Heat stress impacts productivity and methane emissions in dairy cattle

1 Introduction

Greenhouse gases (GHG) accumulate in the troposphere, the lowest layer of the atmosphere, where they trap radiant energy from the sun, thereby maintaining warmth on earth. Without the greenhouse effect, the average global temperature is estimated to be around -19 °C. However, the increasing concentration of GHG is driving average temperatures beyond levels considered suitable for sustaining life, posing a significant threat to ecosystems and human societies (Le Treut et al., 2007). The primary GHG are carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O), which are emitted from various sectors of the economy. In the United States, transportation is the largest contributor to GHG emissions, accounting for 29% of the total, followed by the electric power sector (25%), the industrial sector (24%), and agriculture (10%), according to the Environmental Protection Agency (EPA, 2021). Globally, agriculture was responsible for approximately 22% of total GHG emissions in 2019 (EPA, 2024). Within the agricultural sector, livestock farming contributes 14.5% of emissions, with cattle accounting for 65% of emissions from livestock systems (Rivera and Chará, 2021).

Brohan et al. (2006) demonstrated that the continuous accumulation of GHG has contributed to global warming by analyzing records of average temperature changes from 1850 to 2000 across both the northern and southern hemispheres. Their analysis revealed increases in average temperatures of approximately 1.2 °C and 1.0 °C, respectively. The temperature trends show a gradual rise from 1850 to 1925, followed by a sharp and sustained increase from 1925 to 2000, which is largely attributed to rapid industrialization. Over time, global warming drives climate change, which negatively impacts multiple economic sectors. Agriculture is likely the most vulnerable sector, facing adverse effects on crops, soil health, water availability, livestock, and even agricultural labor. These disruptions pose a significant threat to global food security (EPA, 2024).

It is estimated that approximately 50% of the global biomass harvest is consumed by livestock, making feed availability a critical factor in animal agriculture. Consequently, climate change indirectly affects livestock by disrupting feed supply chains, leading to nutritional deficiencies that can cause a range of welfare issues in farm animals (Herrero and Thornton, 2013). In addition, several studies have reported an increase in disease outbreaks linked to shifting climate patterns. For example, the spread of vectors responsible for transmitting sheep bluetongue virus and Rift Valley fever among ruminants in Africa has been associated with climate-related phenomena such as the El Niño Southern Oscillation, which is influenced by rising average temperatures (Bett et al., 2017).

2 Heat stress effects on dairy cattle

The thermoneutral zone in dairy cattle refers to the ambient temperature range within which cows can maintain their internal body temperature through homeostatic heat exchange with the environment. This range is typically between 5 °C and 25 °C (Becker et al., 2020). To better assess heat stress (HS) potential, temperature is often combined with relative humidity to calculate the Temperature-Humidity Index (THI), which provides a more accurate representation of environmental stress. Dairy cows, especially those producing high milk volumes, have elevated metabolic rates that generate substantial metabolic heat requiring dissipation. As THI increases, the ability to release this heat is compromised, leading to physiological and productive signs of HS. Traditionally, a THI threshold for dairy cows has been between 68 and 71, a THI range where cows start to show mild HS signs such as increases in respiration rate and milk yield loses (Collier et al., 2011; Renaudeau et al., 2012). Moreover, moderate to severe HS signs are evident with THI that ranges from 72 to 89, where breathing rate becomes noticeably increased (75–85 breaths per minute) and rectal temperature exceeds 39 °C while a THI exceeding 90 is considered of risk to death (Renaudeau et al., 2012). Recent studies have reevaluated THI threshold for dairy cows showing that cows producing more than 31 kg of milk per day begin to exhibit HS effects, such as increased rectal temperature and reduced milk yield, at a THI threshold of 64 (Ji et al., 2020). In subtropical and tropical regions like Florida, summer THI values typically range from 71 to 84. It is estimated that cows in Florida are exposed to HS conditions for over 4,200 hours annually, a figure expected to rise due to ongoing climate change. This makes Florida one of the U.S. states most affected by global warming in terms of livestock heat stress (St-Pierre et al., 2003). The effects of HS on dairy cattle are summarized in Figure 1.

2.1 Heat stress effects on feed intake and rumen function

Feed intake reduction is the initial physiological response of dairy cows to HS. This response is mediated by the hypothalamic cooling center, which regulates feed intake (Albright and Alliston, 1971). When body temperature rises above the homeostatic threshold, the cooling center signals the appetite center to suppress intake in an effort to reduce heat production from rumen fermentation and, consequently, lower body temperature. As a result, nutrient absorption becomes insufficient to support high levels of milk production (Albright and Alliston, 1971).

In addition to reduced intake, mild to severe HS can increase maintenance energy requirements by 7% to 25%, primarily due to prolonged standing, elevated respiration rates, and increased heart rate (Grandin, 2016). The combination of increased energy demands, and reduced intake contributes to a negative energy balance, particularly during early lactation (Becker et al., 2020). Nutrient partitioning shifts toward maintenance functions, leaving fewer resources available for the mammary gland, thereby reducing milk yield. This response occurs across physiological stages, but multiparous and high-producing cows are more susceptible than primiparous and low-producing cows due to their greater nutritional demands for milk synthesis, making nutritional management under HS conditions especially challenging (Becker et al., 2020).

Rumen function is also compromised under HS through multiple mechanisms. HS reduces rumination time, decreases rumen motility and alters ruminal pH (Yadav et al., 2016; Kim et al., 2022). Changes in rumen function are influenced by reduced feed intake; however, other mechanisms are also involved.

