
Supplemental material for "Evaluation of ruminal amino acid outflow predictions by nutritional models in dairy cattle"
The objective was to evaluate the fit statistics for the predictions of ruminal AA outflows by NRC (2001), NASEM (2021), CNCPS (v.6.5.5) and NittanyCow (NC) models in lactating dairy cows. Sixty-seven studies published in English between 1984 and 2020 with 252 treatment means were considered for analysis. Lactational performance (DMI, milk yield, milk fat and true protein, and BW data), dietary nutrient composition (CP, NDF, ether extract, and ash), and ruminal outflow of total AA, microbial CP (MicP), RUP, and EAA determined by omasal or duodenal sampling techniques were extracted and used in the analysis. Production and dietary nutrient composition data reported in the studies were used as inputs to predict ruminal outflows of MP supply, MicP, RUP, and EAA using NRC, NASEM, CNCPS and NC models. Model fit statistics (i.e., observed – predicted means) and performances of nutritional models were assessed using root mean squared error (RMSE, g/d and % of observed mean), and Lin’s concordance correlation coefficient (CCC). Predictions were considered accurate, accurate with biological concern, acceptable with biological concern, or compromised if mean or linear biases (% of observed mean) were < 5%, 5 to 10% with P ≤ 0.10, 10 to 15% with P ≤ 0.10, or > 15%, respectively. Overall and based on mean biases, predictions of most variables were accurate or acceptable with biological concern across all nutritional models. Models performed similarly when predicting ruminal total AA outflow with CCC ranging from 65 to 71% and RMSE ranging from 19 to 20% of observed mean. Predictions of ruminal MicP and RUP outflows had CCC ranging from 33 to 57% and RMSE ranging from 24 to 42% of observed mean. Predictions of Lys, Met, and His had CCC ranging from 39 to 66% and RMSE ranging from 22 to 34% observed mean. Overall, nutritional models presented accurate or acceptable predictions with biological concern for most AA when considering both mean and linear biases. Accurate predictions based on mean bias were: Lys and Ile for NRC; Met, Arg, and Phe for NASEM and NC; His and Val for NRC and NASEM; and Leu and Thr for all nutritional models. Accurate predictions based on linear biases were: Met for NRC and NASEM; Phe for NRC, NASEM, and CNCPS; and Leu for all nutritional models. Compromised predictions were Met, His, and Arg for CNCPS based on mean bias. All models presented limitations if an acceptable threshold for the linear bias is set at < 5% observed mean to avoid Type I error. These biases should be considered by nutritionists when balancing rations for AA.
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Work Title | Supplemental material for "Evaluation of ruminal amino acid outflow predictions by nutritional models in dairy cattle" |
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Access | |
Creators |
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License | CC BY 4.0 (Attribution) |
Work Type | Other |
Publication Date | 2025 |
DOI | doi:10.26207/aj0d-8v80 |
Deposited | October 21, 2024 |
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