PSXII-2 Lactation Persistence Analysis and Its Genetic Correlations with Productive, Reproductive, and Health Traits in the First Two Parities in Lucerna Cattle

Abstract Lactation persistency (LP) is a trait of economic relevance in dairy cattle since persistent cows are more profitable by presenting fewer diseases, requiring fewer inputs, and having better reproductive performance. Therefore, the main objective of this study was to estimate genetic relatio...

Full description

Saved in:
Bibliographic Details
Published inJournal of animal science Vol. 101; no. Supplement_3; pp. 352 - 353
Main Authors Sierra, Sergio N Sanchez, Herrera, Luis Gabriel Gonzalez, Peñagaricano, Francisco
Format Journal Article
LanguageEnglish
Published US Oxford University Press 06.11.2023
Subjects
Online AccessGet full text

Cover

Loading…
Abstract Abstract Lactation persistency (LP) is a trait of economic relevance in dairy cattle since persistent cows are more profitable by presenting fewer diseases, requiring fewer inputs, and having better reproductive performance. Therefore, the main objective of this study was to estimate genetic relationships between lactation persistency for mastitis (MT), calving interval (CI), and 305–day milk yield (305M) in first and second Lucerna cattle lactations. Records from 67,952 test–day milk, 7,100 CI, and 1,074 clinical-mastitis evaluations from two Colombian farms of Creole dual-purpose cattle were considered. Five three-parameter equations, as reported in previous literature, were graphically and statistically evaluated for fitting a lactation curve (LC) for each parity. The goodness-of-fit criteria included AIC, BIC, RSS, and R2. The most appropriate equation was identified and implemented for predicting 305M for 4,620 lactations (2,716 and 1,904 from first and second parity, respectively) for which LP was estimated. Bi-trait animal models between LP-MT, LP-CI, and LP-M305 for each parity were executed in the BLUPF90+ software (AI-REML algorithm) to estimate heritabilities (h2) and genetic correlations (GC). Fixed effects of herd, year of calving, season of calving, b0 lactation parameter, and age at calving were included. Estimates of goodness-of-fit criteria for all LC equations varied between R2 (0.29 – 0.68), BIC (132,322 – 207,415), AIC (132,289 – 207,389), and RSS (188,231 – 414,007). The incomplete gamma equation best satisfied the goodness-of-fit-criteria and drew the most accurate LC in both parities. Due to the low data density in this work, estimates involving MT and CI had increased standard deviations; therefore, the interpretation should be considered cautiously. The h2 estimates were 0.0 and 0.24 for MT, 0.02 and 0.09 for CI, 0.18 and 0.36 for M305, and 0.14 and 0.15 for LP, for the first and second parity, respectively. The GC estimates were -0.24 and -0.41 for LP–M305, 0.31 – 0.35 for LP–CI, and -0.76 for LP–MT for each parity, respectively. The results of this study suggest that LP could be considered as a selection target in the farms’ breeding program since desirable relationships were found with all evaluated traits for the first and second parity.
