Responses to 19 generations of litter size selection in the NE Index line. II. Growth and carcass responses estimated in pure line and crossbred litters1

Petry, D. B.; Holl, J. W.; Johnson, R. K.

doi:10.2527/2004.8271895x

Cited by 9 publications

(4 citation statements)

References 12 publications

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“…The lack of response for most traits is in agreement with the results of selection experiments for increased litter size (Noguera et al, 2002b;Petry et al, 2004). Similarly, no significant response in litter size was obtained in several selection experiments for lean growth rate (Fredeen and Mikami, 1986;Cleveland et al, 1988;Kerr and Cameron, 1995).…”

Section: Discussionsupporting

confidence: 83%

Correlated responses of pre- and postweaning growth and backfat thickness to six generations of selection for ovulation rate or prenatal survival in French Large White pigs

Rosendo¹,

Canario²,

Druet³

et al. 2007

Journal of Animal Science

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Correlated effects of selection for components of litter size on growth and backfat thickness were estimated using data from 3 pig lines derived from the same base population of Large White. Two lines were selected for 6 generations on either high ovulation rate at puberty (OR) or high prenatal survival corrected for ovulation rate in the first 2 parities (PS). The third line was an unselected control (C). Genetic parameters for individual piglet BW at birth (IWB); at 3 wk of age (IW3W); and at weaning (IWW); ADG from birth to weaning (ADGBW), from weaning to 10 wk of age (ADGPW), and from 25 to 90 kg of BW (ADGT); and age (AGET) and average backfat thickness (ABT) at 90 kg of BW were estimated using REML methodology applied to a multivariate animal model. In addition to fixed effects, the model included the common environment of birth litter, as well as direct and maternal additive genetic effects as random effects. Genetic trends were estimated by computing differences between OR or PS and C lines at each generation using both least squares (LS) and mixed model (MM) methodology. Average genetic trends for direct and maternal effects were computed by regressing line differences on generation number. Estimates of direct and maternal heritabilities were, respectively, 0.10, 0.12, 0.20, 0.24, and 0.41, and 0.17, 0.33, 0.32, 0.41, and 0.21 (SE = 0.03 to 0.04) for IWB, IW3W, IWW, ADGBW, and ADGPW. Genetic correlations between direct and maternal effects were moderately negative for IWB (-0.21 +/- 0.18), but larger for the 4 other traits (-0.59 to -0.74). Maternal effects were nonsignificant and were removed from the final analyses of ADGT, AGET, and ABT. Direct heritability estimates were 0.34, 0.46, and 0.21 (SE = 0.03 to 0.05) for ADGT, AGET, and ABT, respectively. Direct and maternal genetic correlations of OR with performance traits were nonsignificant, with the exception of maternal correlations with IWB (-0.28 +/- 0.13) and ADGPW (0.23 +/- 0.11) and direct correlation with AGET (-0.23 +/- 0.09). Prenatal survival also had low direct but moderate to strong maternal genetic correlations (-0.34 to -0.65) with performance traits. The only significant genetic trends were a negative maternal trend for IBW in the OR line and favorable direct trends for postweaning growth (ADGT and AGET) in both lines. Selection for components of litter size has limited effects on growth and backfat thickness, although it slightly reduces birth weight and improves postweaning growth.

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Section: Discussionsupporting

confidence: 83%

Correlated responses of pre- and postweaning growth and backfat thickness to six generations of selection for ovulation rate or prenatal survival in French Large White pigs

Rosendo¹,

Canario²,

Druet³

et al. 2007

Journal of Animal Science

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“…Landrace pigs tended to have longer DAYS90 and thicker BF than Yorkshire or Duroc pigs, which might somehow support the evidence of maternal breed selection for bigger litter size as was found out of the experiments of Estany et al (2002). However, Petry et al (2004) could not find any strong evidence of correlated responses in growth performance or in carcass characteristics as responses to selection for litter size. Therefore, paternal or maternal breed differences weekly observed in our study populations cannot be understood as differences in the directions of selection by breeds.…”

Section: Resultssupporting

confidence: 50%

Genetic Parameter Estimation in Seedstock Swine Population for Growth Performances

