7.83 BA. At Generation 16, responses in Line IOL relative to Line C2were 2.08 OR, 2.64 FF, and 1.68 BA; responses in Line COL were 2.32OR, 2.16 FF, and 1.92 BA. Line means at Generation 23 were: L45 =13.2 FF and 11.4 BA, Line C2 = 8.63 FF and 7.91 BA. With the OR/UCmodel, predicted UC in Lines IOL, COL, and C2 at Generation 16 were16.3, 15.6, and 10.5 fetuses, respectively. Responses in UC in latergenerations cannot be predicted because OR was not recorded. Balancingselection for OR and UC to increase LS based on the OR/UC modelappears to be more effective than index selection for OR and ES or directselection for LS. Direct LS selection is expected to be most effective inpopulations with high mean OR but average LS. QTL scans in theselines have identified one chromosomal position affecting OR and 14others affecting FF, BA, or numbers <strong>of</strong> mummified and stillborn piglets.Key Words: Pigs, Selection, Litter size95 What we have learned about prenatal physiology in the pigfrom uterine crowding experiments. J. Vallet*, B. Freking, J. P.Kayser, R. Christenson, and K. Leymaster, USDA, ARS, Roman L.Hruska U.S. Meat <strong>Animal</strong> Research Center, Clay Center, NE.The factor most limiting to litter size is becoming uterine capacity, thenumber <strong>of</strong> fetuses that the uterus can maintain until farrowing. Intrauterinecrowding does not appreciably limit litter size until after day 30<strong>of</strong> gestation, with most fetal loss occurring between day 30 and 40 <strong>of</strong>gestation, although further losses occur in later gestation. We have usedunilateral hysterectomy-ovariectomy (UHO) to study the effects <strong>of</strong>intrauterine crowding on the uterus, fetus and placenta. Studies indicatedfew effects on uterine function, measured as endometrial proteinsecretion. In UHO gilts, fetal hematocrits decreased with fetal weight,suggesting that small fetuses were anemic. This observation led to thediscovery <strong>of</strong> a polymorphism in the porcine erythropoietin receptorgene that is associated with litter size. Fetal brain growth is relativelyresistant to intrauterine crowding, particularly during late gestation. Incontrast, growth <strong>of</strong> the fetal heart is more resistant to crowding duringearly pregnancy. Further work on the mechanisms that shunt nutrientsto various organs could provide improvements in litter size. Finally,several previous studies indicate that placental efficiency (fetalweight:placental weight ratio) increased due to intrauterine crowding.Other studies suggest that placental folding may influence the efficiency<strong>of</strong> the placenta. The depth <strong>of</strong> placental folding increased in placentasassociated with the smallest fetus in a litter. This occurred at the expense<strong>of</strong> the fetal stroma layer surrounding the placental interface. Duringlate gestation in some small fetuses, the placenta may have no furtherroom to increase folding, potentially resulting in death. This couldexplain fetal losses due to intrauterine crowding that occur during lategestation. In summary, although the full effects <strong>of</strong> intrauterine crowdingare still unclear, clues are beginning to unfold that could result in improvementsin litter size in swine.Key Words: Uterus, Placenta, Fetus96 Fetal programming: what do we know and what are theimplications for the swine industry? R. Anthony* 1,2 , 1 ColoradoState University, Fort Collins, 2 University <strong>of</strong> Colorado Health <strong>Science</strong>sCenter, Aurora.The concept <strong>of</strong> “fetal programming” or the “fetal origins <strong>of</strong> adult disease”hypothesis originated with extensive epidemiological studies <strong>of</strong>various human populations. It is now well documented that growthrestrictedinfants, or infants <strong>of</strong> normal birth weights that experience analtered growth trajectory sometime during gestation, have a greater predispositionfor coronary heart disease, hypertension, obesity, and type2 diabetes as adults. These disease states are inter-related, and collectivelythey have been designated as the Metabolic Syndrome. Fetalgrowth restriction can result from a variety <strong>of</strong> causes, the majority <strong>of</strong>which cause functional placental insufficiency and a failure to provideadequate nutrition to