The agricultural sector, encompassing agriculture, forestry, and land use, significantly contributes to global greenhouse gas (GHG) emissions, accounting for 23% of the total (IPCC 2019).  It faces substantial challenges due to population growth and the urgent need to reduce its GHG emissions.  Livestock husbandry, a crucial component of agriculture, accounts for a significant proportion of agricultural GHG emissions (Nugrahaeningtyas et al. 2024).  Reducing emissions from livestock is essential not only for addressing climate change but also for protecting the ecological environment and achieving sustainable development.  This is a critical task for the future of our planet and the well-being of future generations.

In recent years, China has made significant strides in reducing GHG emissions (MEE 2024), particularly in mitigating emissions from livestock (He et al. 2023).  This Special Focus of the Journal of Integrative Agriculture (JIA) explores innovative strategies proposed by Chinese researchers with practical potential for reducing livestock GHG emissions while maintaining productivity and cost efficiency.  The Focus comprises nine papers covering strategies such as optimizing livestock production systems, selecting animal genetics, and formulating balanced diets.  We hope these articles provide readers with detailed insights into China’s efforts to reduce livestock-related GHG emissions and offer valuable perspectives for policymakers, researchers, and industry professionals.

Section 1: Livestock production systems

This section examines the characteristics of GHG emissions from various livestock production systems, including dairy farms, grassland grazing systems, and silage-based feeding.  The studies analyze how these systems influence GHG emissions, nutrient utilization, and animal performance.

Abdul et al. (2025) assessed the contribution of cattle farms to methane emissions globally, identifying strategies such as modifying feed quantity and quality and altering gut microflora to reduce emissions.  This research introduces a novel method for estimating GHG emissions, which could also be applied to other livestock species.

Shi et al. (2025) investigated the effects of stocking rates on growth performance, energy and nitrogen utilization, and methane emissions in grazing systems.  Their results indicate that higher stocking rates may lead to lower methane emissions, underscoring the importance of optimizing grazing management based on the nutritional value of grasses.

Tian et al. (2025) analyzed the impact of different silages on gas production, including CO₂, CH₄, and N₂O, and examined the effects of adding Lactiplantibacillus plantarum (LP) or corn meal (CM) on reducing emissions.  Their findings reveal that triticale silage produced more gas than oat silage, while LP and CM significantly reduced gas production.  The study also identified Lactococcus and Enterobacter as bacterial biomarkers for assessing gas emissions from silage.  These findings contribute to reducing GHG emissions in silage production.

The findings from these studies highlight potential strategies for mitigating GHG emissions in both extensive farming and grazing systems.

Section 2: Animal genetics

This section explores the influence of animal genetics on GHG emissions, focusing on species-specific characteristics.  The studies analyze how genetic factors affect GHG emissions and feed efficiency in different ruminants.

Zhang et al. (2025) conducted a genome-wide association study on Hu lambs and identified two single nucleotide polymorphisms positively associated with feed efficiency, providing promising molecular markers for genetic selection in sheep.  These findings offer valuable reference data and key genetic variants for breeding feed-efficient sheep.

Wang et al. (2025) examined the effects of different ratios of yak to cattle inocula on methane production and fiber digestion.  Their findings indicate that increasing the proportion of yak inoculum reduces methane production while enhancing fiber digestibility and volatile fatty acid production.  The results suggest that yaks produce less methane than cattle, providing valuable data for genetic selection among ruminants.

These findings highlight species-specific methane production characteristics.  Genome-wide association studies may serve as valuable tools for identifying potential genetic markers for future breeding programs aimed at reducing methane emissions.

Section 3: Diet components and feed additives

This section examines the impact of diet composition and feed additives on GHG emissions.  The studies analyze how these factors influence nutrient metabolism, GHG emissions, and the ruminal microbial community.

Li et al. (2025) investigated the effect of dietary fat on nitrogen metabolism efficiency in lambs.  Their findings suggest that a high-fat diet may enhance body weight gain, energy utilization, and nitrogen efficiency by promoting rumen propionate fermentation through Succinivibrio enrichment.

Biao et al. (2025) examined the impact of feeding steers sorghum grain rich in condensed tannins.  Their results show that while nitrogen utilization efficiency remained unchanged, urinary nitrous oxide emissions increased.  These findings suggest that high levels of tannin-rich sorghum grain may not be an effective feed component for reducing GHG emissions.

Ma et al. (2025) studied the effects of cordycepin on methane emissions in vitro.  Their results indicate that cordycepin significantly reduces methane production by shifting rumen fermentation from acetate to propionate formation and decreasing the relative abundance of Methanobrevibacter.

