P. K. Mathur

A human nose scoring system for boar taint and its relationship with androstenone and skatole

A system for sensory evaluation of boar taint was used to evaluate boar taint in fat samples from 6574 entire males. The term human nose scoring has been used to describe this system. The samples from each boar were heated with a hot iron and three panelists assigned scores of 0 to 4. The reproducibility of HNS ranged from 0.19 to 0.32 reflecting natural variation in the ability of human beings to detect different odors. The correlations of HNS with androstenone ranged from 0.22 to 0.52, while those with skatole ranged from 0.31 to 0.89, suggesting that skatole is a better predictor of boar taint. Considering (1) the relationship of HNS with the boar taint compounds, (2) the ability of HNS to capture variation not accounted for by the boar taint compounds, (3) low estimation costs and (4) low time requirements, HNS can be used in large scale evaluations of boar taint.

Genetic parameters for androstenone, skatole, indole, and human nose scores as measures of boar taint and their relationship with finishing traits

The purpose of this study was to evaluate measures of boar (Sus scrofa) taint as potential selection criteria to reduce boar taint so that castration of piglets will become unnecessary. Therefore, genetic parameters of boar taint measures and their genetic correlations with finishing traits were estimated. In particular, the usefulness of a human panel assessing boar taint (human nose score) was compared with chemical assessment of boar taint compounds, androstenone, skatole, and indole. Heritability estimates for androstenone, skatole, and indole were 0.54, 0.41, and 0.33, respectively. The heritability for the human nose score using multiple panelists was 0.12, and ranged from 0.12 to 0.19 for individual panelists. Genetic correlations between scores of panelists were generally high up to unity. The genetic correlations between human nose scores and the boar taint compounds ranged from 0.64 to 0.999. The boar taint compounds and human nose scores had low or favorable genetic correlations with finishing traits. Selection index estimates indicated that the effectiveness of a breeding program based on human nose scores can be comparable to a breeding program based on the boar taint compounds themselves. Human nose scores can thus be used as a cheap and fast alternative for the costly determination of boar taint compounds, needed in breeding pigs without boar taint.

Sire evaluation for total number born in pigs using a genomic reaction norms approach

In the era of genome-wide selection (GWS), genotype-by-environment (G×E) interactions can be studied using genomic information, thus enabling the estimation of SNP marker effects and the prediction of genomic estimated breeding values (GEBV) for young candidates for selection in different environments. Although G×E studies in pigs are scarce, the use of artificial insemination has enabled the distribution of genetic material from sires across multiple environments. Given the relevance of reproductive traits, such as the total number born (TNB) and the variation in environmental conditions encountered by commercial dams, understanding G×E interactions can be essential for choosing the best sires for different environments. The present work proposes a two-step reaction norm approach for G×E analysis using genomic information. The first step provided estimates of environmental effects (herd-year-season, HYS), and the second step provided estimates of the intercept and slope for the TNB across different HYS levels, obtained from the first step, using a random regression model. In both steps, pedigree ( A: ) and genomic ( G: ) relationship matrices were considered. The genetic parameters (variance components, h(2) and genetic correlations) were very similar when estimated using the A: and G: relationship matrices. The reaction norm graphs showed considerable differences in environmental sensitivity between sires, indicating a reranking of sires in terms of genetic merit across the HYS levels. Based on the G: matrix analysis, SNP by environment interactions were observed. For some SNP, the effects increased at increasing HYS levels, while for others, the effects decreased at increasing HYS levels or showed no changes between HYS levels. Cross-validation analysis demonstrated better performance of the genomic approach with respect to traditional pedigrees for both the G×E and standard models. The genomic reaction norm model resulted in an accuracy of GEBV for juvenile boars varying from 0.14 to 0.44 across different HYS levels, while the accuracy of the standard genomic prediction model, without reaction norms, varied from 0.09 to 0.28. These results show that it is important and feasible to consider G×E interactions in evaluations of sires using genomic prediction models and that genomic information can increase the accuracy of selection across environments.