AbstractList Abstract Lactation persistency (LP) is a trait of economic relevance in dairy cattle since persistent cows are more profitable by presenting fewer diseases, requiring fewer inputs, and having better reproductive performance. Therefore, the main objective of this study was to estimate genetic relationships between lactation persistency for mastitis (MT), calving interval (CI), and 305–day milk yield (305M) in first and second Lucerna cattle lactations. Records from 67,952 test–day milk, 7,100 CI, and 1,074 clinical-mastitis evaluations from two Colombian farms of Creole dual-purpose cattle were considered. Five three-parameter equations, as reported in previous literature, were graphically and statistically evaluated for fitting a lactation curve (LC) for each parity. The goodness-of-fit criteria included AIC, BIC, RSS, and R2. The most appropriate equation was identified and implemented for predicting 305M for 4,620 lactations (2,716 and 1,904 from first and second parity, respectively) for which LP was estimated. Bi-trait animal models between LP-MT, LP-CI, and LP-M305 for each parity were executed in the BLUPF90+ software (AI-REML algorithm) to estimate heritabilities (h2) and genetic correlations (GC). Fixed effects of herd, year of calving, season of calving, b0 lactation parameter, and age at calving were included. Estimates of goodness-of-fit criteria for all LC equations varied between R2 (0.29 – 0.68), BIC (132,322 – 207,415), AIC (132,289 – 207,389), and RSS (188,231 – 414,007). The incomplete gamma equation best satisfied the goodness-of-fit-criteria and drew the most accurate LC in both parities. Due to the low data density in this work, estimates involving MT and CI had increased standard deviations; therefore, the interpretation should be considered cautiously. The h2 estimates were 0.0 and 0.24 for MT, 0.02 and 0.09 for CI, 0.18 and 0.36 for M305, and 0.14 and 0.15 for LP, for the first and second parity, respectively. The GC estimates were -0.24 and -0.41 for LP–M305, 0.31 – 0.35 for LP–CI, and -0.76 for LP–MT for each parity, respectively. The results of this study suggest that LP could be considered as a selection target in the farms’ breeding program since desirable relationships were found with all evaluated traits for the first and second parity.
Lactation persistency (LP) is a trait of economic relevance in dairy cattle since persistent cows are more profitable by presenting fewer diseases, requiring fewer inputs, and having better reproductive performance. Therefore, the main objective of this study was to estimate genetic relationships between lactation persistency for mastitis (MT), calving interval (CI), and 305–day milk yield (305M) in first and second Lucerna cattle lactations. Records from 67,952 test–day milk, 7,100 CI, and 1,074 clinical-mastitis evaluations from two Colombian farms of Creole dual-purpose cattle were considered. Five three-parameter equations, as reported in previous literature, were graphically and statistically evaluated for fitting a lactation curve (LC) for each parity. The goodness-of-fit criteria included AIC, BIC, RSS, and R2. The most appropriate equation was identified and implemented for predicting 305M for 4,620 lactations (2,716 and 1,904 from first and second parity, respectively) for which LP was estimated. Bi-trait animal models between LP-MT, LP-CI, and LP-M305 for each parity were executed in the BLUPF90+ software (AI-REML algorithm) to estimate heritabilities (h2) and genetic correlations (GC). Fixed effects of herd, year of calving, season of calving, b0 lactation parameter, and age at calving were included. Estimates of goodness-of-fit criteria for all LC equations varied between R2 (0.29 – 0.68), BIC (132,322 – 207,415), AIC (132,289 – 207,389), and RSS (188,231 – 414,007). The incomplete gamma equation best satisfied the goodness-of-fit-criteria and drew the most accurate LC in both parities. Due to the low data density in this work, estimates involving MT and CI had increased standard deviations; therefore, the interpretation should be considered cautiously. The h2 estimates were 0.0 and 0.24 for MT, 0.02 and 0.09 for CI, 0.18 and 0.36 for M305, and 0.14 and 0.15 for LP, for the first and second parity, respectively. The GC estimates were -0.24 and -0.41 for LP–M305, 0.31 – 0.35 for LP–CI, and -0.76 for LP–MT for each parity, respectively. The results of this study suggest that LP could be considered as a selection target in the farms’ breeding program since desirable relationships were found with all evaluated traits for the first and second parity.