jae-gwan

Cho

Choi³

et al. 2013

Asian Australas. J. Anim. Sci

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The objective of this study was to estimate genetic parameters that are to be used for across-herd genetic evaluations of seed stock pigs at GGP level. Performance data with pedigree information collected from swine breeder farms in Korea were provided by Korea Animal Improvement Association (AIAK). Performance data were composed of final body weights at test days and ultrasound measures of back fat thickness (BF), rib eye area (EMA) and retail cut percentage (RCP). Breeds of swine tested were Landrace, Yorkshire and Duroc. Days to 90 kg body weight (DAYS90) were estimated with linear function of age and ADG calculated from body weights at test days. Ultrasound measures were taken with A-mode ultrasound scanners by trained technicians. Number of performance records after censoring outliers and keeping records pigs only born from year 2000 were of 78,068 Duroc pigs, 101,821 Landrace pigs and 281,421 Yorkshire pigs. Models included contemporary groups defined by the same herd and the same seasons of births of the same year, which was regarded as fixed along with the effect of sex for all traits and body weight at test day as a linear covariate for ultrasound measures. REML estimation was processed with REMLF90 program. Heritability estimates were 0.40, 0.32, 0.21 0.39 for DAYS90, ADG, BF, EMA, RCP, respectively for Duroc population. Respective heritability estimates for Landrace population were 0.43, 0.41, 0.22, and 0.43 and for Yorkshire population were 0.36, 0.38, 0.22, and 0.42. Genetic correlation coefficients of DAYS90 with BF, EMA, or RCP were estimated to be 0.00 to 0.09, −0.15 to −0.25, 0.22 to 0.28, respectively for three breeds populations. Genetic correlation coefficients estimated between BF and EMA was −0.33 to −0.39. Genetic correlation coefficient estimated between BF and RCP was high and negative (−0.78 to −0.85) but the environmental correlation coefficients between these two traits was medium and negative (near −0.35), which describes a highly correlated genetic response to selection on one or the other of these traits. Genetic Trends of all three breeds tend to be towards bigger EMA or greater RCP and shorter DAYS90 especially from generations born after year 2000.

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“…En el número de lechones destetados influye la supervivencia durante la lactación y la prolificidad o el tamaño de la camada al nacimiento; éste último utilizado también como alternativa en la medida del rendimiento económico (Martínez-Giner et al, 2008). Por ello es habitual que los programas de mejora hagan hincapié en la selección por prolificidad en líneas maternas (Sørensen et al, 2000;Petry et al, 2004). En la bibliografía hay distintas opiniones en cuanto a si la prolificidad en diferentes partos debe ser considerada como medidas repetidas de la misma característica (Southwood y Kennedy, 1990;See et al, 1993;Crump et al, 1997;Lourenço et al, 2008) o como rasgos diferentes (Irgang et al, 1994;Roehe y Kennedy, 1995;Rydhmer et al, 1995;Barbosa et al, 2008).…”

Section: Introductionunclassified

Impacto de la prolificidad en la politica de reemplazamiento de cerdas reproductoras

Fernández¹,

Bono²,

Gaspa³

et al. 2015

ITEA

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Se estimó la curva de prolificidad media de cinco poblaciones tipo de cerdas obtenidas a partir de una muestra de 53 granjas comerciales (24 españolas, 19 danesas y 10 cubanas) para compararlas y analizar posteriormente su impacto sobre la política óptima de reemplazamiento de cerdas reproductoras. Los parámetros de la curva de prolificidad de las cinco poblaciones mostraron diferencias (P<0,05) que permitieron asociar el tamaño de la camada al primer parto y el máximo tamaño de camada alcanzado con una prolificidad más elevada. En cambio, la pendiente con la que la prolificidad desciende con la edad no mostró diferencias entre las poblaciones. Posteriormente, se analizó el impacto de la prolificidad sobre la política óptima de reemplazamiento. Con ese propósito, se simuló la dinámica productiva de cinco granjas de cerdas con idénticos parámetros excepto en su prolificidad, para la que se consideró cada una de las curvas estimadas previamente. En cada caso se calculó la política óptima de reemplazamiento y se analizó la estructura censal e índices técnicos y económicos asociados. Los índices técnicos y económicos mostraron diferencias entre las cinco granjas (P<0,05). Así, se encontró que mientras el ritmo productivo era similar en todas las poblaciones, la longevidad y estructura censal variaba. Se apreció un acortamiento de la longevidad con prolificidad elevada y viceversa, asociado a una concentración de cerdas superior en la franja más productiva de entre 2 y 7 partos, sin aumentar necesariamente la tasa de reposición. También se demostró que los ingresos netos de las granjas analizadas dependían fundamentalmente de los lechones destetados por cerda y año, así como que una baja prolificidad conducía a reemplazamientos tardíos en relación directa con la amortización de los reproductores.Palabras clave: Manejo reproductivo, remplazo óptimo, tamaño de camada, productividad.

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Responses to 19 generations of litter size selection in the NE Index line. II. Growth and carcass responses estimated in pure line and crossbred litters1

Cited by 9 publications

References 12 publications

Correlated responses of pre- and postweaning growth and backfat thickness to six generations of selection for ovulation rate or prenatal survival in French Large White pigs

Correlated responses of pre- and postweaning growth and backfat thickness to six generations of selection for ovulation rate or prenatal survival in French Large White pigs

Genetic Parameter Estimation in Seedstock Swine Population for Growth Performances

Impacto de la prolificidad en la politica de reemplazamiento de cerdas reproductoras

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