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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
24/05/2016 |
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Actualizado : |
24/06/2021 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
GOLDBERG, V.; RAVAGNOLO, O. |
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Afiliación : |
VIRGINIA GOLDBERG BIANCHI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; OLGA RAVAGNOLO GUMILA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Description of the growth curve for Angus pasture-fed cows under extensive systems. |
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Fecha de publicación : |
2015 |
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Fuente / Imprenta : |
Journal of Animal Science, 2015, v.93, no. 9, p. 4285-4290. |
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ISBN : |
10.2527/jas.2015-9208 |
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Idioma : |
Inglés |
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Notas : |
This work would not be possible without the support and data from the Uruguayan Aberdeen Angus Breed Society and the Rural Association of Uruguay. Appreciation is expressed to Drs. Ignacio Aguilar, Mario Lema, and Graciela Quintans from INIA for their valuables comments and suggestions.
Received April 15, 2015. / Accepted July 10, 2015 / Published September 8, 2015 |
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Contenido : |
ABSTRACT.
Growth curves are useful for describing the sigmoid shape of an animal?s weight pattern over time. The purpose of the present study was to describe, for the first time, a complete growth curve for pasture-fed Angus cows in Uruguay and to analyze the major fixed effects that affect the estimation of mature cow weight (CW). A total of 22,743 records from 5,284 cows belonging to 73 herds were used in the statistical analysis. Five nonlinear models (Brody, Gompertz, Von Bertalanffy, logistic, and Richards) and a 3-knot cubic spline function were fitted to model weight change across age. Body weights were recorded at birth, weaning, and 18 mo and as an adult (at 2.3?3.6, 3.6?4.6, 4.6 to 5.6, 5.6 to 6.6, and 6.6 to 8.1 yr). After preliminary analyses, the fixed effects included in the model to estimate CW were BCS, herd, year and month of measurement, and age of dam. The herd and BCS were the major significant sources of variation. The Richards model had the lowest values for Akaike information criterion, Bayesian information criterion, and ?2 log likelihood, with the asymptotic weight being 542 kg. The spline function was the model that fitted the data most closely to the observed weights followed by the Richards function. The Richards model gave better predictions of weights from birth to maturity than the other 4 nonlinear models, because these functions were shown to over- or underestimate weights at different ages in this beef cattle data set. The predicted curve showed that cows reach mature CW after 5 yr of age, which is the age commonly assumed as adult weight in beef cattle. Results form this analysis allowed the estimation of CW and rate of maturing and to take knowledge of the shape of growth curve for Angus females in Uruguay under extensive conditions, helping breeders to take selection decisions. In this way, breeders can optimize the management and efficiency for each production system.
© 2015 American Society of Animal Science. All rights reserved. MenosABSTRACT.
Growth curves are useful for describing the sigmoid shape of an animal?s weight pattern over time. The purpose of the present study was to describe, for the first time, a complete growth curve for pasture-fed Angus cows in Uruguay and to analyze the major fixed effects that affect the estimation of mature cow weight (CW). A total of 22,743 records from 5,284 cows belonging to 73 herds were used in the statistical analysis. Five nonlinear models (Brody, Gompertz, Von Bertalanffy, logistic, and Richards) and a 3-knot cubic spline function were fitted to model weight change across age. Body weights were recorded at birth, weaning, and 18 mo and as an adult (at 2.3?3.6, 3.6?4.6, 4.6 to 5.6, 5.6 to 6.6, and 6.6 to 8.1 yr). After preliminary analyses, the fixed effects included in the model to estimate CW were BCS, herd, year and month of measurement, and age of dam. The herd and BCS were the major significant sources of variation. The Richards model had the lowest values for Akaike information criterion, Bayesian information criterion, and ?2 log likelihood, with the asymptotic weight being 542 kg. The spline function was the model that fitted the data most closely to the observed weights followed by the Richards function. The Richards model gave better predictions of weights from birth to maturity than the other 4 nonlinear models, because these functions were shown to over- or underestimate weights at different ages in this beef cattle data set. The predicted curve s... Presentar Todo |
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Palabras claves : |
ABERDEEN ANGUS; BEEF CATTLE; GROWTH MODELS; MATURE COW WEIGHT. |
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Thesagro : |
BOVINOS PARA CARNE; MODELOS DE CRECIMIENTO. |
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Asunto categoría : |
-- |
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Marc : |
LEADER 03004naa a2200217 a 4500
001 1054844
005 2021-06-24
008 2015 bl uuuu u00u1 u #d
100 1 $aGOLDBERG, V.