Lactation persistency (LP) is a trait of economic relevance in dairy cattle since persistent cows are more profitable by presenting fewer diseases, requiring fewer inputs, and having better reproductive performance. Therefore, the main objective of this study was to estimate genetic relationships between lactation persistency for mastitis (MT), calving interval (CI), and 305–day milk yield (305M) in first and second Lucerna cattle lactations. Records from 67,952 test–day milk, 7,100 CI, and 1,074 clinical-mastitis evaluations from two Colombian farms of Creole dual-purpose cattle were considered. Five three-parameter equations, as reported in previous literature, were graphically and statistically evaluated for fitting a lactation curve (LC) for each parity. The goodness-of-fit criteria included AIC, BIC, RSS, and R 2 . The most appropriate equation was identified and implemented for predicting 305M for 4,620 lactations (2,716 and 1,904 from first and second parity, respectively) for which LP was estimated. Bi-trait animal models between LP-MT, LP-CI, and LP-M305 for each parity were executed in the BLUPF90+ software (AI-REML algorithm) to estimate heritabilities (h 2 ) and genetic correlations (GC). Fixed effects of herd, year of calving, season of calving, b 0 lactation parameter, and age at calving were included. Estimates of goodness-of-fit criteria for all LC equations varied between R 2 (0.29 – 0.68), BIC (132,322 – 207,415), AIC (132,289 – 207,389), and RSS (188,231 – 414,007). The incomplete gamma equation best satisfied the goodness-of-fit-criteria and drew the most accurate LC in both parities. Due to the low data density in this work, estimates involving MT and CI had increased standard deviations; therefore, the interpretation should be considered cautiously. The h 2 estimates were 0.0 and 0.24 for MT, 0.02 and 0.09 for CI, 0.18 and 0.36 for M305, and 0.14 and 0.15 for LP, for the first and second parity, respectively. The GC estimates were -0.24 and -0.41 for LP–M305, 0.31 – 0.35 for LP–CI, and -0.76 for LP–MT for each parity, respectively. The results of this study suggest that LP could be considered as a selection target in the farms’ breeding program since desirable relationships were found with all evaluated traits for the first and second parity.
Author Sierra, Sergio N Sanchez
Peñagaricano, Francisco
Herrera, Luis Gabriel Gonzalez
Author_xml – sequence: 1
  givenname: Sergio N Sanchez
  surname: Sierra
  fullname: Sierra, Sergio N Sanchez
– sequence: 2
  givenname: Luis Gabriel Gonzalez
  surname: Herrera
  fullname: Herrera, Luis Gabriel Gonzalez
– sequence: 3
  givenname: Francisco
  surname: Peñagaricano
  fullname: Peñagaricano, Francisco
BookMark eNqFUUtrGzEQFiWFOG7OuQp6K91YWq20u6cSTB4GQ03rQm5irJ2t5W4kV9Im5N_0p1aJTWlPPQ0z32OY-c7IifMOCbng7JKzVsx2EGfxB3Rlwy8r3rwhEy5LWQiuxAmZMFbyoml4eUrOYtwxxkvZygn5tfp6v1gUJV2CSZCsd3SFIdqY0BmkVw6G59xRcB1dpEhv0WGyhs59CDi8CiJ9smlLV8F3o0n2ET_SL7j_q3vR3iEMmbQOYLOLdTRtkd7YEBNdP3m6gmCTxVdkORoMDugcUhrwHXnbwxDx_Fin5NvN9Xp-Vyw_3y7mV8vClIw1heoQVd02fKOaEmpQEqqK52mlNlx2Ld9ABcJ0rBe1kpUoe9bWgpsa695wRDElnw6--3HzgJ1BlwIMeh_sA4Rn7cHqfxFnt_q7f9ScKSFk_vKUvD86BP9zxJj0zo_5kCFqwSSvVVMpmVmzA8sEH2PA_s8KzvRLkDoHqY9B6hxkVnw4KPy4_y_5N7znpSs
ContentType Journal Article
Copyright The Author(s) 2023. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. 2023
The Author(s) 2023. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Copyright_xml – notice: The Author(s) 2023. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. 2023
– notice: The Author(s) 2023. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
DBID AAYXX
CITATION
K9.
