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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
02/10/2017 |
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Actualizado : |
02/10/2017 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
FRIONI, N.; ROVERE, G.; AGUILAR, I.; URIOSTE, J. |
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Afiliación : |
NICOLÁS FRIONI, Universidad de la República (UdelaR)/ Facultad de Agronomía (UY); Animal Breeding and Genetics Group, Department of Animal Sciences, Georg-August-University (DE); GABRIEL ROVERE, Universidad de la República (UdelaR)/ Facultad de Agronomía (UY); Department of Molecular Biology and Genetics, Centre for Quantitative Genetics and Genomics, Aarhus University (DK); IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JORGE I. URIOSTE, Universidad de la República (UdelaR)/ Facultad de Agronomía (UY). |
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Título : |
Genetic parameters and correlations between days open and production traits across lactations in pasture based dairy production systems. |
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Fecha de publicación : |
2017 |
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Fuente / Imprenta : |
Livestock Science, 2017, 204:104-109. |
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ISSN : |
1871-1413 |
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DOI : |
10.1016/j.livsci.2017.08.018 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 14 November 2016; Received in revised form 20 June 2017; Accepted 23 August 2017. |
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Contenido : |
ABSTRACT.
The aim of this study was to estimate the additive genetic correlations, heritabilities and repeatabilities of days open (DO), milk (MY), fat (FY) and protein yields (PY), using data from pasture based dairy systems of Uruguay, and to explore whether DO should be interpreted as a different trait across lactations or as a trait with repeated measures. The database contained 500, 412 and 294 thousand records of first, second and third lactation, respectively. Cows were offspring of 7747 sires. Fertility records lower and upper limits were 42 and 250 days, respectively. In a first approach (Mdiff) we estimated variance components and covariances over lactations, assuming that the traits were different at each lactation. In a second approach (Mrep) estimations were carried out considering each trait as a repeated measure along lactations. In Mdiff, DO with a production trait was analyzed considering each lactation as a different trait. Three six-variate linear models were analyzed (DO-MY, DO-FY, DO-PY, and lactations first to third). In the Mrep procedure, DO, MY, FY and PY were analyzed together with a multiple trait repeatability model. For all models, the fixed effects were herd-year-season and lactationage classes. Animal and the permanent environment effect were included as random effects. The additive genetic correlations between DO and yield traits by Mdiff were between +0.39 and +0.78; by Mrep, they ranged from +0.44 to +0.55. Heritabilities of DO by Mdiff were between 0.04 and 0.06 and 0.05 by Mrep. The additive genetic correlations of DO between lactations ranged from +0.76 to +0.91. Heritabilities of MY, FY and PY were 0.23, 0.21 and 0.21, respectively. Repeatabilities obtained were 0.10, 0.49, 0.47 and 0.49 for DO, MY, FY and PY, respectively. We concluded that the heritability of DO was low but enough to consider the trait in selection programs. We confirmed unfavorable additive genetic correlations between DO and yield traits for the Uruguayan pasture systems, which supports the importance of considering fertility in selection programs to reduce or avoid a decline in reproduction. The additive genetic correlations of DO between lactations were high, suggesting that a plausible model should consider DO records of a given animal as repeated measures.
© 2017 Elsevier B.V. All rights reserved. MenosABSTRACT.
The aim of this study was to estimate the additive genetic correlations, heritabilities and repeatabilities of days open (DO), milk (MY), fat (FY) and protein yields (PY), using data from pasture based dairy systems of Uruguay, and to explore whether DO should be interpreted as a different trait across lactations or as a trait with repeated measures. The database contained 500, 412 and 294 thousand records of first, second and third lactation, respectively. Cows were offspring of 7747 sires. Fertility records lower and upper limits were 42 and 250 days, respectively. In a first approach (Mdiff) we estimated variance components and covariances over lactations, assuming that the traits were different at each lactation. In a second approach (Mrep) estimations were carried out considering each trait as a repeated measure along lactations. In Mdiff, DO with a production trait was analyzed considering each lactation as a different trait. Three six-variate linear models were analyzed (DO-MY, DO-FY, DO-PY, and lactations first to third). In the Mrep procedure, DO, MY, FY and PY were analyzed together with a multiple trait repeatability model. For all models, the fixed effects were herd-year-season and lactationage classes. Animal and the permanent environment effect were included as random effects. The additive genetic correlations between DO and yield traits by Mdiff were between +0.39 and +0.78; by Mrep, they ranged from +0.44 to +0.55. Heritabilities of DO by Mdiff were... Presentar Todo |
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Palabras claves : |
DAIRY PRODUCTION; GENETIC CORRELATION; HERITABILITY; HOLSTEIN; REPRODUCTIVE PERFORMANCE. |
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Thesagro : |
GANADO LECHERO; RENDIMIENTO LECHERO. |
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Asunto categoría : |
-- |
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Marc : |
LEADER 03282naa a2200277 a 4500
001 1057620
005 2017-10-02
008 2017 bl uuuu u00u1 u #d
022 $a1871-1413
024 7 $a10.1016/j.livsci.2017.08.018$2DOI
100 1 $aFRIONI, N.
