5/yr. lbs. K2/yr.4. lbs. N/yr. lbs. P2O5/yr. lbs. K2/yr.

Nutrients Remaining After Storage Losses1. Earthen Storage 139,643 lbs. N/yr. 69,393 lbs. P2O5/yr. 77,422 lbs. K2O/yr.2. lbs. N/yr. lbs. P2O5/yr. lbs. K2/yr.3. lbs. N/yr. lbs. P2O5/yr. lbs. K2/yr.4. lbs. N/yr. lbs. P2O5/yr. lbs. K2/yr.TOTAL 139,643 lbs. N/yr. 69,393 lbs. P2O5/yr. 77,422lbs.K2O/yr.

Nutrients Remaining After Field Application Losses (ammonia losses only)1. Earthen Storage 132,661 lbs. N/yr. 69,393 lbs. P2O5/yr. 77,422 lbs. K2O/yr.2. lbs. N/yr. lbs. P2O5/yr. lbs. K2/yr.3. lbs. N/yr. lbs. P2O5/yr. lbs. K2/yr.4. lbs. N/yr. lbs. P2O5/yr. lbs. K2/yr.TOTAL 132,661 lbs. N/yr. 69,393 lbs. P2O5/yr. 77,422lbs.K2O/yr.

Manure Nutrient Application Rate Assuming That Manure is Distributed Evenly Over Existing Land Base1. Earthen Storage 800 ac. 165 lbs. N/yr. 87 lbs. P2O5/yr. 97 lbs. K2O/yr.2. lbs. N/yr. lbs. P2O5/yr. lbs. K2/yr.3. lbs. N/yr. lbs. P2O5/yr. lbs. K2/yr.4. lbs. N/yr. lbs. P2O5/yr. lbs. K2/yr.

Crop Land Requirements if Manure Nutrients are Distributed According to Crop Nutrient Removal Rates.

Land Base Nitrogen P2O5 K2OIdentified Available Utilized Remaining Available Utilized Remaining Available Utilized Remaining

1,460 ac 132,661 lb. 132,661 lb 0 lb. 69,393 lb 46,626 lb 22,767 lb. 77,422 lb. 77,422 lb. 0 lb.650 acres to utilize N 1,460 acres to utilize P 650 acres to utilize K

Crop Land Requirements for Accumulated Phosphorus in Settled Solids of an Anaerobic Lagoon

Land Base P2O5Identified Available Utilized Remaining

600 ac 0 lb. 0 lb. 0 lb.

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The Accuracy of Test Strategies to ClassifyHerds by Johne’s Disease Status

they are unlikely to have infected cattlecan begin to address biosecurity strate-gies to prevent introduction of the agentthrough purchased bulls and replace-ments. Also, the cattle from herds thatare reliably classified as unlikely tocontain M. paratuberculosis may haveadded value when marketed as replace-ments.

Proposals to classify herds by M.paratuberculosis infection status makessome producers and their veterinariansnervous. Herds classified as M. paratu-berculosis infected may suffer a loss ofmarket and increased liability concerns.Misclassification of herd infection sta-tus also has serious implications forboth buyers and sellers. Buyers of re-placement cattle want assurance thatherds classified as uninfected are classi-fied correctly. Sellers of replacementcattle want assurance that their herdswill not be classified as infected unlessthey truly are. Veterinarians workingwith these herds should have confi-dence that the herd-testing strategiesthey recommend will accurately deter-mine a herd’s infection status.

The probability of correctly classify-ing a truly infected herd is termed herd-level sensitivity. Herd-level specificityis the probability of correctly classifyinga truly non-infected herd. When a herd’sinfection status is determined by testingindividuals within the herd, then theherd-level sensitivity and specificity canbe calculated from the sensitivity andspecificity of the test for individuals, theexpected prevalence of infected indi-viduals within infected herds, the num-ber of herdmates tested, and the numberof reactors (positive tests) that will clas-sify a herd as infected (Martin et al.1992).

