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The effects of climate change on humans and other living ecosystems is an area of on-going research. The ruminant livestock sector is considered to be one of the most significant contributors to the existing greenhouse gas (GHG) pool. However the there are opportunities to combat climate change by reducing the emission of GHGs from ruminants. Methane (CH4) and nitrous oxide (N2O) are emitted by ruminants via anaerobic digestion of organic matter in the rumen and manure, and by denitrification and nitrification processes which occur in manure. The quantification of these emissions by experimental methods is difficult and takes considerable time for analysis of the implications of the outputs from empirical studies, and for adaptation and mitigation strategies to be developed. To overcome these problems computer simulation models offer substantial scope for predicting GHG emissions. These models often include all farm activities while accurately predicting the GHG emissions including both direct as well as indirect sources. The models are fast and efficient in predicting emissions and provide valuable information on implementing the appropriate GHG mitigation strategies on farms. Further, these models help in testing the efficacy of various mitigation strategies that are employed to reduce GHG emissions. These models can be used to determine future adaptation and mitigation strategies, to reduce GHG emissions thereby combating livestock induced climate change.

It has been well-established that dark cutting (DC) is a multifactorial issue that is associated with numerous animal and management factors. However, there is limited understanding of the feedlot-based factors that contribute to the influence of DC. The aim of this study was to evaluate the effect of climate, animal, and feedlot factors on the incidence of pH non-compliance in Australian grain-fed cattle. For this study, feedlot and abattoir records from 142,228 individual cattle over a 1-year period were investigated. These data incorporated records from seven feedlots that consigned cattle to three abattoirs. The average incidence of DC in these carcasses was 2.8%. The production factors that were associated with increased risk of DC included feedlot, sex, hormone growth promotants (HGP), cattle health, and days on feed (DOF). Additionally, DC also increased by reduced solar radiation (SR, W/m2), lower wind speeds (WS, m/s), increased ambient temperature (TA, °C), higher rainfall, a higher average temperature–humidity index (THI), and increased duration of time above heat-load-index threshold of 86 (HLI ≥ 86) during the 7 days prior to feedlot departure. This study identified the feedlot factors that increase the risk of DC from a feedlot-management perspective.

The aim of this study was to evaluate the effect of carcass traits, lairage time and weather conditions during lairage and abattoir factors that impact the incidence of dark cutting in 142,228 grain-fed carcasses, as defined by Meat Standards Australia (MSA) guidelines. This study was conducted over a 12-month period analysing data from cattle that were supplied from seven feedlots and processed at three abattoirs. Abattoir data indicated that the average incidence of dark cutting within the study was 2.8%. Increased wind speeds (WSs) and rain during lairage at the abattoir was associated with an increased risk of dark cutting, whereas variation in ambient temperature and/or relative humidity did not influence dark cutting. Heavier carcasses with whiter fat, larger hump heights, more rib fat, higher marble scores and lower ossification had lower incidences of dark cutting. The factors abattoir, time in lairage, time to grading and grader within Abattoir had significant effects on the incidence of dark cutting. The results from this study suggest that reducing the time in lairage and increasing the time between slaughter and grading are the two major ways to reduce dark cutting in MSA carcasses.

Heat stress and cold stress have a negative influence on cattle welfare and productivity. There have been some studies investigating the influence of cold stress on cattle, however the emphasis within this review is the influence of heat stress on cattle. The impact of hot weather on cattle is of increasing importance due to the changing global environment. Heat stress is a worldwide phenomenon that is associated with reduced animal productivity and welfare, particularly during the summer months. Animal responses to their thermal environment are extremely varied, however, it is clear that the thermal environment influences the health, productivity, and welfare of cattle. Whilst knowledge continues to be developed, managing livestock to reduce the negative impact of hot climatic conditions remains somewhat challenging. This review provides an overview of the impact of heat stress on production and reproduction in bovines.

Integrated farm system model (IFSM) is a cost effective and efficient method of estimating greenhouse gas (GHG) emissions from dairy farms and analyzing how management strategies affect these emissions. An IFSM (DairyGHG model) was employed in this study to predict the GHG emission and assess the carbon footprints of four dairy farms in Southeast Queensland, Australia. Four representative commercial farms were selected: Farm 1 (220 cows; Jersey), Farm 2 (460 cows; Holstein Friesian), Farm 3 (850 cows; Holstein Friesian) and Farm 4 (434 cows; Holstein Friesian). The animal emission contribution to carbon footprints for Farm 1, 2, 3 and 4 were 54.2, 60.0, 59.6 and 38.6 % respectively for total output. Likewise the manure emission contribution to carbon footprints for Farm 1, 2, 3 and 4 were 30.6, 29.0, 29.0 and 58.3 % respectively. On the basis of per kg of energy corrected milk the amount of GHG produced for Farm 1, 2, 3 and 4 are 0.39 kg CO2Eq, 0.64 kg CO2Eq, 0.54 kg CO2Eq and 1.35 kg CO2Eq respectively. The method and database developed for these dairy farm GHG assessments may be considered an important step towards a harmonized methodology for the quantification of emissions in dairy farms.

