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作 者:Xuelin FU Yajing CHEN Manting WU Junyong HU Wanghong LIU
机构地区:[1]The Breeding Swine Quality Supervision and Testing Center,Ministry of Agriculture and Rural Affairs(Wuhan),Wuhan 437770,China [2]National Engineering Research Center for Livestock,Wuhan 437770,China
出 处:《Agricultural Biotechnology》2021年第2期78-83,共6页农业生物技术(英文版)
摘 要:A statistical analysis was conducted on the feeding behavior of 106 York breeding pigs.Pearson correlation analysis,principal component correlation analysis and multiple stepwise regression equation methods were applied to establish regression equations of the York breeding pigs total feed intake per time and average feed intake per time with corrected fat thickness,feed conversion rate,and corrected daily gain.The results showed that:①there were three peak feed intake periods for the pigs,and the correlation coefficient between the feed intake and the corrected fat thickness of the pigs in the 24 h period was positive or negative,that is,increasing the number of feeding times and the feed intake was not necessarily conducive to the fat thickness accumulation,but the breeding goal of fat thickness could be achieved by controlling the feeding times and feed intake;②the average feed intake of pigs in the 60-90 kg body weight stage was 30%-50%higher than that of the 30-60 kg body weight stage,but the number of feeding times decreased,the peak feeding time was more concentrated,and the feeding duration per time was 3.0 min longer,indicating that as the weight of pigs increased,the feed intake increased significantly;and③the stepwise regression equations and the principal component equations showed that the feeding behavior of York pigs in the 30-90 kg growth stage was not only affected by the feeding time within 24 h,but also by environmental factors such as temperature and humidity.The feeding behavior of York pigs is a complex process of interaction between environmental factors and animal factors.
关 键 词:Feed intake Corrected daily weight gain Feed conversion ratio Corrected fat thickness Stepwise regression Principal component regression
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