245 $aGenetic parameters and correlations between days open and production traits across lactations in pasture based dairy production systems.$h[electronic resource]
260 $c2017
500 $aArticle history: Received 14 November 2016; Received in revised form 20 June 2017; Accepted 23 August 2017.
520 $aABSTRACT. The aim of this study was to estimate the additive genetic correlations, heritabilities and repeatabilities of days open (DO), milk (MY), fat (FY) and protein yields (PY), using data from pasture based dairy systems of Uruguay, and to explore whether DO should be interpreted as a different trait across lactations or as a trait with repeated measures. The database contained 500, 412 and 294 thousand records of first, second and third lactation, respectively. Cows were offspring of 7747 sires. Fertility records lower and upper limits were 42 and 250 days, respectively. In a first approach (Mdiff) we estimated variance components and covariances over lactations, assuming that the traits were different at each lactation. In a second approach (Mrep) estimations were carried out considering each trait as a repeated measure along lactations. In Mdiff, DO with a production trait was analyzed considering each lactation as a different trait. Three six-variate linear models were analyzed (DO-MY, DO-FY, DO-PY, and lactations first to third). In the Mrep procedure, DO, MY, FY and PY were analyzed together with a multiple trait repeatability model. For all models, the fixed effects were herd-year-season and lactationage classes. Animal and the permanent environment effect were included as random effects. The additive genetic correlations between DO and yield traits by Mdiff were between +0.39 and +0.78; by Mrep, they ranged from +0.44 to +0.55. Heritabilities of DO by Mdiff were between 0.04 and 0.06 and 0.05 by Mrep. The additive genetic correlations of DO between lactations ranged from +0.76 to +0.91. Heritabilities of MY, FY and PY were 0.23, 0.21 and 0.21, respectively. Repeatabilities obtained were 0.10, 0.49, 0.47 and 0.49 for DO, MY, FY and PY, respectively. We concluded that the heritability of DO was low but enough to consider the trait in selection programs. We confirmed unfavorable additive genetic correlations between DO and yield traits for the Uruguayan pasture systems, which supports the importance of considering fertility in selection programs to reduce or avoid a decline in reproduction. The additive genetic correlations of DO between lactations were high, suggesting that a plausible model should consider DO records of a given animal as repeated measures. © 2017 Elsevier B.V. All rights reserved.
650 $aGANADO LECHERO
650 $aRENDIMIENTO LECHERO
653 $aDAIRY PRODUCTION
653 $aGENETIC CORRELATION
653 $aHERITABILITY
653 $aHOLSTEIN
653 $aREPRODUCTIVE PERFORMANCE
700 1 $aROVERE, G.
700 1 $aAGUILAR, I.
700 1 $aURIOSTE, J.
773 $tLivestock Science, 2017, 204:104-109.