Saliva plays a critical role in buffering ruminal pH. However, during HS, saliva production decreases as a physiological strategy to conserve water and as a consequence of reduced rumination. Panting, a common behavioral response to HS, leads to significant saliva loss. These factors collectively diminish the buffering capacity of saliva, contributing to reductions in ruminal pH. Additionally, lactate-producing bacteria have been shown to be more tolerant to elevated rumen temperatures observed when under HS than other microbial populations further contributing to lower pH (Kim et al., 2022). Heat stress may also reduce blood flow to the rumen epithelium, potentially impairing nutrient absorption and rumen motility (Yadav et al., 2016). Reduced motility slows feed passage rate and increases feed retention time, which can enhance digestibility under moderate HS conditions. However, extreme heat loads may reverse this effect. Yadav et al. (2016) demonstrated that dry matter digestibility improved at 30 °C and 35 °C compared to 20 °C, 25 °C, and 40 °C in crossbred heifers housed in climate-controlled chambers. Similarly, Nonaka et al. (2008) reported increased dry matter digestibility in Holstein heifers exposed to 33 °C compared to 20 °C, under constant 60% relative humidity in respiratory chambers. The observed increase in digestibility under moderate HS is attributed to slower passage rates, allowing for extended fermentation time in the rumen. However, this does not mitigate the overall negative effects of HS on cow health and productivity (Kim et al., 2022).

2.2 Heat stress effects on volatile fatty acids and ruminal microbiota

Volatile fatty acid (VFA) profiles in the rumen are also altered under HS conditions. Meneses et al. (2021) investigated VFA shifts in beef heifers exposed to HS or cooling, including a pair-fed thermoneutral group that received the same feed allowance as HS animals. Although total VFA concentrations were similar between HS and pair-fed heifers, the HS group showed a significantly higher proportion of propionic acid, along with lower ruminal pH and higher ruminal temperature. Similarly, Guo et al. (2022) reported that lactating cows under HS had an increased propionate proportion, a reduced acetate: propionate ratio, and decreased ruminal pH compared with pair-fed thermoneutral cows. These alterations in VFA profiles may be driven by shifts in rumen microbiota associated with elevated ruminal temperatures. Kim et al. (2022) demonstrated that lactate-producing bacteria such as Streptococcus show elevated tolerance to high temperatures, and when combined with reduced saliva inflow, contribute to a decline in ruminal pH. This acidic environment inhibits fibrolytic bacteria, whereas propionate-producing bacteria are more tolerant to low pH, ultimately shifting fermentation patterns and VFA proportions toward propionate, consistent with the findings of Meneses et al. (2021) and Guo et al. (2022).

The phyla Firmicutes and Bacteroidetes are the most dominant microbial groups in the rumen, comprising bacteria that degrade structural and non-structural carbohydrates, respectively (Kim et al., 2022). Zhao et al. (2019) conducted a study focusing on mid-lactation cows, comparing rumen microbiota during cool (THI ~71) and hot months (THI ~87) using 16S rRNA sequencing. They used different individuals during hot and cool seasons, all with similar days in milk and lactation number at sample collection time. HS cows exhibited a reduced relative abundance of Prevotella, a fiber-degrading genus, and an increase in lactate-producing bacteria such as Streptococcus and members of Enterobacteriaceae. Furthermore, HS was associated with significantly lower ruminal pH and lower acetate concentration, alongside elevated lactate concentration.

Feng et al. (2023) further investigated the effects of seasonal HS on ruminal microbiota using 16S rRNA sequencing. They followed the same individuals across different life stages (i.e., prepubertal heifers, 6.9 months old; post pubertal heifers, 16.5 months old; and ≥ 2 lactations cows) during the cool season (THI ~65) and the HS season (THI ~81). Seasonal HS was associated with increased relative abundance of Firmicutes and Bacteroidetes in prepubertal and post pubertal heifers, whereas no significant differences were observed in lactating cows. Additionally, Clostridium, a cellulose-degrading genus, was significantly reduced in both heifer groups during the HS season but remained unchanged in lactating cows. Furthermore, Feng et al. (2023) also observed increased abundance of pathogenic bacteria such as Treponema, Sphingobacterium, and Streptococcus during the HS season compared to the cooler season. These findings suggest that both age and seasonal variation are important factors influencing rumen microbial composition under HS conditions (Feng et al., 2023). Although seasonal comparisons may be confounded by time-related variables, these findings are consistent with those of Zhong et al. (2019), who exposed goats to HS in respiration chambers, thereby controlling for temporal confounding. Their 16S rRNA sequencing analysis also revealed increased abundance of pathogenic bacteria, including Lachnospiraceae and Treponema.

These findings support the hypothesis that HS alters rumen microbial populations, leading to shifts in fermentation end products. However, further research under controlled conditions is necessary to confirm the specific effects of HS on the gastrointestinal microbiota of dairy cows.

2.3 Heat stress effects on endocrine system

The endocrine system also responds to HS, with various hormones playing critical roles in physiological adaptation. The hypothalamic–pituitary–adrenal axis is considered the primary regulator of stress hormones during HS. When body temperature rises, the hypothalamus increases production of corticotropin-releasing hormone, which stimulates the pituitary gland to release adrenocorticotropic hormone (ACTH). ACTH then acts on the adrenal glands to promote the secretion of cortisol, a key stress hormone (Binsiya et al., 2017).

Cortisol regulates numerous physiological functions, including cellular metabolism, immune response, and inflammation. It affects nearly all body systems; nervous, immune, cardiovascular, respiratory, reproductive, and musculoskeletal, in an effort to maintain homeostasis under stress (Kaur et al., 2023). The cortisol response is most pronounced during acute HS and tends to normalize over time as animals acclimate, often at the expense of productivity. For example, Kim et al. (2022) exposed 6-month-old calves to varying levels of HS (threshold, mild, moderate, and severe) for 21 days using respiratory chambers. Blood cortisol concentrations spiked in the moderate and severe HS groups but returned to baseline after nine days. Similarly, Marins et al. (2021) observed elevated cortisol levels in lactating dairy cows during the initial days of HS exposure, which normalized after eight days. However, milk production remained significantly reduced, indicating that acclimation lowers cortisol levels but does not restore productivity. Cortisol also stimulates the production and activity of heat shock proteins (HSP), which serve as molecular protectants at the cellular level. HSP70 is the most expressed HSP in ruminants (Chen et al., 2023). These proteins act as molecular chaperones, stabilizing other proteins under stress conditions. Cellular stress, such as mitochondrial membrane damage, can release apoptosis-triggering factors. HSP bind to these factors and inhibit apoptosis, including blocking activation by plasma factors like tumor necrosis factor (Lanneau et al., 2007).