Previous studies have indicated that cattle with more excitable temperaments exhibit an increased stress response. The objective of this study was to investigate the relationship between temperament traits, handling, and stress-induced hyperthermia (SIH) in beef cattle. Rectal temperatures (TREC, °C) of 60 purebred Angus cattle (30 heifers, 30 steers; 235.2 ± 5.11 kg) were recorded at 20 s intervals from 30 min prior to handling until two hours post handling. All cattle were exposed to a standardized handling procedure consisting of (i) being restrained in a weighing box for 30 s; (ii) being held within the crush for 30 s; and then (iii) being restrained in a head bail for 60 s. Cattle temperaments were evaluated via three traits: (1) agitometer score (AG); (2) crush score (CS); and (3) flight speed (FS) during the handling procedure. Agitometer scores and FS measures were used to describe an AG category (AGCAT) and an FS category (FSCAT) that were used to classify animals into three temperament categories: 1, calm; 2, intermediate; and 3, temperamental. Pearson’s correlation coefficients were used to evaluate the associations between (i) AG, CS, FS, and TREC 30 min prior to entry into the weighing box (T-30) and then at 1 min intervals between time of entry into the weighing box (T0) until 10 min post-weighing (T10); and (ii) the relationship between AG, CS, and FS. The relationship between TREC and temperament traits over the 2.5 h were modeled by using a first-order autoregressive repeated measures model. Flight speed had strong to moderate associations with TREC at T-30 (r ≥ 0.37; p ≤ 0.006) and between T0 and T10 (r ≥ 0.36; p ≤ 0.01). There were moderate associations amongst TREC between T0 and T10 and CS (r ≥ 0.31; p ≤ 0.01). A weak relationship existed with CS (r = 0.16; p = 0.16). There were no associations between AG and TREC at T-30 (r ≥ −0.15; p = 0.84) or between T0 and T10 (r ≤ 0.04; p ≥ 0.4). Rectal temperature, irrespective of sex and temperament traits, was influenced by time (p < 0.0001), and maximum TREC (39.3 ± 0.04 °C) occurred between 4 and 5.7 min after entry into the weighing box. In addition, CS (p = 0.007) influenced TREC in these cattle. There were also time × temperament trait × sex interactions with the CS (p = 0.0003) and FSCAT (p = 0.043) categories; however, time × temperament trait interactions were not statistically significant. Results from this study suggest that cattle with excitable temperaments, as evaluated by FS and CS, have a greater increase in TREC. In addition, these results suggest that a relationship exists between basal TREC and FS and CS. Together, these results highlight that temperament, as assessed by FS and CS, influences both basal TREC and the peak temperature recorded following handling but does not influence the magnitude of change in TREC post handling.

This study evaluated the relationship between rectal temperature (TREC, °C) and vaginal temperature (TVAG, °C) in grazing Bos taurus heifers, to develop an understanding of the reliability of these measures as estimates of core body temperature. Nineteen Angus heifers (BW = 232.2 ± 6.91 kg) were implanted with intra-rectal and intra-vaginal data loggers. Rectal temperature and TVAG were simultaneously recorded at 20 s intervals over 18.5 h. Heifers were housed as a singular cohort on grazing pastures for the duration of the study. A strong linear relationship (R2 = 0.72, p < 0.0001) between the measurement sites was identified. The mean difference between TREC and TVAG was small, in which TVAG was on average 0.22 ± 0.01 °C lower than TREC. Individual twenty second TREC and TVAG data were used to determine the pooled mean TREC and TVAG and then to highlight the within measure variation over time. The coefficient of variation was, on average, lower (p < 0.001) for TVAG (0.38%) than TREC (0.44%), indicating that TVAG exhibited less variation. Overall, the results from the current study suggest that a strong relationship exists between TREC and TVAG, and that TVAG may be a more reliable estimate of core body temperature than TREC in grazing Bos taurus heifers.