the developing fetus. Consequently, growth-restrictedfetuses are <strong>of</strong>ten hypoglycemic, hypoinsulinemic and hypoxic,and in more severe cases the fetus is also hypertensive and acidemic.Impaired organ growth and development, particularly with the abdominalorgans, occurs in these individuals, altering postnatal growth ratesand metabolic regulation as these <strong>of</strong>fspring age. While these adult diseasestates are not <strong>of</strong>ten a concern in livestock production, altered metabolichomeostasis as a result <strong>of</strong> impaired fetal growth may well impactlivestock production efficiency. A number <strong>of</strong> animal models, primarilyin rodents and sheep, have been developed and used to investigate fetalgrowth restriction and the postnatal consequences, providing considerableinsight into the fetal and postnatal manifestation <strong>of</strong> fetal growthrestriction and the development <strong>of</strong> the metabolic syndrome. While pigshave not been used as extensively as sheep and rodents, recent studiescomparing low-birthweight (1.5 kg) pigsprovide evidence for “fetal programming” and its impact on adult metabolism.Low-birthweight pigs exhibit altered juvenile cardiovascularfunction, impaired glucose tolerance and insulin resistance as adults, aswell as increased adult fat depth. These results suggest impaired fetalgrowth may well have a significant impact on growth and composition<strong>of</strong> swine, thereby impacting the efficiency <strong>of</strong> swine production.Key Words: Swine, Fetal growth restriction, Metabolic syndromeDairy Extension Symposium - Starch Utilization by Ruminants97 Laboratory methods <strong>of</strong> analysis for feedstuff starch contentand availability. M. B. Hall*, U. S. Dairy Forage Research Center,USDA-ARS, Madison, WI.The relationships that starch has with pr<strong>of</strong>itable production or withhealth disorders in cattle advise closer accounting <strong>of</strong> its quantity andquality in diets. Native starch is an Α-(1-4)-linked-glucan with Α-(1-6)linked branch points found in crystalline granules in plants. In feedstuffs,it can be analyzed by enzymatic hydrolysis, or by polarimetry, thoughboth suffer from interferences. Analysis by enzymatic hydrolysis requiresgelatinization, hydrolysis with enzymes specific for starch anddetection <strong>of</strong> glucose. Gelatinization breaks hydrogen bonds and the32
crystalline structure <strong>of</strong> starch granules, making starch more available toenzymatic attack. It has been accomplished using water + heating, alkali,and dimethyl sulfoxide among other methods. Enzymatic hydrolysisrequires enzymes <strong>of</strong> adequate specificity to release glucose onlyfrom starch, and appropriate conditions to take hydrolysis to completion.Heat-stable, Α-amylase, an endoamylase, can partially hydrolyzestarch before amyloglucosidase, an exoamylase, completes the hydrolysisto glucose. Detection <strong>of</strong> released glucose is best done by assaysspecific for glucose. Recoveries <strong>of</strong> pure starch <strong>of</strong>ten range from 90% to98% on a dry matter basis, and analyses typically have a repeatability<strong>of</strong> + 2% units. Pure starches from different plant sources may differ inrecovery values. Most <strong>of</strong>t noted errors include use <strong>of</strong> enzyme preparationsthat release glucose from non-starch molecules, lack <strong>of</strong> correctionfor free glucose, and incomplete hydrolysis. Indices <strong>of</strong> rate and potentialextent <strong>of</strong> digestibility <strong>of</strong> starch could be useful to formulate dietsthat promote both good production and health. Assays using enzymaticglucose release from starch and disappearance <strong>of</strong> starch during microbialfermentation have been used to assess these characteristics. Method <strong>of</strong>sample processing for analysis affects the results. Relative indices <strong>of</strong>rate or extent <strong>of</strong> starch digestion could be useful in the field. However,for these assays to be applied to describing quantitative differencesamong starch sources, they need to be linked to a ration formulation orevaluation system that is calibrated to the values they provide.Key Words: Starch, Analysis, Nonfiber carbohydrate98 Applied aspects <strong>of</strong> starch in dairy cattle feeding programs.R. Shaver and P. H<strong>of</strong>fman*, University <strong>of</strong> Wisconsin, Madison.varying proportions <strong>of</strong> starch, sugar, soluble fiber, organic acids, and issubject to errors associated with analyzing the five nutrients (CP, NDF,NDFCP, Fat, Ash) used to calculate NFC. Components <strong>of</strong> NFC varygreatly in their ruminal degradability as well as the end-products <strong>of</strong> theirdegradation in the rumen. Starch is the component <strong>of</strong> NFC most closelyrelated to ruminal propionate production and thus likely <strong>of</strong> highestinterest from the standpoint <strong>of</strong> ruminal pH, milk fat content, and subacuterumen acidosis. Dose response trials evaluating dietary starchcontent versus lactation performance are limited. Dietary starch allowancescommonly used in the field range from 25% to 30% (DM basis)depending on the content <strong>of</strong> physically-effective NDF and (or) theruminal degradability <strong>of</strong> starch sources in the diet. Future research aimedat this dose response and on these interactions is needed. Although theDairy NRC 2001 summative energy equation was based on NFC, starchrather than NFC is being used in summative energy equations by manycommercial feed testing labs especially for corn silage. However, determiningdigestion coefficients for starch to use in summative energyequations has been difficult. The Dairy NRC 2001 uses arbitrary processingadjustment factors, while the MILK2000 corn silage evaluationprogram varies the starch digestion coefficient by regression using wholeplantDM and kernel processing as factors. Both approaches are limitedin their ability for detecting potential variation in starch digestibilityacross a wide array <strong>of</strong> samples, and novel lab assays are needed. Ruminalin-vitro or in-situ degradation, either alone or in combination with invitro post-ruminal enzymatic digestion <strong>of</strong> the ruminal residues, havebeen explored by some research groups. We recently developed an enzymaticlab assay, Degree <strong>of</strong> Starch Access (DSA), which is sensitive todifferences in particle size, moisture content, and vitreousness <strong>of</strong> cornbasedfeeds. Field and in vivo evaluation <strong>of</strong> these assays in dairy cattlefeeding programs is needed.Key Words: Starch, Digestion, Dairy cattleDairy cattle nutritionists have long used non-fiber carbohydrate (NFC)as a quasi-nutrient. However, NFC is a calculated value comprised <strong>of</strong>Growth and Development, Muscle Biology, and Meat <strong>Science</strong> Symposium -Components <strong>of</strong> Meat Quality99 Crossing the line between muscle and meat: The influence<strong>of</strong> muscle cell physiology on meat quality. E. Huff-Lonergan* and S.Lonergan, Iowa State University, Ames.Efforts designed to develop an understanding <strong>of</strong> the mechanisms behindthe manifestation <strong>of</strong> many meat quality attributes must first define thepostmortem biology <strong>of</strong> muscle tissue. Only by having a good understanding<strong>of</strong> these mechanisms can investigators efficiently solve qualityinconsistencies that face the meat industry now and in the future. Muscleis an extremely intricate and dynamic tissue that depends on highlycoordinated interactions between numerous my<strong>of</strong>ibrillar, cytoskeletaland sarcoplasmic proteins to maintain its function and integrity. Likewise,meat is also a highly complex substance that depends upon many<strong>of</strong> the factors present in living muscle for its quality attributes. Therefore,it is imperative that researchers investigating fresh meat qualityhave an understanding <strong>of</strong> how muscle proteins (both structural proteinsand enzyme systems) function and how these proteins respond tointracellular changes occurring during the early postmortem period. Theconversion <strong>of</strong> muscle to meat results in a set <strong>of</strong> conditions in postmortemmuscle that is vastly different from those in living tissue. As muscleis converted to meat, many changes occur, including: 1) a gradual depletion<strong>of</strong> available energy, 2) a shift from aerobic to anaerobic metabolism,favoring the production <strong>of</strong> lactic acid