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Registro original : |
INIA Las Brujas (LB) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
25/10/2016 |
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Actualizado : |
28/02/2020 |
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Tipo de producción científica : |
Trabajos en Congresos/Conferencias |
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Autor : |
SCARLATO, M.; DOGLIOTTI, S.; BERRUETA, C.; BARROS, C.; REHERMAN, F.; BORGES, A.; GARCÍA, M.; GIMÉNEZ, G. |
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Afiliación : |
MARIANA SCARLATO GARCIA, Universidad de la República (UdelaR)/ Facultad de Agronomía; SANTIAGO DOGLIOTTI, Universidad de la República (UdelaR)/ Facultad de Agronomía; MARIA CECILIA BERRUETA MOREIRA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; CARLOS BARROS, Universidad de la República (UdelaR)/ Facultad de Agronomía; FACUNDO REHERMAN, Universidad de la República (UdelaR)/ Facultad de Agronomía; ALEJANDRA BORGES, Universidad de la República (UdelaR)/ Facultad de Agronomía; MARGARITA GARCIA, Universidad de la República (UdelaR)/ Facultad de Agronomía; GUSTAVO GIMÉNEZ FRANQUEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Explaining yield variability between farmers as a first step to reduce gaps. |
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Complemento del título : |
T3. Crop modeling and yield gap analysis for agricultural systems analysis and design. |
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Fecha de publicación : |
2015 |
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Fuente / Imprenta : |
In: Proceedings of the 5th international symposium for farming systems design. Multi-functional farming systems in a changing world. Montpellier (Francia): European Society of Agronomy, 2015. |
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Páginas : |
p. 119-122 |
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Idioma : |
Inglés |
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Notas : |
Acknowledgements. Without the help of all the farmers that gently contributed their time and fields, and the help of the technical advisers and experts
to select a representative sample of farms, this research would have not be possible, so our sincere gratitude to all of them. This research was funded
by the National Institute of Agricultural Research (INIA), Project FPTA 288. |
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Contenido : |
Reducing yield gaps is one of the major pathways identified to meet the future food demand (Keating et al., 2014). A prerequisite to design strategies to reduce the yield gap of crops is to understand its causes. The sustainability of most vegetable farms in south Uruguay is threatened by low family income and deteriorating soil quality. The main cause of low income is that most farms obtain 50% or less of the attainable crop yields in the region, with similar production resources and proper management (Dogliotti et al., 2014). Low yields are the main cause of low labour productivity and resource use efficiency. There is a huge variability between farmers in crop yields, product quality and economic results. To explain the main causes of this variability and to identify strategies to reduce the distance between the average yield and the top yielding fields and farms, we started a project to study important vegetable crops in south Uruguay (onion, tomato, sweet potato and strawberry). In this paper we present the method developed to explain variability in physical and economic results, the main causes identified in the seasons studied on strawberry and onion,
and discuss strategies to reduce the observed gaps. |
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Palabras claves : |
ONION; STRAWBERRY. |
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Thesagro : |
CEBOLLA; FRUTILLA. |
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Asunto categoría : |
-- |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/6241/1/Scarlato-M.-2015.-5th-Int.Symp.Farming-Systems-Montpellier.pdf
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Marc : |
LEADER 02440nam a2200265 a 4500
001 1055898
005 2020-02-28
008 2015 bl uuuu u01u1 u #d
100 1 $aSCARLATO, M.
245 $aExplaining yield variability between farmers as a first step to reduce gaps.$h[electronic resource]
260 $aIn: Proceedings of the 5th international symposium for farming systems design. Multi-functional farming systems in a changing world. Montpellier (Francia): European Society of Agronomy$c2015
300 $ap. 119-122
500 $aAcknowledgements. Without the help of all the farmers that gently contributed their time and fields, and the help of the technical advisers and experts to select a representative sample of farms, this research would have not be possible, so our sincere gratitude to all of them. This research was funded by the National Institute of Agricultural Research (INIA), Project FPTA 288.
520 $aReducing yield gaps is one of the major pathways identified to meet the future food demand (Keating et al., 2014). A prerequisite to design strategies to reduce the yield gap of crops is to understand its causes. The sustainability of most vegetable farms in south Uruguay is threatened by low family income and deteriorating soil quality. The main cause of low income is that most farms obtain 50% or less of the attainable crop yields in the region, with similar production resources and proper management (Dogliotti et al., 2014). Low yields are the main cause of low labour productivity and resource use efficiency. There is a huge variability between farmers in crop yields, product quality and economic results. To explain the main causes of this variability and to identify strategies to reduce the distance between the average yield and the top yielding fields and farms, we started a project to study important vegetable crops in south Uruguay (onion, tomato, sweet potato and strawberry). In this paper we present the method developed to explain variability in physical and economic results, the main causes identified in the seasons studied on strawberry and onion, and discuss strategies to reduce the observed gaps.
650 $aCEBOLLA
650 $aFRUTILLA
653 $aONION
653 $aSTRAWBERRY
700 1 $aDOGLIOTTI, S.
700 1 $aBERRUETA, C.
700 1 $aBARROS, C.
700 1 $aREHERMAN, F.
700 1 $aBORGES, A.
700 1 $aGARCÍA, M.
700 1 $aGIMÉNEZ, G.
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