Liu et al. (2025) reviewed the effects of seaweed, particularly Asparagopsis taxiformis, on methane emissions from ruminants in vitro and in vivo.  They found that the seaweed has significant potential for mitigating enteric methane emissions, primarily due to its bromoform content.

These findings underscore the importance of diet composition and feed additives in reducing livestock GHG emissions.  Optimizing dietary components and supplementing feed additives could be a practical and effective strategy for lowering emissions in the near future.

This Special Focus contributes to the advancement of green, low-carbon, and sustainable livestock production.  By addressing livestock production systems, animal genetics, and diet optimization, these studies provide valuable knowledge and practical strategies for reducing GHG emissions while improving feed efficiency.  However, further research is needed to refine management practices in both extensive and intensive systems, identify additional genetic markers for targeted breeding, optimize feed formulations, enhance nutrient digestibility, and develop more effective, economical, and environmentally friendly feed additives.  We hope this collection will attract increasing attention from researchers and industry professionals interested in sustainable livestock production.

Methane contributes to global warming, and livestock is one of the sources of methane production.  However, methane emission studies using bibliometric tools in livestock are lacking.  Given the negative impact of climate change on the ecosystem and the rise in methane emissions, it is essential to conduct a bibliometrics study to provide an overview and research trends.  We used the Bibliometrix package and VOSviewer to decipher bibliometric indices for methane emissions in cattle farms (MECF).  Current dataset were collected from the Web of Science (Core Collection) database, and 8,998 publications were analyzed.  The most co-occurring keywords scientists preferred were methane (1,528), greenhouse gas (443), methane emissions (440), and cattle (369).  Methane was the most frequently used keyword in the published scientific literature.  Thematic evolution of research themes and trend results highlighted carbon dioxide, methane, dairy cattle, cattle, and risk factors during 1999–2017.  Chinese Academy of Sciences ranked on top with 485 publications, followed by Agriculture & Agri-Food Canada, University of Colorado, National Oceanic and Atmospheric Administration, and Aarhus University.  Chinese Academy of Sciences was also the most cited organization, followed by the University of Colorado, Agriculture & Agri-Food Canada, National Oceanic and Atmospheric Administration, and United States Geological Survey.  Source analysis showed that the Science of the Total Environment was cited with the highest total link strength.  Science of the Total Environment ranked first in source core 1 with 290 citation frequencies, followed by Journal of Dairy Science with 223 citation frequencies.  Currently, no bibliometric study has been conducted on MECF, and to fill this knowledge gap, we carried out this study to highlight methane emissions in cattle farms, aiming at a climate change perspective.  In this regard, we focused on the research productivity of countries authors, journals and institutions, co-occurrence of keywords, evolution of research trends, and collaborative networking.  Based on relevance degree of centrality, methane emissions and greenhouse gases appeared as basic themes, cattle, and dairy cattle appeared as emerging/declining themes, whereas, methane, greenhouse gas and nitrous oxide appeared to fall amongst basic and motor themes.  On the other hand, beef cattle, rumen and dairy cow seem to be between motor and niche themes, and risk factors lie in niche themes.  The present bibliometric analysis provides research progress on methane emissions in cattle farms.  Current findings may provide a framework for understanding research trends and themes in MECF research. 

Understanding livestock performance in typical steppe ecosystems is essential for optimizing grassland-livestock interactions and minimizing environmental impact.  To assess the effects of different stocking rates on the growth performance, energy and nitrogen utilization, methane (CH₄) emissions, and grazing behavior of Tan sheep, a 2-year grazing experiment in the typical steppe was conducted.  The grazing area was divided into 9 paddocks, each 0.5 ha, with 3 spatial replicates for each stocking rate treatment (4, 8, and 13 sheep per paddock), corresponding to 2.7, 5.3, and 8.7 sheep ha^–1.  The results showed that the neutral detergent fiber (NDF) and acid detergent fiber (ADF) contents of herbage varied between grazing years (P<0.05), with a positive correlation between stocking rate and crude fiber content in the herbage (P<0.05).  Dry matter intake (DMI) decreased with increasing stocking rate (P<0.05), and the average daily gain (ADG) was highest at 2.7 sheep ha^–1 (P<0.05).  Compared to 2.7 and 8.7 sheep ha^–1, the 5.3 sheep ha^–1 treatment exhibited the lowest nutrient digestibility for dry matter, nitrogen, and ether extract (P<0.05).  Fecal nitrogen was lowest at 8.7 sheep ha^–1 (P<0.05), while retained nitrogen as a proportion of nitrogen intake was highest.  Digestive energy (DE), metabolic energy (ME), and the ratios of DE to gross energy (GE) and ME to GE were highest at 8.7 sheep ha^–1 (P<0.05).  In contrast, CH₄ emissions, CH₄ per DMI, and CH₄E as a proportion of GE were highest at 2.7 sheep ha^–1 (P<0.05).  Stocking rate and grazing year did not significantly affect rumen fermentation parameters, including volatile fatty acids, acetate, propionate, and the acetate/propionate ratio.  At 8.7 sheep ha^–1, daily grazing time and inter-individual distance increased, while time allocated to grazing, walking, and ruminating/resting decreased as stocking rates increased (P<0.05).  This study highlights the importance of adjusting stocking rates based on the nutritional value of forage and grazing year to optimize grazing management. 

