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The measurement and prediction of pasture intake in extensive grazing systems, typical of northern Australia, remain elusive after 50 years of research. The aim of this paper is to review research conducted over the past 50 years, highlight advances in understanding, discuss remaining challenges and consider future developments with digital technologies. While the fundamental components of voluntary intake are well understood, their measurement is difficult, particularly in extensive grazing systems, which has limited the development of predictive models that adequately address the interplay of factors influencing intake from the bite to the landscape scale. Ongoing research by the authors is used as an example to highlight the potential application of digital technologies to overcome limitations in measurement and prediction. Digital technologies offer the opportunity for monitoring factors that control voluntary pasture intake at scale and under commercial conditions. However, our ability to ground-truth novel indices of intake remains limited without ongoing development of physical methods. This will limit the accuracy and precision of predictive models incorporating digital technologies that can be applied to the extensive grazing conditions of northern Australia. The advent of precision livestock management for extensive cattle production is essential if the industry is to remain viable in the future where production is transparent, ethically sound and environmentally defensible as well as profitable. Feed intake is fundamental to animal performance and efficiency. Yet, for the cattle industry of northern Australia, our understanding of pasture intake is limited. While much is known about the components of feed intake, it remains difficult to integrate this knowledge into a dynamic and responsive estimation of voluntary intake under typical grazing conditions. This paper reviews the state of understanding, highlights gaps in knowledge and discusses the potential impact of digital technologies that will offer new solutions to old challenges. [ABSTRACT FROM AUTHOR]

Beef production drives a significant proportion of Australia's agricultural economy, representing AUD11 billion in agricultural production value annually. The profitability of cattle farms across seasons varies greatly and is particularly influenced by weather and associated uncertainty through pasture growth. Furthermore, producers must be careful in managing stocking rates to avoid overgrazing which has a significant environmental and economic impact. Predictive modelling of pasture and cattle liveweight can help producers to better manage this difficult balancing act. In this paper, we integrate a model for pasture growth and cattle weight gain to formulate predictions of liveweight production volume and pasture biomass. Monte‐Carlo simulation was used to understand the impact of uncertainty in model inputs relating to weather. Through such an approach, a distribution of possible pasture outcomes and beef production is formed which can be inspected to determine, for example expected production volume and risk of overgrazing. The methodology is demonstrated and validated through application to case study data sourced from Australian beef producers. Results demonstrate that it is possible to obtain reasonable predictions of liveweight gain and highlight the importance of considering the associated uncertainty. The accuracy of the proposed models has been examined by calculating statistical parameters MSE, MAE and R2. This approach can provide insight into the distribution of possible production outcomes given the long‐term rainfall outlook. The use of such predictive models and simulations by producers will lead to better‐informed planning of stocking rates, with benefits to productivity and sustainable utilisation of pasture. [ABSTRACT FROM AUTHOR]

Data concerning the practices and policies of collaborating properties for nutritional, breeding and health management of herds were captured by survey of herd owners/managers (n = 78) at the commencement of a large observational study conducted across northern Australia to identify and quantify the effect of major animal-, management group- and property-level risk factors on measures of reproductive performance. The cooperating herds in this study were considered to be broadly representative of north Australian beef breeding enterprises in terms of geography, size and ownership. Using four broad regional categories, this paper presents descriptive summaries of the management practices and nutritional conditions of cooperating herds in what was known as the Cash Cow project. Property sizes were largest within the Northern Downs and Northern Forest, and smallest within the Southern Forest. The expected average annual growth of yearling steers was >50 kg less in the Northern Forest, compared with the other country types, which also appeared to be associated with the identified production system and turnoff animal. Despite the exacerbated nutrition and environmental challenges and likely increased time required for new managers within the Northern Forest to attain an in depth understanding of the cattle and property dynamics, this region had the greatest incidence of management changes. The nutritional information summarised in this study highlights that available phosphorus during the wet season, as indicated by faecal levels in proportion to dietary energy, was likely to limit animal production within the Northern Downs and Northern Forest. During the dry season, pasture digestibilty and protein levels were likely to be approaching maintenance for cows on ~50% of properties in each country type and that responses to rumen degradable protein were also likely on 50% of properties. Despite this finding, low use of dry season supplements was observed for the Northern Downs, which was partially explained by the high incidence of the management systems based on segregating cows on lactation status and pregnancy. In all country types, the ratio of bulls to cows was higher than the 2.5% recommended for extensively managed situations, while limited use of vaccines to control infectious causes of reproductive loss was also observed. The major conclusion of this study is that there was marked variation in the adaption of interventions to specific businesses, indicating considerable opportunity exists for further adaptation in the region. A large epidemiological study known as the Cash Cow project was conducted in commercial beef breeding herds across northern Australia between 2007 and 2011 with the aim of determining and quantifying the effect of management, nutritional and environmental factors on reproductive outcomes. This paper describes results from survey questionnaires examining their nutritional, breeding and herd health management practices and policies completed by herd managers/owners of participating properties at the commencement of the study. [ABSTRACT FROM AUTHOR]

