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A limited understanding of the potential to reduce emissions and a lack of climate incentives hinder progress toward mitigating greenhouse gas (GHG) emissions from beef production. This study explored the GHG mitigation potential in South America by evaluating nearly 30 beef cattle production systems across five key beef-producing countries (Argentina, Brazil, Colombia, Paraguay, and Uruguay). The study outlined a low-emission beef roadmap for this major beef producing region. Data from this study indicate that the current business-as-usual trajectory of improvements in South America’s beef cattle production is insufficient to reduce GHG emissions at a pace that aligns with the urgency of climate crisis. Results from this study show that scaling up existing practices -such as improved forages, rotational grazing, and feed supplementation- to match the performance of the region’s lowest-emission systems at 20 th percentile could deliver significant results. Emission intensities could decrease by 33–50% compared to the projected 2050 regional average (35 tons carbon dioxide equivalent/ton of carcass weight). This would flatten the emissions curve, cutting total emissions by 20–40% while simultaneously increasing beef production by 43%. With annual methane (CH 4 ) emission reductions by 1.5%, the warming effect could decrease by 70–90%, offering a transformative pathway to lower GHG emissions from beef production. This emissions trajectory offers a feasible path toward net-zero warming from beef production, primarily through sustained reductions in CH 4 emissions intensity and absolute emissions as systems become more production efficient. These findings highlight the need and an opportunity for a drastic reduction in emissions from beef cattle production and can foster collaboration among conservation, industry, and finance stakeholders towards a common climate-oriented beef production agenda.

Perception of freshwater use varies between nations and has led to concerns of how to evaluate water use for sustainable food production. The water footprint of beef cattle (WFB) is an important metric to determine current levels of freshwater use and to set sustainability goals. However, current WFB publications provide broad WF values with inconsistent units preventing direct comparison of WFB models. The water footprint assessment (WFA) methodologies use static physio-enviro-managerial equations, rather than dynamic, which limits their ability to estimate cattle water use. This study aimed to advance current WFA methods for WFB estimation by formulating the WFA into a system dynamics methodology to adequately characterize the major phases of the beef cattle industry and provide a tool to identify high-leverage solutions for complex water use systems. Texas is one of the largest cattle producing areas in the United States, a significant water user. This geolocation is an ideal template for WFB estimation in other regions due to its diverse geography, management-cultures, climate and natural resources. The Texas Beef Water Footprint model comprised seven submodels (cattle population, growth, nutrition, forage, WFB, supply chain and regional water use; 1432 state variables). Calibration of our model replicated initial WFB values from an independent study by Chapagain and Hoekstra in 2003 (CH2003). This CH2003 v. Texas production scenarios evaluated model parameters and assumptions and estimated a 41–66% WFB variability. The current model provides an insightful tool to improve complex, unsustainable and inefficient water use systems.

Maternal overnutrition and targeted supplements during pregnancy strongly affect fetal development in beef cattle, influencing gene expression, tissue development, and productivity after birth. As modern feeding practices often result in cows receiving energy and protein above requirements, understanding the balance between adequate nutrition and overconditioning is critical for sustainable beef production. This review synthesizes findings from recent studies on maternal overnutrition and supplementation, focusing on macronutrients (energy, protein, methionine) and key micronutrients (e.g., selenium, zinc). It evaluates the timing and impact of supplementation during different gestational stages, with emphasis on fetal muscle and adipose tissue development, immune function, and metabolic programming. The role of epigenetic mechanisms, such as DNA methylation and non-coding RNAs, is also discussed in relation to maternal dietary inputs. Mid-gestation supplementation promotes muscle growth by activating muscle-specific genes, whereas late-gestation diets enhance marbling and carcass traits. However, maternal overnutrition may impair mitochondrial efficiency, encourage fat deposition over muscle, and promote collagen synthesis, reducing meat tenderness. Recent evidence highlights sex-specific fetal programming differences, the significant impact of maternal diets on offspring gut microbiomes, and breed-specific nutritional responses, and multi-OMICs integration reveals metabolic reprogramming mechanisms. Targeted trace mineral and methionine supplementation enhance antioxidant capacity, immune function, and reproductive performance. Precision feeding strategies aligned with gestational requirements improve feed efficiency and minimize overfeeding risks. Early interventions, including protein and vitamin supplementation, optimize placental function and fetal development, supporting stronger postnatal growth, immunity, and fertility. Balancing nutritional adequacy without excessive feeding supports animal welfare, profitability, and sustainability in beef cattle systems.