Statistics such as predictive value,efficiency and apparent prevalence canbe used to interpret the diagnostic valueof a herd-level classification of infec-tion based on tests of individuals. Thesestatistics can be calculated if herd-levelsensitivity and specificity and the ex-

pected prevalence of infected herds areknown. The predictive value of a posi-tive herd classification is the probabilitythat there truly are infected animals inherds classified as infected (Martin etal.1992; Martin, 1977). Similarly, thepredictive value of a negative herd clas-sification is the probability that thereare truly no M. paratuberculosis in-fected animals in a herd classified as notinfected (Martin et al.1992; Martin,1977).

The proportion of herds classifiedcorrectly is termed efficiency(Trajstman, 1979). The efficiency of aherd-testing strategy is a function of thesensitivity and specificity at the herdlevel, and the prevalence of infectedherds. The proportion of herds that testpositive with a herd-testing strategy,the apparent prevalence, is also a func-tion of the same factors (Martin et al.1992; Martin, 1977).

The objective of this study was to usethese statistics to determine an optimaldiagnostic strategy to classify a herdcorrectly by M. paratuberculosis infec-tion status.

Procedure

A spreadsheet software program wasused to calculate herd-level sensitivity,specificity, predictive value, efficiency,and apparent prevalence with varyingnumbers of animals tested within a herd.

Two herd-testing strategies wereevaluated over a range of herd samplesizes:

1) ELISA screening — Testingserum collected from a randomsample of the herd for thepresence of antibodies directedagainst M. paratuberculosisby enzyme-linked-immuno-sorbent-assay (ELISA). Allcattle with positive ELISAresults would be consideredreactors.

2) Serial testing — ELISA screen-ing, followed by culturing the

David R. Smith1

Summary

To prevent movement from farm tofarm of Mycobacterium paratubercu-losis, the agent of Johne’s disease,dairymen must be able to accuratelydetermine the infection status of theirown herds and the herds that are sourcesof replacement cattle. The accuracy oftwo herd-testing strategies were graphi-cally modeled using assumptions aboutthe performance of Johne’s diseasediagnostic tests on healthy adult cattle,the expected percentage of herds har-boring cattle infected with M. paratu-berculosis, and the percentage of cattleinfected within those herds. The modelpredicts that it is possible to correctlyclassify 99% of herds by M. paratuber-culosis infection status if 125 cattle inthe herd are tested by ELISA for anti-bodies directed against M. paratuber-culosis, and if positive serology testresults are confirmed with fecal cul-ture. Dairy farmers following this herd-testing strategy can determine theJohne’s disease status of their herdswith confidence, and cattle sold fromdairies classified as negative may haveadditional value as replacements withlow risk of infection.

Introduction

The ability to accurately classify aherd by Mycobacterium paratubercu-losis infection status is an importantdiagnostic challenge for veterinarians.Dairy farmers cannot fully addressJohne’s disease control and preventionuntil they can reliably know the infec-tion status of their herds as well as theherds from which they purchase re-placements. Producers can addresspathogen containment within their ownoperations once they reliably know M.paratuberculosis infected cattle existwithin their herds. Producers that know

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feces of ELISA-positive cattleto confirm positive ELISA testresults. Only cattle testing posi-tive to both ELISA and fecalculture testing would be consid-ered reactors.

The prevalence of infected herds wasassumed to be 22% and the prevalenceof infected individuals within infectedherds was assumed to be 15% (3.4%overall prevalence of infected individu-als divided by 22 percent prevalence ofherds with infected individuals) basedon the results of a recent national survey(NAHMS, 1997). One reactor was usedto classify a herd as infected.