U9A
5PM
DOI 10.1093/jas/skad281.418
DatabaseName CrossRef
ProQuest Health & Medical Complete (Alumni)
PubMed Central (Full Participant titles)
DatabaseTitle CrossRef
ProQuest Health & Medical Complete (Alumni)
Career and Technical Education (Alumni Edition)
DatabaseTitleList CrossRef

ProQuest Health & Medical Complete (Alumni)

DeliveryMethod fulltext_linktorsrc
Discipline Agriculture
DocumentTitleAlternate ASAS Annual 2023 Meeting Abstracts
EISSN 1525-3163
EndPage 353
ExternalDocumentID 10_1093_jas_skad281_418
10.1093/jas/skad281.418
GroupedDBID ---
..I
.55
.GJ
0R~
186
18M
29J
2WC
3V.
48X
53G
5GY
5RE
5WD
7RQ
7X2
7X7
7XC
88A
88E
88I
8AF
8FE
8FG
8FH
8FI
8FJ
8FW
8G5
8R4
8R5
AAHBH
AAIMJ
AAPQZ
AAPXW
AARHZ
AASNB
AAUAY
AAUQX
AAVAP
AAWDT
ABCQX
ABJCF
ABJNI
ABMNT
ABPTD
ABSAR
ABUWG
ABWST
ABXVV
ACFRR
ACGFO
ACGFS
ACGOD
ACIWK
ACPRK
ACQAM
ACUTJ
ACZBC
ADBBV
ADFRT
ADGZP
ADIPN
ADNWM
ADQBN
ADRTK
ADVEK
AELWJ
AENEX
AETBJ
AFFZL
AFGWE
AFKRA
AFRAH
AFYAG
AGINJ
AGKRT
AGMDO
AGQXC
AHMBA
AI.
AJEEA
ALIPV
ALMA_UNASSIGNED_HOLDINGS
ANFBD
AOIJS
APJGH
AQDSO
ASAOO
ATCPS
ATDFG
ATGXG
AZQEC
BAYMD
BBNVY
BCRHZ
BENPR
BES
BEYMZ
BGLVJ
BHPHI
BKOMP
BPHCQ
BVXVI
C1A
CCPQU
CS3
DIK
DU5
DWQXO
E3Z
EBS
ECGQY
EJD
ELUNK
EYRJQ
F5P
F9R
FHSFR
FJW
FLUFQ
FOEOM
FQBLK
FYUFA
GAUVT
GNUQQ
GUQSH
H13
HCIFZ
HMCUK
HYE
INIJC
KBUDW
KOP
KSI
KSN
L6V
L7B
LK8
M0K
M0L
M1P
M2O
M2P
M2Q
M7P
M7S
MBTAY
ML0
MV1
MW2
NEJ
NHB
NLBLG
NOMLY
NVLIB
O9-
OBOKY
ODMLO
OJZSN
OK1
OWPYF
P-O
P0-
P2P
PATMY
PQQKQ
PRG
PROAC
PSQYO
PTHSS
PYCSY
Q2X
ROX
RPM
RUSNO
RWL
RXW
S0X
SJN
TAE
TCN
TJA
TR2
TWZ
UKHRP
VH1
W8F
WH7
WOQ
X7M
XOL
YKV
YXANX
ZCG
ZGI
ZXP
~KM
AAYXX
CITATION
ABEJV
K9.