Prolactin (PRL) is another hormone that has adaptive changes due to HS. Prolactin was first associated with milk yield but later, it was found to have a variety of effects including immune modulation and osmotic regulation of fluids and electrolytes (Freeman et al., 2000). Some studies have reported that blood prolactin concentrations increased when cows are exposed to HS (Tucker and Wettemann, 1976; Collier et al., 1982), and such an increase could be attributed to the potential of PRL to contribute to regulation of water and electrolyte balance which could be altered during HS (Collier et al., 1982; Shennan, 1994). In addition, dopaminergic neuron activity is reduced during HS which allows for increased secretion of PRL from the anterior pituitary; therefore, PRL is considered a stress hormone (Marins et al., 2021). However, the effects of PRL are dependent on its receptor (PRL-R) expression of target cells such as mammary gland epithelial cells, hepatocytes and lymphocytes (Auchtung et al., 2003).

Heat stress also induces changes in post-absorptive metabolism by maintaining or increasing blood insulin concentration despite a reduction in glucose levels driven by decreased feed intake. Additionally, HS cows exhibit a greater glucose disposal rate following a glucose tolerance test compared to pair-fed cows maintained under thermoneutral conditions (Wheelock et al., 2010). Similarly, when HS is applied during the dry period, cows show elevated blood insulin concentrations and increased glucose disposal rates during the subsequent early lactation, relative to cows that were cooled during the dry period (Tao et al., 2012). Furthermore, the mobilization of non-esterified fatty acids is reduced in HS cows compared to pair-fed cows in thermoneutral conditions. This reduction may be driven by elevated insulin concentrations, suggesting that HS cows preferentially utilize glucose as a primary energy source in peripheral tissues, potentially limiting energy availability for milk synthesis in the mammary gland (Tao et al., 2012).

2.4 Heat stress effects on milk production and mammary gland

Numerous studies have demonstrated that HS negatively impacts milk production across all stages of lactation, a concern of significant economic importance due to the associated losses. For instance, Ferreira and De Vries (2015) analyzed seasonal effects on milk yield across various farms in Florida, U.S., a subtropical region, during 2012 and 2013. They found that on average, milk production during the hot months was 31% lower than during the cool months. Experimental studies, such as those conducted by Tao et al. (2018), further confirmed these seasonal effects and revealed different responses depending on lactation stage. In these studies, HS was induced by disabling evaporative cooling systems in free-stall barns, while control cows had access to cooling. Early-lactation cows experienced a reduction in milk yield after one week of HS exposure. However, these cows recovered to expected milk production levels once cooling was restored. Similarly, late-lactation cows showed reduced milk yield during HS, but production returned to normal after the stress was removed. In contrast, mid-lactation cows experienced reduced milk yield almost immediately applying HS and failed to fully recover after cooling was reintroduced, with lower yields persisting for the remainder of lactation. These findings suggest that early- and late-lactation cows are more resilient to HS, whereas mid-lactation cows may experience lasting impacts, potentially due to altered mammary gland persistence after peak lactation (Tao et al., 2018).

In early lactation, the improved resilience to HS compared to mid-lactation may be attributed to the intensive mobilization of body energy reserves characteristic of this stage. This mobilization can help counteract the negative effects of reduced feed intake due to HS, as cows are typically in a state of negative energy balance. In contrast, mid-lactation cows are approaching or have reached a positive energy balance, resulting in reduced reliance on body reserves. Consequently, the impact of HS-induced reductions in feed intake becomes more pronounced, leading to greater declines in milk production (Bernabucci et al., 2010). Moreover, after peak lactation, milk yield naturally declines due to the apoptosis of mammary epithelial cells. Heat stress accelerates this process, which may explain the reduced resilience of mid-lactation cows during and after HS exposure (Capuco et al., 2003; Tao et al., 2018).

In addition to reduced milk production, HS has been associated with lower milk quality, primarily due to increased somatic cell count (SCC). In Florida, SCC levels have been reported to rise during the warmer months compared to the cooler ones (Ferreira and De Vries, 2015). Similar seasonal trends have been observed in other regions, including England (Green et al., 2006), Ireland, and Wales (Archer et al., 2013). SCC in milk consists of mammary epithelial cells and immune cells recruited from circulation. The presence of epithelial cells reflects natural cell turnover and apoptosis, both of which are elevated under HS, contributing to higher SCC (Lengi et al., 2022). Additionally, warmer temperatures are associated with increased pathogen loads, which trigger inflammatory responses in the mammary gland and promote leukocyte migration into the milk (Lengi et al., 2022). HS may also activate the heat shock response, which enhances cytokine activity and further stimulates leukocyte infiltration into the mammary gland (Bagath et al., 2019). However, the immune response to HS remains complex and not fully understood. While some studies suggest an activated immune response, others report immunosuppression. For example, Lacetera et al. (2006) observed reduced proliferation of peripheral blood mononuclear cells exposed to HS cycles up to 42 °C. Similarly, in vitro studies have shown that increasing temperatures impair the phagocytic and oxidative burst activity of bovine polymorphonuclear cells (Lecchi et al., 2016). These conflicting findings highlight the need for further research to clarify the mechanisms by which HS affects immune function and its implications for udder health and milk quality.

The negative effects of HS are not limited to lactation but also occur when the insult takes place during the dry period, with consequences that extend into the subsequent lactation. Tao and Dahl (2013) demonstrated that cows exposed to HS during the dry period, by removing access to cooling systems during the summer, produced, on average, 5 kg/day less milk than their cooled counterparts. In a similar study, Tao et al. (2011) compared dry cows with and without access to cooling systems during the summer. They monitored milk yield and composition throughout most of the following lactation and collected mammary gland biopsies both before and shortly after calving. Their findings showed that HS impaired mammary gland development during the dry period which reduced milk yield and tended to increase SCC over 280 days of the following lactation period. Specifically, HS decreased the rate of mammary epithelial cell proliferation, indicating compromised mammary tissue growth and function.