The herd screening protocol wasbased on the expected performance of acommercially available antibody-capture ELISA (HerdChek M.pt.,IDEXX Laboratories, Westbrooke, MN04092) because the test is already beingused by many veterinary diagnosticlaboratories; it is relatively inexpen-sive; and a short time is required toobtain results. The ELISA for indi-vidual adult cattle without clinical signsof Johne’s disease was estimated to be45% sensitive and 99% specific, and theserial testing strategy 25% sensitive and99.99% specific, based on expert opin-ion (National Johne’s Disease WorkingGroup, 1998). The sensitivity of the testfor individuals is lower with serial test-ing because some truly infected cattle,positive by ELISA, will not be culturepositive (more false negative test resultsthan ELISA screening alone). Serialtesting is more specific (fewer falsepositive test results than ELISA screen-ing alone) because a positive ELISAresult must be confirmed by fecal cul-ture.

Results

With both testing strategies thecalculated herd-level sensitivityincreased and herd-level specificitydecreased as the number of cattle testedper herd increased (Figures 1 and 2).The sensitivity of a herd-level classi-fication increases with larger samplesizes because there are more opportuni-ties to find the one positive test resultthat will classify the herd as infected.The specificity of a herd-level classifi-

cation decreases as more cattle in a herdare tested because of the increasing op-portunity to find a false positive testresult.

Compared to serial testing, ELISAscreening was predicted to have higherherd-level sensitivity at smaller samplesizes and lower herd-level specificity at

Figure 2. The probability that an infected herd will be correctly classified (herd sensitivity) and theprobability that an uninfected herd will be correctly classified (herd specificity) by M.paratuberculosis infection status when various numbers of cattle in the herd are testedby serology in series with fecal culture. Calculations assume that the sensitivity andspecificity of testing for individual cattle when ELISA serology is conducted in serieswith fecal culture is 25 percent and 99.99 percent respectively, and that in infected herds15 percent of the cattle will be infected.

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Figure 1. The probability that an infected herd will be correctly classified (herd sensitivity) and theprobability that an uninfected herd will be correctly classified (herd specificity) by M.paratuberculosis infection status when various numbers of cattle in the herd are testedusing ELISA serology alone. Calculations assume that the sensitivity and specificity ofthe test for individual cattle is 45 percent and 99 percent respectively, and that in infectedherds 15 percent of the cattle will be infected.

Performance of herd-testing strategytesting individuals by ELISA serology

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all herd sample sizes. The graphicalmodels illustrate that as sample sizeincreases, increasing numbers of herdswill be incorrectly classified as infectedwhen screening herds by ELISA serol-ogy alone.

The predictive value of a negativeherd classification was similar for bothstrategies regardless of herd sample size(Figures 3 and 4). The predictive valueof a positive herd classification decreasedwith both test strategies as the number ofcattle tested increased but was lower forELISA screening at all sample sizes.

Serial testing was predicted to cor-rectly classify a greater percentage ofherds (greater efficiency) than ELISAscreening over the range of sample sizes.The efficiency of ELISA screeningdecreased as the number of cattle testedper herd increased because uninfectedherds were predicted to be incorrectlyclassified as infected. The efficiency ofserial testing was maximized at a samplesize of 125 cattle. Efficiency of serialtesting was predicted to be less at samplesizes below 125 because of false nega-tive classifications and less at samplesizes above 125 because of increasingfalse positive classifications. The modelpredicted that if 125 cattle were testedper herd, then 99% of herds would beclassified correctly by serial testingcompared to less than 45% by ELISAscreening.

As the number of cattle tested perherd increased, the apparent prevalenceof herds classified as infected was pre-dicted to increase (Figures 5 and 6).Because of false-positive herd classifi-cations, ELISA screening was predictedto overestimate the prevalence of in-fected herds over the entire range ofsample sizes. Serial testing was predictedto underestimate the prevalence of in-fected herds at low sample sizes, butmore closely approximate the assumedtrue prevalence as sample sizes increased.

Except for finite sample size correc-tions not calculated, herd-level sensitiv-ity and specificity are not related to herdsize (Martin et al. 1992). Therefore, thenumber of cattle to test in a herd does notdepend on the size of the herd in order tooptimize herd-level predictive value andefficiency.