Greenhouse gas (GHG) production during ensiling not only causes the nutrient losses of silage but also promotes climate warming.  However, there is little information on the production of GHG and strategies for mitigating GHG emissions during ensiling.  This work aimed to study the gas production characteristics and techniques for reducing gas emissions during ensiling.  Oats and triticale, with Lactiplantibacillus plantarum (LP) or corn meal (CM) addition, were ensiled.  The cumulative gas volume rapidly increased and reached to the peak within the first 9 d of ensiling for both forage crops.  The highest cumulative gas volume of triticale silage was twice as much as that of oats silage.  Triticale silage produced lower carbon dioxide (CO₂) concentration, higher methane (CH₄) and nitrous oxide (N₂O) concentrations than oats silage within the 28 d of ensiling.  Adding LP or CM significantly improved the fermentation quality and decreased the gas volume and GHG concentrations of 2 silages on d 56 (except CH₄ of triticale).  At the early stage of ensiling, more Enterobacter, Lactococcus and Leuconostoc related to gas production were observed, and adding LP increased the abundance of Lactobacillus and decreased the abundance of bacteria like Kosakonia, Pantoea, Enterobacter and Lactococcus positively correlated with gas volume, CO₂ and N₂O concentrations.  These results suggest that gas formation during ensiling mainly occurs in the first 9 d.  Adding LP or CM can significantly improve the fermentation quality and decrease the gas volume.  This would benefit to reducing GHG emissions in silage production.

The aim of this study was to investigate the effects of dietary fat on energy and nitrogen (N) metabolism efficiency, rumen fermentation, and microbiota in twin suckling lambs.  Thirty pairs of twin male lambs were randomly divided into two groups with one group receiving a high-fat diet (HF) and the other a normal-fat diet (NF).  Two diets (milk replacer and starter) of equal protein and different fat levels.  The metabolism test was conducted when the lambs were 50–60 days old, and nine pairs of twin lambs were randomly selected for slaughter to collect rumen fluid at 60 days old.  The result showed that fat addition increased the final body weight (BW), ruminal ammonia nitrogen (NH₃-N) content, proportion of propionic acid, and estimated methane production (CH_4e) (P<0.05).  The high fat diet tended to improve digestive energy (DE), metabolism energy (ME), DE/ME, utilisation of N (0.05<P<0.1).  However, microbial crude protein (MCP) content, total volatile fatty acids (VFA), acetic acid ratio, and the ratio of acetate to propionate (A:P) were lower than that in the NF group (P<0.05).  Regardless of whether fat is added or not, no different were observed in blood metabolites between the treatment.  High-throughput sequencing revealed that fat addition before weaning increased phyla Proteobacteria and genera of Succinivibrio, but decreased the relative abundance of Clostridium IV, Dialister, Roseburia, Acidaminococcus, and Megasphaera genera.  These findings indicated that high fat diet improved body weight, energy and nitrogen utilization may by shifting the rumen toward propionate fermentation via the enrichment of Succinivibrio.

The TSJT1 protein belongs to the class-II glutamine amidotransferase (GATase) superfamily.  Research on the functions and underlying mechanisms of TSJT1 in plants is limited.  In this study, the abscisic acid (ABA)-inducible gene IbTSJT1 was isolated from drought-tolerant sweetpotato line Xushu 55-2.  Its expression was strongly induced by PEG6000 and ABA.  The IbTSJT1 protein was localized in the nucleus and cell membrane.  IbTSJT1-overexpressing sweetpotato plants exhibited significantly enhanced drought tolerance.  Their ABA and proline contents and superoxide dismutase (SOD) and peroxidase (POD) activities were increased, and their reactive oxygen species (ROS) scavenging-related genes were upregulated under drought stress.  The stomatal aperture assay confirmed that the IbTSJT1-overexpressing plants had greater sensitivity to ABA.  The results of yeast one-hybrid (Y1H) assay, electrophoretic mobility shift assay (EMSA), luciferase reporter assay and ChIP-qPCR assay indicated that IbABF2 can directly bind to the cis-acting ABA-responsive element (ABRE) in the IbTSJT1 promoter to activate the expression of IbTSJT1.  These findings suggest that IbTSJT1 mediates ABA-dependent drought stress responses and enhances drought tolerance by inducing stomatal closure and activating the ROS scavenging system in transgenic sweetpotato.  Our study provides a novel gene for improving drought tolerance in sweetpotato and other plants. 