3 Enteric methane emissions from cattle

Methane (CH₄) is a waste product resulting from microbial degradation of organic matter in the rumen (Khan et al., 1997). Methanogenic archaea are the microorganisms responsible for CH₄ production, primarily through the reduction of carbon dioxide (CO₂) and hydrogen (H₂; Figure 2). The most common genera of methanogenic archaea identified in the cattle rumen across multiple diets and geographical regions include Methanobrevibacter, Methanomicrobium, Methanosphaera, Thermoplasma, Methanomassiliicoccaceae, and Methanobacterium (Henderson et al., 2015; Matthews et al., 2018) These microorganisms play a crucial role in maintaining low hydrogen concentrations in the rumen, thereby creating a favorable environment for the growth of other microbial species and supporting efficient fermentation of feedstuffs (Matthews et al., 2018).

Beyond its environmental impact as a potent greenhouse gas, CH₄ production also represents an energy loss for the animal, estimated at 2–12% of gross energy intake (Johnson and Johnson, 1995). Hydrogen is generated during ruminal fermentation, initially through glycolysis, where glucose monomers are broken down into pyruvate, and subsequently during the oxidative decarboxylation of pyruvate to acetyl-CoA. In contrast, CO₂ is released during the conversion of pyruvate into formate, propionate, and acetyl-CoA (Lan and Yang, 2019). Methanogens utilize H₂ and CO₂ in the hydrogenotrophic pathway, following the reaction: CO₂ + 4H₂ → CH₄ + 2H₂O, with methane and water as the end products. While the majority of CH₄ in the rumen is produced via this pathway, smaller amounts are generated through the methylotrophic and acetoclastic pathways (Hill et al., 2016).

Methanogens in the rumen exist in two forms: free-living or associated with other microorganisms. Most associations occur with protozoa, though a small proportion are linked to fungi. These associations enhance methanogens’ access to hydrogen. Methanobacterium and Methanosphaera are typically free-living, whereas Methanobrevibacter and Methanomicrobium are commonly associated with protozoa. Approximately 9–25% of rumen methanogens are protozoa-associated and are estimated to contribute to around 37% of total methane production in the rumen (Belanche et al., 2014).

Methane emissions from cattle can be expressed in several ways. Daily methane represents the total amount of CH₄ emitted per day, often expressed in grams per day. Methane yield expresses CH₄ emissions relative to feed intake (i.e. grams of CH₄/kg of DMI), and methane intensity corrects emissions for productive output, such as milk yield in dairy cows (i.e. grams of CH₄/kg of milk yield) or beef gain in beef cattle (i.e. grams of CH₄/kg of body weight). While total CH₄ reflects the absolute quantity of methane released, methane yield and intensity are particularly important because they provide insight into the efficiency of nutrient use and the environmental cost per unit of production.

3.1 Methane emissions quantification techniques in cattle

Several techniques for quantifying CH₄ emissions from ruminants have been developed and applied globally (Table 1). These methods vary in ease of application, accuracy, and cost, but all are based on measuring CH₄ concentrations in gases emitted by animals. The selection of an appropriate technique depends on logistical constraints and budget considerations (Hammond et al., 2016). Additionally, considering the experimental design is advised when choosing CH₄ emissions quantifying techniques.

Table 1. Summary of methane measurement techniques advantages and disadvantages.

Respiration chambers (RC) are considered the gold standard for measuring gaseous emissions from ruminants. There are two types: open-circuit and closed-circuit chambers. Open-circuit systems measure the composition of incoming and outgoing air and are the most commonly used. In contrast, closed-circuit systems analyze the composition of air accumulated over time (Tedeschi et al., 2022). The principle of an open-circuit chamber involves introducing outside air with known gas concentrations into an enclosed chamber housing the animal, then comparing it to the gas concentrations in the outflow air (Arceo-Castillo et al., 2019). These chambers are climate-controlled, with adjustable temperature and humidity, and are equipped with in-line electronic flow meters to continuously monitor air volume. Gas concentrations, including oxygen (O₂), CO₂, ammonia (NH₃), and CH₄, are measured using infrared analyzers, gas chromatographs, or laser-based sensors (Soliva and Hess, 2007). Despite their precision, RC have notable disadvantages. They can negatively affect animal behavior and feeding patterns, which in turn may influence CH₄ measurements due to the artificial environment of the chamber that differs from natural conditions, making it difficult to extrapolate findings to large populations (Hill et al., 2016). RC are also expensive, require intensive maintenance, and typically accommodate only one or a few animals at a time (Tedeschi et al., 2022).

The sulfur hexafluoride (SF₆) tracer technique involves administering a small permeation tube containing SF₆ into the rumen of an animal. This tube releases SF₆ at a known, constant rate. Externally, the animal wears a halter equipped with a capillary tube connected to a valve and an evacuated sampling canister. One end of the capillary tube is positioned near the animal’s nostrils and mouth to collect emitted gases at a constant rate as the vacuum in the canister dissipates. After sample collection, the concentrations of CH₄ and SF₆ in the canister are determined using gas chromatography (Johnson et al., 2007). Methane emissions are then calculated based on the CH₄/SF₆ ratio, adjusted for background concentrations and the known SF₆ permeation rate. Efforts are made to ensure uniform permeation rates across tubes to improve accuracy and consistency (Pinares-Patiño and Clark, 2008).

Short-term measurements of CH₄ emissions from individual cattle are possible using automated head chambers such as the GreenFeed (GF) system (C-Lock Inc., Rapid City, South Dakota). The GF unit integrates airflow, gas concentration, and head position measurements during each visit. It uses an extractor fan and sensors to collect air samples from the animal’s exhaled breath. Animals are attracted to the unit by small bait portions dispensed at scheduled intervals throughout the day.

A proximity sensor located at the sampling port monitors the animal’s head position and distance, allowing the system to adjust for variations in head placement relative to airflow. When deployed outdoors, the unit includes an anemometer to measure wind speed, enabling correction for wind effects on gas capture (Hammond et al., 2016). Collected air samples pass through an airflow line equipped with a nondispersive infrared sensor, which continuously measures gas concentrations. Daily CH₄ emissions are calculated using the volumetric airflow rate, adjusted for temperature and pressure, and corrected for capture efficiency and background CH₄ levels (Huhtanen et al., 2015).