and resulting in tissue pH decline,and 3) a rise in ionic strength, in part, because <strong>of</strong> the inability <strong>of</strong> ATPdependentcalcium, sodium, and potassium pumps to function. Anotherchange that occurs in postmortem muscle is increased oxidation <strong>of</strong> proteins.Differences in the rate <strong>of</strong> oxidation and other postmortem changesin muscle tissue are seen when comparing the same muscles betweenanimals and/or carcasses. These differences may arise because <strong>of</strong> differencesin diet, breed, antemortem stress, postmortem handling <strong>of</strong> carcasses,etc. There are also numerous differences in the way specificmuscles undergo many postmortem changes. Therefore, there may bemany differences between muscles in their susceptibility to oxidationand other postmortem changes that could be capitalized upon to improvemeat quality.Key Words: Muscle, Meat, Meat quality33
- Page 1: Table of ContentsAbstractPageNumber
- Page 5 and 6: Graduate Student Oral Competition -
- Page 7 and 8: 13 Effect of corn hybrid and proces
- Page 9 and 10: height. About 5 g of cecum content
- Page 11 and 12: to 70. Placental IGF-I tended to in
- Page 13 and 14: dent-intruder score (RIS) was given
- Page 15 and 16: 37 Hormone concentrations of produc
- Page 17 and 18: main person responsible for managin
- Page 19 and 20: 50 Environmental factors affecting
- Page 21 and 22: tions did not differ among treatmen
- Page 23 and 24: Table 1. Effects of ractopamine on
- Page 25 and 26: 67 Effect of feeding reduced phosph
- Page 27 and 28: 73 Effect of feed intake level, bod
- Page 29 and 30: Ruminant Nutrition79 Effect of impr
- Page 31 and 32: and site of digestion. Treatments c
- Page 33: Menten (GMM) functions. Two pig spe
- Page 37 and 38: 103 Relationship between dietary fa
- Page 39 and 40: 112 Effects of supplementing natura
- Page 41 and 42: 118 Application of 2-hydroxy-4-(met
- Page 43 and 44: 124 Ruminant diet composition effec
- Page 45 and 46: 131 Impact of fiber types on rumen
- Page 47 and 48: 138 Sow and litter performance in i
- Page 49 and 50: 147 Structural correctness and mobi
- Page 51 and 52: 153 Propionate regulation of feed i
- Page 53 and 54: 161 Genetically improving the produ
- Page 55 and 56: elative to heifers receiving MGA al
- Page 57 and 58: tus ventralis and the infraspinatus
- Page 59 and 60: three weeks for the remainder of th
- Page 61 and 62: tion over the course of a 112-d per
- Page 63 and 64: ies have indicated that a sizable p
- Page 65 and 66: lower urine pH (P < 0.0001) and blo
- Page 67 and 68: 204 Effect of weaning age on nurser
- Page 69 and 70: Ten Broeck*, D. Clopton, R. Bott, M
- Page 71 and 72: creasing DDGS. Forage intake in hay
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- Page 75 and 76: offal from 26,231 head; and 406,405
- Page 77 and 78: heritability and gain during the 20
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- Page 81 and 82: having rancid, bloody, and bitter f
- Page 83 and 84: to 14, and was higher (P < 0.03) in
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261 Effects of supplemental RDP ver
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ammonia, and total VFA increased ov
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Dairy Extension Symposium - Innovat
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tion of nonpregnant cows early post
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285 Effect of feeding diets contain
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291 Effect of dietary flaxseed, fla
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Edmonton, AB. Canada, 2 Department
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capillary number density (CND)) by
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allowed to expose for 2 weeks, deve
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of sulfur (1700 ppm) and fed with r
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correlated (r=0.56; P
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Table 1. CDR (% of BLUP) for S1-S5
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Author IndexASAS/ADSA Midwestern Se
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Jenschke, B., 170Jiménez, E., 307J
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Stahly, T. S., 66Stalder, K., 9, 56