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Biblioteca (s) : |
INIA Tacuarembó. |
Fecha : |
27/04/2020 |
Actualizado : |
27/04/2020 |
Autor : |
MAZZANTI, A; MARINO, M.A; LATTANZI, F; ECHEVERRÍA, H.A.; ANDRADE, F |
Afiliación : |
A. MAZZANTI, INTA (Instituto Nacional de Tecnología Agropecuaria)- Balcarce; M. A. MARINO, FCA - UNMDP. Unidad Integrada Balcarce. Becaria de la Comisión de Investigaciones Científicas de la Provincia de Buenos Aires.; F. LATTANZI, Postgrado en Producción Animal. Becario FCA - UNMDP. Unidad Integrada Balcarce.; H. A. ECHEVERRÍA, INTA (Instituto Nacional de Tecnología Agropecuaria)- Balcarce; F. ANDRADE, INTA (Instituto Nacional de Tecnología Agropecuaria)- Balcarce. |
Título : |
Efecto de la fertilización nitrogenada sobre el crecimiento y la calidad del forraje de avena y raigrás anual en el sudeste bonaerense. |
Fecha de publicación : |
1997 |
Fuente / Imprenta : |
Boletín Técnico, no. 143, p. 1-28, 1997. |
ISSN : |
ISSN 0522-0548 |
Idioma : |
Español |
Contenido : |
El crecimiento inverno primaveral de gramíneas forrajeras es limitado por las temperaturas del período. Para el sudeste bonaerense se han identificado especies y
cultivares de gramíneas introducidas o nativas con alto potencial para crecer a las temperaturas que normalmente ocurren en los meses de invierno y principios de primavera. No obstante, la expresión de dicho potencial, se hallaría limitada por la baja disponibilidad de formas asimilables de nitrógeno en los suelos. En este trabajo se condensa información publicada en una serie de trabajos en los que se estudió el efecto de la fertilización nitrogenada sobre el crecimiento de forraje a fines de invierno y principios de primavera de pasturas de raigrás anual y avena, que son las especies anuales más sembradas en la región,y se las utiliza para atenuar las deficiencias en el crecimiento de forraje de pasturas cultivadas y pastizales naturales. |
Palabras claves : |
FERTILIZACIÓN NITROGENADA; FORRAJE; PASTURAS. |
Asunto categoría : |
A50 Investigación agraria |
Marc : |
LEADER 01588naa a2200217 a 4500 001 1061038 005 2020-04-27 008 1997 bl uuuu u00u1 u #d 022 $aISSN 0522-0548 100 1 $aMAZZANTI, A 245 $aEfecto de la fertilización nitrogenada sobre el crecimiento y la calidad del forraje de avena y raigrás anual en el sudeste bonaerense.$h[electronic resource] 260 $c1997 520 $aEl crecimiento inverno primaveral de gramíneas forrajeras es limitado por las temperaturas del período. Para el sudeste bonaerense se han identificado especies y cultivares de gramíneas introducidas o nativas con alto potencial para crecer a las temperaturas que normalmente ocurren en los meses de invierno y principios de primavera. No obstante, la expresión de dicho potencial, se hallaría limitada por la baja disponibilidad de formas asimilables de nitrógeno en los suelos. En este trabajo se condensa información publicada en una serie de trabajos en los que se estudió el efecto de la fertilización nitrogenada sobre el crecimiento de forraje a fines de invierno y principios de primavera de pasturas de raigrás anual y avena, que son las especies anuales más sembradas en la región,y se las utiliza para atenuar las deficiencias en el crecimiento de forraje de pasturas cultivadas y pastizales naturales. 653 $aFERTILIZACIÓN NITROGENADA 653 $aFORRAJE 653 $aPASTURAS 700 1 $aMARINO, M.A 700 1 $aLATTANZI, F 700 1 $aECHEVERRÍA, H.A. 700 1 $aANDRADE, F 773 $tBoletín Técnico, no. 143, p. 1-28, 1997.
