Evaluation of age, weaning weight, body condition score, and reproductive tract score in pre-selected beef heifers relative to reproductive potential
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摘要
Background: Artificial insemination is a preferred breeding method for beef heifers as it advances the genetic background, produces a predictive and profitable calving season, and extends the heifer's reproductive life span.As reproductive efficiency in heifers is key for the success of beef cattle production systems, following artificial insemination, heifers are exposed to a bull for the remainder of the breeding season. Altogether, up to 95% of heifers might become pregnant in their first breeding season. Heifers that do not become pregnant at the end of the breeding season represent an irreparable economical loss. Additionally, heifers conceiving late in the breeding season to natural service, although acceptable, poses serious losses to producers. To minimize losses due to reproductive failure, different phenotypic parameters can be assessed and utilized as selection tools. Here, we tested the hypothesis that in a group of pre-selected heifers, records of weaning weight, age at weaning, age at artificial insemination, and age of dam differ among heifers of varied reproductive outcomes during the first breeding season.Results: None of the parameters tested presented predictive ability to discriminate the heifers based on the response variable(‘pregnant to artificial insemination', ‘pregnant to natural service', ‘not pregnant'). Heifers categorized with body condition score = 6 and reproductive tract score ≥ 4 had the greatest proportion of pregnancy to artificial insemination(49% and 44%, respectively). Furthermore, it was notable that heifers presenting body condition score = 6 and reproductive tract score = 5 presented the greatest pregnancy rate at end of the breeding season(89%). Heifers younger than 368 d at the start of the breeding season did not become pregnant to artificial insemination. Those young heifers had 12.5% chance to become pregnant in their first breeding season,compared to 87.5% if the heifers were older than 368 days.Conclusion: Our results suggest that beef heifers with body condition score = 6 and reproductive tract score ≥ 4 are more likely to become pregnant to artificial insemination. Careful assessment should be undertaken when developing replacement heifers that will not reach 12 months of age by the beginning of the breeding season.
Background: Artificial insemination is a preferred breeding method for beef heifers as it advances the genetic background, produces a predictive and profitable calving season, and extends the heifer's reproductive life span.As reproductive efficiency in heifers is key for the success of beef cattle production systems, following artificial insemination, heifers are exposed to a bull for the remainder of the breeding season. Altogether, up to 95% of heifers might become pregnant in their first breeding season. Heifers that do not become pregnant at the end of the breeding season represent an irreparable economical loss. Additionally, heifers conceiving late in the breeding season to natural service, although acceptable, poses serious losses to producers. To minimize losses due to reproductive failure, different phenotypic parameters can be assessed and utilized as selection tools. Here, we tested the hypothesis that in a group of pre-selected heifers, records of weaning weight, age at weaning, age at artificial insemination, and age of dam differ among heifers of varied reproductive outcomes during the first breeding season.Results: None of the parameters tested presented predictive ability to discriminate the heifers based on the response variable(‘pregnant to artificial insemination', ‘pregnant to natural service', ‘not pregnant'). Heifers categorized with body condition score = 6 and reproductive tract score ≥ 4 had the greatest proportion of pregnancy to artificial insemination(49% and 44%, respectively). Furthermore, it was notable that heifers presenting body condition score = 6 and reproductive tract score = 5 presented the greatest pregnancy rate at end of the breeding season(89%). Heifers younger than 368 d at the start of the breeding season did not become pregnant to artificial insemination. Those young heifers had 12.5% chance to become pregnant in their first breeding season,compared to 87.5% if the heifers were older than 368 days.Conclusion: Our results suggest that beef heifers with body condition score = 6 and reproductive tract score ≥ 4 are more likely to become pregnant to artificial insemination. Careful assessment should be undertaken when developing replacement heifers that will not reach 12 months of age by the beginning of the breeding season.