U9A
5PM
ID FETCH-LOGICAL-c2008-6dee67981b682a7a65a4416de46b15d91ba4a3cd0f3765432f09731c7e7fc1ee3
IEDL.DBID RPM
ISSN 0021-8812
IngestDate Thu Nov 07 05:35:30 EST 2024
Wed Nov 06 08:06:35 EST 2024
Thu Sep 12 18:31:51 EDT 2024
Wed Aug 28 03:18:16 EDT 2024
IsDoiOpenAccess false
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue Supplement_3
Keywords dairy performance
genetic parameters
animal genetic resources
Language English
License This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/pages/standard-publication-reuse-rights)
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c2008-6dee67981b682a7a65a4416de46b15d91ba4a3cd0f3765432f09731c7e7fc1ee3
OpenAccessLink https://academic.oup.com/jas/article-pdf/101/Supplement_3/352/52958127/skad281.418.pdf
PQID 3051768465
PQPubID 49113
PageCount 2
ParticipantIDs pubmedcentral_primary_oai_pubmedcentral_nih_gov_10633516
proquest_journals_3051768465
crossref_primary_10_1093_jas_skad281_418
oup_primary_10_1093_jas_skad281_418
PublicationCentury 2000
PublicationDate 20231106
PublicationDateYYYYMMDD 2023-11-06
PublicationDate_xml – month: 11
  year: 2023
  text: 20231106
  day: 6
PublicationDecade 2020
PublicationPlace US
PublicationPlace_xml – name: US
– name: Champaign
PublicationTitle Journal of animal science
PublicationYear 2023
Publisher Oxford University Press
Publisher_xml – name: Oxford University Press
SSID ssj0012595
Score 2.4585435
Snippet Abstract Lactation persistency (LP) is a trait of economic relevance in dairy cattle since persistent cows are more profitable by presenting fewer diseases,...
Lactation persistency (LP) is a trait of economic relevance in dairy cattle since persistent cows are more profitable by presenting fewer diseases, requiring...
SourceID pubmedcentral
proquest
crossref
oup
SourceType Open Access Repository
Aggregation Database
Publisher
StartPage 352
SubjectTerms Algorithms
Animal lactation
Animal models
Cattle
Criteria
Curve fitting
Dairy cattle
Estimates
Farms
Genetic analysis
Genetic relationship
Goodness of fit
Lactation
Mastitis
Milk
Parameters
Parity
Reproduction
Title PSXII-2 Lactation Persistence Analysis and Its Genetic Correlations with Productive, Reproductive, and Health Traits in the First Two Parities in Lucerna Cattle
URI https://www.proquest.com/docview/3051768465
https://pubmed.ncbi.nlm.nih.gov/PMC10633516
Volume 101
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3JTsMwELVoT3BArGKtRoIDB9LgeElyRBWFIkCVAKm3yHYcCNCA2iJ-h09lnAW1JySOiWPH0pvYz5mZN4Qca-HOGVZ4SnPrca4jT3ORejzUMhMsFnHmkpNv7-TVI78eidESkU0uTBm0b3TeLd7G3SJ_LmMrP8bGb-LE_OFtD4dnTFDpt0gLLbQ5o9e-AyT0Vd2CgHoR7l-NoE_M_Bc19aevKg0i2uWuzsfcXrSQ3-Zo5mKQ5Nyu018jqzVdhPNqWutkyRYbZOX8aVJLZthN8j28Hw0GXgA3ylR-dXBh7Q4-BBQa1RFQRQqD2RSc0DSOBj1Xl6OOhAP3OxaGlforrn-ngMR87sr1rRKWADe3HEfJC0DqCP0c2SM8fL3DUE1KcVbXcoP2gvOGXqmQvEUe-xcPvSuvrrvgmTIaQqbWOucM1TIKVKikUEia8C6Xmoo0plpxxUx6luHqJDgLMqf5Q01ow8xQa9k2aRfvhd0hEIvAahMqqpELhCqL4siGSKoyEximjdglJw0CyUclr5FUbnGWIFhJDVaCYO2SI0To76cOGgST-mucJswJkUlkWvi-aAHV3-GcyvZiCxpfqbbdGNve_7vuk2VXpb5MYZQHpD2bfNpD5DIz3SGtqH_ZKQ34B9qS-Qc
