Relationship between litters per sow per year sire breeding values and sire progeny means for farrowing rate, removal parity and lifetime born alive

Abell, Caitlyn; Mabry, John W.; Dekkers, Jack C. M.; Stalder, K. J.

doi:10.1111/j.1439-0388.2012.01012.x

Cited by 5 publications

(9 citation statements)

References 7 publications

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“…The overall mean and the means by farm obtained in this study for LBA are lower than the means reported by Abell et al (2013) in USA, in Japan, and Engblom et al (2007) in Sweden (53.8, 52.5, and 52.7 piglets, respectively). However, they are higher than values (34.9 and 38.5 piglets) reported in the USA by Hoge and Bates (2011) and Nikkilä et al (2013)).…”

Section: Discussioncontrasting

confidence: 83%

See 1 more Smart Citation

Lifetime and per year productivity of sows in four pig farms in the tropics of Mexico

Ek-Mex

Segura-Correa

Alzina-López

et al. 2014

Trop Anim Health Prod

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The objectives of this study were to estimate the lifetime and per year productivity of sows and to determine the effect of some factor on those traits in four pig farms in the tropics of Mexico. Data from 7526 sows for lifetime number of piglets born alive per sow (LBA), lifetime kilograms of piglets at farrowing (LKF), number of piglets born alive per year (NPF/Y), and kilograms of piglets at farrowing per year (KPF/Y); and data from 7230 sows for lifetime number of piglets weaned (LPW), lifetime kilograms of piglets weaned (LKW), number of piglets weaned per year (NPW/Y), and kilograms of piglets weaned per year (KPW/Y) per sow were used. The statistical model for all traits included the fixed effects of farm, year of first farrowing, season of first farrowing, litter size at first farrowing, age at first farrowing, removal reason, simple interactions, and the error term. The means for LBA, LKF, NPF/Y, and KPF/Y were 45.1 piglets, 67.1 kg, 22.7 piglets, and 33.7 kg, respectively. The means for LPW, LKW, NPW/Y, and KPW/Y were 43.2 piglets, 251.9 kg, 21.5 piglets, and 125.1 kg, respectively. All factors were significant for all traits, except for age at first farrowing on LPW and LKW. Sows with large litter sizes and those that farrowed the first time, at an early age, had the highest lifetime and per year productivity. Therefore, more care and better management should be provided to those types of sows to improve the farms profit.

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Section: Discussioncontrasting

confidence: 83%

“…1 and 2) by year may be due in part because it considers only sows that culled. Thus, the lower means observed in the last 2 years are due in part to the culling of low-parity young (1-3 farrowing) sows (Soltesz and Balogh 2013;Abell et al 2013).…”

Section: Discussionmentioning

confidence: 97%

Lifetime and per year productivity of sows in four pig farms in the tropics of Mexico

Ek-Mex

Segura-Correa

Alzina-López

et al. 2014

Trop Anim Health Prod

View full text Add to dashboard Cite

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“…Four general methods were used to calculate accuracy: using prediction error variance (PEV) from the inverse left‐hand side (iLHS) and calculating the traditional accuracy (Forni et al., ), approximated accuracies (Misztal & Wiggans, ; Misztal et al., ), correlating predictions to the GEBV from the full data set (similar to Aguilar et al., ) and correlating predictions to the corrected phenotypes (Abell et al., ; Christensen et al., ; Lourenco et al., ). There were three separate implementations using the corrected phenotypes (see below).…”

Section: Methodsmentioning

confidence: 99%

“…Much of the focus for GS has been placed on models and far less on the accompanying validation methods being used. Many articles use only one or maybe two methods and have ignored justification of the validation methods being used for accuracy comparisons between models (Abell, Mabry, Dekkers, & Stalder, ; Christensen, Madsen, Nielsen, Ostersen, & Su, ; Forni et al., ; Guo et al., ; Lourenco et al., ; Serão et al., ). In a review paper on GS by de los Campos, Hickey, Pong‐Wong, Daetwyler, and Calus (), accuracy validation methods were not thoroughly discussed, yet play a critical role to compare alternative breeding programmes.…”

Section: Introductionmentioning

confidence: 99%

A comparison of accuracy validation methods for genomic and pedigree‐based predictions of swine litter size traits using Large White and simulated data

