4.7 Article

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

Journal

JOURNAL OF DAIRY SCIENCE
Volume 104, Issue 5, Pages 5539-5556

Publisher

ELSEVIER SCIENCE INC
DOI: 10.3168/jds.2020-19581

Keywords

dry matter intake; growth; prediction equations; calves

Funding

  1. Provimi North America, a division of Cargill Animal Nutrition

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This study aimed to predict voluntary daily dry feed intake in Holstein calves using various linear and nonlinear models. The best model identified was an exponential model, with factors such as age, temperature, and neutral detergent fiber concentration being used for prediction. The models developed may provide a better understanding of nutrient supply to young Holstein calves and improve growth performance prediction.
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 x e([(-5.3892 + 0.6376 x MEgap) x EXP(-0.0392 x Age)]) - 0.0013 x Temp + 0.0032 x NDFDM + 0.0026 x Age x MEgap - 0.3646 x 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 (degrees 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 x Age + 0.1808 x MEgap + 0.0013 x Age x MEgap + 0.0001 x Temp + 0.00002 x Age x 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 x e([(-4.6646 + 0.5234 x MEgap) x EXP(-0.0361 x Age)]) + 0.0025 x Age x MEgap (R-2 = 0.92, CCC = 0.96, and MSEP = 0.11 kg) and -0.1344 + 0.0102 x Age + 0.1810 x MEgap + 0.0013 x Age x 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.

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