Search

Lean meat yield (LMY) is a key driver of profitability in the beef industry, and it is associated with muscling and feed efficiency (Pethick et al., 2021). No research has studied differences in LMY between British, Continental, and Tropical beef breeds fed for increasing days on feed. The objective of the present study was to compare LMY of Angus, Brahman and Charolais steers with increasing days on feed (DOF). The hypothesis was that Charolais have the greatest LMY throughout the feeding period due to being a later maturing, high muscling breed compared with Angus and Brahman. Angus (n = 30), Brahman (n = 30), and Charolais (n = 29) 12-18 mo-old steers were inducted with a body weight (BW) of 361 ± 5.3 kg, 355 ± 5.3 kg and 317 ± 5.3 kg, respectively. Six animals of each breed were randomly selected for slaughter at 50-d intervals until 200 DOF. Steers were allowed ad libitum access to water and feed (78% rolled barley, 13.76% CP, 12.15 ME MJ/kg DM). Body weight, hot carcass weight (HCW), and LMY were measured at slaughter. All components of the animal were collected, and carcass muscle, fat and bones physically dissected with knives and weighed separately. The LMY as % empty BW (EBW) was calculated as the weight of lean meat separated from the carcass divided by EBW. The LMY as % of HCW was calculated as the weight of lean meat separated from the carcass divided by HCW. Data was analyzed with a model containing the fixed effect of breed, DOF at slaughter, and their interaction. Breed, DOF and their interaction affected LMY expressed as both ratio to EBW and HCW (P < 0.05). Charolais steers had the greatest LMY (% HCW) at 50, 100, and 150 DOF, but similar to Brahman at 0 and 200 DOF (P < 0.05; Figure 1a). Angus steers showed the lowest LMY (% HCW) throughout all DOF (P < 0.05) except at 50 DOF being similar to Brahman (P > 0.05). Furthermore, Charolais had the greatest LMY (% EBW) from 50 to 200 DOF (P < 0.05) but it was similar to Brahman at 0 DOF (Figure 1b; P > 0.05). Angus had the least LMY (% EBW) throughout (P < 0.05) but was not different to Brahman at 50 DOF. Brahman had intermediate LMY (% EBW and % HCW) between Charolais and Angus. Differences between beef breeds suggest that LMY should be considered as another factor to establish an accurate carcass value. [ABSTRACT FROM AUTHOR]

The carbon footprint of beef cattle production may need to consider both the fluxes of greenhouse gases (GHG) of pasture ecosystems and cattle enteric emissions because these are the largest contributors to the carbon balance. The objective of the present study was to measure the fluxes of greenhouse gases from pastures and enteric methane (CH4) emissions from cattle throughout long periods of time under commercial conditions. The fluxes of CH4, carbon dioxide (CO2), and nitrous oxide (N2O) were measured throughout a period of 3 yr in multiple pasture types ranging from native to sown, and from temperate to summer pastures in New South Wales, Australia. A set of 8 dynamic chambers that automatically close for 10 min every 1.5 h were used for this purpose. The chambers measured the change in the concentration of GHG to allow for the estimation of emissions (positive flux) or sinks (negative flux). All data was then summarized to estimate daily fluxes and the global warming potential (CO2e) was calculated multiplying CH4 by 28 and N2O by 265. The final dataset contained 2,709 d of measurements across the 8 chambers. The GreenFeed system was used to measure CH4 production from cattle under varying conditions fed various diets throughout the same period. Cattle categories included weaners, heifers and steers, bulls and cows under both grazing or pen conditions. Cattle were fed a variety of diets ranging from low quality forages to high quality forages, grain supplementation, and grain-based diets. Data were averaged across many days for each animal and the final dataset contained 1,014 measurements. The CO2 flux from pastures ranged from -855 (uptake) to +339 kg CO2 ha-1 d-1 with a mean of -10.4 ± 2.19 kg CO2 ha-1 d-1. The minimum, mean and maximum CH4 fluxes were -192 (uptake), 0.015 ± 0.488, 434 g CH4 hּa-1 d-1, respectively, whereas NO2 values -146 (uptake), 17.1 ± 1.23, 1,293 g N2O ha-1 d-1, respectively. These fluxes resulted in a GWP ranging from -855 (uptake), -5.83 ± 2.222, 445 kg CO2e hּa-1 d-1suggesting that pastures were on average a net sink of GHG throughout the present study. The CH4 production from cattle ranged from 43.6 to 404.6, with an average CH4 production of 192 ± 90.3 g CH4 animal-1 d-1, which is equivalent to 5.37 kg CO2eq animal-1 d-1. These results suggest that a hectare of livestock pastures offsets more than the CH4 produced by the average beef cattle in the present study. The fluxes of GHG from vegetation may need to be considered when estimating the contribution of livestock production to global warming. [ABSTRACT FROM AUTHOR]

