Perception of consultants, feedlot owners, and packers regarding the optimal economic slaughter endpoint in feedlots: a national survey in Brazil (Part I)

Little information exists regarding the optimal economic slaughter endpoint (OSE) for feedlot-finished cattle in Brazil. This study investigated the perceptions of Brazilian feeders regarding the optimal time for slaughter. A total of 52 interviews were conducted involving nutritionist-consultants (n = 23), feedlot owners (n = 21), and packer-owned feedlots (n = 8). The results showed that 65% of the interviewees used weight and fat cover, both estimated visually, to determine the moment for slaughter. Identifying the ideal time for slaughter was considered a challenge for respondents, and 85% of them recognized that their current slaughter endpoint identification method needed improvements. Regarding decision support systems, 58% of respondents reported they would purchase a computer program to help identify OSE, and 73% would be interested in incorporating a prototype of such a system into their feedlots. Carcass dressing (38%) and price (25%) were the main factors driving the feeder’s choice of meatpacker, followed by carcass premiums (10%). Meat quality was found to be an irrelevant criterion for Brazilian meatpackers in awarding both premiums (5%) and deductions (3%). Slaughter endpoint is determined subjectively by the Brazilian feeders, based on a visual evaluation of both weight and fatness.

Perception of consultants, feedlot owners, and packers regarding management and marketing decisions on feedlots: a national survey in Brazil (Part II)

Research interviews with agribusiness professionals are carried out in several countries for updating and developing technologies. This study aimed to investigate the perception of Brazilian feeders regarding management and marketing tools used in the feedlot industry. Interviews were conducted with groups: nutritionist-consultants (n = 23), feedlot owners (n = 21), and packer-owned feedlots (n = 8). Roughly 58% of the interviewees worked with two cycles of animals per year. Roughly 80% of animals on feedlots were males, with 73% of the respondents having fed only intact males and 75% of the animals were Nellore breed. Among the criteria used for pen formation, weight was the most common (75%). The use of computational tools for feedlot management (71%) and diet formulation (69%) were found to be common, although interviewees did not use any software to characterize feeder animals. In 44% of the respondent feedlots, animals that reached the desired weight and degree of finish were removed for slaughter, whereas the unfinished animals remained in the same pen. We found that a need, therefore, exists to develop efficient strategies for forming homogeneous pens upon animal entry onto feedlots, and maintaining homogenous pens upon the exit of animals for slaughter.

A methodological approach to estimate the lactation curve and net energy and protein requirements of beef cows using nonlinear mixed-effects modeling

The objective of this study was to evaluate methods to predict the secretion of milk and net energy and protein requirements of beef cows (Bos indicus and B. taurus) after approximately 1 mo postpartum using nonlinear mixed-effect modeling (NLME). Twenty Caracu × Nellore (CN) and 10 Nellore (NL) cows were inseminated to Red Angus bulls, and 10 Angus × Nellore (AN) were bred to Canchim bulls. Cows were evaluated from just after calving (25 ± 11 d) to weaning (220 d). Milk yield was estimated by weighing calves before and after suckling (WSW) and by machine milking (MM) methods at 25, 52, 80, 109, 136, 164, 193, and 220 ± 11 d of lactation. Brody and simple linear equations were consecutively fitted to the data and compared using information criteria. For the Brody equation, a NLME model was used to estimate all lactation profiles incorporating different sources of variation (calf sex and breed of cow, cow as a nested random effect, and within-cow auto-correlation). The CV for the MM method (29%) was less than WSW (45%). Consequently, the WSW method was responsible for reducing the variance about 1.5 times among individuals, which minimized the ability to detect differences among cows. As a result, only milk yield MM data were used in the NLME models. The Brody equation provided the best fit to this dataset, and inclusion of a continuous autoregressive process improved fit (P < 0.01). Milk, energy and protein yield at the beginning of lactation were affected by cow genotype and calf sex (P < 0.001). The exponential decay of the lactation curves was affected only by genotype (P < 0.001). Angus × Nellore cows produced 15 and 48% more milk than CN and NL during the trial, respectively (P < 0.05). Caracu × Nellore cows produced 29% more milk than NL (P < 0.05). The net energy and net protein requirements for milk yield followed a similar ranking. Male calves stimulated their dams to produce 11.7, 11.4, and 11.9% more milk, energy and protein, respectively (P < 0.05). The MM method is better than the WSW technique to detect genetic or environmental differences in milk yield among beef cows. The data obtained by the MM method and analyzed by NLME models allows the inclusion of fixed effects, random effects and an auto-regressive process in lactation equations to describe lactation curves and net energy and protein requirements. The NLME is a powerful tool to describe differences in the secretion of milk due to heterosis and cell mammary external stimulus in beef cows.