The hydrology of the Brazilian Pantanal, part of the largest humid tropical area on the planet, follows the rhythm of seasonal floods. The traditional movement of cattle herds in the southern Pantanal is defined by these seasonal flooding patterns, which determine the availability and quality of native-grass pastures throughout the year. Extreme hydrological events, such as prolonged droughts and intense floods, can impact the management of cattle in this region, preventing access to, circulation within, and occupation of some grazing areas. This study aims to analyze the spatial and temporal variability of precipitation, the river levels in this region from 1974 to 2012, and assessed the effects on the evolution of local beef cattle stocks. We integrated the spatiotemporal variability of precipitation and river levels for six gaging stations and standardized these variables using standard deviation and linear trends at annual and seasonal scales. Additionally, we integrated the results with an analysis of the livestock production within the region’s municipalities. Regional precipitation was highly variable, including an almost decadal oscillation, with positive trends in parts of the 1970s and 1980s and a negative trend since the 1990s. River levels in the northern portion of the basin and in the Paraguay River corresponded to those dynamics while presenting marked anomalies. Simultaneously, river levels in the eastern Pantanal changed from negative to positive anomalies, which were more intense in wet months. Both the eastern and western patterns reflected the occurrence of extreme El Niño–Southern Oscillation events and other large-scale climatic patterns. In intra-annual terms, the variability of the river levels during the flooded months at four of the six gaging stations studied suggests an early onset or delay of the flood season, as well as positive anomalies in the ebbing months and in the southeast. Given the lags in flow between different rivers in the region, this behavior draws attention to dam construction and intensification of localized flooding in the southern areas, which may impact everyday life and cattle management. For example, from 2009 to 2012, two severe droughts and an extreme flood significantly impacted livestock numbers in the region. Overall, herd numbers decreased (increased) in humid (dry) periods, including a reduction of over 1 million head during the flood of 1973–1974. The differential level patterns at annual, wet season, and dry season between the eastern and western sides of the Pantanal modulate the livestock activities, where the strong negative anomalies of the levels along the eastern side seem to force the diminution of beef cattle stock at local regions in different intensities in annual scale. This reinforces the effects of climate variability and extreme hydrological events on the management and dynamics of the beef cattle industry and market in Brazil.

The use of cassava as a feed resource is the main focus of strategies that aim to increase the efficiency of beef cattle. In this study, the ratio of fresh cassava tops to roots (CTR) was 1:1, 1:2, 1:3, and 1:4 w/w, in addition to the incorporation of yeast and lactic acid bacteria (YL). CTRS was inoculated in vitro with rumen fluid and a substrate mixture to evaluate the gas production and fermentation quality. In vivo, crossbred beef cattle were randomly allocated to three dietary treatments: a control group and two groups that received total mixed ration (TMR) silage with either 35% or 70% of the concentrate replaced with CTRS. This study found that the levels of crude protein and condensed tannins (CTs) in CTRS were relatively increased by the addition of cassava tops (p < 0.05), while the fermentation pH decreased as the proportion of cassava roots increased. CTRS significantly enhanced in vitro dry matter digestibility, cumulative gas at 96 h, gas production kinetics, and MBP (p < 0.05), especially in the 1:2 group. In the in vivo experiment, CTRS increased DM intake, CP, and propionic acid concentration compared to the control group and showed great potential for improving NDF digestibility. Moreover, when the concentrate in the TMR silage was substituted with CTRS and offered to crossbred beef cattle, it increased ruminal NH3-N and blood glucose levels (p < 0.05). The TMR silage substituted with 70% CTRS reduced the feed cost by 50.54% (p < 0.05). Our study findings suggest that optimizing the inclusion of CTRS in TMR silage could be a viable strategy for beef producers aiming to enhance cattle performance and profitability.