New technologies such as automatic in-pen weighing of cattle offer great opportunities to monitor, improve and control livestock production. The large amount of raw BW data recorded must be processed to estimate BW minimizing the impact of erroneous records and the large variability due to various factors such as fill of the gastrointestinal tract. The objective of the present study was to compare two data processing methods of remotely collected body weight (BW) in feedlot steers against traditional weighing measured in central handling facilities. The BW data were collected from a serial slaughter trial with 26 steers of each Angus, Brahman, and Charolais slaughtered at 50, 100, 150, and 200 DOF (initial BW = 345 ± 29.9 kg). Body weight was measured every 50 d in the central handling facilities (stationary BW in a weighing box) and then using an in-pen weighing system setup in front of the water trough to record animal BW linked to RFID while drinking water. The remotely collected BW data were processed with two smoothing: 1) penalized b-splines (BWpbs) and 2) natural cubic splines (BWncs). After fitting the data from each animal to each smoothing algorithm, datapoints greater or less than the estimated BW × 1.5 residual error were deleted. The BW estimated from remotely collected data with each method was regressed against traditional BW. The former algorithm resulted in a linear regression of the form BWpbs = -13.1 (± 1.46) + 1.04 (± 0.003) BW (R² = 0.996; RMSW = 6.46 kg). The natural cubic spline algorithm resulted in a linear regression of the form BWncs = -11.0 (± 3.02) + 1.04 (± 0.007) BW (R² = 0.985; RMSW = 12.88 kg). Both algorithms had acceptable accuracy and precision although the penalized b-spline algorithm was more sensitive because it better detected sudden changes in BW. The intercept showed that both algorithms estimated heavier BW compared with traditional BW, likely because of BW loss due to defecation and urination during yarding. In conclusion, penalized b-splines smoothing algorithm is recommended over natural cubic splines to process remotely collected BW because of decreased error and greater precision. [ABSTRACT FROM AUTHOR]

Estimation of individual dry matter intake (DMI) is required to optimize feed efficiency, carcass endpoint and profitability of feedlot cattle. However, measuring individual DMI is not practical or economically viable in a commercial setting. It is suggested that feeding behavior measured by remote monitoring technologies could be used to predict DMI of feedlot steers in real-time. However, inherent differences between breeds could influence DMI and feeding behavior and therefore these may need to be considered to predict DMI from feeding behavior. The objective of the present study was to assess differences between breeds in DMI and feeding behavior using data collected from radio-frequency identification (RFID) tags linked to electronic feeders and smart ear tags with accelerometers. Twenty-four steers from each breed [Angus, Brahman and Charolais; initial body weight (BW) = 335 ± 25.0 kg/steer) were fed using 10 electronic feeders in a serial slaughter trial for up to 200 d with 50 d slaughter intervals. Data were averaged per animal and ANOVA was performed with fixed effects of breed and length of the feeding period. There was no interaction between breed and length of feeding period (P > 0.05). DMI, feeding time and visit length measured by RFID, were less in Brahman compared with Angus and Charolais steers (P < 0.05). Eating rate (g/min) was not affected by breeds (P > 0.05); however, Brahmans ate faster compared with the other two breeds when expressed as gּ min-1ּ kg BW-1 (P ≤ 0.001). Smart tags showed that daily eating and ruminating times were longest in Charolais and shortest in Brahman (P < 0.05). In contrast, time spent not active was longest in Brahman and shortest in Charolais (P ≤ 0.001). Daily ‘active’ time was longer and ‘highly active’ shorter in Angus and Brahman compared with Charolais (P < 0.001). Differences in feeding behavior suggest that breed should be considered to predict DMI from RFID and smart ear tag technologies. [ABSTRACT FROM AUTHOR]

