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      • SCIESCOPUSKCI등재

        Lactation Persistency as a Component Trait of the Selection Index and Increase in Reliability by Using Single Nucleotide Polymorphism in Net Merit Defined as the First Five Lactation Milk Yields and Herd Life

        Togashi, K.,Hagiya, K.,Osawa, T.,Nakanishi, T.,Yamazaki, T.,Nagamine, Y.,Lin, C.Y.,Matsumoto, S.,Aihara, M.,Hayasaka, K. Asian Australasian Association of Animal Productio 2012 Animal Bioscience Vol.25 No.8

        We first sought to clarify the effects of discounted rate, survival rate, and lactation persistency as a component trait of the selection index on net merit, defined as the first five lactation milks and herd life (HL) weighted by 1 and 0.389 (currently used in Japan), respectively, in units of genetic standard deviation. Survival rate increased the relative economic importance of later lactation traits and the first five lactation milk yields during the first 120 months from the start of the breeding scheme. In contrast, reliabilities of the estimated breeding value (EBV) in later lactation traits are lower than those of earlier lactation traits. We then sought to clarify the effects of applying single nucleotide polymorphism (SNP) on net merit to improve the reliability of EBV of later lactation traits to maximize their increased economic importance due to increase in survival rate. Net merit, selection accuracy, and HL increased by adding lactation persistency to the selection index whose component traits were only milk yields. Lactation persistency of the second and (especially) third parities contributed to increasing HL while maintaining the first five lactation milk yields compared with the selection index whose only component traits were milk yields. A selection index comprising the first three lactation milk yields and persistency accounted for 99.4% of net merit derived from a selection index whose components were identical to those for net merit. We consider that the selection index comprising the first three lactation milk yields and persistency is a practical method for increasing lifetime milk yield in the absence of data regarding HL. Applying SNP to the second- and third-lactation traits and HL increased net merit and HL by maximizing the increased economic importance of later lactation traits, reducing the effect of first-lactation milk yield on HL (genetic correlation ($r_G$) = -0.006), and by augmenting the effects of the second- and third-lactation milk yields on HL ($r_G$ = 0.118 and 0.257, respectively).

      • SCIESCOPUSKCI등재

        Prediction of random-regression coefficient for daily milk yield after 305 days in milk by using the regression-coefficient estimates from the first 305 days

        Yamazaki, Takeshi,Takeda, Hisato,Hagiya, Koichi,Yamaguchi, Satoshi,Sasaki, Osamu Asian Australasian Association of Animal Productio 2018 Animal Bioscience Vol.31 No.10

        Objective: Because lactation periods in dairy cows lengthen with increasing total milk production, it is important to predict individual productivities after 305 days in milk (DIM) to determine the optimal lactation period. We therefore examined whether the random regression (RR) coefficient from 306 to 450 DIM (M2) can be predicted from those during the first 305 DIM (M1) by using a RR model. Methods: We analyzed test-day milk records from 85,690 Holstein cows in their first lactations and 131,727 cows in their later (second to fifth) lactations. Data in M1 and M2 were analyzed separately by using different single-trait RR animal models. We then performed a multiple regression analysis of the RR coefficients of M2 on those of M1 during the first and later lactations. Results: The first-order Legendre polynomials were practical covariates of RR for the milk yields of M2. All RR coefficients for the additive genetic (AG) effect and the intercept for the permanent environmental (PE) effect of M2 had moderate to strong correlations with the intercept for the AG effect of M1. The coefficients of determination for multiple regression of the combined intercepts for the AG and PE effects of M2 on the coefficients for the AG effect of M1 were moderate to high. The daily milk yields of M2 predicted by using the RR coefficients for the AG effect of M1 were highly correlated with those obtained by using the coefficients of M2. Conclusion: Milk production after 305 DIM can be predicted by using the RR coefficient estimates of the AG effect during the first 305 DIM.

      • KCI등재후보

        Image analysis traits of multiple muscles and intermuscular/subcutaneous fat influence Japanese Black beef carcass price and genetic parameters

        Tamagawa Yuta,Takahashi Mikiya,Hagiya Koichi,Kuchida Keigo 아세아·태평양축산학회 2024 Animal Bioscience Vol.37 No.9