Background: Artificial insemination is a preferred breeding method for beef heifers as it advances the genetic background, produces a predictive and profitable calving season, and extends the heifer's reproductive life span.As reproductive efficiency in heifers is key for the success of beef cattle production systems, following artificial insemination, heifers are exposed to a bull for the remainder of the breeding season. Altogether, up to 95% of heifers might become pregnant in their first breeding season. Heifers that do not become pregnant at the end of the breeding season represent an irreparable economical loss. Additionally, heifers conceiving late in the breeding season to natural service, although acceptable, poses serious losses to producers. To minimize losses due to reproductive failure, different phenotypic parameters can be assessed and utilized as selection tools. Here, we tested the hypothesis that in a group of pre-selected heifers, records of weaning weight, age at weaning, age at artificial insemination, and age of dam differ among heifers of varied reproductive outcomes during the first breeding season.Results: None of the parameters tested presented predictive ability to discriminate the heifers based on the response variable(‘pregnant to artificial insemination', ‘pregnant to natural service', ‘not pregnant'). Heifers categorized with body condition score = 6 and reproductive tract score ≥ 4 had the greatest proportion of pregnancy to artificial insemination(49% and 44%, respectively). Furthermore, it was notable that heifers presenting body condition score = 6 and reproductive tract score = 5 presented the greatest pregnancy rate at end of the breeding season(89%). Heifers younger than 368 d at the start of the breeding season did not become pregnant to artificial insemination. Those young heifers had 12.5% chance to become pregnant in their first breeding season,compared to 87.5% if the heifers were older than 368 days.Conclusion: Our results suggest that beef heifers with body condition score = 6 and reproductive tract score ≥ 4 are more likely to become pregnant to artificial insemination. Careful assessment should be undertaken when developing replacement heifers that will not reach 12 months of age by the beginning of the breeding season.
引文
1.Lamb GC.Criteria for selecting replacements at weaning,before breeding,and after breeding.Vet Clin North Am Food Anim Pract.2013;29(3):567-78.
2.Bormann JM,Totir LR,Kachman SD,Fernando RL,Wilson DE.Pregnancy rate and first-service conception rate in Angus heifers.J Anim Sci.2006;84(8):2022-5.
3.Roberts AJ,Geary TW,Grings EE,Waterman RC,MacNeil MD.Reproductive performance of heifers offered ad libitum or restricted access to feed for a one hundred forty-day period after weaning.J Anim Sci.2009;87(9):3043-52.
4.Rae DO,Kunkle WE,Chenoweth PJ,Sand RS,Tran T.Relationship of parity and body condition score to pregnancy rates in Florida beef-cattle.Theriogenology.1993;39(5):1143-52.
5.Peters SO,Kizilkaya K,Garrick DJ,Fernando RL,Reecy JM,Weaber RL,et al.Heritability and Bayesian genome-wide association study of first service conception and pregnancy in Brangus heifers.J Anim Sci.2013;2013(91):605-12.
6.Grings EE,Geary TW,Short RE,MacNeil MD.Beef heifer development within three calving systems.J Anim Sci.2007;85(8):2048-58.
7.Funston RN,Deutscher GH.Comparison of target breeding weight and breeding date for replacement beef heifers and effects on subsequent reproduction and calf performance.J Anim Sci.2004;82(10):3094-9.
8.Funston RN,Larson DM.Heifer development systems:dry-lot feeding compared with grazing dormant winter forage.J Anim Sci.2011;89(5):1595-602.
9.Gutierrez K,Kasimanickam R,Tibary A,Gay JM,Kastelic JP,Hall JB,et al.Effect of reproductive tract scoring on reproductive efficiency in beef heifers bred by timed insemination and natural service versus only natural service.Theriogenology.2014;81(7):918-24.
10.Martin JL,Creighton KW,Musgrave JA,Klopfenstein TJ,Clark RT,Adams DC,et al.Effect of prebreeding body weight or progestin exposure before breeding on beef heifer performance through the second breeding season.J Anim Sci.2008;86(2):451-9.
11.Rorie RW,Lester TD,Lindsey BR,McNew RW.Effect of timing of artificial insemination on gender ratio in beef cattle.Theriogenology.1999;52(6):1035-41.
12.Diskin MG,Sreenan JM.Fertilization and embryonic mortality rates in beef heifers after artificial insemination.J Reprod Fertil.1980;59(2):463-8.
13.Mathews KH,Short SD.The beef cow replacement decision.Journal of Agribusiness.2001;19(2):191-211.
14.Larson RL,White BJ,Laflin S.Beef Heifer Development.Vet Clin North Am Food Anim Pract.2016;32(2):285-302.
15.Hall JB.Nutritional development and the target weight debate.Vet Clin North Am Food Anim Pract.2013;29(3):537-54.
16.Holm DE,Nielen M,Jorritsma R,Irons PC,Thompson PN.Evaluation of pre-breeding reproductive tract scoring as a predictor of long term reproductive performance in beef heifers.Prev Vet Med.2015;118(1):56-63.
17.Fortes MRS,Snelling WM,Reverter A,Nagaraj SH,Lehnert SA,Hawken RJ,et al.Gene network analyses of fisrst service conception in Brangus heifers:use of genome and trait associations,hypothalamic-transcriptome information,and transcription factors.J Anim Sci.2012;2012(90):2894-906.