Understanding accretion rate of intramuscular and subcutaneous fat in feedlot steers is crucial to ensure that carcasses are meeting market specifications and therefore optimizing profitability. Intramuscular fat (marbling) and subcutaneous fat (P8 and rib) are key areas of assessment on the live animals and carcasses determining quality. The objective of the present study was to determine fat accretion rate in three popular breeds of cattle with contrasting accretion rate throughout the feedlotting period. We hypothesized that Angus would have the fastest fat accretion rate being early maturing. Thirty of each Angus, Brahman and Charolais steers were entered into a feedlot (344 ± 5.3 kg initial BW) and six of each breed randomly selected for slaughter at 50-day intervals for 200 days on feed (DOF). Ultrasound scanning and BW were measured at each slaughter point, measuring fat thickness at the rib and P8 site, intramuscular fat (IMF), kidney fat and the eye muscle area (EMA). Body weight, intramuscular fat (%), P8 and rib fat (mm) all had significant interactions between DOF and breed (P < 0.001). At the start of the feeding period, Charolais were lighter than Angus and Brahman (P > 0.001). However, Charolais (663.7 ± 9.31 kg) and Angus were the heavier (680.4 ± 8.68 kg) than Brahman (539.4 ± 8.68 kg) at 200 DOF (P < 0.05). The interaction for P8 and rib fat was due to all breeds having similar fat thickness at 0 DOF (P > 0.05) but Angus had greatest (21.38 ± 0.882 mm, 17.12 ± 0.549 mm), Brahman intermediate (16.73 ± 0.883 mm and 10.38 ± 0.550 mm) and Charolais thinnest (9.97 ± 0.966 mm, 7.23 ± 0.600 mm) P8 and rib fat, respectively, at 200 DOF (P < 0.05). Similarly, IMF was similar between breeds at 0 DOF (P > 0.05), but Angus had greater IMF (7.76 ± 0.287 %; P < 0.001) compared with Brahman (5.08 ± 0.287 %) and Charolais (5.18 ± 0.314 %), which were not different amongst them (P > 0.10). Results of the present study demonstrated the contrasting fat metabolisms of each genotype with Angus steers showing the fastest fat accretion rate for all fat depots, whereas Brahman steers showed intermediate and Charolais slowest subcutaneous fat accretion rate. However, both Brahman and Charolais steers showed similarly low IMF and kidney fat accretion rates. Fat accretion rate of each depot and whole body should be considered in mathematical simulation models of animal growth. [ABSTRACT FROM AUTHOR]

The profitability of beef feedlot operations depends on accurately predicting the energy and nutrient requirements of the animal to optimize animal growth and carcass quality to meet market specifications. The composition of the gain (i.e., fat and protein) dictates the growth of the animal, and it is highly correlated with the body composition of the mature animal, assuming that the composition of body gain is constant for animals at the same maturity degree. Once the mature weight for a given body composition (i.e., fat) is known, the maturity degree can be estimated, and the equivalent body weight (EqBW) can be used to calculate energy requirements for growth. Several standard feeding systems and nutrition models use the adjusted final body weight (AFBW) at a known fat composition to estimate EqBW. The AFBW is the body weight (BW) at, usually, 28% empty body fat (EBF). Thus, AFBW can be estimated if a given empty BW (EBW) and composition are known, and an EBW-to-EBF factor is used to calculate AFBW from the current BW. Several nutrition models, including the Cattle Value Discovery System, have adopted the 14.26 kg of EBW for each % of EBF. Therefore, this study aimed to determine the amount of body mass deposited per change in body fat content of different breeds commonly used in Australia. We randomly allocated 30 Angus, 30 Brahman, and 29 Charolais into six slaughter groups (6 animals per breed per slaughter group) fed for up to 200 days. Internal organs and carcasses were dissected into physically separable fat, lean, and bones. When we regressed EBW on EBF, the overall regression yielded a slope of 11.2 ± 0.69 kg/%EBF [n = 89, r² = 0.75, and root of the mean square error (RMSE) = 55.7 kg], likely not different from the 14.26 kg/% EBF. However, slopes were different among breeds (P < 0.001), i.e., there was an interaction between breeds and EBF when the breed was added to the ordinary least-square mean regression as a classificatory variable. The slopes were 16.5 ± 0.84 kg/% for Charolais (n = 29, r² = 0.933, RMSE = 33.2 kg), 13.2 ± 0.73 kg/% for Angus (n = 30, r² = 0.921, RMSE = 34.4 kg), and 10.1 ± 1.06 kg/% for Brahman (n = 30, r² = 0.765, RMSE = 38.3 kg). When we regressed the amount of EBF on EBW, we obtained 0.40, 0.58, and 0.52 kg EBF/kg EBW for Charolais, Angus and Brahman, respectively. This confirms that Charolais deposited less EBF per unit of gain compared with Angus and Brahman. Given the similarity between the 14.26 kg/% to the overall value of 11.2 kg/%, we recommend using the 14.26 EBW-to-EBF factor to estimate AFBW when the genetic group is unknown. [ABSTRACT FROM AUTHOR]