N. Bedere, Joëlle Dupont, Y. Baumard, Christophe Staub, D. Gourichon, Elleboudt Frédéric, Pascale Le Roy, Tatiana Zerjal
{"title":"通过背膘厚度表型分析蛋鸡体储的遗传背景","authors":"N. Bedere, Joëlle Dupont, Y. Baumard, Christophe Staub, D. Gourichon, Elleboudt Frédéric, Pascale Le Roy, Tatiana Zerjal","doi":"10.24072/pcjournal.412","DOIUrl":null,"url":null,"abstract":"In this study, we pursued three primary objectives: firstly to test and validate the pheno-typing of backfat thickness as an indicator of the overall fatness of laying hens; secondly, to estimate genetic parameters for this trait; thirdly, to study the phenotypic and genetic relationships between this trait and other traits related to production and body composition. To address these questions, hens from two lines under divergent selection for residual feed intake, were phenotyped for body weight, body composition traits (backfat, total fat volume, and blood adipokines levels), and egg number. Linear mixed models enabled to estimate variance components and calculate","PeriodicalId":74413,"journal":{"name":"Peer community journal","volume":"17 10","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Genetic background of body reserves in laying hens through backfat thickness phenotyping\",\"authors\":\"N. Bedere, Joëlle Dupont, Y. Baumard, Christophe Staub, D. Gourichon, Elleboudt Frédéric, Pascale Le Roy, Tatiana Zerjal\",\"doi\":\"10.24072/pcjournal.412\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this study, we pursued three primary objectives: firstly to test and validate the pheno-typing of backfat thickness as an indicator of the overall fatness of laying hens; secondly, to estimate genetic parameters for this trait; thirdly, to study the phenotypic and genetic relationships between this trait and other traits related to production and body composition. To address these questions, hens from two lines under divergent selection for residual feed intake, were phenotyped for body weight, body composition traits (backfat, total fat volume, and blood adipokines levels), and egg number. Linear mixed models enabled to estimate variance components and calculate\",\"PeriodicalId\":74413,\"journal\":{\"name\":\"Peer community journal\",\"volume\":\"17 10\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Peer community journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.24072/pcjournal.412\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Peer community journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24072/pcjournal.412","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Genetic background of body reserves in laying hens through backfat thickness phenotyping
In this study, we pursued three primary objectives: firstly to test and validate the pheno-typing of backfat thickness as an indicator of the overall fatness of laying hens; secondly, to estimate genetic parameters for this trait; thirdly, to study the phenotypic and genetic relationships between this trait and other traits related to production and body composition. To address these questions, hens from two lines under divergent selection for residual feed intake, were phenotyped for body weight, body composition traits (backfat, total fat volume, and blood adipokines levels), and egg number. Linear mixed models enabled to estimate variance components and calculate