18.MacNeil MD,Geary TW,Perry GA,Roberts AJ,Alexander LJ.Genetic partitioning of variation in ovulatory follicle size and probability of pregnancy in beef cattle.J Anim Sci.2006;84(7):1646-50.
19.Diskin MG,Kenny DA.Managing the reproductive performance of beef cows.Theriogenology.2016;86(1):379-87.
20.Wagner JJ,Lusby KS,Oltjen JW,Rakestraw J,Wettemann RP,Walters LE.Carcass composition in mature Hereford cows:estimation and effect on daily metabolizable energy requirement during winter.J Anim Sci.1988;66(3):603-12.
21.Anderson KJ,Lefever DG,Brinks JS,Odde KG.The use of reproductive tract scoring in beef heifers.AgriPractice.1991;1991(12):19-26.
22.Larson JE,Lamb GC,Stevenson JS,Johnson SK,Day ML,Geary TW,et al.Synchronization of estrus in suckled beef cows for detected estrus and artificial insemination and timed artificial insemination using gonadotropin-releasing hormone,prostaglandin F2α,and progesterone.J Anim Sci.2006;84:332-42.
23.Ihaka R,Gentleman R.A Language and Environment for statistical computing.J Comput Graph Stat.1995;5:299-14.
24.Hedeker D.A mixed-effects multinomial logistic regression model.Stat Med.2003;22(9):1433-46.
25.Venables WN,Ripley BD.Modern applied statistics with S,fourth edition edn.New York:Springer;2002.
26.Bozdogan H.Model selection and Akaike information criterion(Aic)-the general-theory and its analytical extensions.Psychometrika.1987;52(3):345-70.
27.Burnham KP,Anderson DR.Multimodel inference-understanding AIC and BIC in model selection.Sociol Method Res.2004;33(2):261-304.
28.USDA:Beef 2007-08,part III:changes in the U.S.beef cow-calf industry,1993-2008.In.Edited by USDA:APHIS:VS C.Fort Collins,Co;2008.
29.Lamb GC,Dahen C,Mercadante VRG,Bischoff K.What is the impact of infertility in beef cattle?UF IFAS Extension University of Florida;2014.
30.Canellas LC,Barcellos JOJ,Nunes LN,de Oliveira TE,Prates ER,Darde DC.Post-weaning weight gain and pregnancy rate of beef heifers bred at18 months of age:a meta-analysis approach.Rev Bras Zootecn.2012;41(7):1632-7.
31.Holm DE,Thompson PN,Irons PC.The value of reproductive tract scoring as a predictor of fertility and production outcomes in beef heifers.J Anim Sci.2009;87(6):1934-40.
32.Perry GA,Cushman R.Effect of age at puberty/conception date on cow longevity.Vet Clin N Am-Food A.2013;29(3):579-90.
33.Cushman RA,Kill LK,Funston RN,Mousel EM,Perry GA.Heifer calving date positively influences calf weaning weights through six parturitions.J Anim Sci.2013;91(9):4486-91.
2.Bormann JM,Totir LR,Kachman SD,Fernando RL,Wilson DE.Pregnancy rate and first-service conception rate in Angus heifers.J Anim Sci.2006;84(8):2022-5.
3.Roberts AJ,Geary TW,Grings EE,Waterman RC,MacNeil MD.Reproductive performance of heifers offered ad libitum or restricted access to feed for a one hundred forty-day period after weaning.J Anim Sci.2009;87(9):3043-52.
4.Rae DO,Kunkle WE,Chenoweth PJ,Sand RS,Tran T.Relationship of parity and body condition score to pregnancy rates in Florida beef-cattle.Theriogenology.1993;39(5):1143-52.
5.Peters SO,Kizilkaya K,Garrick DJ,Fernando RL,Reecy JM,Weaber RL,et al.Heritability and Bayesian genome-wide association study of first service conception and pregnancy in Brangus heifers.J Anim Sci.2013;2013(91):605-12.
6.Grings EE,Geary TW,Short RE,MacNeil MD.Beef heifer development within three calving systems.J Anim Sci.2007;85(8):2048-58.
7.Funston RN,Deutscher GH.Comparison of target breeding weight and breeding date for replacement beef heifers and effects on subsequent reproduction and calf performance.J Anim Sci.2004;82(10):3094-9.
8.Funston RN,Larson DM.Heifer development systems:dry-lot feeding compared with grazing dormant winter forage.J Anim Sci.2011;89(5):1595-602.
9.Gutierrez K,Kasimanickam R,Tibary A,Gay JM,Kastelic JP,Hall JB,et al.Effect of reproductive tract scoring on reproductive efficiency in beef heifers bred by timed insemination and natural service versus only natural service.Theriogenology.2014;81(7):918-24.