Context: The accuracy of estimated breeding values (EBVs) is an important metric in genetic evaluation systems in Australia. With reduced costs for DNA genotyping due to advances in molecular technology, more and more animals have been genotyped for EBVs. The rapid increase in genotyped animals has grown beyond the capacity of the current genomic best linear unbiased prediction (GBLUP) method. Aims: This study aimed to implement and evaluate a new single-nucleotide polymorphism (SNP)–BLUP model for the computation of prediction error variances (PEVs) to accommodate the increasing number of genotyped animals in beef and sheep single-step genetic evaluations in Australia. Methods: First, the equivalence of PEV estimates obtained from both GBLUP and SNP-BLUP models was demonstrated. Second, the computing resources required by each model were compared. Third, within the SNP-BLUP model, the PEVs obtained from subsets of SNP were evaluated against those from the complete dataset. Fourth, the new model was tested in the Australian Merino sheep and Angus beef cattle datasets. Key results: The PEVs of genotyped animals calculated from the SNP–BLUP model were equivalent to the PEVs derived from the GBLUP model. The SNP–BLUP model used much less time than did the GBLUP model when the number of genotyped animals was larger than the number of SNPs. Within the SNP–BLUP model, the running time could be further reduced using a subset of SNPs makers, with high correlations (>0.97) observed between the PEVs obtained from the complete dataset and subsets. However, it is important to exercise caution when selecting the size of the subsets in the SNP–BLUP model, as reducing the subset size may result in an increase in the bias of the PEVs. Conclusions: The new SNP-BLUP model for PEV calculation for genotyped animals outperforms the current GBLUP model. A new accuracy program has been developed for the Australian genetic evaluation system which uses much less memory and time to compute accuracies. Implications: The new model has been implemented in routine sheep and beef genetic evaluation systems in Australia. This development ensures that the calculation of accuracies is sustainable, with increasing numbers of animals with genotypes. The accuracy of estimated breeding values is routinely provided to breeders as part of genetic evaluations in Australia. A new method to approximate accuracies using genomic information has been developed and is presented in this paper. The new model has been implemented in Australia's routine sheep and beef genetic evaluation systems. This development ensures that the calculation of accuracies is sustainable with increasing numbers of animals with genotypes. [ABSTRACT FROM AUTHOR]