Figure 4. The probability that a herd classified as M. paratuberculosis infected truly has infectedcattle in the herd, the probability that a herd classified as uninfected truly is uninfected,and the percentage of herd classified correctly (efficiency) for a given number of herdmembers tested in series by ELISA serology then fecal culture, assuming the trueprevalence of infected herds is 22 percent.

Predictive valueherd classification by serial testing

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Figure 3. The probability that a herd classified as M. paratuberculosis infected truly has infectedcattle in the herd, the probability that a herd classified as uninfected truly is uninfected,and the percentage of herd classified correctly (efficiency) for a given number of herdmembers tested by serology alone, assuming the true prevalence of infected herds is 22percent.

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(Continued on next page)

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The statistics used to evaluate thediagnostic herd-testing strategies arebased on an assumption that the cattle tobe tested were randomly selected fromthe adult herd, and the inferencesregarding the herd’s infection statusrefer to this population of adult cattle.It may be possible in relatively closedherds, to infer that younger cattle alsoshare the same infection status as adultcattle in the tested population; however,due to the long incubation period ofM. paratuberculosis, this may not betrue in herds that have introduced cattlein recent years.

If the assumptions used to model thestatistics are correct, and if 125 adultcattle were tested per herd, then wewould predict that 77 percent of herdswould have at least one animal testpositive by ELISA serology. Fecal cul-ture would confirm the presence of M.paratuberculosis in 22 percent of theherds and overall only 1 percent ofherds would be classified incorrectly.Serial testing should provide a level ofaccuracy in classifying the Johne’s dis-ease status of herds that should giveveterinarians and dairy farmers confi-dence that Johne’s disease herd-testingprograms can be successful and thatsources of replacement animals at lowrisk for carrying the agent of Johne’sdisease can be identified.

1David R. Smith, Assistant Professor andExtension Dairy/Beef Veterinarian, Veterinary andBiomedical Sciences, Lincoln.

Reference List

Martin, S.W. 1977. The evaluation of tests. Can JComp Med, 41:19.

Martin, S.W., M. Shoukri, and M.A. Thorburn1992. Evaluating the health status of herdsbased on tests applied to individuals. Prev.Vet. Med. 14:33.

NAHMS. Johne’s disease on U.S. Dairy Opera-tions. 1997. Fort Collins, CO, USDA: APHIS:VS, CEAH, #N245.1097. National AnimalHealth Monitoring System.

National Johne’s Disease Working Group. 1998.U.S. Voluntary Johne’s disease herd status

program. USAHA (Draft 9-18-1998).Trajstman, A.C. 1979. Diagnostic tests, sensitiv-

ity, specificity, efficiency and prevalence.Aust. Vet. J. 55:501.

Figure 6. The percentage of herds predicted to be classified as infected with M. paratuberculosis(apparent prevalence) when various numbers of cattle in the herd are tested by serologyin series with fecal culture. The percentage of herds classified as infected by this samplingscheme is predicted to closely approximate the assumed true prevalence over a widerange of sample sizes.

Apparent prevalencepredicted from serial testing

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Figure 5. The percentage of herds predicted to be classified as infected with M. paratuberculosis(apparent prevalence) when various numbers of cattle in the herd are tested by serologyalone. The percentage of herds classified as infected by this sampling scheme is predictedto greatly exceed the assumed true prevalence.

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Dairy Research Herd Report

all the cows on nutrition experiments.With new facilities we may group ourfirst lactation cows separately. All ofour replacements are grown at the unit,and all are sired and bred using AI. Ouraverage age at first calving is 25 monthsand our average age of the milking herdis 38 months with 50% being first-lactation animals.

