Data from six experiments (two with dry cows) were used to predict partitioning of gross energy to CH4 in Holstein cows using selected independent variables, some of which were intercorrelated, and a stepwise backward elimination regression procedure. Methane outputs ranged from 3.1 to 8.3% (mean 5.5) of gross energy intake for 134 dry cow balance trials and from 1.7 to 14.9% (mean 5.2) of gross energy intake for 358 lactating cow energy balance trials. This is equivalent to 176 and 300 g/d or 245 and 419 L/d of CH4 for dry and lactating Holstein cows, respectively. Digestibilites of hemicellulose and neutral detergent solubles were positive predictors, and cellulose digestibility was a negative predictor of CH4 output in dry cows fed all forage diets, but hemicellulose digestibility was not a significant variable for predicting CH4 production by lactating cows fed diets with concentrate and forages. Fiber digestibility generally remained in models to predict CH4 output. Except for one data set, regression equations accounted for 50 to 72% of the variation in percentage of gross energy partitioned to CH4 by Holstein cows. Results confirm that increased concentrate feeding reduces CH4 production. Supplementation of lactation diets with fat generally increases fat digestibility, and this trait was associated with reduced CH4 output. Results enable 1) estimation of CH4 output for calculation of metabolizable energy and 2) computation of the contribution from dairy cows to global warming.

Data from four energy and N balance trials with lactating Holstein cows (n = 329) and one trial with dry cows (n = 60) were used to predict free water intake and water-related traits. Lactating cows were between 36 and 159 DIM and, individually, were allowed ad libitum water and forage (corn silage without or with wilted haycrop silage) plus concentrates; dry cows accessed ad libitum water and single forages (grass, clover, or alfalfa, as hays or as wilted silages, or corn silage) varying in maturity. Intake of DM per day and dietary DM percentage were significant and positively related predictors of free water intake in dry and lactating cows. Daily milk yield (range 16 to 52 kg/d) was related linearly to water consumption (.60 L/kg of milk), and season effect in lactating cows was curvilinear; peak water intake was in late June and nadir in late December. Ration CP percentage (DM basis) affected free water intake only in dry cows; 1 unit of increase resulted in an increase of about 1 kg/d in water intake between 12 and 13% CP. As ration moisture dropped from 70 to 40%, free water intake increased about 7 L/d in dry cows, but this was accompanied by a drop of 15 L/d in total water intake (free plus feed water). Free water intakes were predicted with R2 of .64 and .69 in dry and lactating Holstein cows, respectively. Fecal water and urine outputs also were predicted. We found no significant relationship between DM content of the diet and the resulting ad libitum intake in either dry or lactating cows.

The accuracy of seven DMI prediction equations based only on animal factors was evaluated with 11 independent data files. Mean square prediction error was used to compare equation accuracy, which was considered to be unsatisfactory when the square root of the mean square prediction error was greater than +/-20% of the observed mean DMI. Robust intake equations that have a tolerable level of prediction errors for most data files would be less risky for practical use than models that are highly accurate for some data files but highly inaccurate for others. The number of independent data files for which equation accuracy was unsatisfactory was used to measure lack of robustness. No equation evaluated was able to predict individual cow DMI with a prediction error that was consistently lower than +/-20% of the observed mean intake. The most robust equation in this study predicted intake unsatisfactorily for 3 of the 11 evaluation data files. Unsatisfactory accuracy for this equation was mainly due to mean bias.

Two data files, one from New Hampshire (n = 3308) and one from Georgia (n = 678), containing 4-wk or weekly means, respectively, of ad libitum dry matter intakes (DMI) and related variables were used to predict DMI and yields of 4% fat-corrected milk and milk protein in lactating Holstein cows. The DMI ranged from 5.9 to 30.4 kg/d, and milk yield ranged from 5.8 to 64.3 kg/d. Because of the lack of data from < 14 d in milk, prediction was not possible for the first 2 wk of lactation. Factors considered for inclusion in the DMI prediction model were parity number (1 or > or = 2), treatment with bovine somatotropin (bST), day of year, days in milk, minimum (nighttime) temperature-humidity index, body weight, 4% fat-corrected milk yield, milk protein yield, and corn silage and total silage percentages in forage dry matter. In separate models, the silage predictors were replaced with more specific descriptors of ration dry matter, including percentages of crude protein, fat (ether extract plus soaps of fatty acids), concentrate, acid detergent fiber or neutral detergent fiber, and forage acid detergent fiber or neutral detergent fiber. The square and sometimes natural logarithm of predictors were included in models, which then were subjected to a stepwise backward elimination option of a multiple regression procedure. Several useful equations were developed to predict ad libitum DMI; the best models accounted for about 80% of the variability in DMI, and standard deviations were < 9% of mean DMI. Depression in DMI related to heat stress was higher in pluriparous cows than in primiparous cows (22% vs. 6%). The negative coefficient for effects of bST treatment on DMI suggested that milk yield increased proportionally more in response to bST than did DMI. About 74 to 77% of DMI predictions were within 2 kg/d of observed DMI.

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