Context: There are multiple reports of high annual cow mortality rates in northern Australia, but no reports clearly indicating the overall rates and the impact of primary risk factors. Aims: The research aimed to determine which measured region-, property-, management group- and animal-level risk factors are associated with missing pregnant females. Methods: Risk factors for the annual rate of pregnant-cow mortality were investigated in an epidemiological study using outcomes for 21 554 cows from 52 beef herds in 2009 and 2010 in four primary country types within the mostly-dry tropical north Australian environment. Modelling of 2001–2011 Australian beef-herd statistics was used to corroborate and further quantify findings. Key results: In the epidemiological study, the overall predicted annual mean incidence of missing pregnant cows, a surrogate for mortality, was 10.9%, including lost tags and unrecorded cow movement that were estimated to constitute up to 9% missing cows. Risk factors associated with higher pregnant-cow mortality were as follows: not having follow-up rainfall more than 30 days after the first wet-season storms (4 percentage point increase); <2 t/ha of available pasture biomass in the early dry season (2–6 percentage point increase); pasture dry-season biomass <2 t/ha interacting with less than moderate mid-dry-season body condition score (3–10 percentage point increase); and, calving between April and September (non-significant trend for a 1–2 percentage point increase). Feed-quality measures did not affect mortality rate. Population modelling of Australian beef herd statistics suggested an average annual cow mortality rate in the Northern Forest region of ~7% compared with 2% in more nutritionally endowed regions. Conclusions: The major risk factor for cow mortality is under-nutrition, related either to generally-low soil fertility, seasonally-dry conditions, or management that exposes animals to poor nutrition. Annual mortality of pregnant cows appears 6–9 percentage points higher in the low-fertility Northern Forest region than elsewhere. Implications: Beef cow mortality is a major business cost in northern Australia. The efficacy of targeted management to achieve high cow performance was demonstrated by losses in a third of studied businesses in the Northern Forest being kept to the same or lower levels as median loss in endowed regions. An epidemiological study was conducted in commercial beef-breeding herds in northern Australia to determine and quantify the major associations between measures of performance and risk factors for herd management, nutritional, environmental and individual cow attributes. This paper presents the findings from the study using 21 554 pregnant cows in 52 herds that determined the major risk factors associated with those that went missing. This was supported by an analysis to calculate mortality rates using contemporary statistical data for the Australian beef herd. [ABSTRACT FROM AUTHOR]

Context: Sound reproductive efficiency is a key determinant for the overall productivity and profitability of a beef breeding business. Failure of a cow to conceive results in either culling or the cost of carrying non-pregnant animals. Aims: This study aimed to determine and quantify the major factors associated with non-pregnancy in commercial beef breeding herds of northern Australia. Methods: A prospective population-based epidemiological study of the likelihood of non-pregnancy in cows after an annual mating in northern Australian beef breeding cows used data from 73 herds from four broad country types and 62 323 animal years; approximately 80 property-, management-group- and cow-level risk factors were considered. A multivariable model building process was employed to scrutinise the resulting dataset, so as to identify what herd management practices, nutritional, environmental, and individual cow factors were associated with non-pregnancy and estimate their magnitude of effect. Key results: Non-pregnancy was disproportionately high in the Northern Forest (32.1%), compared with the Northern Downs, Central Forest and Southern Forest where it was 17.1%, 16.0% and 13.2% respectively. Time of expected calving had the largest impact on occurrence of non-pregnancy. Parity also had a significant influence, with first-lactation cows typically having 5–12% higher non-pregnancy than did mature cows. Non-pregnancy decreased with an increasing body condition score at the branding/weaning muster for lactating cows. The difference in non-pregnancy when comparing availability of wet-season pasture phosphorus content and digestibility of pasture during the dry season was 13.2 and 10.2 percentage points respectively. Conclusions: This study demonstrated the substantial impact environment, herd management practices, nutrition and disease factors can have on the reproductive performance of females. Implications: To optimise the efficiency of females (through reducing the occurrence of non-pregnancy) under commercial conditions in northern Australia, production systems should support beef herds calving early in the production year, being in at least moderate body condition and having access to more digestible pastures that address the nutritional requirements for both protein and phosphorus. This indicates focus for management, especially in the Northern Forest where the likelihood of non-pregnancy was highest. A large epidemiological study of annual pregnancy rate was conducted in commercial beef cattle breeding herds in northern Australia. The effect on non-pregnancy of the major herd management, nutritional and environmental risk factors and individual cow factors was determined and quantified. This paper presents the findings of the study designed to determine the major predictors of cows not achieving pregnancy. [ABSTRACT FROM AUTHOR]

