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Biblioteca (s) : |
INIA Treinta y Tres. |
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Fecha : |
24/11/2015 |
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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 : |
COTTLE, D.J.; VELAZCO, J.I.; HEGARTY, R.S.; MAYER, D.G. |
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Afiliación : |
JOSÉ IGNACIO VELAZCO DE LOS REYES, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Estimating daily methane production in individual cattle with irregular feed intake patterns from short-term methane emission measurements. |
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Fecha de publicación : |
2015 |
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Fuente / Imprenta : |
Animal, 2015, v. 9 (12), p. 1949-1957. |
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DOI : |
10.1017/S1751731115001676 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 19 March 2015; Accepted 17 July 2015; First published online 24 August 2015. |
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Contenido : |
Spot measurements of methane emission rate (n = 18 700) by 24 Angus steers fed mixed rations from GrowSafe feeders were made over 3- to 6-min periods by a reenFeed emission monitoring (GEM) unit. The data were analysed to estimate daily methane production (DMP; g/day) and derived methane yield (MY; g/kg dry matter intake (DMI)). A one-compartment dose model of spot emission rate v. time since the preceding meal was compared with the models of Wood (1967) and Dijkstra et al. (1997) and the average of spot measures. Fitted values for DMP were calculated from the area under the curves. Two methods of relating methane and feed intakes were then studied: the classical calculation of MY as DMP/DMI (kg/day); and a novel method of estimating DMP from time and size of preceding meals using either the data for only the two meals preceding a spot measurement, or all meals for 3 days prior. Two approaches were also used to estimate DMP from spot measurements: fitting of
splines on a ?per-animal per-day? basis and an alternate approach of modelling DMP after each feed event by least squares (using Solver), summing (for each animal) the contributions from each feed event by best-fitting a one-compartment model. Time since the preceding meal was of limited value in estimating DMP. Even when the meal sizes and time intervals between a spot measurement and all feeding events in the previous 72 h were assessed, only 16.9% of the variance in spot emission rate
measured by GEM was explained by this feeding information. While using the preceding meal alone gave a biased (underestimate) of DMP, allowing for a longer feed history removed this bias. A power analysis taking into account the sources of variation in DMP indicated that to obtain an estimate of DMP with a 95% confidence interval within 5% of the observed 64 days mean of spot measures would require 40 animals measured over 45 days (two spot measurements per day) or 30 animals measured over 55 days. These numbers suggest that spot measurements could be made in association with feed efficiency tests made over 70 days. Spot measurements of enteric emissions can be used to define DMP but the number of animals and samples are larger than are needed when day-long measures are made. MenosSpot measurements of methane emission rate (n = 18 700) by 24 Angus steers fed mixed rations from GrowSafe feeders were made over 3- to 6-min periods by a reenFeed emission monitoring (GEM) unit. The data were analysed to estimate daily methane production (DMP; g/day) and derived methane yield (MY; g/kg dry matter intake (DMI)). A one-compartment dose model of spot emission rate v. time since the preceding meal was compared with the models of Wood (1967) and Dijkstra et al. (1997) and the average of spot measures. Fitted values for DMP were calculated from the area under the curves. Two methods of relating methane and feed intakes were then studied: the classical calculation of MY as DMP/DMI (kg/day); and a novel method of estimating DMP from time and size of preceding meals using either the data for only the two meals preceding a spot measurement, or all meals for 3 days prior. Two approaches were also used to estimate DMP from spot measurements: fitting of
splines on a ?per-animal per-day? basis and an alternate approach of modelling DMP after each feed event by least squares (using Solver), summing (for each animal) the contributions from each feed event by best-fitting a one-compartment model. Time since the preceding meal was of limited value in estimating DMP. Even when the meal sizes and time intervals between a spot measurement and all feeding events in the previous 72 h were assessed, only 16.9% of the variance in spot emission rate
measured by GEM was explained by ... Presentar Todo |
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Palabras claves : |
GASES DE EFECTO INVERNADERO; GREENFEED; MODELS; SPLINES. |
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Thesagro : |
METANO; MODELOS ANIMALES; VACUNOS. |
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Asunto categoría : |
-- |
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Marc : |
LEADER 03126naa a2200265 a 4500
001 1053984
005 2021-06-24
008 2015 bl uuuu u00u1 u #d
024 7 $a10.1017/S1751731115001676$2DOI
100 1 $aCOTTLE, D.J.