Estimation of genetic parameters and breeding values across challenged environments to select for robust pigs

Robustness is an important issue in the pig production industry. Since pigs from international breeding organizations have to withstand a variety of environmental challenges, selection of pigs with the inherent ability to sustain their productivity in diverse environments may be an economically feasible approach in the livestock industry. The objective of this study was to estimate genetic parameters and breeding values across different levels of environmental challenge load. The challenge load (CL) was estimated as the reduction in reproductive performance during different weeks of a year using 925,711 farrowing records from farms distributed worldwide. A wide range of levels of challenge, from favorable to unfavorable environments, was observed among farms with high CL values being associated with confirmed situations of unfavorable environment. Genetic parameters and breeding values were estimated in high- and low-challenge environments using a bivariate analysis, as well as across increasing levels of challenge with a random regression model using Legendre polynomials. Although heritability estimates of number of pigs born alive were slightly higher in environments with extreme CL than in those with intermediate levels of CL, the heritabilities of number of piglet losses increased progressively as CL increased. Genetic correlations among environments with different levels of CL suggest that selection in environments with extremes of low or high CL would result in low response to selection. Therefore, selection programs of breeding organizations that are commonly conducted under favorable environments could have low response to selection in commercial farms that have unfavorable environmental conditions. Sows that had experienced high levels of challenge at least once during their productive life were ranked according to their EBV. The selection of pigs using EBV ignoring environmental challenges or on the basis of records from only favorable environments resulted in a sharp decline in productivity as the level of challenge increased. In contrast, selection using the random regression approach resulted in limited change in productivity with increasing levels of challenge. Hence, we demonstrate that the use of a quantitative measure of environmental CL and a random regression approach can be comprehensively combined for genetic selection of pigs with enhanced ability to maintain high productivity in harsh environments.

Estimating challenge load due to disease outbreaks and other challenges using reproduction records of sows

A method was developed and tested to estimate challenge load due to disease outbreaks and other challenges in sows using reproduction records. The method was based on reproduction records from a farm with known disease outbreaks. It was assumed that the reduction in weekly reproductive output within a farm is proportional to the magnitude of the challenge. As the challenge increases beyond certain threshold, it is manifested as an outbreak. The reproduction records were divided into 3 datasets. The first dataset called the Training dataset consisted of 57,135 reproduction records from 10,901 sows from 1 farm in Canada with several outbreaks of porcine reproductive and respiratory syndrome (PRRS). The known disease status of sows was regressed on the traits number born alive, number of losses as a combination of still birth and mummified piglets, and number of weaned piglets. The regression coefficients from this analysis were then used as weighting factors for derivation of an index measure called challenge load indicator. These weighting factors were derived with i) a two-step approach using residuals or year-week solutions estimated from a previous step, and ii) a single-step approach using the trait values directly. Two types of models were used for each approach: a logistic regression model and a general additive model. The estimates of challenge load indicator were then compared based on their ability to detect PRRS outbreaks in a Test dataset consisting of records from 65,826 sows from 15 farms in the Netherlands. These farms differed from the Canadian farm with respect to PRRS virus strains, severity and frequency of outbreaks. The single-step approach using a general additive model was best and detected 14 out of the 15 outbreaks. This approach was then further validated using the third dataset consisting of reproduction records of 831,855 sows in 431 farms located in different countries in Europe and America. A total of 41 out of 48 outbreaks detected using data analysis were confirmed based on diagnostic information received from the farms. Among these, 30 outbreaks were due to PRRS while 11 were due to other diseases and challenging conditions. The results suggest that proposed method could be useful for estimation of challenge load and detection of challenge phases such as disease outbreaks.

Genetic relationship between boar taint compounds, human nose scores, and reproduction traits in pigs.

A reduction in boar taint, an unpleasant odor arising in pork from some intact males, is desirable if routine castration of piglets needs to be stopped. Commercial slaughter pigs are typically crosses between sire lines mainly selected for finishing traits and dam lines mainly selected for reproduction traits. Previous studies suggest the possibility of reducing boar taint in sire lines due to favorable genetic correlations between boar taint and finishing traits. However, there are indications of unfavorable genetic associations between boar taint and female reproduction traits, but a lack of genetic correlation estimates remain a major roadblock in reducing boar taint in dam lines. This study was conducted to estimate genetic correlations between boar taint traits and female reproduction traits, investigate differences in these genetic relationships among sire and dam lines, and evaluate possible consequences of selection against boar taint in dam lines. The data consisted of 32,549 reproduction records from a Landrace dam line, 23,874 records from a Yorkshire dam line, and 3,745 records from a Pietrain sire line. Androstenone, skatole, and indole were measured on 1,896 carcasses, and human nose scores were recorded on 7,742 carcass samples. In general, the level of boar taint was significantly greater (P < 0.05) in the two dam lines than in the sire line. A majority of genetic correlations of boar taint compounds with reproduction traits were either low or nonsignificant, except for those of skatole and indole, with age at first insemination in dam lines that were -0.32 and -0.46, respectively. Genetic correlations also differed (P < 0.05) between sire and dam lines. The consequences of selection against boar taint in dam lines were evaluated, using selection indexes based on reproduction traits only, boar taint traits only, and both boar taint and reproduction traits. Selection on an index of only reproduction traits increased the number of carcasses with boar taint from 4 to 7.3% in 5 generations. Selection on a combined index reduced carcasses with boar taint from 4 to <0.1% in 19 generations at the cost of a 10% less economic gain in reproduction traits. In markets for intact males, overall economic gain is 78% greater than with selection for reproduction only. Breeding programs for boar taint in commercial production should include boar taint in breeding goals of dam lines as the levels of boar taint and the risk of a further increase are greater.