Some studies have compared CH₄ emission measurements obtained using GF, RC, and the SF₆ to assess consistency and reliability. Hammond et al. (2015) describes a comparison of GF and RC in Holstein heifers fed two different diets. While average CH₄ measurements were similar between the two methods, GF exhibited greater variability than RC. The study reported a low concordance correlation coefficient between GF and RC, and GF failed to detect treatment differences that RC identified. The lower concordance and detection sensitivity of GF were attributed to its higher measurement variability. Additionally, Hammond et al. (2015) describes evaluations of GF and SF₆ simultaneously in grazing heifers. In this case, the concordance correlation coefficient improved, and both techniques significantly detected treatment differences. However, GF underestimated CH₄ emissions by up to 18% compared to SF₆. The authors noted that diurnal patterns of CH₄ emissions, variability in the timing of animal visits to GF units, and low visit frequency may have influenced the results. In a separate study, Alemu et al. (2017) assessed CH₄ emissions in growing heifers with high and low residual feed intake (RFI) using both RC and GF. Significant differences in daily CH₄ emissions between low- and high-RFI heifers were observed using GF, but not with RC. Interestingly, DMI also differed significantly between RFI groups when measured with GF, but not with RC. This suggests that DMI influences daily CH₄ emissions and must be accounted for in emission estimates. The authors concluded that GF provides reliable CH₄ measurements without disrupting natural animal behavior; however, ensuring enough numbers of visits dispersed throughout the day is important. Moreover, recent studies in growing beef cattle show that in order to achieve a reliable phenotype of enteric methane emissions using GF, a minimum of 60 effective visits (those of 2 min or more) are required (Vargas et al., 2024).

Laser-based methane detectors have been primarily used to assess emissions from wetlands with reliable results (Rey-Sanchez et al., 2019). The principle of this technique is based on detecting the wavelength of light absorbed by the target gas and its reflectivity (Rey-Sanchez et al., 2019). Lately, laser-based techniques have also been implemented for CH₄ emission detection from ruminants, offering several advantages over traditional methods due to their ease of use, minimal animal handling, applicability at both the individual-animal and herd level, and their ability to estimate emissions from manure pits, providing a comprehensive farm-level assessment (Kumari et al., 2020). For instance, a study in ruminants have demonstrated the effectiveness of laser methane devices in detecting differences in methane emissions associated with heat stress and the subsequent decrease in feed intake (Lanzoni et al., 2022). However, methane values obtained from laser devices do not always correlate with expected outcomes because these instruments measure concentration at a given moment rather than emission rate. Additionally, environmental factors such as wind, background gases, and distance from the animal can reduce the reliability of measurements (Sorg, 2022). Although the practical benefits of laser-based devices may still outweigh these limitations, more research is needed to validate the use of this technique.

3.2 Strategies to reduce enteric methane emissions from ruminants

A wide range of factors influence methane emissions from ruminants. Genetics is one of the most important, as evidence shows that some animals are phenotypically more efficient than others of the same breed and physiological status, resulting in lower CH₄ output (Alemu et al., 2017). This has motivated efforts to select and breed animals with inherently lower CH₄ emissions (Glasson et al., 2022). Breed differences also contribute substantially: beef cattle generally produce less daily CH₄ than dairy cows (Alemu et al., 2017; Hristov and Melgar, 2020). However, this difference is largely driven by variation in DMI, because dairy cows consume considerably more feed to sustain high milk production. Higher DMI increases the amount of fermentable substrate available in the rumen, which in turn elevates total methane production (Bačėninaitė et al., 2022). Housing system further influences methane emissions, partly through its effects on diet composition and intake behavior. For example, grazing cattle typically consume diets with higher fiber content but lower overall DMI compared with confined systems, which alters fermentation patterns and methane output (Gislon et al., 2020; Ormston et al., 2025). These interacting factors highlight the complexity of predicting and mitigating methane emissions at the individual-animal level.

Reducing CH₄ emissions from cattle has the potential to benefit the environment while also improving feed efficiency (Wallace et al., 2014). Although the search for strategies to reduce enteric CH₄ emissions is an active area of research, it remains highly challenging. Investigated approaches include selective breeding, vaccines, methanogenesis inhibitors, and dietary interventions, with most efforts focusing on the direct inhibition of methanogenesis through dietary compounds (Glasson et al., 2022); therefore, in the present review we focus specifically on dietary modulators.

Among the compounds that have been tested and successfully commercialized, ionophores stand out. As their name suggests, their mechanism of action is based on their ability to interact with ions forming ionophore-cation complexes that can solubilize through bacterial or protozoal cell membranes, exchanging Na⁺ for K⁺. This exchange increases the intracellular Na⁺ concentration while reducing the K⁺ gradient, forcing the cell’s proton ATPase pump to expend additional energy to restore ionic balance. As a result, the cell is left with reduced energy reserves for division (McGuffey et al., 2001). Due to differences in cell membrane structure, ruminal protozoa and gram-positive bacteria are particularly sensitive to monensin. Protozoa, which are colonized by methanogenic archaea, contribute to CH₄ production; monensin disrupts this association, thereby reducing methane emissions. Additionally, some acetate-producing bacteria are gram-positive and thus sensitive to monensin, which reduces acetate production and the availability of hydrogen for CH₄ synthesis (Russell and Strobel, 1989) yet, results on methane reduction in dairy cattle are variable, likely due to differences in diet composition, intake levels, and dosing. For instance, Sauer et al. (1998) reported a 21% reduction in CH₄, Odongo et al. (2007) found a 7% reduction, while Benchaar (2016) observed no significant change.

Another promising compound for reducing CH₄ emissions is 3-nitrooxypropanol (3-NOP). Its mechanism of action involves competitive, reversible inhibition of methyl-coenzyme M reductase, a key enzyme in the final step of methanogenesis in archaea, thereby blocking CH₄ formation (Yu et al., 2021). In beef (Vyas et al., 2016) and lactating dairy cattle (Haisan et al., 2014; Reynolds et al., 2014), CH₄ reductions ranged from 10–50% and 10–65%, respectively, with no adverse effects on feed intake, milk yield, or body weight gain. Differences in outcomes are attributed to doses and dietary strategies. For example, Vyas et al. (2016) compared various 3-NOP levels in backgrounding and finishing diets, while in dairy cows, Haisan et al. (2014) mixed 3-NOP into the ration, and Reynolds et al. (2014) administered it directly into the rumen via fistula. Rapid CH₄ reductions observed in respiration chambers suggest that 3-NOP may be quickly metabolized (Hristov et al., 2013). A meta-analysis by Dijkstra et al. (2018) found that 3-NOP efficacy is positively correlated with inclusion level and negatively correlated with dietary fiber.