Abstract Growth data of 77,372 Nelore steers were used to estimate the selection effect on energy requirements considering two beef production systems: cow-calf and slaughter cycles. All the animals had measures from 120 days to 7 years old. The parameters necessary to evaluate the selection effect on energy requirements were obtained by random regression analysis using Legendre polynomials. The models included additive direct and maternal effects, and animal and maternal permanent environmental effects as random terms. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of animal age (cubic regression) were considered random covariables. The coefficients from the model M3353_5 were used to calculate the genetic gains necessary to predict the increase in phenotypes. The selection was simulated for body weight (BW) and weight gain (WG) at different ages and energy requirements were calculated using NRC equations. The cost of feed was calculated for a cow-calf and slaughter cycle of production considering a system of Brachiaria decumbens pasture without supplementation. In slaughter system, the selection for weight of 365 days of age is the best option. In cow-calf systems, the selection W120 is the best choice.

Estimates of global population growth are often cited as a significant challenge for global food production. It is estimated that by 2050 there will be approximately two- billion additional people on earth, with the greatest proportion of that growth occurring in central Africa. To meet recommended future protein needs (60 g/d), approximately 120 million kg of protein must be produced daily. The production of ruminant meat (particularly beef cattle) offers the potential to aid in reaching increased global protein needs. However, advancements in beef cattle production are necessary to secure the industry’s future sustainability. This article draws attention to a subset of sustainable beef cattle production challenges, including the role of ruminant livestock in meeting global human protein needs, the environmental relationships of advanced beef cattle production, and big data and machine learning in beef cattle production. Considering the significant quantities of resources necessary to produce this form of protein, such advancements are not just a moral imperative but critical to developing advanced beef cattle production practices and predictive models that will reduce costs and liabilities and advance industry sustainability.

This study was conducted within the context of providing an improved understanding of New Mexico’s food, energy, water systems (FEWS) and their behavior under variable climate and socioeconomic conditions. The goal of this paper was to characterize the relationships between production and prices of some forage crops (hay, grain sorghum, and corn) that can be used as feed supplements for beef cattle production and the potential impacts from a changing climate (precipitation, temperature) and energy inputs (crude oil production and prices). The analysis was based on 60 years of data (1958–2017) using generalized autoregressive conditional heteroscedasticity models. Hay production showed a declining trend since 2000 and in 2017, it dropped by ~33% compared to that of 2000. Crude oil production (R2 = 0.83) and beef cattle population (R2 = 0.85) were negatively correlated with hay production. A moderate declining trend in mean annual hay prices was also observed. Mean annual range conditions (R2 = 0.60) was negatively correlated with mean annual hay prices, whereas mean annual crude oil prices (R2 = 0.48) showed a positive relationship. Grain sorghum production showed a consistent declining trend since 1971 and in 2017, it dropped by ~91% compared to that of 1971. Mean annual temperature (R2 = 0.58) was negatively correlated with grain sorghum production, while beef cattle population (R2 = 0.61) and range conditions (R2 = 0.51) showed positive linear relationships. Mean annual grain sorghum prices decreased since the peak of 1974 and in 2017, they dropped by ~77% compared to those of 1974. Crude oil prices (R2 = 0.72) and beef cattle population (R2 = 0.73) were positively correlated with mean annual grain sorghum prices. Corn production in 2017 dropped by ~61% compared to the peak that occurred in 1999. Crude oil production (R2 = 0.85) and beef cattle population (R2 = 0.86) were negatively correlated with corn production. Mean annual corn prices showed a declining trend since 1974 and in 2017, they dropped by ~75% compared to those of 1974. Mean annual corn prices were positively correlated with mean annual precipitation (R2 = 0.83) and negatively correlated with crude oil production (R2 = 0.84). These finding can particularly help in developing a more holistic model that integrates FEWS components to explain their response to internal (i.e., management practices) and external (i.e., environmental) stressors. Such holistic modeling can further inform the development and adoption of more sustainable production and resource use practices.

