ABSTRACT
In Korea, Korea Proven Bulls (KPN) program has been well-developed. Breeding and evaluation of cows are also an essential factor to increase earnings and genetic gain. This study aimed to evaluate the accuracy of cow breeding value by using three methods (pedigree index [PI], pedigree-based best linear unbiased prediction [PBLUP], and genomic-BLUP [GBLUP]). The reference population (n = 16,971) was used to estimate breeding values for 481 females as a test population. The accuracy of GBLUP was 0.63, 0.66, 0.62 and 0.63 for carcass weight (CWT), eye muscle area (EMA), back-fat thickness (BFT), and marbling score (MS), respectively. As for the PBLUP method, accuracy of prediction was 0.43 for CWT, 0.45 for EMA, 0.43 for MS, and 0.44 for BFT. Accuracy of PI method was the lowest (0.28 to 0.29 for carcass traits). The increase by approximate 20% in accuracy of GBLUP method than other methods could be because genomic information may explain Mendelian sampling error that pedigree information cannot detect. Bias can cause reducing accuracy of estimated breeding value (EBV) for selected animals. Regression coefficient between true breeding value (TBV) and GBLUP EBV, PBLUP EBV, and PI EBV were 0.78, 0.625, and 0.35, respectively for CWT. This showed that genomic EBV (GEBV) is less biased than PBLUP and PI EBV in this study. In addition, number of effective chromosome segments (Me) statistic that indicates the independent loci is one of the important factors affecting the accuracy of BLUP. The correlation between Me and the accuracy of GBLUP is related to the genetic relationship between reference and test population. The correlations between Me and accuracy were -0.74 in CWT, -0.75 in EMA, -0.73 in MS, and -0.75 in BF, which were strongly negative. These results proved that the estimation of genetic ability using genomic data is the most effective, and the smaller the Me, the higher the accuracy of EBV.
ABSTRACT
Stacking fault energy is one of key parameters for understanding the mechanical properties of face-centered cubic materials. It is well known that the plastic deformation mechanism is closely related to the size of stacking fault energy. Although alloying is a conventional method to modify the physical parameter, the underlying microscopic mechanisms are not yet clearly established. Here, we propose a simple model for determining the effect of interstitial alloying on the stacking fault energy. We derive a volumetric behaviour of stacking fault energy from the harmonic approximation to the energy-lattice curve and relate it to the contents of interstitials. The stacking fault energy is found to change linearly with the interstitial content in the usual low concentration domain. This is in good agreement with previously reported experimental and theoretical data.
ABSTRACT
The activation of plastic deformation mechanisms determines the mechanical behavior of crystalline materials. However, the complexity of plastic deformation and the lack of a unified theory of plasticity have seriously limited the exploration of the full capacity of metals. Current efforts to design high-strength structural materials in terms of stacking fault energy have not significantly reduced the laborious trial and error works on basic deformation properties. To remedy this situation, here we put forward a comprehensive and transparent theory for plastic deformation of face-centered cubic metals. This is based on a microscopic analysis that, without ambiguity, reveals the various deformation phenomena and elucidates the physical fundaments of the currently used phenomenological correlations. We identify an easily accessible single parameter derived from the intrinsic energy barriers, which fully specifies the potential diversity of metals. Based entirely on this parameter, a simple deformation mode diagram is shown to delineate a series of convenient design criteria, which clarifies a wide area of material functionality by texture control.
