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Anim Biosci > Accepted Articles
DOI: https://doi.org/10.5713/ajas.20.0684    [Accepted] Published online November 9, 2020.
Evaluation of the equation for predicting dry matter intake of lactating dairy cows in the Korean feeding standards for dairy cattle
Mingyung Lee1  , Junsung Lee1  , Seoyoung Jeon1  , Seong-Min Park2, Kwang-Seok Ki2, Seongwon Seo1,* 
1Division of Animal and Dairy Sciences, Chungnam National University, Daejeon 34134, Republic of Korea
2National Institute of Animal Science, Rural Development Administration, Cheonan 31000, Republic of Korea
Correspondence:  Seongwon Seo, Tel: +82-42-821-5787, Fax: +82-42-823-2766, Email: swseo@cnu.kr
Received: 28 September 2020   • Revised: 19 October 2020   • Accepted: 9 November 2020
Abstract
Objective
This study aimed to validate and evaluate the dry matter (DM) intake prediction model of the Korean feeding standards for dairy cattle (KFSD).
Methods
The KFSD DM intake (DMI) model was developed using a database containing the data from the Journal of Dairy Science from 2006 to 2011 (1065 observations 287 studies). The development (458 observations from 103 studies) and evaluation databases (168 observations from 74 studies) were constructed from the database. The body weight (kg; BW), metabolic BW (BW0.75, MBW), 4% fat-corrected milk (FCM), forage as a percentage of dietary DM, and the dietary content of nutrients (% DM) were chosen as possible explanatory variables. A random coefficient model with the study as a random variable and a linear model without the random effect was used to select model variables and estimate parameters, respectively, during the model development. The best-fit equation was compared to published equations, and sensitivity analysis of the prediction equation was conducted. The KFSD model was also evaluated using in vivo feeding trial data.
Results
The KFSD DMI equation is 4.103 (± 2.994) + 0.112 (± 0.022) × MBW + 0.284 (± 0.020) × FCM - 0.119 (± 0.028) × NDF, explaining 47% of the variation in the evaluation dataset with no mean nor slope bias (p > 0.05). The root mean square prediction error was 2.70 kg/d, best among the tested equations. The sensitivity analysis showed that the model is the most sensitive to FCM, followed by MBW and NDF. With the in vivo data, the KFSD equation showed slightly higher precision (R2 = 0.39) than the NRC equation (R2 = 0.37), with a mean bias of 1.19 kg and no slope bias (p > 0.05).
Conclusion
The KFSD DMI model is suitable for predicting the DMI of lactating dairy cows in practical situations in Korea.
Keywords: Dry Matter Intake; Lactating Dairy Cow; Meta-analysis; Modeling


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