In 1999, we are planning the con-struction of a new free-stall barn toaccommodate the loss of some animalhousing due to building demolition. Weare constructing a hoop-style barn tohouse approximately 55-60 cows. Thebarn will improve cow comfort byenabling the cows to eat inside the barn.This should be beneficial both in thesummer and winter months. It will have10-feet high side walls to allow foradequate ventilation and will beapproximately 40 x 130 feet in dimen-sions. It will be equipped with sand-bedded free stalls that should maximizecow comfort. We are also planning toupgrade the equipment in the milkingparlor. The parlor is a double-5 herring-bone equipped with computerized metersand automatic detachers. We willreplace the old meters with new, morereliable and advanced meters and auto-matic detachers. This was September1999. Other future improvements thatwe hope to make are a new feed mixerthat will allow us to incorporate long-stem alfalfa into the ration, and updat-ing of equipment with which to performthe daily chores.

Along with dairy research, anotherimportant service the dairy unit pro-vides is education and public aware-

ness. This is becoming more importantas the average citizen is becoming far-ther removed from agriculture. In 1998,we had approximately 2,000 visitors tothe dairy. The majority of them weregrade school children who were here tolearn more about agriculture. A com-mon educational tour for these childrenis to visit the dairy unit and learn aboutbaby calf care, the milking procedure,and some housing and nutrition. Thesekids also tour other units such as thesheep, crops and horticulture units tolearn more about agriculture. We alsoprovide some education for the dairyand animal science classes at UNL.International visitors frequent the dairywith people coming from Japan, SouthAmerica, and the Middle East. Linkingprograms with Cooperative Extensionhas increased. We hosted the PAK 10Judging Contest in 1998 and 1999; thisis a combination workshop and judgingcontest. In 1999, we hosted the NebraskaHolstein Association’s Spring FlingFancy Heifer Sale in conjunction withthe PAK 10 event. This day was a hugesuccess with over 150 people in atten-dance and 75 people participating in thejudging clinic.

The Dairy Unit employs seven peopleto accomplish the many tasks to allowfor optimum research. Erin Marotzserves as the manager, and is respon-sible for overall management andresearch coordination. Erin has beenthe unit manager for six years. Theoutside crew consists of three people.Darren Strizek serves the NutritionResearch Barn and is responsible forreplacement management. Darren also

Erin Marotz1

The University Dairy Unit’s appear-ance was changed dramatically in 1998with the demolition of the former ordi-nance plant buildings. Demolitionstarted in July and was completed byyear’s end — finally no more old uglybuildings to look at. With the demoli-tion came new challenges and newopportunities. Some of the buildingswere still being used by the dairy foreverything from storage to cattle hous-ing and thus replacements had to befound. These buildings also served asboundary fences for many of our pas-tures; therefore, new fences will have tobe built. So, 1999 will find us buildingnew facilities and new pasture fences.The good news is that these buildingsand fences will be the type that we wantand in the location that best suits thedairy’s needs.

We are currently milking 120 cowswith a rolling herd average (RHA) of22,065 pounds of milk, 822 pounds offat, and 715 pounds of protein. Ourcurrent SCC is 200 to 220,000. Cowsare housed in two groups according tostage of lactation and milk production.Both groups are housed in free-stallbuildings with outside feeding facili-ties. The lactating cows are fed a totalmixed ration twice daily in a fence linebunk with refusals monitored daily andweigh backs fed to heifers. Currentlythe ration consists of corn silage, alfalfasilage, wet corn gluten feed, and a pro-tein, mineral, and vitamin mix. We alsohave a 40 cow tie-stall barn that houses

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assists in pasture management as mostof the pastures are intensively grazed.Darren has been with the University for10 years. Scott Ellinger’s position isthat of feeder and waste removal. Hisresponsibilities include feeding the milk-ing herd, dry cows and bred heifers,along with daily manure removal. Scotthas been with us for three years. GeneAnderson serves in the swing position,performing the daily operations of bothoutside positions when Darren and Scotthave the day off. Gene also has theresponsibility of light mechanic dutyand maintenance; he has served in hiscapacity for two years. Performing themilking operations are three milkers.One person does the milking per shift.Serving as the day milker is Kent Sweet.