245 $aEstimating daily methane production in individual cattle with irregular feed intake patterns from short-term methane emission measurements.$h[electronic resource]
260 $c2015
500 $aArticle history: Received 19 March 2015; Accepted 17 July 2015; First published online 24 August 2015.
520 $aSpot measurements of methane emission rate (n = 18 700) by 24 Angus steers fed mixed rations from GrowSafe feeders were made over 3- to 6-min periods by a reenFeed emission monitoring (GEM) unit. The data were analysed to estimate daily methane production (DMP; g/day) and derived methane yield (MY; g/kg dry matter intake (DMI)). A one-compartment dose model of spot emission rate v. time since the preceding meal was compared with the models of Wood (1967) and Dijkstra et al. (1997) and the average of spot measures. Fitted values for DMP were calculated from the area under the curves. Two methods of relating methane and feed intakes were then studied: the classical calculation of MY as DMP/DMI (kg/day); and a novel method of estimating DMP from time and size of preceding meals using either the data for only the two meals preceding a spot measurement, or all meals for 3 days prior. Two approaches were also used to estimate DMP from spot measurements: fitting of splines on a ?per-animal per-day? basis and an alternate approach of modelling DMP after each feed event by least squares (using Solver), summing (for each animal) the contributions from each feed event by best-fitting a one-compartment model. Time since the preceding meal was of limited value in estimating DMP. Even when the meal sizes and time intervals between a spot measurement and all feeding events in the previous 72 h were assessed, only 16.9% of the variance in spot emission rate measured by GEM was explained by this feeding information. While using the preceding meal alone gave a biased (underestimate) of DMP, allowing for a longer feed history removed this bias. A power analysis taking into account the sources of variation in DMP indicated that to obtain an estimate of DMP with a 95% confidence interval within 5% of the observed 64 days mean of spot measures would require 40 animals measured over 45 days (two spot measurements per day) or 30 animals measured over 55 days. These numbers suggest that spot measurements could be made in association with feed efficiency tests made over 70 days. Spot measurements of enteric emissions can be used to define DMP but the number of animals and samples are larger than are needed when day-long measures are made.
650 $aMETANO
650 $aMODELOS ANIMALES
650 $aVACUNOS
653 $aGASES DE EFECTO INVERNADERO
653 $aGREENFEED
653 $aMODELS
653 $aSPLINES
700 1 $aVELAZCO, J.I.
700 1 $aHEGARTY, R.S.
700 1 $aMAYER, D.G.
773 $tAnimal, 2015$gv. 9 (12), p. 1949-1957.
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Registro original : |
INIA Treinta y Tres (TT) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
20/06/2015 |
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Actualizado : |
20/06/2015 |
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Tipo de producción científica : |
Informes Agroclimáticos |
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Autor : |
GIMENEZ, A.; CASTAÑO, J.; FUREST, J.; CAL, A.; TISCORNIA, G. |
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Afiliación : |
