Vijayakumar, Mayakrishnan
(Dairy Science Division, National Institute of Animal Science, Rural Development Administration)
,
Choy, Yun-Ho
(Animal Breeding and Genetics Division, National Institute of Animal Science, Rural Development Administration)
,
Kim, Tae-Il
(Dairy Science Division, National Institute of Animal Science, Rural Development Administration)
,
Lim, Dong-Hyun
(Dairy Science Division, National Institute of Animal Science, Rural Development Administration)
,
Park, Seong-Min
(Dairy Science Division, National Institute of Animal Science, Rural Development Administration)
,
Alam, Mahboob
(Animal Breeding and Genetics Division, National Institute of Animal Science, Rural Development Administration)
,
Choi, Hee-Chul
(Dairy Science Division, National Institute of Animal Science, Rural Development Administration)
,
Ki, Kwang-Seok
(Dairy Science Division, National Institute of Animal Science, Rural Development Administration)
,
Lee, Hyun-Jeong
(Dairy Science Division, National Institute of Animal Science, Rural Development Administration)
The objective of the present study was to determine the best model to describe and quantify the changes in live body weight, height at withers, height at rump, body length and chest girth of Holstein cows raised under Korean feeding conditions for 50 months. The five standard growth models namely po...
The objective of the present study was to determine the best model to describe and quantify the changes in live body weight, height at withers, height at rump, body length and chest girth of Holstein cows raised under Korean feeding conditions for 50 months. The five standard growth models namely polynomial linear regression models, regression of growth variables on the first and second-order of ages in days (model 1) and regression of growth variables on age covariates from first to the third-order (model 2) as well as non-linear models were fitted and evaluated for representing growth pattern of Holstein cows raised in Korean feeding circumstances. Nonlinear models fitted were three exponential growth curve models; Brody, Gompertz, and von Bertalanffy functional models. For this purpose, a total of 22 Holstein cows raised in Korea used in the period from April 2016 to May 2020. Each model fitted to monthly growth curve records of dairy cows by using PROC NLIN procedure in SAS program. On the basis of the results, nonlinear models showed the lower root mean square of error (RMSE) for live body weight, height at withers, height at rump, body length and chest girth (12.22, 1.95, 1.55, 4.04, 2.06) with higher correlation coefficiency (R2) values for live body weight, height at withers, height at rump, body length and chest girth (0.99, 0.99, 0.99, 1.00, 1.00). Overall, the evaluation of the different growth models indicated that the Gompertz model used in the study seemed to be the most appropriate one for standard growth of Holstein cows raised under Korean feeding system.
The objective of the present study was to determine the best model to describe and quantify the changes in live body weight, height at withers, height at rump, body length and chest girth of Holstein cows raised under Korean feeding conditions for 50 months. The five standard growth models namely polynomial linear regression models, regression of growth variables on the first and second-order of ages in days (model 1) and regression of growth variables on age covariates from first to the third-order (model 2) as well as non-linear models were fitted and evaluated for representing growth pattern of Holstein cows raised in Korean feeding circumstances. Nonlinear models fitted were three exponential growth curve models; Brody, Gompertz, and von Bertalanffy functional models. For this purpose, a total of 22 Holstein cows raised in Korea used in the period from April 2016 to May 2020. Each model fitted to monthly growth curve records of dairy cows by using PROC NLIN procedure in SAS program. On the basis of the results, nonlinear models showed the lower root mean square of error (RMSE) for live body weight, height at withers, height at rump, body length and chest girth (12.22, 1.95, 1.55, 4.04, 2.06) with higher correlation coefficiency (R2) values for live body weight, height at withers, height at rump, body length and chest girth (0.99, 0.99, 0.99, 1.00, 1.00). Overall, the evaluation of the different growth models indicated that the Gompertz model used in the study seemed to be the most appropriate one for standard growth of Holstein cows raised under Korean feeding system.