Kent’s duties also include parlor main-tenance and assisting the outside crewas needed. Kent has served as a milkerfor six years. Milking the night shift,which starts at 5 p.m., is Robin Drake-Woods. Her duties include milking,Heatwatch patch application, parlorsanitation, and nutrition barn cleaning.She has been with us for six months.Ken Cejka’s time is split between theday and night shifts. He does milking aswell as the other responsibilities of bothshifts. Ken has been a part of the DairyUnit for six years. Many of the employ-ees are cross-trained and perform amultitude of tasks at the Dairy Unit.

We are located at the AgricultureResearch and Development Centersouth of Mead. Our phone number is

(402) 624-8068 and someone is hereevery day of the year. If you would liketo schedule a visit, please give us a callor simply stop by; I will do what I can toaccommodate you. If you have anyquestions about the research or man-agement practices in use, do not hesi-tate to call. If you have a larger groupthat would like to tour the Dairy or theARDC in general, contact the ARDC at(402) 624-8022 and schedule a tour;last year about 20,000 people did.

1Erin Marotz, Manager, Dairy Research Unit,Agricultural Research and Development Center,Mead.

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Dairy Extension Publications Available fromUniversity of Nebraska

The following Dairy publications provide timely information for dairy producers. If you would like a copy of a NebGuide, pleasecontact your local Cooperative Extension office or write:

BulletinsP.O. Box 830918

University of NebraskaLincoln, NE 68583-0918

For a comprehensive listing of available dairy publications, visit our web site at: http://www.ianr.unl.edu/pubs/Dairy/Up to 10 single NebGuide titles are free to Nebraskans; additional titles or copies are available at a charge of $.25 per piece.

A $1.50 shipping and handling charge will be added to copies ordered from the address above. Copies obtained from your localCooperative Extension office do not usually have a shipping fee.

Feeding and Nutrition

! RP-346 Feeding the Dairy Herd! G90-961 Supplemental Fat for High Producing

Dairy Cows! G90-978 Byproduct Feedstuffs for Beef and Dairy

Cattle! G90-1003 Maximizing Feed Intake for Maximum

Milk Production! G91-1027 Protein and Carbohydrate Nutrition of

High Producing Dairy Cows! G92-1111 Mineral and Vitamin Nutrition of Dairy

Cattle! G93-1138 Water Quality and Requirements for

Dairy Cattle! G93-1177 Feeding and Managing Holstein Steers! G94-1201 Feeding the Dry Cow! G94-1229 Importance of Grain Quality, Nutrient

Composition and Processing for DairyCattle

! G95-1256 Managing Dairy Cattle for Cow Comfortand Maximum Intake

! G95-1265 Guidelines for Using Computerized Con-centrate Feeders for Dairy Herds

! G96-1298 Milk Urea Nitrogen Testing! NF 96-270 Handling Feed Moisture in Ration For-

mulation and Inventory Control! G96-1306 Feeding Dairy Cows to Reduce Nitro-

gen, Phosphorus and Potassium Excre-tion into the Environment

! G98-1358 Feeding to Maximize Protein and Fat

Forages and Pasture

! G74-142 Harvesting and Preserving Hay CropSilage

! G84-696 Small Grains for Silage or Hay! G84-738 Management to Minimize Hay Waste! G86-775 Prussic Acid Poisoning! G88-874 Management Tips for Round Bale Hay

Harvesting, Moving, and Storage! G91-1034 Evaluating the Feeding Value of Fibrous

Feeds for Dairy Cattle! G92-1118 Forage Allocation System for Dairy

Producers — Using a Forage Inventoryand Allocation Worksheet

! G94-1192 Feeding Dairy Cows with Limited HighQuality Forage

! NF94-129 Adding Water to Grain, Silage, or Hay! G94-1231 Harvesting Corn and Sorghum for Silage

Forage and Feed Testing

! G74-170 Nitrates in Livestock Feeding! G77-331 Sampling Feeds for Analyses! G89-915 Testing Livestock Feeds for Beef Cattle,