Putz

Tiezzi

Maltecca

et al. 2017

J Animal Breeding Genetics

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SummaryThe objective of this study was to compare and determine the optimal validation method when comparing accuracy from single-step GBLUP (ssGBLUP) to traditional pedigree-based BLUP. Field data included six litter size traits. Simulated data included ten replicates designed to mimic the field data in order to determine the method that was closest to the true accuracy. Data were split into training and validation sets. The methods used were as follows: (i) theoretical accuracy derived from the prediction error variance (PEV) of the direct inverse (iLHS), (ii) approximated accuracies from the accf90(GS) program in the BLUPF90 family of programs (Approx), (iii) correlation between predictions and the single-step GEBVs from the full data set (GEBV Full ), (iv) correlation between predictions and the corrected phenotypes of females from the full data set (Y c ), (v) correlation from method iv divided by the square root of the heritability (Y ch ) and (vi) correlation between sire predictions and the average of their daughters' corrected phenotypes (Y cs ). Accuracies from iLHS increased from 0.27 to 0.37 (37%) in the Large White. Approximation accuracies were very consistent and close in absolute value (0.41 to 0.43). Both iLHS and Approx were much less variable than the corrected phenotype methods (ranging from 0.04 to 0.27). On average, simulated data showed an increase in accuracy from 0.34 to 0.44 (29%) using ssGBLUP. Both iLHS and Y ch approximated the increase well, 0.30 to 0.46 and 0.36 to 0.45, respectively. GEBV Full performed poorly in both data sets and is not recommended. Results suggest that for within-breed selection, theoretical accuracy using PEV was consistent and accurate. When direct inversion is infeasible to get the PEV, correlating predictions to the corrected phenotypes divided by the square root of heritability is adequate given a large enough validation data set. K E Y W O R D Saccuracy comparison, accuracy validation, litter size, piglet mortality, single-step GBLUP

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“…One of the major components of litter index is lactation length (Abell et al, 2013). In a simplistic approach, farms that opt out for a higher weaning age of the piglets are expected to have a lower litter index.…”

Section: Sow-related Performance Parametersmentioning

confidence: 99%

Factors associated with specific health, welfare and reproductive performance indicators in pig herds from five EU countries

Chantziaras

Dewulf

Limbergen

et al. 2018

Preventive Veterinary Medicine

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Production diseases are often of multi-factorial origin in which environment (housing, nutrition and management) health and reproductive challenges show complex interactions. The aim of this study was to identify specific environment-related factors and to discuss their associations with health, welfare and reproductive performance in sows and piglets, in diverse systems using data from 130 farms from five EU countries. Two sets of data were used: a) a questionnaire was developed for sows and piglets covering farm management, interventions and housing and b) farm production data covering various performance parameters. Eight parameters were further selected, four of which were related to sow reproductive performance (litter index, replacement rate, repeat breeding (i.e. failure to breed after one mating), weaning to first mating interval) and the remaining four to litter / piglet health performance (piglets born alive per litter, piglets born dead per litter, preweaning mortality rate and weaned piglets per litter). Univariable and multivariable linear models were employed to identify risk factors. Associations were considered significant if P ≤ 0.007 (a criterion of p≤0.05 corrected for the number of parameters tested). Various risk and protective factors were identified for each tested outcome variable. Country effects were included in all models as a fixed factor. Adjusted R-squared values for the multivariable models varied between 9.6% (preweaning mortality) and 66% (litter index). Litter index (litters/sow/year) was negatively associated with a higher weaning age of the piglets. Housing recently weaned sows to be inseminated in a separate unit from the gestation unit had a positive association with litter index. Repeat breeding was negatively associated with PRRS-free farms, farms that bred (raised) all gilts on the farm and farms that perform farrowing induction of sows. PRRS-free farms were also associated with a higher replacement rate. Farms that bred gilts on the farm and PRRS-free farms were negatively associated with preweaning mortality. Natural ventilation in the gestation unit was associated with fewer piglets born alive and with fewer weaned piglets. Closed type of farms was associated with less piglets born dead. The use of open box housing system for pregnant sows (provision of individual resting areas) was associated with more weaned piglets. In conclusion, several factors related to applying good farm and health management, and optimal housing conditions showed positive association with various sow and piglet performance parameters. Further studies will help to assess causal links for these factors.

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Relationship between litters per sow per year sire breeding values and sire progeny means for farrowing rate, removal parity and lifetime born alive

Cited by 5 publications

References 7 publications

Lifetime and per year productivity of sows in four pig farms in the tropics of Mexico

Lifetime and per year productivity of sows in four pig farms in the tropics of Mexico

A comparison of accuracy validation methods for genomic and pedigree‐based predictions of swine litter size traits using Large White and simulated data

Factors associated with specific health, welfare and reproductive performance indicators in pig herds from five EU countries

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