Context: Sound reproductive efficiency is a key determinant for the overall productivity of a beef breeding business. For beef breeding herds to obtain high levels of reproductive productivity, breeding females need to efficiently become pregnant while lactating. Aims: This study aimed to determine and quantify the major factors associated with lactating cows becoming pregnant within 4 months of calving (P4M) in commercial beef breeding herds of northern Australia. Methods: A prospective epidemiological study was conducted using 78 commercial northern Australian beef breeding herds and involved 78 000 cattle that were monitored for 3–4 years. A multivariable model-building process was employed to scrutinise the resulting dataset to identify what herd-management practices, and nutritional, environmental and individual cow factors were major determinants of lactating cows becoming pregnant within 4 months of calving (P4M) and to estimate their magnitudes of effect. Key results: Overall, 41.6% of cows per production year were successful for P4M. Country type was strongly associated with 65.4%, 57.5%, 61.8% and 16.4% P4M for the Southern Forest, Central Forest, Northern Downs, and Northern Forest respectively. Between-year variability ranged between 3.3 and 11.7 percentage points. Cows calving in December–January (61%) had a substantially higher occurrence of P4M than did cows calving between July and September (15%). The difference in P4M when comparing availability of wet-season pasture protein and phosphorus was 12.7 and 20.3 percentage points respectively. Modelling of the impact of group seroprevalence and management group prevalence of recent infection with several infectious diseases was estimated, with a large negative association between group bovine viral diarrhoea seroprevalence and P4M suggested. Conclusions: This study further demonstrated the substantial impact that environment, herd management practices, nutrition and disease factors can have on the reproductive performance of females. Implications: To optimise the performance of females (through increasing the occurrence of cows contributing calves in consecutive years) under commercial conditions in northern Australia, herd managers should focus on maximising the proportion of cows within a herd calving at the desired time of the year, ensuring that any nutritional deficiencies and herd health issues are managed, and that cows are managed such that they are of good body condition score at the time of calving. An observational study was conducted in commercial beef breeding herds in northern Australia to determine and quantify the major associations between herd management, and nutritional, environmental and individual cow factors and measures of reproductive performance. This paper presents the findings of the study designed to determine the major predictors of lactating cows becoming pregnant within 4 months of calving. [ABSTRACT FROM AUTHOR]

Sustainability credentialling is the communication of environmental, social, economic, or animal-welfare-related information about a producer or product. Demand for sustainability credentials has been increasing and the aim of this study was to describe the main drivers for this kind of information in Australian red meat value chains that reach consumers across Australia and internationally, mainly in Asia, the USA, and the Middle East. The mixed methods approach included consultation with red meat processors. Desk-based research explored drivers from outside the value chain identified in the consultation. Little evidence was found that consumers are a driver of sustainability credentialling. The main drivers were in the global financial system, expressed in coordinated climate action policies by financial service providers and emerging government climate-related financial legislation. The inclusion of Scope 3 emissions extends coverage to most value chain participants. Net zero transitioning presents many risks to red meat value chains, potentially involving costly interventions and greater difficulty accessing financial services, with direct implications for production costs and asset values. Urgent action is recommended to achieve the formal recognition and use of climate metrics that differentiate the management strategies that are applicable to short-lived biogenic methane compared to CO2 to achieve the Paris Agreement goals. [ABSTRACT FROM AUTHOR]

Although Australia remains committed to the Paris Agreement and to reducing its greenhouse gas emissions, it was late in joining the 2021 Global Methane Pledge. Finding suitable methane (CH4) mitigation solutions for Australia's livestock industry should be part of this journey. Based on a 2020–2023 systematic literature review and multicriteria decision approach, this study analyses the available strategies for the Australian beef and dairy sector under three scenarios: baseline, where all assessment criteria are equally weighted; climate emergency, with a significant emphasis on CH4 reduction for cattle in pasture and feedlot systems; and conservative, where priority is given to reducing costs. In total, 46 strategies from 27 academic publications were identified and classified as 'Avoid', 'Shift', or 'Improve' with respect to their impact on current CH4 emissions. The findings indicate that 'Avoid' strategies of conversion of agricultural land to wetlands, salt marshes, and tidal forest are most efficient in the climate emergency scenario, while the 'Improve' strategy of including CH4 production in the cattle breeding goals is the best for the conservative and baseline scenarios. A policy mix that encourages a wide range of strategies is required to ensure CH4 emission reductions and make Australia's livestock industry more sustainable. [ABSTRACT FROM AUTHOR]