link.rule.ids 230,315,730,783,787,888,27936,27937,33385,53804,53806
linkProvider National Library of Medicine
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LT9tAEF4BPRQOqIVWBGg7Ehw41HHW-7B9RFajpCQoUoOUm7W7XoOBGJQE8Xf4qcz6USWnSj36seOVvt2db70z3xByroXbZ1jhKc2tx7mOPM1F5vFQy1ywWMS5S04eX8vBDf89E7MtIttcmCpo3-iiWz7Ou2VxV8VWPs-N38aJ-ZNxguYZE1T62-QDTtgeb3fpzekBUvq6ckFAvQg9WCvpEzP_Xi395YPKgoh2uav0seaNNjLcHNHcDJNc8zv9T2S_IYxwWXfsM9my5QHZu7xdNKIZ9pC8Tf7MhkMvgJEy9ck6uMB2ByBCCq3uCKgyg-FqCU5qGq1B4ipzNLFw4H7IwqTWf8UV8CcgNV-7cm3rlCVA91aglaIEJI_QL5A_wvT1CSZqUcmzuicjHDHYb0gqjeQv5Kb_a5oMvKbygmeqeAiZWeuOZ6iWUaBCJYVC2oR3udRUZDHViitmsl6O65PgLMid6g81oQ1zQ61lX8lO-VTaIwKxCKw2oaIa2UCo8iiObIi0KjeBYdqIDrloEUifa4GNtD4YZymClTZgpQhWh5whQv9-67RFMG3m4zJlTopMItfC70UbqP4153S2N5_g8Kv0ttvhdvz_TX-Qj4PpeJSOhtdXJ2TX1ayvEhrlKdlZLV7sN2Q2K_29GsbvOKH7dw
linkToPdf http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LT9wwELYoSFV7QNCHoLxGag89NBscP5Ic0cKKhQVFKkh7i2zHaUNLWG0W8Xf4qYwTp9o9VeKYhyeWPtvzOTP-hpBvWrh9hhWB0twGnOsk0FwUAY-1LAVLRVq6w8lX1_L8ll9MxdRnVTY-rbI2uhrUf-8HdfW7za2c3ZuwzxMLs6shmmdMUBnOijJ8QzZw0h7LfqfuIwhI67vqBRENEvRivaxPysI71YTNH1VECR1wV-1jySOtnHJzZHM1VXLJ94y2yKYnjXDSdW6brNn6A3l_8mvuhTPsR_Kc_ZyOx0EEE2W66Dq45HYHIsIKvfYIqLqA8aIBJzeN1mDoqnP4fDhwP2Uh6zRgcRX8AUjPl65c2-7YEqCLq9BKVQMSSBhVyCHh5ukBMjVvJVrdkwmOGuw3DFud5E_kdnR2MzwPfPWFwLQ5EbKw1oVoqJZJpGIlhULqhHe51FQUKdWKK2aK4xLXKMFZVDrlH2piG5eGWss-k_X6obY7BFIRWW1iRTUygliVSZrYGKlVaSLDtBG75HuPQD7rRDbyLjjOcgQr92DlCNYu-YoI_f-t_R7B3M_JJmdOjkwi38LvJSuo_jPntLZXn-AQbDW3-yH35fVNj8jb7HSUT8bXl3vknStb355plPtkfTF_tAdIbhb6sB3FL8X3_Io
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=PSXII-2+Lactation+Persistence+Analysis+and+Its+Genetic+Correlations+with+Productive%2C+Reproductive%2C+and+Health+Traits+in+the+First+Two+Parities+in+Lucerna+Cattle&rft.jtitle=Journal+of+animal+science&rft.au=Sierra%2C+Sergio+N+Sanchez&rft.au=Herrera%2C+Luis+Gabriel+Gonzalez&rft.au=Pe%C3%B1agaricano%2C+Francisco&rft.date=2023-11-06&rft.pub=Oxford+University+Press&rft.issn=0021-8812&rft.eissn=1525-3163&rft.volume=101&rft.issue=Supplement_3&rft.spage=352&rft.epage=353&rft_id=info:doi/10.1093%2Fjas%2Fskad281.418&rft.externalDocID=10.1093%2Fjas%2Fskad281.418
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0021-8812&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0021-8812&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0021-8812&client=summon