Browsing by Author "Weiss, W. P."

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    Evaluation of the National Research Council (2001) dairy model and derivation of new prediction equations. 1. Digestibility of fiber, fat, protein, and nonfiber carbohydrate
    White, Robin R.; Roman-Garcia, Y.; Firkins, J. L.; VandeHaar, M. J.; Armentano, L. E.; Weiss, W. P.; McGill, Tyler R.; Garnett, R.; Hanigan, Mark D. (2017-05)
    Evaluation of ration balancing systems such as the National Research Council (NRC) Nutrient Requirements series is important for improving predictions of animal nutrient requirements and advancing feeding strategies. This work used a. literature data set (n = 550) to evaluate predictions of total-tract digested neutral detergent fiber (NDF), fatty acid (FA), crude protein (CP), and nonfiber carbohydrate (NFC) estimated by the NRC (2001) dairy model. Mean biases suggested that the NRC (2001) lactating cow model overestimated true FA and CP digestibility by 26 and 7%, respectively, and under-predicted NDF digestibility by 16%. All NR,C (2001) estimates had notable mean and slope biases and large root mean squared prediction error (RMSPE), and concordance (CCC) ranged from poor to good. Predicting NDF digestibility with independent equations for legumes, corn silage, other forages, and nonforage feeds improved CCC (0.85 vs. 0.76) compared with the re-derived NRC (2001) equation form (NRC equation with parameter estimates re-derived against this data set). Separate FA digestion coefficients were derived for different fat supplements (animal fats, oils. and other fat types) and for the basal diet. This equation returned improved (from 0.76 to 0.94) CCC compared with the re-derived NRC (2001) equation form. Unique CP digestibility equations were derived for forages, animal protein feeds, plant protein feeds, and other feeds, which improved CCC compared with the re-derived NRC (2001) equation form (0.74 to 0.85). New NFC digestibility coefficients were derived for grain-specific starch digestibilities, with residual organic matter assumed to be 98% digestible. A Monte Carlo cross-validation was performed to evaluate repeatability of model fit. In this procedure, data were randomly subsetted 500 tunes into derivation (60%) and evaluation (40%) data sets, and equations were derived using the derivation data and then evaluated against the independent evaluation data. Models derived with random study effects demonstrated poor repeatability of fit in independent evaluation. Similar equations derived without random study effects showed improved fit against independent data, and little evidence of biased parameter estimates associated with failure to include study effects. The equations derived in this analysis provide interesting insight, into how NDF, starch, FA, and CP digestibilities are affected by intake, feed type, and diet composition.
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    Predictions of ruminal outflow of essential amino acids in dairy cattle
    Fleming, A. J.; Lapierre, H.; White, Robin R.; Tran, H.; Kononoff, P. J.; Martineau, R.; Weiss, W. P.; Hanigan, Mark D. (2019-12)
    The objective of this work was to update and evaluate predictions of essential AA (EAA) outflows from the rumen. The model was constructed based on previously derived equations for rumen-undegradable (RUP), microbial (MiCP), and endogenous (EndCP) protein outflows from the rumen, and revised estimates of ingredient composition and EAA composition of the protein fractions. Corrections were adopted to account for incomplete recovery of EAA during 24-h acid hydrolysis. The predicted ruminal protein and EAA outflows were evaluated against a data set of observed values from the literature. Initial evaluations indicated a minor mean bias for non-ammonia, non-microbial nitrogen flow ([RUP EndCP]/6.25) of 16 g of N per day. Root mean squared errors (RMSE) of EA.A predictions ranged from 26.8 to 40.6% of observed mean values. Concordance correlation coefficients (CCC) of EAA predictions ranged from 0.34 to 0.55. Except for Leu, all ruminal EA.A outflows were overpredicted by 3.0 to 32 g/d. In addition, small but significant slope biases were present for Arg [2.2% mean squared error (MSE)] and Lys (3.2% MSE). The overpredictions may suggest that the mean recovery of AA from acid hydrolysis across laboratories was less than estimates encompassed in the recovery factors. To test this hypothesis, several regression approaches were undertaken to identify potential causes of the bias. These included regressions of (1) residual errors for predicted EAA flows on each of the 3 protein-driven EA flows, (2) observed EAA flows on each protein-driven EAA flow, including an intercept, (3) observed EAA. flows on the protein-driven EAA flows, excluding an intercept term, and (4) observed EAA. flows on IMP and MiCP. However, these equations were deemed unsatisfactory for bias adjustment, as they generated biologically unfeasible predictions for some entities. Future work should focus on identifying the cause of the observed prediction bias.