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INIA Tacuarembó (TBO) |
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Biblioteca (s) : |
INIA Las Brujas. |
Fecha actual : |
26/11/2015 |
Actualizado : |
29/01/2020 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Circulación / Nivel : |
Internacional - -- |
Autor : |
LOURENCO, D. A. L.; TSURUTA, S.; FRAGOMENI, B. O.; MASUDA, Y.; AGUILAR, I.; LEGARRA, A.; BERTRAND, J. K.; AMEN, T. S.; WANG. L.; MOSER, D. W.; MISZTAL, I. |
Afiliación : |
D. A. L. LOURENCO, Universidad de Georgia (UG); SHOGO TSURUTA, Universidad de Georgia (UG); B. O. FRAGOMENI, Universidad de Georgia (UG); Y. MASUDA, Universidad de Georgia (UG); IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; A. LEGARRA, INRA (Institut National de la Recherche Agronomique); J. K. BERTRAND, Universidad de Georgia (UG); T. S. AMEN, Angus Genetics Inc.; L. WANG, Angus Genetics Inc.; D. W. MOSER, Angus Genetics Inc.; IGNACY MISZTAL, Universidad de Georgia (UG). |
Título : |
Genetic evaluation using single-step genomic best linear unbiased predictor in American Angus.(*) |
Fecha de publicación : |
2015 |
Fuente / Imprenta : |
Journal of Animal Science, 2015, v. 93, p. 2653-2662. Published June 25, 2015. OPEN ACCESS. |
DOI : |
10.2527/jas.2014-8836 |
Idioma : |
Inglés |
Notas : |
(*) This study was partially funded by the American Angus Association (St. Joseph, MO), Zoetis (Kalamazoo, MI), and Agriculture and Food Research Initiative Competitive Grants no. 2015-67015-22936 from the U.S. Department of Agriculture?s National Institute of Food and Agriculture. We gratefully acknowledge the very helpful comments by the two anonymous reviewers. |
Contenido : |
ABSTRACT.
Predictive ability of genomic EBV when using single-step genomic BLUP (ssGBLUP) in Angus cattle was investigated. Over 6 million records were available on birth weight (BiW) and weaning weight (WW), almost 3.4 million on postweaning gain (PWG), and over 1.3 million on calving ease (CE). Genomic information was available on, at most, 51,883 animals,
which included high and low EBV accuracy animals. Traditional EBV was computed by BLUP and genomic EBV by ssGBLUP and indirect prediction based on SNP effects was derived from ssGBLUP; SNP effects were calculated based on the following reference populations: ref_2k (contains top bulls and top cows that had an EBV accuracy for BiW ≥0.85), ref_8k (contains all parents that were genotyped), and ref_33k (contains all genotyped animals born up to 2012). Indirect prediction was obtained as direct genomic value (DGV) or as an
index of DGV and parent average (PA). Additionally, runs with ssGBLUP used the inverse of the genomic relationship matrix calculated by an algorithm for proven and young animals (APY) that uses recursions on a small subset of reference animals. An extra reference subset included 3,872 genotyped parents of genotyped animals (ref_4k). Cross-validation was used to assess predictive ability on a validation population of 18,721 animals born in 2013. Computations for growth traits used multiple-trait linear model and, for CE, a bivariate CE?BiW threshold-linear model. With BLUP, predictivities were 0.29, 0.34, 0.23, and 0.12 for BiW, WW, PWG, and CE, respectively. With ssGBLUP and ref_2k, predictivities were 0.34, 0.35, 0.27, and 0.13 for BiW, WW, PWG, and CE, respectively, and with ssGBLUP and ref_33k, predictivities were 0.39, 0.38, 0.29, and 0.13 for BiW, WW, PWG, and CE, respectively. Low predictivity for CE was due to low incidence rate of difficult calving. Indirect predictions with ref_33k were as accurate as with full ssGBLUP. Using the APY and recursions on ref_4k gave 88% gains of full ssGBLUP and using the APY and recursions on ref_8k gave 97% gains of full ssGBLUP. Genomic evaluation in beef cattle with ssGBLUP is feasible while keeping the models (maternal, multiple trait, and threshold) already used in regular BLUP. Gains in predictivity are dependent on the composition of the reference population. Indirect predictions via SNP effects derived from ssGBLUP allow for accurate genomic predictions on young animals, with no advantage of including PA in
the index if the reference population is large. With the APY conditioning on about 10,000 reference animals, ssGBLUP is potentially applicable to a large number of genotyped animals without compromising predictive ability.
© 2015 American Society of Animal Science. All rights reserved MenosABSTRACT.