Background: We investigated breed and gender variations in the compositions of long-chain (≥ C20) omega-3 polyunsaturated fatty acids (LC omega-3 PUFA), fat melting point (FMP) and intramuscular fat (IMF) contents in biopsy samples of the M. longissimus dorsi muscle of grazing beef cattle. The hypothesis that biopsy compositions of health-beneficial LC omega-3 PUFA, FMP and IMF in a pasture-based production system will vary with breed, was tested. Muscle biopsies were taken from 127 yearling pasture-based Angus, Hereford, and Wagyu heifers and young bulls exclusive to the Australian Bowen Genetics Forest Pastoral breeding stud averaging 12 ± 2.43 months of age and under the same management routine. Results: Breed had a significant influence on IMF, FMP, and the compositions of oleic acid, α-linolenic acid (ALA), eicosapentaenoic (EPA), docosahexaenoic (DHA), docosapentaenoic (DPA), and total EPA + DHA + DPA in the M. longissimus dorsi muscle biopsies (P ≤ 0.03). The Wagyu breed had the highest (11.1%) and Hereford the lowest (5.9%) IMF (P = 0.03). The reverse trend was observed in FMP values where the Hereford breed had the highest (55 °C), Angus intermediate (46.5 °C), and Wagyu the lowest (33 °C) FMP. The Wagyu and Angus breeds had similar oleic fatty acid (18:1n-9) content, while the Hereford breed had the lowest (P < 0.01). The highest ALA, DPA, total EPA + DHA, total EPA + DHA + DPA and total ALA + EPA + DHA + DPA contents were detected in the Wagyu breed (P ≤ 0.03). The Hereford had similar EPA and DPA contents to the Angus (P ≥ 0.46). Total EPA + DHA + DPA contents in Wagyu, Angus, and Hereford were 28.8, 21.5, and 22.1 mg/100g tissue (P = 0.01), respectively. Sex was an important source of variation that influenced LC omega-3 PUFA composition, FMP and IMF, where yearling heifers had higher IMF (11.9% vs 5.3%), lower FMP (33°C vs 37°C), and higher LC omega-3 PUFA than bulls. Conclusion: All the results taken together indicate that the Wagyu breed at 28.8 mg/100g tissue, was the closest to meeting the Australia and New Zealand recommended source level threshold of 30 mg/100g tissue of health-beneficial ≥ C20 omega-3 FA content. Since gender was a significant determinant of LC omega-3 PUFA composition, IMF content and FMP, it should be factored into enhancement strategies of healthy meat eating quality traits in grazing cattle. These findings also suggest that the Bowen Genetics Forest Pastoral beef cattle studs are important sources of LC omega-3 PUFA that can be used to cover the deficit in these health claimable fatty acids in Western diets. [ABSTRACT FROM AUTHOR]

One of the major challenges for the Australian feedlot and meat sectors is to have accurate and robust long-term greenhouse gas (GHG) emissions data. Long-term measurements of methane (CH4) emissions (2015–2017) were made at two Australian beef feedlots having different climates, cattle types, and management practices. Emissions were measured using the inverse-dispersion model (IDM) micrometeorological technique, using CH4 concentrations measured at the feedlots with a closed-path Fourier transform infrared spectroscopic technique (CP-FTIR). The emissions data were used to evaluate methods used by the Department of Climate Change, Energy, the Environment and Water to estimate CH4 emissions from feedlots in Australian national inventory calculations. Expressed as a CH4 yield (emissions per unit dry matter intake, DMI), the two feedlots had emissions of 13.1 and 18.9 g CH4 kg−1 DMI. The lower-emitting feedlot had emissions that were 30% lower than the national inventory calculations based on feed intakes, while the second feedlot had emissions that were similar to the inventory calculations. The accurate quantification of emissions from feedlots, as demonstrated as part of this study, is important for validating the national accounting methods and therefore the sector's GHG emissions profile. [ABSTRACT FROM AUTHOR]

