Models to predict dry feed intake in Holstein calves to 4 months of age

Abstract

Voluntary daily dry feed intake (DFI) in Holstein calves was predicted using 60,761 individual daily observations collected from 1,235 Holstein calves in 30 experiments from 4 research stations in the United States and Europe. Consumption of dry feed (calf starter and hay, kg/d or percent of body weight) was measured from 3 to 114 d of age. Linear models and 2-and 3-parameter nonlinear models were evaluated to predict DFI using age of calf, intake of milk replacer, ambient temperature, percent forage, and neutral detergent fiber concentration in ration dry matter (DM) as independent variables. The initial data set was randomly divided within study location into development (80% of all observations) and validation data sets, and initial screening was conducted using the development data set. Five nonlinear models and 3 linear models (candidate models) were identified and used in further model evaluation. Cross-validation studies (n = 20) with the validation data set were conducted by linear regression of DFI with predicted DFI as independent variable. Candidate models were subsequently evaluated with data from 12 published studies in 2 analyses. The exponential model that best predicted daily DFI in Holstein calves in original and external data sets was DFI (kg/d) = 1.3207 × e [(−5.3892 + 0.6376 × MEgap) × EXP(−0.0392 × Age)] -0.0013 × Temp + 0.0032 × NDFDM + 0.0026 × Age × MEgap -0.3646 × PctForage [coefficient of determination (R 2 ) = 0.92, concordance correlation coefficient (CCC) = 0.96, and mean square error of prediction (MSEP) = 0.10 kg]; where MEgap (Mcal/d) = difference of daily metabolizable energy (ME) requirement and ME intake from milk replacer; Age = age of calf (d) from 3 to 114, Temp = mean daily ambient temperature (°C), NDFDM = ration neutral detergent fiber (% DM); PctForage = percent forage in ration DM. The linear model that best predicted DFI was DFI (kg/d = −0.1349 + 0.0106 × Age + 0.1808 × MEgap + 0.0013 × Age × MEgap + 0.0001 × Temp + 0.00002 × Age × Temp (R 2 = 0.93, CCC = 0.96, and MSEP = 0.10 kg). When Temp and ration characteristics were not included, optimal models were 1.4362 × e [(−4.6646 + 0.5234 × MEgap) × EXP(−0.0361 × Age)] + 0.0025 × Age × MEgap (R 2 = 0.92, CCC = 0.96, and MSEP = 0.11 kg) and −0.1344 + 0.0102 × Age + 0.1810 × MEgap + 0.0013 × Age × MEgap [R 2 = 0.93, CCC = 0.96, and MSEP = 0.10 kg]. Models of daily DFI may improve prediction of nutrient supply to young Holstein calves to approximately 4 mo of age, thereby increasing prediction of growth performance.

Performance and visceral tissue growth and development of Holstein calves fed differing milk replacer allowances and starch concentrations in pelleted starter

“…For the low MR intake, this could have been mitigated using 3 feedings throughout the day, but it is also partly explained by the feeding schedule, which had unequal spacing at 14-and 10-h intervals compared with feedings evenly spaced at 12-h intervals. For the starter intake, in Supplemental Figure S1 (https: / / doi .org/ 10 .6084/ m9 .figshare .19010174 .v1) we used a nonlinear equation ( 22.2 from Table 4 in Quigley et al, 2021) to predict starter DMI to compare with actual DMI for each treatment. From studies using similar MR diets (Klopp et al, 2019;Hu et al, 2020;van Niekerk et al, 2020), we took growth data to calculate ME gap (i.e., ME requirement for a certain ADG − ME intake from MR), which would ultimately help predict the amount of starter DMI required to achieve the desired growth rate.…”