Qualidade de dados de ingestão de matéria seca na predição do consumo alimentar residual em provas de eficiência alimentar de bovinos de corte

Abstract

A challenge in beef cattle production is to increase the output of animal-derived products while reducing one of the main costs, which is feed. Selecting animals for feed efficiency is essential to achieve this goal, and one of the traits used is residual feed intake (RFI). However, it is necessary for these data to be of high quality; therefore, the objective of this study was to analyze whether invalid dry matter intake (DMI) data affect the prediction of RFI in beef cattle feed efficiency trials. The study was conducted with data from 52 Nellore heifers subjected to a 56-day feed efficiency trial at the Capim Branco Experimental Farm Technology Showcase (UFU), in Uberlândia, MG, using Vytelle Sense® electronic feeders. Six scenarios were simulated with different patterns of invalid DMI data. In scenario A, there were 21 days of invalid data at the beginning of the trial; in scenario B, 21 days at the end; in scenario C, invalid data from the 18th to the 38th day; in scenario D, invalid data every two days; in scenario E, invalid data every three days; and in scenario F, invalid data every seven days. These were compared with the reference scenario (REF), with no invalid data. RFI was calculated using a multiple regression equation, and the change in animal ranking compared to the REF scenario was analyzed through Spearman’s correlation. The scenarios with invalid data distributed alternately throughout the trial (D, E, and F) showed little change in animal classification, while scenarios with invalid data concentrated at the beginning, middle, or end of the trial impacted data quality, increasing ranking changes, reaching 11.45% in scenario B (21 invalid days at the end of the trial). It is concluded that the collection of DMI data must occur in conjunction with measurements of average metabolic body weight (MBW) and average daily gain (ADG), so that invalid days do not affect RFI prediction, ensuring greater reliability in the selection of superior animals for feed efficiency.