Dairy Cattle, Sheep and Horses! G93-1168 Moisture Testing of Grain, Hay and

Silage

Metabolic Disorders

! G91-1032 Dairy Cow Health and MetabolicDisease Relative to Nutritional Factors

! NF 97-317 Managing Dairy Cows to AvoidAbomasal Displacement

- 36 -

Business Management

! EC98-818 Nebraska Livestock Budgets! G91-1064 Managing Dairy Labor! G92-1114 Hiring Non-Farm Dairy Personnel! G93-1189 Developing Dairy Heifer Rearing

Expenses! NF94-204 Computing the Dollar Value of Concen-

trates and Byproduct Feeds for DairyCattle

! G94-1234 Should You Consider Expanding YourDairy Herd?

! G95-1224 How to Write a Dairy Job Description! NF96-252 Controlling Feed Costs on Your Dairy

Farm! EC96-824 Dairy Economics in Nebraska — An

Analysis of Costs and Returns andComparisons with Other States

! G97-1325 What Management Practices are HighProducing Dairy Herds Using?

Breeding and Reproductive Management

! G85-755 How to Set Goals for Your BreedingProgram

! G86-818 How to Use Milk Progesterone Tests! G86-822 How to Estimate a Dairy Herd’s Repro-

ductive Losses! G89-898 How to Interpret the New Animal Model

for Dairy Sire Evaluation! G89-952 Estrus Detection Guidelines! G94-1197 The Genetics and Management of Sound

Feet and Legs! G96-1285 Dairy Heath Management for Optimum

Production and Reproductive Perfor-mance

Mastitis, SCC, and Milk Quality

! EC-726 Mastitis Control Guidelines! G81-556 Using the California Mastitis Test (CMT)

to Detect Subclinical Mastitis! G86-778 Do You Practice Good Milking

Procedures?! G92-1101 Dairy 10-Point Quality Control Program

— Mastitis Treatment Records! G93-1143 How to Use the National Genetic

Evaluations for Somatic Cell Scores! G93-1151 The Somatic Cell Count and Milk Quality! G93-1170 Bacteria in Milk-Sources and Control! G95-1253 Basic Principles of Mastitis Control! G95-1271 Mastitis is a Disease — Control is an

Everyday Task

Replacements

! RP-205 Raising Dairy Replacements! G86-819 At What Weight Should Holstein Heifers

Freshen?! G86-799 Health Management and Recommended

Vaccination for Dairy Replacements

Disease and Health Management

! G74-149 Bloat Prevention and Treatment! G77-355 A Guide for the Control of Flies in

Nebraska Feedlots and Dairies! G78-417 Leptospirosis of Domestic Animals! G81-574 Reproductive Diseases in Cattle! G82-620 Pinkeye! G90-977 Johne’s Disease (Paratuberculosis)! G93-1141 Dairy Cattle Insect Management

BST

! G91-1041 Feeding the BST Treated Dairy Cow! NF94-175 Can You Afford to Use BST?

Body Condition Scoring

! G90-997 How to Body Condition Score DairyAnimals

! G92-1070 Feeding Dairy Cattle for Proper BodyCondition Score

Heat Stress

! G91-1063 How to Reduce Heat Stress in DairyCattle

- 37 -

Career

Your undergraduate degreewith an Animal Sciencemajor prepares you for anumber of careers in thelivestock and meat industriesas well as professional studyin veterinary medicine,medicine, law or teaching.

Courses

You select course workranging from animalmanagement to in-depthscientific studies to buildyour own specializedprogram.

Animal ScienceCollege of Agricultural Sciences and Natural Resources

Resources

You also have opportunitiesfor hands-on experiencethrough internships andclass tours of agribusinessesand production units acrossthe country. And you studyin state-of-the-artlaboratories and classrooms.

Activities

As an Animal Sciencemajor you may beparticularly interested inBlock & Bridle to buildleadership, communicationand organizational skillswhile you meet new friendswith similar interests.