The wheat above-ground biomass (AGB) is an important index that shows the life activity of vegetation, which is of great significance for wheat growth monitoring and yield prediction.  Traditional biomass estimation methods specifically include sample surveys and harvesting statistics.  Although these methods have high estimation accuracy, they are time-consuming, destructive, and difficult to implement to monitor the biomass at a large scale.  The main objective of this study is to optimize the traditional remote sensing methods to estimate the wheat AGB based on improved convolutional features (CFs).  Low-cost unmanned aerial vehicles (UAV) were used as the main data acquisition equipment.  This study acquired RGB and multi-spectral (MS) image data of the wheat population canopy for two wheat varieties and five key growth stages.  Then, field measurements were conducted to obtain the actual wheat biomass data for validation.  Based on the remote sensing indices (RSIs), structural features (SFs), and convolutional features (CFs), this study proposed a new feature named AUR-50 (Multi-source combination based on convolutional feature optimization) to estimate the wheat AGB.  The results show that AUR-50 could more accurately estimate the wheat AGB than RSIs and SFs, and the average R² exceeded 0.77.  AUR-50_MS had the highest estimation accuracy (R² of 0.88) in the overwintering period.  In addition, AUR-50 reduced the effect of the vegetation index saturation on the biomass estimation accuracy by adding CFs, where the highest R² was 0.69 at the flowering stage.  The results of this study provide an effective method to evaluate the AGB in wheat with high throughput and a research reference for the phenotypic parameters of other crops.

Adelphocoris suturalis is a polyphagous pest that is increasingly causing severe economic damage due to more frequent outbreaks.  The development of non-target resistance to commercial Bacillus thuringiensis (Bt) cotton has further exacerbated its pest status and amplified the need for more sustainable methods of control.  RNA interference (RNAi)-based pest management strategies, such as root soaking and transgenic plants that express dsRNAs, have proven to be reliable, eco-friendly pest control strategies.  To identify new RNAi targets for potential A. suturalis population control, we investigated the target of rapamycin (TOR) signaling pathway.  A critical role for this pathway in A. suturalis reproductive regulation was suggested by pharmacological analyses.  Subsequent RNAi-mediated knockdown of the A. suturalis TOR pathway genes TOR, Ras homolog enriched in the brain (Rheb), and ribosomal S6 kinase (S6K) reduced fertility.  Moreover, a spray-induced and nanocarrier-delivered gene silencing (SI-NDGS) system targeting TOR successfully suppressed ovarian development, which demonstrates its effectiveness as a pest control target.  These results provide a critical foundation for understanding reproductive regulation in A. suturalis and introduce new candidates for RNAi-based A. suturalis management.

The accumulation of soil organic carbon (SOC) and total nitrogen (TN) is easily accomplished by returning crop straw, which strongly affects the formation and pore structure of aggregates, especially in black soil.  We returned maize straw at different rates (6,000, 9,000, 12,000 and 15,000 kg ha^–1) for nine years to investigate its influence on the SOC and TN contents in the SOC fractions of aggregates by combining size and density fractionation.  Their subsequent influences on pore morphology and size distribution characteristics were examined using X-ray micro-computed tomography scanning (μCT).  The results showed that returning straw significantly increased the contents of C and N in the SOC fractions of aggregates, especially at the return rates of 12,000 and 15,000 kg ha^–1, which in turn promoted aggregate formation and stability, and ultimately amended pore structure.  The pore size>100 μm, porosity (>2 μm), and morphological characteristics (anisotropy, circularity, connectivity and fractal dimension) significantly increased, but the total number of pores significantly decreased (P<0.05).  Our results indicated that the amendment of the pore morphology and size distribution of soil aggregates was primarily controlled by the higher contents of C and N in the density fractions of aggregates, rather than in the aggregate sizes.  Furthermore, this pore network reconfiguration favored the storage of C and N simultaneously.  The findings of this study offer valuable new insights into the relationships between C and N storage and the pore characteristics in soil aggregates under straw return.