Simple Summary: The beef industry plays a crucial role in the livestock supply chain, and data are becoming increasingly vital for informed decision-making. In Australia, significant amounts of data are collected within cattle farms; however, due to a lack of suitable data-driven methods, much of the data go to waste without being effectively utilized. This study developed a statistical model to predict the carcass weight (CW) of grass-fed beef cattle at four different stages before slaughter using farm-level data. Two statistical modelling approaches were used, and results were compared. Four timespans prior to the slaughter, i.e., 1 month, 3 months, 9–10 months, and at weaning, were considered in the predictive modelling. Seven phenotypic features of cattle were used to describe the CW. The results showed that the CW of the cattle was strongly associated with the animal's body weight at each stage before slaughter. The CW can be predicted with an average error of 4% (~12–16 kg) at three months before slaughter. The predictive error increased gradually when moving away from the slaughter date, where the prediction error at weaning was ~8% (~20–25 kg). The outcomes of this study demonstrate the value of using historical data in optimizing production and improving efficiency in the supply chain. Gaining insights into the utilization of farm-level data for decision-making within the beef industry is vital for improving production and profitability. In this study, we present a statistical model to predict the carcass weight (CW) of grass-fed beef cattle at different stages before slaughter using historical cattle data. Models were developed using two approaches: boosted regression trees and multiple linear regression. A sample of 2995 grass-fed beef cattle from 3 major properties in Northern Australia was used in the modeling. Four timespans prior to the slaughter, i.e., 1 month, 3 months, 9–10 months, and at weaning, were considered in the predictive modelling. Seven predictors, i.e., weaning weight, weight gain since weaning to each stage before slaughter, time since weaning to each stage before slaughter, breed, sex, weaning season (wet and dry), and property, were used as the potential predictors of the CW. To assess the predictive performance in each scenario, a test set which was not used to train the models was utilized. The results showed that the CW of the cattle was strongly associated with the animal's body weight at each stage before slaughter. The results showed that the CW can be predicted with a mean absolute percentage error (MAPE) of 4% (~12–16 kg) at three months before slaughter. The predictive error increased gradually when moving away from the slaughter date, e.g., the prediction error at weaning was ~8% (~20–25 kg). The overall predictive performances of the two statistical approaches was approximately similar, and neither of the models substantially outperformed each other. Predicting the CW in advance of slaughter may allow farmers to adequately prepare for forthcoming needs at the farm level, such as changing husbandry practices, control inventory, and estimate price return, thus allowing them to maximize the profitability of the industry. [ABSTRACT FROM AUTHOR]

Simple Summary: Cattle are vulnerable to hot environmental temperatures, and this can lead to severe heat stress, resulting in behaviour and welfare issues. The automated recording of cattle behavioural responses would be helpful in the timely diagnosis of cattle experiencing heat loading. We investigated whether video-digitised image analysis could identify behavioural responses of cattle, especially during heat stress conditions. It was further explored whether a substituted diet (in which some of the grain normally fed as a finisher diet was substituted for forage) would affect the behavioural responses to heat stress, which were measured by digitised movements. An increased digitally recorded movement in animals was observed during high environmental temperatures, which was related to stepping and grooming/scratching activities in standing animals. Under hot temperatures, cattle on the substituted diet displayed less discomfort in terms of a smaller increase in digitally recorded movements than those on the finisher diet. The results suggest that automated video digitisation software could be used as a non-invasive tool for tracking cattle behavioural responses during hot conditions and may have broader applications for behavioural studies. Cattle change their behaviour in response to hot temperatures, including by engaging in stepping that indicates agitation. The automated recording of these responses would be helpful in the timely diagnosis of animals experiencing heat loading. Behavioural responses of beef cattle to hot environmental conditions were studied to investigate whether it was possible to assess behavioural responses by video-digitised image analysis. Open-source automated behavioural quantification software was used to record pixel changes in 13 beef cattle videorecorded in a climate-controlled chamber during exposure to a simulated typical heat event in Queensland, Australia. Increased digitised movement was observed during the heat event, which was related to stepping and grooming/scratching activities in standing animals. The 13 cattle were exposed in two cohorts, in which the first group of cattle (n = 6) was fed a standard finisher diet based on a high percentage of cereal grains, and the second group of cattle (n = 7) received a substituted diet in which 8% of the grains were replaced by lucerne hay. The second group displayed a smaller increase in digitised movements on exposure to heat than the first, suggesting less discomfort under hot conditions. The results suggest that cattle exposed to heat display increased movement that can be detected automatically by video digitisation software, and that replacing some cereal grain with forage in the diet of feedlot cattle may reduce the measured activity responses to the heat. [ABSTRACT FROM AUTHOR]