In North America, beef production relies on the administration of antimicrobials to manage disease. Bovine respiratory disease (BRD) is the most significant disease of beef cattle, and antimicrobial resistance (AMR) to conventional therapies presents an existential risk to animal welfare and food production. While AMR surveillance programs are poised to help facilitate antimicrobial stewardship and decision making at feedlots, monitoring strategies for large numbers of animals at an individual or group level are time consuming and costly. Accordingly, we completed a pilot investigation of feedlot water bowls, which is an understudied interface between cattle and bacteria. By performing cultivation-dependent and cultivation-independent studies, we demonstrate that water bowl-dwelling bacteria can act as sentinel organisms for clinically relevant antimicrobial resistance genes (ARGs) and that cattle have an impact on the microbial communities in the bowls. Moreover, by sampling water at a feedlot site before animal arrival, we detected resistance to two antibiotics: florfenicol and tulathromycin. After just 4 weeks of operation, multidrug-resistant bacteria were routinely found in most water bowls. A comparison of ARGs encoded by five water bowl bacterial isolates along with previously reported source and wastewater metagenomes to those found in BRD pathogens confirmed the utility of using water samples for AMR surveillance. A better understanding of how environmental reservoirs of ARGs in the feedlot relate to those found in animal pathogens will help inform and improve disease management, treatment strategies, and outcomes. Monitoring individual cattle or small groups is invasive, logistically challenging, expensive, and unlikely to gain adoption by the beef cattle industry. Wastewater surveillance has become standard in public health studies and has inspired similar work to better our understanding of AMR in feedlots. We derived our insights from sampling water bowls in a newly established feedlot: a unique opportunity to observe AMR prior to animal arrival and to monitor its development over 2 months. Importantly, the bacterial community of a single water bowl can be influenced by direct contact with hundreds of animals. Our results suggest that water bowl microbiomes are economical and pragmatic sentinels for monitoring relevant AMR mechanisms.

Background Oil palm is a tropical crop with worldwide plantings approaching 20 million ha and large areas in Indonesia, Malaysia and Thailand. The plantations are readily managed as silvopastoral systems incorporating cattle grazing (Oil Palm Silvopastoral System for Cattle, OPSC) but there is a need for analytical tools and data to understand system herbage supply and feed conversion efficiency (FCE). Methods Metabolic energy budgeting was used to estimate herbage harvested by cattle in three OPSC subsystems, 9 and 12 years after oil palm establishment, and FCE of the subsystems was determined. Understorey herbage was also analysed for nutritive value, botanical composition and herbage accumulation within one grazing‐regrowth cycle. Results The herbage‐harvested estimate was 2.0−2.4 t dry matter (DM) ha−1 year−1 for 9 year old subsystems and 1.4−1.7 t DM ha−1 year−1 for a 12 year old subsystem. Herbage metabolisable energy (ME) was 8.3−8.5 MJ kg−1 DM and crude protein (CP) was 15%−16% DM. FCE values for subsystems ranged from 32 to 94 kg DM kg−1 liveweight‐gain. Conclusions Herbage DM yield is declining, while herbage ME is marginal but CP is adequate. FCE is suboptimal but can be optimised by defining the trajectory of declining herbage production with canopy closure as plantations age and matching stocking rate to herbage supply using a comparative‐stocking‐rate‐type statistic. Years‐9–12‐Oil‐palm Beef‐silvopastoral Assessment in Sabah, Malaysia Using Metabolic‐energy‐budgeting: Herbage yield (2.2 to 1.6 t DM ha−1 year−1): declined; herbage energy (8.4 MJ ME kg−1 DM): marginal; crude protein (15.5% kg−1 DM): adequate; feed conversion efficiency (32–94 kg DM kg−1 LWG): suboptimal. Cattle‐stock–Pasture‐supply could optimally be matched using a CSR‐type statistic.