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Prediction of dry matter intake by meat sheep on tropical pastures.

Antonio Leandro Chaves GurgelGelson Dos Santos DifanteJoão Virgínio Emerenciano NetoJuliana Caroline Santos SantanaPatrick Bezerra FernandesGeraldo Tadeu Dos SantosAlexandre Menezes DiasLuís Carlos Vinhas ÍtavoCamila Celeste Brandão Ferreira ÍtavoHenrique Rocha de Medeiros
Published in: Tropical animal health and production (2021)
This study was undertaken to determine whether equations for prediction of dry matter intake (DMI) by meat sheep are valid for animals raised solely on tropical pastures and to propose a new equation to predict the DMI of sheep raised on tropical pastures. The DMI prediction from published equations was evaluated by regressing the predicted and observed values, using the F test, for the identity of the parameters (β0 = 0 and β1 = 1) of the regression of predicted on observed data. If the null hypothesis is not rejected, the tested equation accurately estimates DMI. The proposed equation was evaluated in the same way as the published equations. The animal performance and pasture structure and chemical composition data used originated from an experiment conducted with 32 Santa Inês sheep raised on tropical pastures. In the analysis of model adequacy, the null hypothesis was rejected (P < 0.001) and the equations generated predictions that differ (β0 = 0 and β1 = 1) from the DMI observed under practical feeding conditions for grazing sheep. The proposed equation, DMI (%LW) = 7.16545 (± 0.76522) - 0.21799 (± 0.01812) * LW + 0.00273 (± 0.00034) * LW2-0.00688 (± 0.00299) * GT + 0.000007 (± 0.000002) * GT2 + 0.00271 (± 0.00108) * GHA, where LW is live weight (kg), GT is grazing time (min/day), and GHA is green herbage allowance (kg DM/100 kg LW), should be used to more accurately predict DMI by grazing sheep.
Keyphrases
  • climate change
  • electronic health record
  • weight gain
  • weight loss
  • big data
  • randomized controlled trial
  • metabolic syndrome
  • type diabetes
  • machine learning
  • adipose tissue
  • skeletal muscle
  • data analysis