Genetic and environmental factors affecting reproductive traits in sows in an outdoor production system

Bell, Washington; Urioste, J. I.; Barlocco, N.; Vadell, A.; Clariget, Raquel Pérez

doi:10.1016/j.livsci.2015.10.025

Cited by 8 publications

(5 citation statements)

References 30 publications

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“…Sesti and Sobestiansky (1998) suggested as a productivity parameter for modern, high-technology pig production systems, a maximum pre-weaning mortality rate of 6%, which is close to the present values. Bell et al (2015) reported a mortality rate of 12% between birth and weaning in an extensive production system in Uruguay.…”

Section: Discussionmentioning

confidence: 99%

“…With respect to reproductive rates, according to several researchers (Dobao et al, 1983;Fuentes et al, 2000;Peltoniemi et al, 2000;Lipenský et al, 2010;Bell et al, 2015;Peltoniemi and Oliviero, 2015), many factors influence the performance of a female pig, e.g., genotype effects, sow and boar age, number of farrowings, feeding level, season of the year when mating occurs, among others.…”

Section: Introductionmentioning

confidence: 99%

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Impact of reproductive and productive rates on levels of inbreeding and genetic gain of pigs through data simulation

Lopes

Rorato²,

Breda³

et al. 2019

R. Bras. Zootec.

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The objective of this study was to evaluate the impact of farrowing and mortality rates on inbreeding levels and genetic gain through data simulation. Data came from two real populations A and B, composed of Pietrain and Landrace breed pigs, respectively. To generate the simulated populations, a Fortran-language simulator was developed using the (co)variances of the breeding values and productive and reproductive information obtained from populations A and B, as well as restrictions on mating and animals selected per generation. Two data files were created. The first contained the pedigree of the previous 10 years, with 21,906 and 251,343 animals in populations A and B, respectively. The second included the breeding values for age, backfat thickness, and feed conversion, all of which were adjusted for 110 kg live weight, for both populations; longissimus dorsi muscle depth adjusted for 110 kg live weight, for population A only; and number of live piglets at the fifth day of life per farrowing, for population B only. Three scenarios were simulated by varying the farrowing and mortality rates during the lactation period. Ten generations were simulated, with 30 replicates for each generation and scenario. Inbreeding levels in closed production units increase with productive and reproductive losses, and these reduce the variances of breeding values, selection intensity, and genetic gains by reducing the number of animals available for selection. Actions that maximize farrowing rates are more important than those that minimize mortality rates during the lactation period, since a reduction in simulated farrowing resulted in greater losses of genetic gains.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Impact of reproductive and productive rates on levels of inbreeding and genetic gain of pigs through data simulation

Lopes

Rorato²,

Breda³

et al. 2019

R. Bras. Zootec.

View full text Add to dashboard Cite

show abstract

“…The papers that both assessors assessed affirmatively for all questions were included in the analysis, yielding 28 papers. These articles were Nielsen et al (2001), Houška et al (2004, Wellock et al (2008), Li et al (2008), Kutzer et al (2009), Zonderland et al (2010), Fels et al (2012, Madsen & Bee (2014), Bell et al (2015), Baldinger et al (2016), Van Wettere et al (2016, Almeida et al (2017), Vanrolleghem et al (2019, Montsho et al (2016), Kalita et al (2015), Jin et al (2019), Tsourgianis et al (2004, Devillers and Farmer (2009), Bohnenkamp et al (2013) Using Excel® software, the data regarding the impact of weaning age on piglet performance were organized for statistical analysis. The variables were tested for normality of the residuals using Shapiro-Wilk test and homogeneity of variance using Levene's test.…”

Section: Methodsmentioning

confidence: 99%

Meta-analysis of relationship between weaning age and daily weight gain of piglets in the farrowing and nursery phases

Valentim¹,

Mendes²,

Caldara³

et al. 2021

SA J. An. Sci.

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A systematic review of the literature was carried out to perform a meta-analysis to assess effects of age at weaning on the performance of piglets in the range of 14 to 42 days old. This step consisted in defining the databases and keywords to be employed in searching for papers for the meta-analysis. To that end, the databases Capes Publication Portal and Google Scholar were searched for researches published from 2001 to 2019. After the acceptance and exclusion criteria had been defined and applied, 28 papers were selected. The data were collected with Excel® software of Microsoft Office for later statistical analysis. Orthogonal polynomial contrasts were used and the linear and quadratic regression equations were fitted with hypotheses tested at the 5% significance level. The results confirmed the disadvantages of early weaning and the benefits of weaning at around 28 days old. In the farrowing phase, piglets weaned after 35 days had lower daily weight gain (DWG) (P =0.002) than those weaned at 27 days. The derivative of the regression of DWG while nursing on age revealed that a weaning age of 26.34 days yielded the maximum DWG among the ages assessed. After weaning, the maximum DWG was achieved by weaning piglets at 32.26 days. Given the performance of piglets in the farrowing and nursery phases, the results of this meta-analysis indicated the best weaning age was between 26 and 32 days.

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“…Piglets weaned per sow per year (PSY) is an important factor to measure the efficiency of pig farms and the reproductive performance of sows. It is closely related to number of weaned piglets per litter, farrowing rate, non-productive days (NPD) and other production factors [ 1 ]. By increasing PSY, the purchase cost of gilts and the feeding cost of sows can be shared equally among more weaned piglets, to improve the profits of commercial pig farms [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

Study on the influence of different production factors on PSY and its correlation

Guan

Zhou²,

Cai³

et al. 2022

Porc Health Manag

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Background Finding out the key reproductive performance factors, affecting piglets weaned per sow per year (PSY) can improve the production efficiency and profitability of pig farms. The objective was to understand the actual distribution of different production factors and PSY of breeding pig farms, analyze the correlation to find the main production factors affecting PSY, and formulating a Production Efficiency Improvement Plan in practice. Data included 603 breeding pig farms from September 28, 2020 to September 26, 2021. Regression analysis was used to evaluate the relationship between PSY and key production factors, and the characteristics of total pig farms versus high performance (HP) pig farms (the production performance was in the top 10%) or top 5% pig farms were compared. Spearman’s rank correlation coefficient was used to analyze the correlation between production factors and find the factors related to PSY. Non-linear support vector regression (NL-SVR) was used to analyze the personalized PSY improvement through a various change of the four key factors. Results The median distribution of 15 production factors and PSY in total pig farms were different from those of HP farms. All of data were distributed nonlinearly. Mating rate within 7 days after weaning (MR7DW), farrowing rate (FR), number of piglets born alive per litter (PBAL) and number of weaned piglets per litter (WPL) were moderately correlated with PSY, and the correlation coefficients were 0.5058, 0.4427, 0.3929 and 0.3839, respectively. When the four factors in NL-SVR changed in medium (0.5 piglet or 5%) or high level (1.0 piglet or 10%), PSY can be increased by more than 0.5. Conclusion NL-SVR model can be used to analyze the impact of changes in key production factors on PSY. By taking measures to improve MR7DW, FR, PBAL and WPL, it may effectively improve the current PSY and fully develop the reproductive potential of sows.

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Genetic and environmental factors affecting reproductive traits in sows in an outdoor production system

Cited by 8 publications

References 30 publications

Impact of reproductive and productive rates on levels of inbreeding and genetic gain of pigs through data simulation

Impact of reproductive and productive rates on levels of inbreeding and genetic gain of pigs through data simulation

Meta-analysis of relationship between weaning age and daily weight gain of piglets in the farrowing and nursery phases

Study on the influence of different production factors on PSY and its correlation

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