Search Results (705)

Livestock represent a key asset in the livelihood of smallholder farmers and play a critical role in the social dynamics and nutritional security of resource-poor communities. However, within these resource-poor communities, livestock productivity remains low. This is often due to seasonal changes in the quantity and quality of available feed from the natural veld, which in turn also contributes to methane production. This study aimed to evaluate the effects of supplementing Eragrostis curvula hay with Searsia lancea leaf or silage meal on in vitro fermentation efficiency and gas and methane production. Therefore, an in vitro study using a semi-automated pressure transducer technique was conducted on grass hay alone (control) and grass hay supplemented with 15% or 30% of either S. lancea leaf or silage meal. The dietary treatments were arranged in a complete randomized design, with each treatment replicated four times. Total gas and methane production was recorded at 3, 6, 12, 24 and 48 h using a pressure transducer attached to a data logger. After incubation, samples were collected to determine volatile fatty acids. Supplementing grass hay with 15% S. lancea leaf meal increased gas production by 76%, 52%, 32% and 12% in the first 24 h of incubation. Similarly, increasing the supplementation level to 30% increased gas production by 75%, 63%, 45% and 14%. However, supplementing grass hay with silage meal at 15% significantly reduced gas production by 37% during the first 3 h of incubation, whereas supplementation at 30% had no effect. Supplementing grass hay with S. lancea meals effectively reduced methane production at 24 and 48 h. Grass hay supplemented with 15% or 30% silage meal reduced methane by 46% and 39% at 24 h, while at 48 h, methane was reduced by 39% and 49%, respectively. Supplementing grass hay with S. lancea meals, however, did not affect volatile fatty acids. In conclusion, S. lancea can be strategically used as a supplementary feed source to modulate the rumen ecosystem by attenuating enteric methane production. Further studies are required to determine the effect of S. lancea on rumen microbial composition and its metabolic function. Full article

This study demonstrates a hierarchical spectral modelling approach for predicting pasture nutrition metrics using TabPFN (Tabular Prior-Data Fitted Network), a transformer-based machine learning architecture. In the face of climate variability, aligning stocking rates with pasture resources is crucial for sustainable livestock grazing, requiring accurate assessments of both pasture biomass and nutrient composition. Our research, conducted across diverse growth stages at five tropical and subtropical savanna rangeland properties in Queensland, Australia, with native and introduced C4 grasses, employed a hierarchical sampling and modelling strategy that scales from laboratory spectroscopy to Sentinel-2 satellite predictions via uncrewed aerial vehicle (UAV) hyperspectral imaging. Spectral data were collected from leaf (laboratory spectroscopy) through field (point measurements), UAV hyperspectral imaging, and Sentinel-2 satellite imagery. Traditional laboratory wet chemistry methods determined plant leaf and stem nutrient content, from which crude protein (CP = total nitrogen (TN) × 6.25) and dry matter digestibility (DMD = 88.9–0.779 × acid detergent fibre (ADF)) were derived. TabPFN models were trained at each spatial scale, achieving validation ${\mathrm{R}}^2$ of 0.76 for crude protein at the leaf scale, 0.95 at the UAV scale, and 0.92 at the Sentinel-2 satellite scale. For dry matter digestibility, validation ${\mathrm{R}}^2$ was 0.88 at the UAV scale and 0.73 at the Sentinel-2 scale. A pasture classification masking approach using a deep neural network with 98.6% accuracy (7 classes) was implemented to focus predictions on productive pasture areas, excluding bare soil and woody vegetation. The Sentinel-2 models were trained on 462 samples from 19 site–date combinations across 11 field sites. The TabPFN architecture provided notable advantages over traditional neural networks: no hyperparameter tuning required, faster training, and superior generalisation from limited training samples. These results demonstrate the potential for accurate and efficient prediction and mapping of pasture quality across large areas (100 s–1000 s ${\mathrm{k}\mathrm{m}}^2$) using freely available satellite imagery and open-source machine learning frameworks. Full article