The northern Australia beef cattle industry operates in harsh environmental conditions which consistently suppress female fertility. To better understand the environmental effect on cattle raised extensively in northern Australia, new environmental descriptors were defined for 54 commercial herds located across the region. Three fertility traits, based on the presence of a corpus luteum at 600 d of age, indicating puberty, (CL Presence, n = 25,176), heifer pregnancy (n = 20,989) and first lactation pregnancy (n = 10,072) were recorded. Temperature, humidity, and rainfall were obtained from publicly available data based on herd location. Being pubertal at 600 d (i.e. CL Presence) increased the likelihood of success at heifer pregnancy and first lactation pregnancy (P < 0.05), underscoring the importance of early puberty in reproductive success. A temperature humidity index (THI) of 65–70 had a significant (P < 0.05) negative effect on first lactation pregnancy rate, heifer pregnancy and puberty at 600 d of age. Area under the curve of daily THI was significant (P < 0.05) and reduced the likelihood of pregnancy at first lactation and puberty at 600 days. Deviation from long-term average rainfall was not significant (P < 0.05) for any trait. Average daily weight gain had a significant and positive relationship (P < 0.05) for heifer and first lactation pregnancy. The results indicate that chronic or cumulative heat load is more determinantal to reproductive performance than acute heat stress. The reason for the lack of a clear relationship between acute heat stress and reproductive performance is unclear but may be partially explained by peak THI and peak nutrition coinciding at the same time. Sufficient evidence was found to justify the use of average daily weight gain and chronic heat load as descriptors to define an environmental gradient. [ABSTRACT FROM AUTHOR]

In this study accumulation has been determined of several per- and polyfluoroalkyl substances (PFAS) from ingested water to steady state serum concentration for adult beef cattle and sheep raised on a hobby farm impacted by PFAS contamination. PFAS concentrations in stock water were stable for more than a year, they were non-measurable in grass but present at very low levels in soil which equated to just 1% of the intake from water. Prior to quantifying PFAS in cattle serum there had been no breeding for 18 months. Although there were high concentrations of several PFAS in the water, only perfluorooctane sulphonate (PFOS) and perfluorohexane sulphonate (PFHxS) were in cattle serum in appreciable amounts; perfluoroheptane sulphonate (PFHpS), perfluorononanoic acid (PFNA) and perfluorodecanoic acid (PFDA) were much lower. Transfer factors (TFs) for cattle were calculated by dividing steady state serum concentration (ng PFAS/mL) by water concentration (µg PFAS/L). Average and upper estimate TF values for cattle were calculated; the former were 140 (total PFOS, i.e. tPFOS), 130 (PFHpS), 65 (PFHxS), 170 (PFNA), and 120 (PFDA). Previous investigation campaigns at the farm provided relative steady state serum PFAS concentrations for sheep and cattle that allowed adjustment of the cattle TFs. The resulting average estimate TFs for ewes (non-pregnant and not lactating) were 20 (tPFOS) and 30 (PFHxS), other PFAS were not measurable in sheep serum. Discussion on using these TFs in human health risk assessments is provided. With certain assumptions/caveats the TFs allow estimations of PFAS steady state serum concentrations for use in preliminary human health risk assessments (HHRAs) when only PFAS in stock water is known. [ABSTRACT FROM AUTHOR]

Pregnancy in cattle is the outcome of the complex process of initiation of cycling, fertilization, maternal recognition of pregnancy and foeto‐placental development. Though much is known about initiation of cycling and associated risk factors, there are virtually no data on pregnancy rate per cycle for naturally mated cattle, especially for extensively managed, tropically adapted genotypes, which this study aimed to determine. Tropical composite (Bos indicus and African Sanga crosses with Bos taurus) and Brahman cattle (n = 2,181) of known pedigree in four‐year groups at four sites were mated annually for 84 days. Body condition, ovarian function, pregnancies, calving and lactation were monitored through six full reproductive cycles using 4–8 weekly ultrasound of the reproductive tract outside the calving period and daily monitoring during calving. From this, dates of commencement of cycling and conception in each year were estimated for each animal, enabling calculation of established pregnancy for consecutive 21‐day periods while cycling and of pregnancies within four months of calving while lactating (P4M). Pregnancy per 21‐day period (cycle) during mating for cycling animals averaged 63%, 71%, 41% and 28% in four consecutive cycles. Pregnant per cycle was 2%–11% higher in tropical composites than in Brahmans. The only other consistently significant risk to becoming pregnant was if cycling commenced later than three weeks before mating commenced. P4M averaged 62% and was lower for cows in sub‐optimal body condition and in first‐parity and later‐calving cows. Pregnant per cycle was moderately heritable (~20%), while heritability was moderate to high (33%) for P4M. Selection for pregnant per cycle could be achieved indirectly by selection for P4M, a trait that is readily measured. [ABSTRACT FROM AUTHOR]

