Models for Predicting Dry Matter Intake of Holsteins During the Prefresh Transition Period

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Abstract
The objectives of this study were to develop and validate a model for predicting dry matter intake (DMI) of Holsteins during the prefresh transition period. The original database (ODB) for model development was established by compiling parity, body condition score (BCS), and DMI data during the final 3 wk of gestation from 366 Holsteins fed 24 different diets that were used in eight experiments conducted at three universities. For model validation, a validation database (VDB) was established by compiling data from 333 prefresh transition Holsteins fed 25 different diets that were used in eight experiments conducted at five universities. Dry matter intake during the prefresh transition period was fitted to an exponential function: DMI(t) = a + pe(kt), where DMI(t) = DMI as a percentage of body weight (BW) at time t, a = asymptotic intercept at time--infinity, p = change in intake (kg) from the asymptotic intercept until parturition, k = rate constant influencing the shape of the curve, and t = day relative to parturition expressed as days pregnant--280. The model developed from the ODB predicted DMI of heifers in the VDB with satisfactory accuracy and precision. However, this was not true for cows, probably due to differences in BCS of cows and diets fed to cows from the two data sets. When a subset of cows was selected from each data set that had similar BCS (> 4.0) and were fed similar diets, accuracy and precision of the model predicting DMI was improved. Finally, both databases were combined to develop final models for predicting DMI of heifers and cows. Proposed models for predicting mean daily DMI of heifers and cows during the prefresh transition period were DMI(t) = 1.713-0.688e(0.344t) (R2 = 0.96) and DMI(t) = 1.979-0.756e(0.154t) (R2 = 0.97), respectively. Adjustment factors for animal and dietary factors were generated to demonstrate the plausibility of adaptive fitting of the prediction. The regression coefficients of prediction models (a, p, and k) were affected by BCS and dietary organic macronutrient concentrations.