245 $aDescription of the growth curve for Angus pasture-fed cows under extensive systems.$h[electronic resource]
260 $c2015
500 $aThis work would not be possible without the support and data from the Uruguayan Aberdeen Angus Breed Society and the Rural Association of Uruguay. Appreciation is expressed to Drs. Ignacio Aguilar, Mario Lema, and Graciela Quintans from INIA for their valuables comments and suggestions. Received April 15, 2015. / Accepted July 10, 2015 / Published September 8, 2015
520 $aABSTRACT. Growth curves are useful for describing the sigmoid shape of an animal?s weight pattern over time. The purpose of the present study was to describe, for the first time, a complete growth curve for pasture-fed Angus cows in Uruguay and to analyze the major fixed effects that affect the estimation of mature cow weight (CW). A total of 22,743 records from 5,284 cows belonging to 73 herds were used in the statistical analysis. Five nonlinear models (Brody, Gompertz, Von Bertalanffy, logistic, and Richards) and a 3-knot cubic spline function were fitted to model weight change across age. Body weights were recorded at birth, weaning, and 18 mo and as an adult (at 2.3?3.6, 3.6?4.6, 4.6 to 5.6, 5.6 to 6.6, and 6.6 to 8.1 yr). After preliminary analyses, the fixed effects included in the model to estimate CW were BCS, herd, year and month of measurement, and age of dam. The herd and BCS were the major significant sources of variation. The Richards model had the lowest values for Akaike information criterion, Bayesian information criterion, and ?2 log likelihood, with the asymptotic weight being 542 kg. The spline function was the model that fitted the data most closely to the observed weights followed by the Richards function. The Richards model gave better predictions of weights from birth to maturity than the other 4 nonlinear models, because these functions were shown to over- or underestimate weights at different ages in this beef cattle data set. The predicted curve showed that cows reach mature CW after 5 yr of age, which is the age commonly assumed as adult weight in beef cattle. Results form this analysis allowed the estimation of CW and rate of maturing and to take knowledge of the shape of growth curve for Angus females in Uruguay under extensive conditions, helping breeders to take selection decisions. In this way, breeders can optimize the management and efficiency for each production system. © 2015 American Society of Animal Science. All rights reserved.
650 $aBOVINOS PARA CARNE
650 $aMODELOS DE CRECIMIENTO
653 $aABERDEEN ANGUS
653 $aBEEF CATTLE
653 $aGROWTH MODELS
653 $aMATURE COW WEIGHT
700 1 $aRAVAGNOLO, O.
773 $tJournal of Animal Science, 2015$gv.93, no. 9, p. 4285-4290.
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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 : |
12/06/2024 |
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Actualizado : |
12/06/2024 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
FARIÑA, S.; MORENO, O.V.; CANDIOTI, F.; VILLANUEVA, C.; LEDEZMA, W.S.; MOSCOSO, C.J.; CAJARVILLE, C.; CHARLÓN, V.; ABAUNZA, L.U.; VITERI, A.G.; CHIRIFE, S.; HERRERA, D.; STIRLING, S. |
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Afiliación : |
SANTIAGO FARIÑA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ORCID: https://orcid.org/0000-0003-2386-7136; OSIRIS VIGIL MORENO, Instituto de Innovación Agropecuaria de Panamá (IDIAP), Ciudad del Saber, Clayton, Cuidad de Panamá, Panama; FRANCISCO CANDIOTI, Salto Agro S.S., Bgdier. E. López 1822, Gdor. Candioti, Santa Fe, Argentina; CRISTÓBAL VILLANUEVA, Centro Agronómico Tropical de Investigación y Enseñanza (CATIE), Turrialba, Costa Rica; WILLIAM SÁNCHEZ LEDEZMA, Instituto Nacional de Innovación y Transferencia en Tecnología Agropecuaria (INTA), Costa Rica; CRISTIAN J. MOSCOSO, Instituto de Investigaciones Agropecuarias, INIA Remehue, P.O. Box 24-0, Osorno, Chile; CECILIA CAJARVILLE, Facultad de Veterinaria, Universidad de la República (UdelaR), Ruta 1, km 42.5, San José, Uruguay; VERÓNICA CHARLÓN, Instituto Nacional de Tecnología Agropecuaria (INTA), Estación Experimental Rafaela, Francia 459, Rafaela, Santa Fe, Argentina; LUIS URBINA ABAUNZA, Instituto Nicaragüense de Tecnología Agropecuaria (INTA), Managua, Nicaragua; ANTONIO GUACAPIÑA VITERI, Instituto Nacional de Investigaciones Agropecuarias (INIAP), Estación Experimental Santa Catalina, Panamericana Sur km. 1, Mejía, Ecuador; SILVIA CHIRIFE, Instituto Paraguayo de Tecnología Agraria (IPTA), Oficina Central, Ruta 2, Km 10,5, San Lorenzo, Paraguay; DOMICIANO HERRERA, Instituto de Innovación Agropecuaria de Panamá (IDIAP), Ciudad del Saber, Clayton, Cuidad de Panamá, Panama; MARÍA SOFÍA STIRLING SANTOS, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ORCID: https://orcid.org/0000-0001-6053-0386. |
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Título : |
Milk production systems in Latin America and the Caribbean: Biophysical, socio-economic, and environmental performance. |