Tannins are among the most extensively studied dietary inhibitors of enteric methane. They are polyphenolic secondary metabolites naturally present in trees, shrubs, legumes, cereal grains, and many other plant species (Zhao et al., 2025). Tannins occur in two major chemical classes; hydrolysable and condensed tannins, which differ in molecular structure and stability. Condensed tannins are highly resistant to degradation, remaining stable even under the lower pH conditions of the rumen, whereas hydrolysable tannins are readily hydrolyzed (Zhao et al., 2025). Their methane-mitigating effects arise from several complementary mechanisms. Tannins can reduce fiber digestion, thereby decreasing the production of H₂, which is the key precursor for methanogenesis. They also exert direct inhibitory effects on rumen methanogens, protozoa, and other hydrogen-producing microbes, altering the microbial ecosystem in ways that decrease CH₄ formation (Souza et al., 2025). Grainger et al. (2009) reported reductions of 29% in methane emissions and 22% in methane intensity, while Yang et al. (2017) observed reductions of up to 34% in total CH₄ and methane intensity. These findings highlight the potential of tannins as a practical mitigation strategy across diverse production systems. However, the same mechanisms that reduce methane can also lead to undesirable nutritional consequences if tannins are not carefully used. Tannins may decrease DMI and nutrient digestibility, particularly fiber digestibility, which can limit energy availability (Min et al., 2003; Piñeiro-Vázquez et al., 2018). These effects can translate into lower milk yield and reduced milk components, especially milk fat percentage, as reported by Grainger et al. (2009). The magnitude of these tradeoffs depends on tannin type, dose, and diet composition (Souza et al., 2025). Besharati et al. (2022) underscore the need for careful tannins selection and application when incorporating tannins into dairy rations to prevent negative outcomes.

Halogenated compounds, such as bromoform, bromochloromethane, and dibromochloromethane, found in seaweed species like Asparagopsis spp., have also shown substantial CH₄ inhibition potential. Bromoform, particularly abundant in Asparagopsis taxiformis (red seaweed), interferes with methanogenesis by inhibiting key enzymes, including coenzyme M methyltransferase, thereby blocking methyl transfer and subsequent CH₄ formation (Glasson et al., 2022). The effect is dose-dependent, and since bromoform concentrations vary among seaweed species, they are often used as proxies for estimating CH₄ reduction potential (McGurrin et al., 2023).

In vitro studies have reported near-complete CH₄ inhibition. For example, Machado et al. (2017) observed nearly 100% reduction with 2% A. taxiformis inclusion, and Chagas et al. (2019) reported a 99.5% reduction at the same level. In vivo studies also show promising results. Kinley et al. (2020) tested red seaweed at 0.05%, 0.10%, and 0.20% of organic matter in beef steers, achieving 40% and 98% CH₄ reductions at 0.10% and 0.20% inclusion, respectively, without negative effects on intake or feed efficiency. In contrast, Roque et al. (2019) found that in lactating cows, Asparagopsis armata inclusion at 0.5% and 1% reduced CH₄ yield by 20.3% and 42.7%, and CH₄ intensity by 18.2% and 60.1%, respectively. However, feed intake declined linearly with increasing inclusion, likely due to low palatability, resulting in reduced milk yield.

A second major group of macroalgae is the brown seaweeds, which include species such as Ascophyllum nodosum, Fucus vesiculosus, Laminaria digitata, Saccharina latissima, and Zonaria farlowii, among others (De Bhowmick and Hayes, 2023; Künzel et al., 2022). Unlike red seaweed, the methane-mitigating potential of brown seaweeds is generally limited. In vitro studies have reported modest reductions of 8.9% (Künzel et al., 2022) and 26% (Choi et al., 2021), while others have found no reduction (Belanche et al., 2016). In vivo evidence is scarce; however, Antaya et al. (2019) observed an 11.5% reduction in CH₄ emissions in lactating cows, although this effect disappeared during a subsequent supplementation period, suggesting possible rumen adaptation. Similarly, Bošnjaković et al. (2024), observed dose-dependent decreases in CH₄ emissions on lactating cows without affecting productivity; nonetheless, Antaya et al. (2019) advises caution with high dose inclusion due to potential negative effects from other components accumulation such as iodine. The lower methane-reduction potential of brown seaweed may be related to their greater diversity of bioactive compounds and, consequently, their lower concentrations of halogenated metabolites, which are the primary anti-methanogenic agents in red seaweeds (Makkar et al., 2016).

3.3 Effectiveness of methane mitigation strategies under heat stress

As previously explained, heat stress induces a wide range of physiological alterations, many of which could modify the effectiveness of methane-mitigation strategies, particularly dietary ones. However, few studies have directly evaluated methane-mitigation interventions under HS conditions. Consequently, our discussion in this section is necessarily speculative and based on the physiological responses reported for methane-mitigation supplements when tested under HS, where such information exists.

For example, monensin supplementation has been evaluated in growing dairy calves exposed to thermoneutral or HS conditions induced by a respiratory chamber. In that study, monensin partially counteracted the negative effects of HS by improving weight gain, feed efficiency, and total VFA concentrations relative to heat-stressed non supplemented calves; however, these improvements did not restore performance to the levels observed in thermoneutral non supplemented calves (Salles et al., 2008). A separate study in lactating cows compared heat-stressed versus pair-fed thermoneutral cows, with or without monensin supplementation including pre-HS baseline measurements. As expected, HS reduced DMI relative to the pre-HS baseline period and the thermoneutral group was adjusted to the HS level of intake. Monensin further decreased DMI in both pair-fed and HS groups relative to their non-supplemented counterparts. Despite monensin helped improve feed efficiency within both, pair-fed and HS cows relative to their non-supplemented counter parts, pair-fed thermoneutral cows were more feed efficient when compared with HS cows (Baumgard et al., 2011). The authors also measured glucose appearance rate, an indicator of hepatic glucose output, and lactose synthesis. Although monensin increased glucose appearance rate, it did not increase lactose yield in HS cows, suggesting that monensin cannot rescue milk production during HS because glucose is diverted away from the mammary gland toward peripheral tissues when under HS (Baumgard et al., 2011).

