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...
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Published in | Journal of animal science Vol. 101; no. Supplement_3; pp. 352 - 353 |
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Format | Journal Article |
Language | English |
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Oxford University Press
06.11.2023
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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. |
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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 |
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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. |
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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... |
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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 |
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