Background Boars undergo physiological and biochemical changes in semen composition as they grow from puberty to sexual maturity.However,comprehensive metabolomic profiles of boar semen remain uncharacterised.Understa...Background Boars undergo physiological and biochemical changes in semen composition as they grow from puberty to sexual maturity.However,comprehensive metabolomic profiles of boar semen remain uncharacterised.Understanding metabolic alterations in semen during this period is important for optimising reproductive performance in breeding programs.The aim of this study was to characterise the semen metabolome as boars mature,utilising an untargeted metabolomic approach.Semen samples were collected from 15 Duroc boars at three developmental ages:~7 months,8.5 months,and 10 months.Sperm and seminal plasma were separated and analysed by hydrophilic interaction and reversed-phase liquid chromatography coupled with mass spectrometry to capture a wide range of metabolites.Results We identified a total of 4,491 features in boar semen,annotating 92 distinct metabolites.Amino acids,peptides and analogues constituted the most abundant components,followed by fatty acid esters.Principal component analysis(PCA)and partial least squares discriminant analysis(PLS-DA)showed a clear separation between metabolomic profiles by age groups.PERMANOVA analysis of PCA scores confirmed statistically significant differences(P<0.05)between younger(7 months)and more mature boars(8.5 months and 10 months).Pathway analysis identified porphyrin metabolism,taurine and hypotaurine metabolism,and glycerolipid metabolism as significantly enriched pathways in sperm,while glutathione and nitrogen metabolism were prominently enriched in seminal plasma.Using linear modelling,partial Spearman correlation and random forest analyses,we identified homoisovanillic acid as a key metabolite discriminating age groups in both sperm and seminal plasma.Additionally,L-glutamic acid,decanoyl-L-carnitine and N-(1,3-Thiazol-2-yl)benzenesulfonamide emerged as important sperm metabolites,while glyceric acid,myo-inositol,glycerophosphocholine,and several other compounds were identified as critical seminal plasma metabolites.Conclusion This study provides a detailed characterisation of metabolic changes in Duroc boar semen during the transition from puberty to sexual maturity.Our findings enhance the understanding of reproductive development and could inform strategies to assess sexual maturity in breeding programs.展开更多
Avoiding lameness or leg weakness in pig production is crucial to reduce cost, improve animal welfare and meat quality. Detection of lameness detection by the use of vision systems may assist the farmer or breeder to ...Avoiding lameness or leg weakness in pig production is crucial to reduce cost, improve animal welfare and meat quality. Detection of lameness detection by the use of vision systems may assist the farmer or breeder to obtain a more accurate and robust measurement of lameness. The paper presents a low-cost vision system for measuring the locomotion of moving pigs based on motion detection, frame-grabbing and multivariate image analysis. The first step is to set up a video system based on web camera technology and choose a test area. Secondly, a motion detection and data storage system are used to build a processing system of video data. The video data are analyzed measuring the properties of each image, stacking them for each animal and then analyze these stacks using multivariate image analysis. The system was able to obtain and decompose information from these stacks, where components could be extracted, representing a particular motion pattern. These components could be used to classify or score animals according to this pattern, which might be an indicator of lameness. However, further improvement is needed with respect to standardization of herding, test area and tracking of animals in order to have a robust system to be used in a farm environment.展开更多
One hundred and four pure-bred Norwegian Duroc boars were CT (computed tomography) scanned to predict the in vivo intramuscular fat percentage in the loin. The animals were slaughtered and the loin was cut commerciall...One hundred and four pure-bred Norwegian Duroc boars were CT (computed tomography) scanned to predict the in vivo intramuscular fat percentage in the loin. The animals were slaughtered and the loin was cut commercially. A muscle sample of the m. Longissimus dorsi was sampled and analyzed by the use of near-infrared spectroscopy. Data from CT images were collected using an in-house MATLAB script. Calibration models were made using PLS (partial least square) regression, containing independent data from CT images and dependent data from near-infrared spectroscopy. The data set used for calibration was a subset of 72 animals. The calibration models were validated using a subset of 32 animals. Scaling of independent data and filtering using median filtering were tested to improve predictions. The results showed that CT is not a feasible method for in vivo prediction of intramuscular content in swine.展开更多
基金Open access funding provided by University of Inland Norway The Research Council of Norway provided financial support(grant number 331878).