Given the absence of studies directly assessing the combined effects of monensin and heat stress on methane emissions, the studies discussed above provide a basis for only cautious speculation regarding their potential interaction. Monensin may reduce total daily methane production under HS because it further decreases feed intake relative to HS alone. Methane intensity may decline in growing animals, as monensin improves feed efficiency even under HS. However, in lactating cows, this potential improvement might not be evident, because the additional energy made available by monensin is redirected to peripheral tissues rather than supporting milk synthesis.

The effects of 3-NOP under season-induced HS conditions were evaluated by Moschini et al. (2025). In their study, methane emissions were measured in cows supplemented with 3-NOP during the summer and fall seasons. As expected, 3-NOP caused a substantial reduction in daily CH₄ production, CH₄ yield, and CH₄ intensity of 46.3%, 46%, and 44.2% respectively. The authors also reported the typical summer-associated decline in DMI and its subsequent reduction in milk yield; however, 3-NOP itself had no main effect on milk production. Daily CH₄ emissions were lower in summer, driven primarily by reduced intake, and H₂ emissions increased with 3-NOP, consistent with its mechanism of action. Although this study cannot establish a causal relationship between HS and the efficacy of 3-NOP, because heat stress was seasonal rather than experimentally imposed, and different cows were used in each period, it provides evidence that 3-NOP effectively reduces CH₄ emissions regardless of heat load.

Although few, if any, studies have evaluated tannin supplementation under HS conditions, several experiments have shown that tannins can enhance oxidative status and modulate immune function, as demonstrated by Santillo et al. (2022). These improvements may, in turn, strengthen the animal’s capacity to cope with HS. However, as previously noted, tannins can negatively affect fiber digestibility, a parameter already compromised under HS, which raises the possibility that tannins, particularly at higher inclusion rates, may further reduce both daily methane emissions and methane intensity by simultaneously lowering intake and depressing digestibility which is not desired under HS.

A limited body of research has examined the effects of seaweed on methane emissions under HS, and the few existing studies have focused exclusively on brown seaweed. As noted previously, brown seaweeds exhibit a much lower capacity to reduce CH₄ emissions than red seaweeds, likely due to their greater diversity of bioactive compounds and correspondingly low concentrations of halogenated metabolites (Makkar et al., 2016). Nevertheless, the higher levels of other constituents, particularly sodium chloride and potassium gluconate in A. nodosum (Archer et al., 2008), have been proposed as beneficial for supporting animals under HS. For example, Williams et al. (2009) reported small reductions in respiration rate in steers supplemented with brown seaweed during HS conditions. However, other studies have not observed improvements in HS responses or in resilience to other stressors such as transportation, and no consistent effects on production traits have been documented (Makkar et al., 2016). To date, no studies have simultaneously evaluated the effects of seaweed supplementation on both HS and methane emissions; existing research addresses these outcomes independently. Based on the proposed mechanisms of action and the distinct active compounds involved, the effects of brown seaweed on CH₄ mitigation and HS responses appear to be unrelated, suggesting little potential for interaction. Overall, current evidence indicates that the efficacy of brown seaweed in reducing either methane emissions or heat stress remains uncertain, and additional controlled in vivo research is required to clarify its potential.

3.4 Where is H₂ going to when CH₄ is reduced?

As previously mentioned, CH₄ production in the rumen depends on the availability of CO₂ and H₂. While CO₂ is generally assumed to be expelled or combined with CO₂ from the respiratory tract when CH₄ is inhibited, the expected increase in H₂ emissions is not always observed. This raises the question, where is excess H₂ being redirected to during methanogenesis inhibition?

Ungerfeld (2018) has explored how methane inhibition, specifically through compounds like 3-NOP and seaweed that selectively target methanogens without affecting other ruminal microorganisms, can alter H₂ flow, rumen fermentation, and even post-absorptive metabolism. However, the author emphasizes that significant changes in these processes typically require substantial reductions in CH₄ due to the buffering capacity and dynamics of dissolved H₂ in the rumen. Supporting this, Morgavi et al. (2023) reported that CH₄ reductions are not linearly correlated with H₂ emissions. For example, an 80% reduction in CH₄ resulted in only an 11% increase in expelled H₂, suggesting that much of the H₂ may be redirected into alternative metabolic pathways. Further, Ungerfeld et al. (2022) demonstrated that inhibiting more than 50% of CH₄ production leads to decreased dry matter intake, increased concentrations of dissolved H₂ in rumen fluid, and a reduced acetate-to-propionate molar ratio. This suggests that some of the redirected H₂ may be channeled into the propionate pathway, potentially explaining the observed decrease in intake. Interestingly, no reduction in milk fat concentration was observed in these studies. Nevertheless, it is well established that accumulation of H₂ in the rumen can inhibit fermentation (Wolin et al., 1997). Therefore, caution is warranted when interpreting the effects of large CH₄ reductions. Several studies have reported no significant responses of H₂ to CH₄ inhibition, which may be attributed to the complex dynamics of H₂ in the rumen and variability in measurement techniques (Morgavi et al., 2023). As such, further research is needed to better understand the fate of H₂ when CH₄ production is suppressed.