Amidst global urbanization and rising psychological stress, urban green spaces are increasingly recognized as critical infrastructure for sustainable urban development and public health. However, the mechanisms by which summer vegetation structure mediates both physiological and psychological restoration, and the interplay between these two dimensions, remain poorly understood. Understanding these mechanisms is essential for designing sustainable, health-promoting urban environments that can support growing urban populations in a warming climate. This study employed a controlled field experiment in Xi’an during summer to examine the effects of five vegetation structure types (Single-Layer Grassland, single-layer woodland, tree–shrub–grass composite woodland, tree–grass composite woodland, and a non-vegetated square) on university students’ physiological (heart rate variability) and psychological (perceived restorativeness and affective states) restoration. Following stress induction, 300 participants engaged with the green spaces through both quiet sitting and walking. The results revealed three key findings: (1) the tree–shrub–grass composite woodland consistently showed the most favorable trends other vegetation types across all psychological restoration dimensions, while also showing favorable trends in physiological recovery, underscoring the importance of structural complexity for restorative quality; (2) walking significantly enhanced physiological recovery compared to seated observation across all settings, confirming the role of physical activity as a critical activator of green space benefits; (3) correlation analysis identified a specific cross-system association: the R-R interval recovery value showed a weak but significant correlation with positive affect (PA) scores, suggesting that physiological calmness and positive emotional experience are linked, yet their weak coupling under short-term exposure indicates they may operate as parallel processes with distinct temporal dynamics. These findings indicate that the restorative potential of summer green spaces emerges from an integrated framework combining vegetation complexity and activity support. We propose that future sustainable landscape design should prioritize multi-layered vegetation structures as nature-based solutions that simultaneously enhance human well-being and urban resilience. These findings provide empirical evidence for integrating health-promoting green infrastructure into sustainable urban planning frameworks, supporting multiple Sustainable Development Goals (SDGs), including SDG 3 (Good Health and Well-being), SDG 11 (Sustainable Cities and Communities), and SDG 13 (Climate Action). Full article

The alpine grassland ecosystem in the Source Region of the Yellow River (SRYR) faces the dual pressures of ecological protection and economic development. Its ecological fragility and climate sensitivity make local animal husbandry susceptible to meteorological disasters. To overcome adverse selection and moral hazard in traditional animal husbandry insurance, this study integrates 963 field sampling observation data, over 400 valid herdsmen survey data, and long-term environmental time series variables. A random forest model (R² = 0.59, RMSE = 65.84 g/m², superior to the artificial neural network in this paper) was used to estimate grass yield. Hodrick–Prescott (HP) filtering was used to separate meteorological yield per unit area and derive yield loss rate. A joint distribution model of meteorological indicators and loss rate was constructed using a Copula function to capture tail-dependent structures, providing a basis for determining trigger thresholds and actuarial pricing of pure insurance premiums. The study reveals the transmission mechanism of climate disasters to feeding costs and designs regional drought and snow disaster index insurance. The compensation standard is based on meteorological indicators falling below the trigger threshold and a yield reduction rate greater than 5%. Using 10,000 Monte Carlo simulations, the drought premium rates for zones I-IV are determined to be 2.03–6.03%, and the snow premium rates to be 2.25–5.42%, corresponding to a premium of RMB 5.21–9.61 per mu for drought and RMB 5.78–8.64 per mu for snow. This design reduces basis risk through zoning and composite triggering, providing a scientific tool for climate risk management in alpine grasslands. Full article

Canine atopic dermatitis (CAD) is a chronic, pruritic inflammatory disease that affects up to 15% of the global canine population. Its etiopathogenesis is multifactorial, involving genetic, immunological, environmental, and dietary factors. It is characterized by pruritus, erythema, alopecia, and secondary lesions, predominantly affecting the abdomen, extremities, and ears. This retrospective cross-sectional descriptive study analyzed 735 medical records of dogs diagnosed with CAD treated at the Veterinary Specialty Center (CEVET) in Quito, Ecuador, between January 2018 and July 2025. Demographic, clinical, housing, diet, and cohabitation data were collected and statistically analyzed using χ² for qualitative variables and the Kruskal–Wallis test for quantitative variables, with post hoc analysis as appropriate. Additionally, pruritus severity was assessed using the Pruritus Visual Analog Scale (pVAS). A composite Clinical Severity and Distribution Score (CSDS) was also developed to classify disease severity. A multivariate logistic regression model was performed to identify factors associated with severe CAD. The results showed a predominance of CAD in adult dogs (84.2%) and purebred dogs (74.97%), with a slight majority being males (52.38%). Pruritus was the most frequent initial symptom (80.27%), with most cases presenting moderate-to-severe pruritus (pVAS 7–10). The most affected areas were the abdomen (24.49%) and forelimbs (17.68%). The geographical distribution showed a predominance of urban areas (88.84%) and cold climates (86.39%). Based on the CSDS, 53.2% of cases were classified as severe, 44.4% as moderate, and 2.4% as mild. Multivariate analysis revealed that grass exposure was significantly associated with severe CAD (OR = 1.78; 95% CI: 1.22–2.60; p = 0.003), while urban environment showed a non-significant trend toward increased severity (OR = 1.41; p = 0.071). Significant associations were identified involving sex and body weight, age and affected area, and temporal variations in the severity of pruritus, age group, and distribution of lesions. Among breeds, French Bulldogs, Standard Schnauzers, and Shih Tzus had the highest prevalence of CAD. These findings provide the first systematic epidemiological and clinical characterization of CAD in Ecuador, highlighting the role of environmental factors in disease severity and supporting the use of composite clinical scoring approaches in retrospective studies, thereby contributing to understanding of the disease and serving as a reference for early diagnosis, clinical management, and the development of preventive strategies. Full article