Genetic Selection to Enhance Animal Welfare Using Meat Inspection Data from Slaughter Plants

Simple Summary Analysis of a large volume of meat inspection data suggests availability of genetic variation for most common indicators of poor animal welfare. This genetic variation can be used to select pigs that have the potential to resist common infections and other unfavorable welfare conditions. Genetic selection can be a tool in addition to farm management in reducing the risk of diseases, thereby reducing pain and suffering of animals. In general, the slaughter remarks have small but favorable genetic relationships with finishing and carcass quality traits. Therefore, it is possible to enhance animal welfare along with the genetic selection for economically important production traits. Abstract Animal health and welfare are monitored during meat inspection in many slaughter plants around the world. Carcasses are examined by meat inspectors and remarks are made with respect to different diseases, injuries, and other abnormalities. This is a valuable data resource for disease prevention and enhancing animal welfare, but it is rarely used for this purpose. Records on carcass remarks on 140,375 finisher pigs were analyzed to investigate the possibility of genetic selection to reduce the risk of the most prevalent diseases and indicators of suboptimal animal welfare. As part of this, effects of some non-genetic factors such as differences between farms, sexes, and growth rates were also examined. The most frequent remarks were pneumonia (15.4%), joint disorders (9.8%), pleuritis (4.7%), pericarditis (2.3%), and liver lesions (2.2%). Joint disorders were more frequent in boars than in gilts. There were also significant differences between farms. Pedigree records were available for 142,324 pigs from 14 farms and were used for genetic analysis. Heritability estimates for pneumonia, pleuritis, pericarditis, liver lesions, and joint disorders were 0.10, 0.09, 0.14, 0.24, and 0.17 on the liability scale, respectively, suggesting the existence of substantial genetic variation. This was further confirmed though genome wide associations using deregressed breeding values as phenotypes. The genetic correlations between these remarks and finishing traits were small but mostly negative, suggesting the possibility of enhancing pig health and welfare simultaneously with genetic improvement in finishing traits. A selection index based on the breeding values for these traits and their economic values was developed. This index is used to enhance animal welfare in pig farms.

Gene networks for total number born in pigs across divergent environments

For reproductive traits such as total number born (TNB), variance due to different environments is highly relevant in animal breeding. In this study, we aimed to perform a gene-network analysis for TNB in pigs across different environments using genomic reaction norm models. Thus, based on relevant single-nucleotide polymorphisms and linkage disequilibrium blocks across environments obtained from GWAS, different sets of candidate genes having biological roles linked to TNB were identified. Network analysis across environment levels resulted in gene interactions consistent with known mammal’s fertility biology, captured relevant transcription factors for TNB biology and pointing out different sets of candidate genes for TNB in different environments. These findings may have important implication for animal production, as optimal breeding may vary depending on later environments. Based on these results, genomic diversity was identified and inferred across environments highlighting differential genetic control in each scenario.

Pigs Can Be Selected forIncreased Natural Resistance to PRRS Without Affecting Overall Economic Value in the Absence ofPRRS

Recommended Citation Dunkelberger, Jenelle; Mathur, Pramod K.; Lopes, Marcos S.; Knol, Egbert F.; and Dekkers, Jack C. M. (2017) Pigs Can Be Selected forIncreased Natural Resistance to PRRS Without Affecting Overall Economic Value in the Absence ofPRRS, Animal Industry Report: AS 663, ASL R3192. DOI: https://doi.org/10.31274/ans_air-180814-378 Available at: https://lib.dr.iastate.edu/ans_air/vol663/iss1/65