        Objective: The purposes of this study were to investigate the relationship between carcass unit price per 1 kg (UP) and multiple muscles and intermuscular fat (IF)/subcutaneous fat of beef carcasses using image analysis of cross-section images for Wagyu beef cattle in Japan, and to estimate their genetic parameters.Methods: The carcasses used in this study were 1,807 Japanese Black (Wagyu) cattle (1,216 steers and 591 heifers). An analysis of variance was conducted with UP as the dependent variable and market date, age in months, sex, and image analysis traits (IAT) as fixed effects, and standard partial regression coefficients were calculated for each IAT on UP. Also, the heritability of each IAT that affected UP and genetic correlation among IAT vs carcass grading traits were estimated.Results: Not only IAT related to carcass grading traits, <i>M. trapezius dorsi, M. latissimus dorsi</i>, and IF traits were significant differences in UP (p<0.05). The heritability of IAT associated with UP was estimated at 0.38 to 0.85. The genetic correlations between the area and thickness of <i>M. trapezius dorsi</i> and <i>M. latissimus dorsi</i> vs rib eye area (REA) were estimated to be moderately positive (0.53 to 0.66), while the genetic correlations between the IF area percentage vs carcass weight, REA, and yield score were estimated to be negative (–0.40, –0.56, and –0.34).Conclusion: UP was influenced by various traits, including <i>M. trapezius dorsi, M. latissimus dorsi</i>, and IF traits, as well as image analysis associated with carcass grading traits. Since these IAT associated with UP had hereditary and desirable genetic correlations with carcass grading traits, these traits were also important for genetic improvement. Objective: The purposes of this study were to investigate the relationship between carcass unit price per 1 kg (UP) and multiple muscles and intermuscular fat (IF)/subcutaneous fat of beef carcasses using image analysis of cross-section images for Wagyu beef cattle in Japan, and to estimate their genetic parameters. Methods: The carcasses used in this study were 1,807 Japanese Black (Wagyu) cattle (1,216 steers and 591 heifers). An analysis of variance was conducted with UP as the dependent variable and market date, age in months, sex, and image analysis traits (IAT) as fixed effects, and standard partial regression coefficients were calculated for each IAT on UP. Also, the heritability of each IAT that affected UP and genetic correlation among IAT vs carcass grading traits were estimated. Results: Not only IAT related to carcass grading traits, M. trapezius dorsi, M. latissimus dorsi, and IF traits were significant differences in UP (p<0.05). The heritability of IAT associated with UP was estimated at 0.38 to 0.85. The genetic correlations between the area and thickness of M. trapezius dorsi and M. latissimus dorsi vs rib eye area (REA) were estimated to be moderately positive (0.53 to 0.66), while the genetic correlations between the IF area percentage vs carcass weight, REA, and yield score were estimated to be negative (–0.40, –0.56, and –0.34). Conclusion: UP was influenced by various traits, including M. trapezius dorsi, M. latissimus dorsi, and IF traits, as well as image analysis associated with carcass grading traits. Since these IAT associated with UP had hereditary and desirable genetic correlations with carcass grading traits, these traits were also important for genetic improvement.

      • SCIESCOPUSKCI등재

        Prediction of 305 Days Milk Production from Early Records in Dairy Cattle Using an Empirical Bayes Method

        Pereira, J.A.C.,Suzuki, M.,Hagiya, K. Asian Australasian Association of Animal Productio 2001 Animal Bioscience Vol.14 No.11

        A prediction of 305 d milk production from early records using an empirical Bayes method (EBM) was performed. The EBM was compared with the best predicted estimation (BPE), test interval method (TIM), and the linearized Wood's model (LWM). Daily milk yields were obtained from 606 first lactation Japanese Holstein cows in three herds. From each file of 305 daily records, 10 random test day records with an interval of approximately one month were taken. The accuracies of these methods were compared using the absolute difference (AD) and the standard deviation (SD) of the differences between the actual and the estimated 305 d milk production. The results showed that in the early stage of the lactation, EBM was superior in obtaining the prediction with high accuracy. When all the herds were analyzed jointly, the AD during the first 5 test day records were on average 373, 590, 917 and 1,042 kg for EBM, BPE, TIM, and LWM, respectively. Corresponding SD for EBM, BPE, TIM, and LWM were on average 488, 733, 747 and 1,605 kg. When the herds were analyzed separately, the EBM predictions retained high accuracy. When more information on the actual lactation was added to the prediction, TIM and LWM gradually achieved better accuracies. Finally, in the last period of the lactation, the accuracy of both of the methods exceeded EBM and BPM. The AD for the last 2 samples analyzing all the herds jointly were on average 141, 142, 164, and 214 kg for LWM, TIM, EBM, and BPE, respectively. In the current practices of collecting monthly records, early prediction of future milk production may be more accurate using EBM. Alternatively, if enough information of the actual lactation is accumulated, TIM may obtain better accuracy in the latter stage of lactation.

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