The live weight (LW) and live weight change (LWC) of cattle in extensive beef production is associated with pasture availability and quality. The remote monitoring of pastures and cattle LWC can be achieved with a combination of satellite imagery and walk-over-weighing (WoW) stations. The objective of the present study is to determine the association, if any, between vegetation indices (VIs) (pasture availability) and the LWC of beef cattle in an extensive breeding operation in Northern Australia. The study also tests a suite of VIs along with variables such as rainfall and Julian day to predict the LWC of breeding cows. The VIs were calculated from Sentinel-2 satellite imagery over a 2-year period from a paddock with 378 cattle. Animal LW was measured remotely using a weighing scale at the water point. The relationship between VIs, the LWC, and LW was assessed using linear mixed-effects regression models and random forest modelling. Findings demonstrate that all VIs calculated had a significant positive relationship with the LWC and LW (p < 0.001). Machine learning predictive modelling showed that the LWC of breeding cows could be predicted from VIs, Julian day, and rainfall information, with a Lin's Concordance Correlation Coefficient of 0.62 when using the leave-one-month-out cross-validation. The LW and LWC were greater during the wet season when VIs were higher compared to the dry season (p < 0.001). Results suggest that the remote monitoring of pasture availability, the LWC and LW is possible under extensive grazing conditions. Further, the use of VIs and other readily available data such as rainfall can be used to predict the LWC of a breeding herd in extensive conditions. Such information could be used to increase the productivity and land management in extensive beef production. The integration of these data streams offers great potential to improve the monitoring, management, and productivity of grazing or cropping enterprises. [ABSTRACT FROM AUTHOR]

Simple Summary: The beef industry in Northern Australia is characterized by an extensive grazing system in dry tropical rangelands defined by climate change indices of very low rainfall, a prolonged dry season and feeds of low nutritive value. In response, beef cattle need to be more efficient in converting the available drought-tolerant feeds to muscle, in an attempt to minimize greenhouse gas emissions. This study addressed the problem of reducing methane emissions from tropical beef cattle with the goal of decreasing the impact of climate change and greenhouse gas emissions in Northern Australia. The primary objective was to compare the effect of supplementing tropical beef cattle with both good quality lucerne and poor quality hay with increasing levels of different Desmanthus cultivars on in vivo methane emission. The results showed that in tropical beef cattle on high-quality diets, irrespective of cultivar and emission evaluation method, Desmanthus does not reduce methane emissions. The main objective of this study was to compare the effect of supplementing beef cattle with Desmanthus virgatus cv. JCU2, D. bicornutus cv. JCU4, D. leptophyllus cv. JCU7 and lucerne on in vivo methane (CH4) emissions measured by open-circuit respiration chambers (OC) or the GreenFeed emission monitoring (GEM) system. Experiment 1 employed OC and utilized sixteen yearling Brangus steers fed a basal diet of Rhodes grass (Chloris gayana) hay in four treatments—the three Desmanthus cultivars and lucerne (Medicago sativa) at 30% dry matter intake (DMI). Polyethylene glycol (PEG) was added to the diets to neutralize tannin binding and explore the effect on CH4 emissions. Experiment 2 employed GEM and utilized forty-eight animals allocated to four treatments including a basal diet of Rhodes grass hay plus the three Desmanthus cultivars in equal proportions at 0%, 15%, 30% and 45% DMI. Lucerne was added to equilibrate crude protein content in all treatments. Experiment 1 showed no difference in CH4 emissions between the Desmanthus cultivars, between Desmanthus and lucerne or between Desmanthus and the basal diet. Experiment 2 showed an increase in CH4 emissions in the three levels containing Desmanthus. It is concluded that on high-quality diets, Desmanthus does not reduce CH4 emissions. [ABSTRACT FROM AUTHOR]