Feed Intake of Growing Dairy Heifers Raised under Tropical Conditions: A Model Evaluation Using Meta-Analysis

Author(s)

Busanello, Marcos ^[1] ; de Sousa, Debora Gomes ^[1] ; Canedo Mendonca, Filipe Araujo ^[1] ; Lourenco Daley, Veridiana ^[2] ; de Almeida, Rodrigo ^[3] ; Machado Bittar, Carla Maris ^[1] ; Duarte Lanna, Dante Pazzanese ^[1]

Affiliation

^[1] Univ Sao Paulo ESALQ USP, Coll Agr Luiz de Queiroz, Dept Anim Sci, BR-13418900 Piracicaba, SP - Brazil

^[2] Virginia Tech, Dept Dairy Sci, Blacksburg, VA 24061 - USA

^[3] Univ Fed Parana, Dept Anim Sci, BR-80035050 Curitiba, Parana - Brazil

• Document type: Journal article
• Source: ANIMALS; v. 11, n. 11 NOV 2021.
• Web of Science Citations: 0

Abstract

Simple Summary: Our study evaluated seven DMI models for dairy heifers grouped by their genotypes (Bos taurus or crossbred Bos taurus x Bos indicus) raised under tropical climatic conditions. The HHJ and OFNLin DMI models performed better for Bos taurus heifers, whereas the STA model performed better for crossbred heifers. NRC, HH, QUI, and OFLin DMI models had significant significant slope bias, mean bias, or both.Several models for predicting dry matter intake (DMI) of replacement dairy heifers have been developed; however, only a few have been evaluated using data from heifers of different breeds raised under tropical conditions. Thus, the objective of this study was to evaluate the DMI equations for dairy heifers managed under tropical conditions. A total of 230 treatment means from 61 studies using dairy heifers (n = 1513 heifers, average body weight = 246 kg) were used. The animals were grouped into two groups based on their genetics: (1) Bos taurus (Holstein, Jersey, Brown Swiss, and Holstein x Jersey) and (2) crossbred (Bos taurus x Bos indicus). Seven previously published DMI equations (HH, HHJ, QUI, STA, 2001 NRC, OFLin, and OFNLin) for heifers were evaluated using mean bias, slope bias, mean squared prediction errors (MSPE) and its decomposition, and other model evaluation statistics. For Bos taurus heifers, our results indicated that OFNLin and HHJ had lower mean bias (0.13 and 0.16 kg/d, respectively) than other models. There was no significant slope or mean bias for HHJ and OFNLin (p > 0.05), indicating agreement between the observed and predicted DMI values. All other models had a significant mean bias (p < 0.05), whereas the QUI model also presented a significant slope bias (p < 0.02). For crossbred heifers, the STA equation was the only one that did not present mean and slope bias significance (p > 0.05). All other DMI models had significant mean bias when evaluated using crossbred data (p < 0.04), and QUI, OFLin, and OFNLin also presented significant slope bias (p < 0.01). Based on our results, predictions from OFNLin and HHJ best represented the observed DMI of Bos taurus heifers (MSPE \& LE; 1.25 kg(2)/d(2), mean bias \& LE; 0.16 kg/d), whereas STA was the best model for crossbred heifers (MSPE = 1.25 kg(2)/d(2), mean bias = 0.09 kg/d). These findings indicate that not all available models are adequate for estimating the DMI of dairy heifers managed under a tropical climate, with HHJ and OFNLin for Bos taurus and STA for crossbreds being the most suitable models for DMI prediction. There is evidence that models from Bos taurus heifers could be used to estimate the DMI of heifers under tropical conditions. For heifer ration formulation is necessary to consider that DMI is influenced by breed, diet, management, and climate. Future work should also include animal genetic and environmental variables for the prediction of DMI in dairy heifers. (AU)

• FAPESP's process: 19/02307-2 - Evaluation and validation of the growth and estimation models for growth to dairy replacement heifers in commercial farms at tropical conditions
• Grantee: Marcos Busanello
• Support Opportunities: Scholarships in Brazil - Doctorate