4 Heat stress effects on enteric methane emissions from cattle

The effects of HS on CH₄ emissions in ruminants remain relatively unexplored. Yadav et al. (2016) investigated CH₄ emissions in cows subjected to simulated HS and observed a reduction in daily average emissions, along with inconsistent fluctuations in CH₄ yield. However, the study involved only four non-lactating crossbred cows and limited HS exposure to a few hours per day in RC, which may account for the variability in the results given the short exposure to HS and changes in eating behavior induced by RC; nonetheless, Yadav et al. (2016) study marked a baseline to understand the potential relationship of HS and CH₄ emissions. Later, Souza et al. (2023), employed a predictive modeling approach using data from previous HS trials rather than direct measurements to describe the impact of HS on CH₄ emissions in lactating dairy cows. Their model indicated a positive relationship between DMI and both daily CH₄ production and yield, while HS was negatively correlated with milk yield. Additionally, CH₄ intensity was found to increase with greater HS exposure. Similarly, Chen et al. (2024) developed a heat-stress simulation herd model, a methane prediction framework that incorporated different combinations of input variables under heat-stress conditions: (1) milk yield; (2) milk yield and reproduction; and (3) milk yield, reproduction, and health. Across all variable combinations, their model indicated that heat stress could increase methane intensity by up to 6.6% when the stress period extends to four months and milk yield, reproduction, and health was accounted for.

Methane emissions from dairy cattle are influenced by DMI, with greater feed consumption leading to increased total CH₄ production due to greater substrate availability for ruminal fermentation (Hristov and Melgar, 2020; Bačėninaitė et al., 2022). Heat stress decreases intake, which in consequence is expected to decrease total methane emitted. Indeed, this was confirmed by Onan-Martinez et al. (2026) as they observed a reduction in daily CH4 emissions along with a reduction in DMI in HS cows compared with cooled cows. While total CH₄ indicates the total amount of CH₄ released, methane yield and intensity are of importance since they indicate efficiency. Souza et al. (2023) estimated that HS decreases methane yield which could be supported by the findings of Meneses et al. (2021) who investigated VFA shifts in heifers exposed to HS and thermoneutral conditions including a pair-fed thermoneutral group. They found that the proportion of ruminal propionic acid was greater in the HS group, potentially leading to lower CH₄ yield by redirecting more hydrogen into propionate formation. Indeed, Wang et al. (2023) describe how increases in propionate formation can partially mitigate methane production in the rumen by reducing the availability of H₂. However, Onan-Martinez et al. (2026) observed increased methane yield in cows exposed to HS compared with cooled cows, they also reported reductions in rumination time and rumen motility. Heat-stress-induced declines in both variables, rumination time and rumen motility, may indicate a slower feed passage rate, which in turn increases rumen retention time (Yadav et al., 2016). Longer retention allows more extensive substrate fermentation, potentially elevating methane yield even in the presence of a higher proportion of ruminal propionic acid, as suggested by Meneses et al. (2021). Souza et al. (2023) and Chen et al. (2024) estimated increased methane intensity based on their predictive models which were later confirmed by Onan-Martinez et al. (2026). Increased intensity is driven by the negative impact of HS on mammary gland function, leading to a reduction in milk yield beyond what would be expected from decreased feed intake alone (Capuco et al., 2003; Tao et al., 2018) leading to increased methane emissions per unit of milk.

The reduction in DMI under HS remains the primary driver of decreased total daily methane output. However, HS also induces multiple gastrointestinal physiological adaptations that extend beyond intake depression. Lower rumination time, partly a consequence of reduced feed intake, and a slower passage rate, likely associated with reduced gastrointestinal blood perfusion, which is diverted towards peripheral tissues, both act to minimize metabolic heat production. Saliva flow to the rumen declines, because of both reduced rumination and water-conserving responses, contributing to a lower ruminal pH. Evidence further indicates that lactate-producing bacteria exhibit greater tolerance to elevated rumen temperatures, reinforcing the decline in pH. This more acidic environment favors a shift from acetate toward propionate, as propionate-producing bacteria perform better under lower pH conditions. Although increased propionate should theoretically enhance ruminal H₂ sequestration and thereby reduce methane yield, this could be dependent on starch inclusion level in the diet. Our controlled study shows that methane yield increases under HS; this paradox is likely explained by increased rumen retention time, which allows more complete substrate fermentation and greater total VFA production, ultimately increasing methane yield despite the reduced acetate to propionate ratio (Onan-Martinez et al., 2026). Beyond the rumen, postabsorptive metabolism is markedly altered under HS due to endocrine adjustments aimed at maintaining homeostasis. Circulating prolactin concentrations increase, reflecting its role in electrolyte and osmolyte regulation, although its classical effects on the mammary gland are blunted because HS reduces mammary prolactin receptor abundance (do Amaral et al., 2010; Fabris et al., 2020). Concurrently, insulin concentrations rise, a response thought to prioritize glucose uptake by peripheral tissues and secure energy supply to vital organs which exhibit increased insulin sensitivity to insulin under HS conditions (Tao et al., 2012). This diversion of glucose away from the mammary gland limits lactose synthesis and contributes to a disproportionate decline in milk yield that exceeds what would be expected from reduced DMI alone. Consequently, methane intensity increases, even when total methane output declines.

In conclusion, the available evidence suggests that methane emissions are primarily driven by DMI, as intake is the main determinant of total CH₄ output, whereas CH₄ yield is more closely associated with changes in rumen physiology under HS conditions. However, caution is warranted when interpreting CH₄ yield during HS, because shifts in forage-to-concentrate ratio may alter rumen fermentation patterns and subsequently influence CH₄ yield. Methane intensity, in turn, is largely affected by the negative impact of HS on the mammary gland, which limits its capacity to synthesize milk beyond what can be explained by reduced DMI alone. Additionally, the diversion of energy toward heat dissipation in peripheral tissues further restricts the energy available for mammary gland metabolism (or tissue accretion in beef cattle), thereby increasing CH₄ intensity.

While the evidence presented here suggests that HS negatively affects methane emissions, more controlled studies are needed to integrate rumen function, pH and temperature dynamics, shifts in rumen microbiota, and the resulting alterations in gas production, all of which interact to influence methane emissions in dairy cattle. A comprehensive understanding of these interactions is essential because HS alters multiple physiological systems simultaneously, making it difficult to attribute methane responses to any single mechanism. Moreover, integrating these components within the same experimental framework would allow researchers to disentangle direct thermal effects from indirect nutritional and microbial pathways, ultimately improving the accuracy of methane mitigation strategies under HS conditions.

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Footnotes

Edited by: Todd Riley Callaway, University of Georgia, United States

Reviewed by: Ljubomir Jovanovic, University of Belgrade, Serbia

Lina Anskienė, Lithuanian University of Health Sciences, Lithuania