AGUSTIN EDUARDO GIMENEZ FUREST, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JOSE PEDRO CASTAÑO SANCHEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JOSE MARIA FUREST CROCCO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ADRIAN TABARE CAL ALVAREZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; GUADALUPE TISCORNIA TOSAR, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Informe Agroclimático 2012 - Situación a Enero. |
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Fecha de publicación : |
2012 |
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Fuente / Imprenta : |
Montevideo (Uruguay): INIA, 2012., |
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Páginas : |
4 p. |
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Idioma : |
Español |
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Palabras claves : |
AGROCLIMA; AGROCLIMATOLOGÍA; BOLETIN AGROCLIMÁTICO; CARACTERIZACIÓN AGROCLIMÁTICA; DIRECCION VIENTO; ESTACIONES AGROMETEOROLOGICAS; ESTACIONES AUTOMATICAS; ESTACIONES INIA; ESTADO DEL TIEMPO; ESTRÉS HÍDRICO; GRAFICAS AGROCLIMATICOS; GRAS; HELIOFANOGRAFO; INFORMACION SATELITAL; INUNDACIONES; LLUVIAS DIARIAS; MAXIMA; MEDIA; MINIMA; PANEL SOLAR; PERSPECTIVAS CLIMATICAS; PLUVIOMETRO; PRECIPITACION NACIONAL; PREVENCION HELADAS; PRONOSTICO; SENSOR; SIMETRICO; TANQUE A; TERMOCUPLAS; TERMOHIDROGRAFO; VARIABLES AGROCLIMATICAS; VELETA. |
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Thesagro : |
AGROCLIMATOLOGIA; CAMBIO CLIMATICO; CLIMA; CLIMATOLOGIA; ESTACIONES METEOROLOGICAS; ESTRES HIDRICO; EVAPORACION; EVAPOTRANSPIRACION; HUMEDAD; HUMEDAD RELATIVA; LLUVIA; METEOROLOGIA; PERSPECTIVAS; PLUVIOMETROS; PRONOSTICO DEL TIEMPO; SENSORES; SISTEMAS; SISTEMAS DE INFORMACION; SUELO; TEMPERATURA; TERMOMETROS. |
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Asunto categoría : |
P40 Meteorología y climatología |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/4707/1/Inf.Agr.-enero-2012.pdf
http://www.inia.uy/Publicaciones/Paginas/publicacion-2456.aspx
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Marc : |
LEADER 02071nam a2200793 a 4500
001 1052863
005 2015-06-20
008 2012 bl uuuu u0uu1 u #d
100 1 $aGIMENEZ, A.
245 $aInforme Agroclimático 2012 - Situación a Enero.$h[electronic resource]
260 $aMontevideo (Uruguay): INIA, 2012.,$c2012
300 $a4 p.
650 $aAGROCLIMATOLOGIA
650 $aCAMBIO CLIMATICO
650 $aCLIMA
650 $aCLIMATOLOGIA
650 $aESTACIONES METEOROLOGICAS
650 $aESTRES HIDRICO
650 $aEVAPORACION
650 $aEVAPOTRANSPIRACION
650 $aHUMEDAD
650 $aHUMEDAD RELATIVA
650 $aLLUVIA
650 $aMETEOROLOGIA
650 $aPERSPECTIVAS
650 $aPLUVIOMETROS
650 $aPRONOSTICO DEL TIEMPO
650 $aSENSORES
650 $aSISTEMAS
650 $aSISTEMAS DE INFORMACION
650 $aSUELO
650 $aTEMPERATURA
650 $aTERMOMETROS
653 $aAGROCLIMA
653 $aAGROCLIMATOLOGÍA
653 $aBOLETIN AGROCLIMÁTICO
653 $aCARACTERIZACIÓN AGROCLIMÁTICA
653 $aDIRECCION VIENTO
653 $aESTACIONES AGROMETEOROLOGICAS
653 $aESTACIONES AUTOMATICAS
653 $aESTACIONES INIA
653 $aESTADO DEL TIEMPO
653 $aESTRÉS HÍDRICO
653 $aGRAFICAS AGROCLIMATICOS
653 $aGRAS
653 $aHELIOFANOGRAFO
653 $aINFORMACION SATELITAL
653 $aINUNDACIONES
653 $aLLUVIAS DIARIAS
653 $aMAXIMA
653 $aMEDIA
653 $aMINIMA
653 $aPANEL SOLAR
653 $aPERSPECTIVAS CLIMATICAS
653 $aPLUVIOMETRO
653 $aPRECIPITACION NACIONAL
653 $aPREVENCION HELADAS
653 $aPRONOSTICO
653 $aSENSOR
653 $aSIMETRICO
653 $aTANQUE A
653 $aTERMOCUPLAS
653 $aTERMOHIDROGRAFO
653 $aVARIABLES AGROCLIMATICAS
653 $aVELETA
700 1 $aCASTAÑO, J.
700 1 $aFUREST, J.
700 1 $aCAL, A.
700 1 $aTISCORNIA, G.
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