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제안 방법
A wide range of mathematical models have been used to estimate the growth curve in dairy cows for a well fit function model as an alternative. Therefore, in this study, we aimed to explore and compare the Polynomial linear regression model 1 and 2 and non-linear (Brody, Gompertz and von Bertalanffy) functional model for the benefit of the growth curve of Holstein dairy cows reared under Korean feeding conditions.
대상 데이터
Individuals from newborn calves to heifers, mature and milking cows we were employed for lifetime growth experiment. The original data set consisted of observation from April 2016 to May 2020 in dairy cattle for 50 months, which a total of 918 measures for body weight, 851 measures for height at wither, 823 measures for height at rump, 813 measures for body length and 561 measures for chest girth for the growth estimation. The study was conducted in the experimental dairy farm, National Institute of Animal Science (NIAS), Cheonan, Republic of Korea.
The original data set consisted of observation from April 2016 to May 2020 in dairy cattle for 50 months, which a total of 918 measures for body weight, 851 measures for height at wither, 823 measures for height at rump, 813 measures for body length and 561 measures for chest girth for the growth estimation. The study was conducted in the experimental dairy farm, National Institute of Animal Science (NIAS), Cheonan, Republic of Korea. The study was approved by the Institutional Animal Care and Use Committee (IACUC, No.
데이터처리
General least-squares analysis was performed to estimate regression coefficient parameters of the polynomial linear growth function for body weight, height at withers, height at rump, body length and, chest girth on age in days using PROC GLM procedure of SAS program (SAS Institute Inc, Cary, NC, USA). Parameters of nonlinear growth curve models were estimated by iteration method with Gauss-Newton or Marquardt iterative methods using PROC NLIN procedure of SAS.
Parameters of nonlinear growth curve models were estimated by iteration method with Gauss-Newton or Marquardt iterative methods using PROC NLIN procedure of SAS. Model comparisons were made based the magnitude of R2 (Model Sum of Squares/ Corrected Total Sum of Squares) and square root of mean squares of error (RMSE) which depend only on age in days as explanatory variable(s) without any other sources of variation.
General least-squares analysis was performed to estimate regression coefficient parameters of the polynomial linear growth function for body weight, height at withers, height at rump, body length and, chest girth on age in days using PROC GLM procedure of SAS program (SAS Institute Inc, Cary, NC, USA). Parameters of nonlinear growth curve models were estimated by iteration method with Gauss-Newton or Marquardt iterative methods using PROC NLIN procedure of SAS. Model comparisons were made based the magnitude of R2 (Model Sum of Squares/ Corrected Total Sum of Squares) and square root of mean squares of error (RMSE) which depend only on age in days as explanatory variable(s) without any other sources of variation.
이론/모형
Most of the recent study, applying nonlinear functions to model the growth curve reported the data from Holstein cows and used routine nonlinear models, but studies on the growth curve of dairy cattle, especially using comparative models, are sparse in the literature. Therefore, in this study, we used Polynomial linear regression model and nonlinear model for model goodness of fit the data (Bahreini Behzadi et al., 2014).
성능/효과
The observed growth curve parameter (A, b and k) values for chest girth of Holstein cows from the selected models with their RMSE and R2 are shown in Table 8. Among the results, the Gompertz model was highly significant and it had a high R2 (1.00) with low RMSE (2.22) value, showings very good performance on the validation data set with 95 % prediction accuracy. Because the model does not consider sex or age to stratify results, it is very amenable to transfer onto a weight tape that can be used for all ages of Holstein cows raised in Korea.
Among the results, the rate of maturity estimates of body measurements revealed lower RMSE values with higher coefficient of determination. It indicated that this tool could have the potential impact for small farm holders to use the accurate growth curve of animal traits to plan feeding strategies for productivity, as well as accurate estimates of slaughter weight at market, which is the primary determinant of market price.
The average A, b and k parameters of the nonlinear for height at rump of cows from the selected models with their RMSE and R2 are summarized in Table 6. The best estimation based on R2 values showed that Gompertz model had a higher R2 (1.00) with lower RMSE (1.55) values than that of Polynomial linear regression, Brody and von Bertalanffy models and it would be more convenient to measure the height at rump.
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