Ito Tetsuya, Fukawa Kazuo, Kamikawa Mai, Nikaidou Satoshi, Taniguchi Masaaki, Arakawa Aisaku, Tanaka Genki, Mikawa Satoshi, Furukawa Tsutomu, Hirose Kensuke
Central Research Institute for Feed and Livestock, ZEN-NOH (National Federation of Agricultural Cooperative Associations), Kamishihoro, Hokkaido, Japan.
Graduate School of Agriculture, Tokyo University of Agriculture, Atsugi, Kanagawa, Japan.
Anim Sci J. 2018 Jan;89(1):12-20. doi: 10.1111/asj.12891. Epub 2017 Aug 30.
Daily feed intake (DFI) is an important consideration for improving feed efficiency, but measurements using electronic feeder systems contain many missing and incorrect values. Therefore, we evaluated three methods for correcting missing DFI data (quadratic, orthogonal polynomial, and locally weighted (Loess) regression equations) and assessed the effects of these missing values on the genetic parameters and the estimated breeding values (EBV) for feeding traits. DFI records were obtained from 1622 Duroc pigs, comprising 902 individuals without missing DFI and 720 individuals with missing DFI. The Loess equation was the most suitable method for correcting the missing DFI values in 5-50% randomly deleted datasets among the three equations. Both variance components and heritability for the average DFI (ADFI) did not change because of the missing DFI proportion and Loess correction. In terms of rank correlation and information criteria, Loess correction improved the accuracy of EBV for ADFI compared to randomly deleted cases. These findings indicate that the Loess equation is useful for correcting missing DFI values for individual pigs and that the correction of missing DFI values could be effective for the estimation of breeding values and genetic improvement using EBV for feeding traits.
日采食量（DFI）是提高饲料效率的一个重要考量因素，但使用电子饲喂系统进行测量时包含许多缺失和错误的值。因此，我们评估了三种校正缺失DFI数据的方法（二次方程、正交多项式和局部加权（Loess）回归方程），并评估了这些缺失值对饲养性状的遗传参数和估计育种值（EBV）的影响。DFI记录来自1622头杜洛克猪，其中包括902头无DFI缺失个体和720头有DFI缺失个体。在这三个方程中，Loess方程是校正5%-50%随机删除数据集中缺失DFI值的最合适方法。平均日采食量（ADFI）的方差分量和遗传力均未因DFI缺失比例和Loess校正而改变。在秩相关和信息准则方面，与随机删除情况相比，Loess校正提高了ADFI的EBV准确性。这些发现表明，Loess方程对于校正个体猪的缺失DFI值很有用，并且校正缺失的DFI值对于使用EBV进行饲养性状的育种值估计和遗传改良可能是有效的。