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Fecha de publicación : |
2024 |
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Fuente / Imprenta : |
Agricultural Systems, 2024, Volume 218, 03987. https://doi.org/10.1016/j.agsy.2024.103987 |
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ISSN : |
0308-521X |
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DOI : |
10.1016/j.agsy.2024.103987 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 2 December 2023, Revised 8 March 2024, Accepted 30 April 2024, Available online 7 May 2024, Version of Record 7 May 2024. -- Correspondence: Fariña, S.; Instituto Nacional de Investigación Agropecuaria (INIA), Ruta 50 km 11, Colonia, Uruguay; email:santiagofarina1@gmail.com -- Funding: This research was funded by FONTAGRO through the project "Sustainable Intensification of Dairy" with grant FTG/RF-15940-RG. |
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Contenido : |
ABSTRACT.- CONTEXT: The Latin America-Caribbean (LAC) region has the potential to pursue a sustainable expansion of livestock production and capitalise on the growing global demand for dairy and beef products. However, it is necessary to understand the predominant production systems and their biophysical, economic, social, and environmental performances. OBJECTIVE: This study aimed to compare the milk production systems of nine countries of the region according to their major biophysical, socio-economic, and environmental performance indicators. METHODS: A panel of experts from different research organisations of each of the 9 countries defined the modal milk production system based on national reports and statistics. Each system was modelled by means of a whole-farm model, and 22 performance indicators were estimated as a result. The countries were classified in groups by cluster and principal component analyses and the sources of similarities and differences among them were described using the information provided by the 22 indicators evaluated. © 2023 |
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Palabras claves : |
Dairy system; Decent work and economic growth - Goal 8; LAC region; Partnership for the goals - Goal 17; Performance indicators; SISTEMA LECHERO - INIA; Sustainability; Sustainable Development Goals (SDGs). |
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Asunto categoría : |
A50 Investigación agraria |
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Marc : |
LEADER 02736naa a2200397 a 4500
001 1064642
005 2024-06-12
008 2024 bl uuuu u00u1 u #d
022 $a0308-521X
024 7 $a10.1016/j.agsy.2024.103987$2DOI
100 1 $aFARIÑA, S.
245 $aMilk production systems in Latin America and the Caribbean$bBiophysical, socio-economic, and environmental performance.$h[electronic resource]
260 $c2024
500 $aArticle history: Received 2 December 2023, Revised 8 March 2024, Accepted 30 April 2024, Available online 7 May 2024, Version of Record 7 May 2024. -- Correspondence: Fariña, S.; Instituto Nacional de Investigación Agropecuaria (INIA), Ruta 50 km 11, Colonia, Uruguay; email:santiagofarina1@gmail.com -- Funding: This research was funded by FONTAGRO through the project "Sustainable Intensification of Dairy" with grant FTG/RF-15940-RG.
520 $aABSTRACT.- CONTEXT: The Latin America-Caribbean (LAC) region has the potential to pursue a sustainable expansion of livestock production and capitalise on the growing global demand for dairy and beef products. However, it is necessary to understand the predominant production systems and their biophysical, economic, social, and environmental performances. OBJECTIVE: This study aimed to compare the milk production systems of nine countries of the region according to their major biophysical, socio-economic, and environmental performance indicators. METHODS: A panel of experts from different research organisations of each of the 9 countries defined the modal milk production system based on national reports and statistics. Each system was modelled by means of a whole-farm model, and 22 performance indicators were estimated as a result. The countries were classified in groups by cluster and principal component analyses and the sources of similarities and differences among them were described using the information provided by the 22 indicators evaluated. © 2023
653 $aDairy system
653 $aDecent work and economic growth - Goal 8
653 $aLAC region
653 $aPartnership for the goals - Goal 17
653 $aPerformance indicators
653 $aSISTEMA LECHERO - INIA
653 $aSustainability
653 $aSustainable Development Goals (SDGs)
700 1 $aMORENO, O.V.
700 1 $aCANDIOTI, F.
700 1 $aVILLANUEVA, C.
700 1 $aLEDEZMA, W.S.
700 1 $aMOSCOSO, C.J.
700 1 $aCAJARVILLE, C.
700 1 $aCHARLÓN, V.
700 1 $aABAUNZA, L.U.
700 1 $aVITERI, A.G.
700 1 $aCHIRIFE, S.
700 1 $aHERRERA, D.
700 1 $aSTIRLING, S.
773 $tAgricultural Systems, 2024, Volume 218, 03987. https://doi.org/10.1016/j.agsy.2024.103987
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