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논문 기본 정보

자료유형
학술저널
저자정보
Mahboob Alam (National Institute of Animal Science) Jae-Gu Lee (National Institute of Animal Science) Chang Gwon Dang (National Institute of Animal Science) Seung Soo Lee (National Institute of Animal Science) Mi Na Park (National Institute of Animal Science) Sang Min Lee (National Institute of Animal Science RDA Korea)
저널정보
한국동물유전육종학회 Journal of Animal Breeding and Genomics Journal of Animal Breeding and Genomics Vol.6 No.4
발행연도
2022.12
수록면
201 - 219 (19page)

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Calving ease is an important reproductive trait in dairy production. We investigated the first five parities calving ease (CE) scores and various factors to identify their relationships with CE in Korean Holstein cows. We analyzed the 83,943, 69,120, 31,500, 29,003, and 9,361 records from parity 1 through 5 provided by Dairy Cattle Improvement Center (DCIC), Korea. The categorical CE scores (1 to 5) were also linearly transformed via the snell procedure and analyzed alongside actual scores. A generalized linear model or GLM analysis was performed in the R software package to estimate the significance of predictor variables. The complete models included the fixed effects of calf sex (SEX), calf size (SIZE), gestation length group (GLEN), dam calving age (DAGE), calving year (YR), calving season (SEA), and calving herd (HERD). Both actual and linear-transformed phenotypes were fitted separately for individual parity datasets. CE rates differed across parity. Male calves tend to have larger body sizes and longer gestation periods. As a result, males were also more inclined to extreme CE. However, longer gestation lengths, irrespective of sex, were also associated with greater CE. The GLM analysis showed that the effect of HERD, SIZE and YR are significant across parities (P<0.05). However, the SEX effect was only non-significant at parity 3, whereas GLEN was significant only up to parity 3. The season effect was mostly non-significant at P<0.05. The DAGE effect was removed by stepwise regression for all datasets. The stepwise regression also retained similar factors for the best-fit models. However, despite some minor variations in model parameter estimates, the identified predictor variables were identical across actual and modified scores. It also indicates the possible use of similar independent variables for any genetic evaluation, regardless of CE datatype. This is the first in depth study on factors of CE in Korean Holstein. We, therefore, believe these findings on significant predictors could greatly assist in designing future genetic evaluations for calving difficulty.

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