文摘Background Boars undergo physiological and biochemical changes in semen composition as they grow from puberty to sexual maturity.However,comprehensive metabolomic profiles of boar semen remain uncharacterised.Understanding metabolic alterations in semen during this period is important for optimising reproductive performance in breeding programs.The aim of this study was to characterise the semen metabolome as boars mature,utilising an untargeted metabolomic approach.Semen samples were collected from 15 Duroc boars at three developmental ages:~7 months,8.5 months,and 10 months.Sperm and seminal plasma were separated and analysed by hydrophilic interaction and reversed-phase liquid chromatography coupled with mass spectrometry to capture a wide range of metabolites.Results We identified a total of 4,491 features in boar semen,annotating 92 distinct metabolites.Amino acids,peptides and analogues constituted the most abundant components,followed by fatty acid esters.Principal component analysis(PCA)and partial least squares discriminant analysis(PLS-DA)showed a clear separation between metabolomic profiles by age groups.PERMANOVA analysis of PCA scores confirmed statistically significant differences(P<0.05)between younger(7 months)and more mature boars(8.5 months and 10 months).Pathway analysis identified porphyrin metabolism,taurine and hypotaurine metabolism,and glycerolipid metabolism as significantly enriched pathways in sperm,while glutathione and nitrogen metabolism were prominently enriched in seminal plasma.Using linear modelling,partial Spearman correlation and random forest analyses,we identified homoisovanillic acid as a key metabolite discriminating age groups in both sperm and seminal plasma.Additionally,L-glutamic acid,decanoyl-L-carnitine and N-(1,3-Thiazol-2-yl)benzenesulfonamide emerged as important sperm metabolites,while glyceric acid,myo-inositol,glycerophosphocholine,and several other compounds were identified as critical seminal plasma metabolites.Conclusion This study provides a detailed characterisation of metabolic changes in Duroc boar semen during the transition from puberty to sexual maturity.Our findings enhance the understanding of reproductive development and could inform strategies to assess sexual maturity in breeding programs.
基金The Norwegian Re-search Council is gratefully acknowledged for providing financial support for this research as part of the Robust Pig project.
文摘Avoiding lameness or leg weakness in pig production is crucial to reduce cost, improve animal welfare and meat quality. Detection of lameness detection by the use of vision systems may assist the farmer or breeder to obtain a more accurate and robust measurement of lameness. The paper presents a low-cost vision system for measuring the locomotion of moving pigs based on motion detection, frame-grabbing and multivariate image analysis. The first step is to set up a video system based on web camera technology and choose a test area. Secondly, a motion detection and data storage system are used to build a processing system of video data. The video data are analyzed measuring the properties of each image, stacking them for each animal and then analyze these stacks using multivariate image analysis. The system was able to obtain and decompose information from these stacks, where components could be extracted, representing a particular motion pattern. These components could be used to classify or score animals according to this pattern, which might be an indicator of lameness. However, further improvement is needed with respect to standardization of herding, test area and tracking of animals in order to have a robust system to be used in a farm environment.
基金support from the Norwegian Research Council,project no 210637/O10 and the Nortura meat cooperative
文摘One hundred and four pure-bred Norwegian Duroc boars were CT (computed tomography) scanned to predict the in vivo intramuscular fat percentage in the loin. The animals were slaughtered and the loin was cut commercially. A muscle sample of the m. Longissimus dorsi was sampled and analyzed by the use of near-infrared spectroscopy. Data from CT images were collected using an in-house MATLAB script. Calibration models were made using PLS (partial least square) regression, containing independent data from CT images and dependent data from near-infrared spectroscopy. The data set used for calibration was a subset of 72 animals. The calibration models were validated using a subset of 32 animals. Scaling of independent data and filtering using median filtering were tested to improve predictions. The results showed that CT is not a feasible method for in vivo prediction of intramuscular content in swine.