Predictive ability of genomic EBV when using single-step genomic BLUP (ssGBLUP) in Angus cattle was investigated. Over 6 million records were available on birth weight (BiW) and weaning weight (WW), almost 3.4 million on postweaning gain (PWG), and over 1.3 million on calving ease (CE). Genomic information was available on, at most, 51,883 animals,
which included high and low EBV accuracy animals. Traditional EBV was computed by BLUP and genomic EBV by ssGBLUP and indirect prediction based on SNP effects was derived from ssGBLUP; SNP effects were calculated based on the following reference populations: ref_2k (contains top bulls and top cows that had an EBV accuracy for BiW ≥0.85), ref_8k (contains all parents that were genotyped), and ref_33k (contains all genotyped animals born up to 2012). Indirect prediction was obtained as direct genomic value (DGV) or as an
index of DGV and parent average (PA). Additionally, runs with ssGBLUP used the inverse of the genomic relationship matrix calculated by an algorithm for proven and young animals (APY) that uses recursions on a small subset of reference animals. An extra reference subset included 3,872 genotyped parents of genotyped animals (ref_4k). Cross-validation was used to assess predictive ability on a validation population of 18,721 animals born in 2013. Computations for growth traits used multiple-trait linear model and, for CE, a bivariate CE?BiW threshold-linear model. With BLUP, predictivities were 0.29,... Presentar Todo |
Palabras claves : |
BEEF CATTLE; GENETIC RESURSION; INDIRECT PREDICTION. |
Thesagro : |
GANADO DE CARNE; GENOMIC SELECTION; MEJORAMIENTO GENETICO ANIMAL. |
Asunto categoría : |
L10 Genética y mejoramiento animal |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/5303/1/Lourenco-et-al-2015-JAS.pdf
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Marc : |
LEADER 04125naa a2200337 a 4500 001 1054005 005 2020-01-29 008 2015 bl uuuu u00u1 u #d 024 7 $a10.2527/jas.2014-8836$2DOI 100 1 $aLOURENCO, D. A. L. 245 $aGenetic evaluation using single-step genomic best linear unbiased predictor in American Angus.(*)$h[electronic resource] 260 $c2015 500 $a(*) This study was partially funded by the American Angus Association (St. Joseph, MO), Zoetis (Kalamazoo, MI), and Agriculture and Food Research Initiative Competitive Grants no. 2015-67015-22936 from the U.S. Department of Agriculture?s National Institute of Food and Agriculture. We gratefully acknowledge the very helpful comments by the two anonymous reviewers. 520 $aABSTRACT. Predictive ability of genomic EBV when using single-step genomic BLUP (ssGBLUP) in Angus cattle was investigated. Over 6 million records were available on birth weight (BiW) and weaning weight (WW), almost 3.4 million on postweaning gain (PWG), and over 1.3 million on calving ease (CE). Genomic information was available on, at most, 51,883 animals, which included high and low EBV accuracy animals. Traditional EBV was computed by BLUP and genomic EBV by ssGBLUP and indirect prediction based on SNP effects was derived from ssGBLUP; SNP effects were calculated based on the following reference populations: ref_2k (contains top bulls and top cows that had an EBV accuracy for BiW ≥0.85), ref_8k (contains all parents that were genotyped), and ref_33k (contains all genotyped animals born up to 2012). Indirect prediction was obtained as direct genomic value (DGV) or as an index of DGV and parent average (PA). Additionally, runs with ssGBLUP used the inverse of the genomic relationship matrix calculated by an algorithm for proven and young animals (APY) that uses recursions on a small subset of reference animals. An extra reference subset included 3,872 genotyped parents of genotyped animals (ref_4k). Cross-validation was used to assess predictive ability on a validation population of 18,721 animals born in 2013. Computations for growth traits used multiple-trait linear model and, for CE, a bivariate CE?BiW threshold-linear model. With BLUP, predictivities were 0.29, 0.34, 0.23, and 0.12 for BiW, WW, PWG, and CE, respectively. With ssGBLUP and ref_2k, predictivities were 0.34, 0.35, 0.27, and 0.13 for BiW, WW, PWG, and CE, respectively, and with ssGBLUP and ref_33k, predictivities were 0.39, 0.38, 0.29, and 0.13 for BiW, WW, PWG, and CE, respectively. Low predictivity for CE was due to low incidence rate of difficult calving. Indirect predictions with ref_33k were as accurate as with full ssGBLUP. Using the APY and recursions on ref_4k gave 88% gains of full ssGBLUP and using the APY and recursions on ref_8k gave 97% gains of full ssGBLUP. Genomic evaluation in beef cattle with ssGBLUP is feasible while keeping the models (maternal, multiple trait, and threshold) already used in regular BLUP. Gains in predictivity are dependent on the composition of the reference population. Indirect predictions via SNP effects derived from ssGBLUP allow for accurate genomic predictions on young animals, with no advantage of including PA in the index if the reference population is large. With the APY conditioning on about 10,000 reference animals, ssGBLUP is potentially applicable to a large number of genotyped animals without compromising predictive ability. © 2015 American Society of Animal Science. All rights reserved 650 $aGANADO DE CARNE 650 $aGENOMIC SELECTION 650 $aMEJORAMIENTO GENETICO ANIMAL 653 $aBEEF CATTLE 653 $aGENETIC RESURSION 653 $aINDIRECT PREDICTION 700 1 $aTSURUTA, S. 700 1 $aFRAGOMENI, B. O. 700 1 $aMASUDA, Y. 700 1 $aAGUILAR, I. 700 1 $aLEGARRA, A. 700 1 $aBERTRAND, J. K. 700 1 $aAMEN, T. S. 700 1 $aWANG. L. 700 1 $aMOSER, D. W. 700 1 $aMISZTAL, I. 773 $tJournal of Animal Science, 2015$gv. 93, p. 2653-2662. Published June 25, 2015. OPEN ACCESS.
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