10.Martin JL,Creighton KW,Musgrave JA,Klopfenstein TJ,Clark RT,Adams DC,et al.Effect of prebreeding body weight or progestin exposure before breeding on beef heifer performance through the second breeding season.J Anim Sci.2008;86(2):451-9.
11.Rorie RW,Lester TD,Lindsey BR,McNew RW.Effect of timing of artificial insemination on gender ratio in beef cattle.Theriogenology.1999;52(6):1035-41.
12.Diskin MG,Sreenan JM.Fertilization and embryonic mortality rates in beef heifers after artificial insemination.J Reprod Fertil.1980;59(2):463-8.
13.Mathews KH,Short SD.The beef cow replacement decision.Journal of Agribusiness.2001;19(2):191-211.
14.Larson RL,White BJ,Laflin S.Beef Heifer Development.Vet Clin North Am Food Anim Pract.2016;32(2):285-302.
15.Hall JB.Nutritional development and the target weight debate.Vet Clin North Am Food Anim Pract.2013;29(3):537-54.
16.Holm DE,Nielen M,Jorritsma R,Irons PC,Thompson PN.Evaluation of pre-breeding reproductive tract scoring as a predictor of long term reproductive performance in beef heifers.Prev Vet Med.2015;118(1):56-63.
17.Fortes MRS,Snelling WM,Reverter A,Nagaraj SH,Lehnert SA,Hawken RJ,et al.Gene network analyses of fisrst service conception in Brangus heifers:use of genome and trait associations,hypothalamic-transcriptome information,and transcription factors.J Anim Sci.2012;2012(90):2894-906.
18.MacNeil MD,Geary TW,Perry GA,Roberts AJ,Alexander LJ.Genetic partitioning of variation in ovulatory follicle size and probability of pregnancy in beef cattle.J Anim Sci.2006;84(7):1646-50.
19.Diskin MG,Kenny DA.Managing the reproductive performance of beef cows.Theriogenology.2016;86(1):379-87.
20.Wagner JJ,Lusby KS,Oltjen JW,Rakestraw J,Wettemann RP,Walters LE.Carcass composition in mature Hereford cows:estimation and effect on daily metabolizable energy requirement during winter.J Anim Sci.1988;66(3):603-12.
21.Anderson KJ,Lefever DG,Brinks JS,Odde KG.The use of reproductive tract scoring in beef heifers.AgriPractice.1991;1991(12):19-26.
22.Larson JE,Lamb GC,Stevenson JS,Johnson SK,Day ML,Geary TW,et al.Synchronization of estrus in suckled beef cows for detected estrus and artificial insemination and timed artificial insemination using gonadotropin-releasing hormone,prostaglandin F2α,and progesterone.J Anim Sci.2006;84:332-42.
23.Ihaka R,Gentleman R.A Language and Environment for statistical computing.J Comput Graph Stat.1995;5:299-14.
24.Hedeker D.A mixed-effects multinomial logistic regression model.Stat Med.2003;22(9):1433-46.
25.Venables WN,Ripley BD.Modern applied statistics with S,fourth edition edn.New York:Springer;2002.
26.Bozdogan H.Model selection and Akaike information criterion(Aic)-the general-theory and its analytical extensions.Psychometrika.1987;52(3):345-70.
27.Burnham KP,Anderson DR.Multimodel inference-understanding AIC and BIC in model selection.Sociol Method Res.2004;33(2):261-304.
28.USDA:Beef 2007-08,part III:changes in the U.S.beef cow-calf industry,1993-2008.In.Edited by USDA:APHIS:VS C.Fort Collins,Co;2008.
29.Lamb GC,Dahen C,Mercadante VRG,Bischoff K.What is the impact of infertility in beef cattle?UF IFAS Extension University of Florida;2014.
30.Canellas LC,Barcellos JOJ,Nunes LN,de Oliveira TE,Prates ER,Darde DC.Post-weaning weight gain and pregnancy rate of beef heifers bred at18 months of age:a meta-analysis approach.Rev Bras Zootecn.2012;41(7):1632-7.
31.Holm DE,Thompson PN,Irons PC.The value of reproductive tract scoring as a predictor of fertility and production outcomes in beef heifers.J Anim Sci.2009;87(6):1934-40.
32.Perry GA,Cushman R.Effect of age at puberty/conception date on cow longevity.Vet Clin N Am-Food A.2013;29(3):579-90.
33.Cushman RA,Kill LK,Funston RN,Mousel EM,Perry GA.Heifer calving date positively influences calf weaning weights through six parturitions.J Anim Sci.2013;91(9):4486-91.
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