This study aimed to assess the effect of concentrate supplementation frequency on the nutrient intake, performance, carcass characteristics, and tissue composition of sheep for meat raised on Panicum maximum cv. Massai pasture. A group of 36 sheep of the Santa Inês breed (18 males and 18 females) with a mean initial weight of 17.0 ± 1.5 kg and mean age of 90 ± 10 days were assigned to three treatments: supplementation every 24 h, every 48 h, and every 72 h. The formulation comprised ground maize kernels (70%), soybean meal (25%), mineral mix (2.5%), urea (1.8%), table salt (0.5%), and ammonium sulfate (0.2%). The females reached a higher final weight than the males (p < 0.05). Dry matter intake did not differ among the treatment groups (p > 0.05), but the sheep supplemented every 72 h showed greater pasture and neutral detergent fiber (NDF) intake, while those supplemented every 24 h and 48 h consumed more concentrate and had higher total weight gain (7.19 and 7.10 × 5.68 kg) (p < 0.05). The same behavior was found for carcass and meat cut weights and for leg and carcass compacity indexes, but carcass and cut yields were not impacted by supplementation strategy. Supplementation on alternate days, i.e., every 48 h, maintains the performance and productive efficiency levels in sheep kept on Massai grass pasture compared to those supplemented daily, but providing intermittent supplementation with intervals above 48 h is not recommended as a nutritional strategy. Full article

Nitrogen is essential for plant growth. Reliance on synthetic nitrogen fertilisers, however, is costly and contributes to soil degradation. Utilising nitrogen-fixing bacteria as biofertilisers may offer a sustainable alternative, reducing fertiliser costs and environmental impact. In this study, we attempted to isolate nitrogen-fixing bacteria from 14 seed batches of warm-season pasture grasses and successfully isolated bacteria from three of these batches. Whole genome sequencing confirmed the presence of the nif operon within all three isolates. Two seed batches of Cenchrus clandestinus (Hochst. ex Chiov.) Morrone from which nif-containing bacteria were isolated, along with two ‘nif’-negative C. clandestinus seed batches, were used in nitrogen-limiting growth assays. This was done to evaluate the effect of the presence of seed-associated nitrogen-fixing bacteria within a seed batch on nitrogen-limited plant growth and the associated plant microbiome composition, using 16S amplicon sequencing of root and shoot samples. Initial plant growth assays revealed significantly reduced root length between plants grown from seed batches harbouring nitrogen-fixing bacteria and those without, under limiting nitrogen availability, but no resulting shoot biomass reduction was observed. The plant microbiomes of these nif-positive seed batches were also statistically similar to each other, compared to the nif-negative seed batch plants. Plant microbiomes of all four C. clandestinus seed batches were significantly different from their original seed microbiomes, showing shifts in community composition. This study demonstrates the presence of potential nitrogen-fixing bacteria associated with warm-season pasture grass seeds at low abundance and reveals differences in plant-associated bacterial community composition between seed batches harbouring and lacking these bacteria. Full article

Cultivation of perennial mixtures has emerged as an efficient way to produce a large amount of forage, supporting a sustainable livestock industry. The stability and sustainability of forage production is largely controlled by soil health. However, variation in soil health in perennial mixtures still needs further investigation under diverse conditions. Clarifying the relationships between soil physicochemical properties and microbial community is of great importance in better understanding soil health in perennial cultivated grasslands. The effects of mixing combination of alfalfa with timothy or smooth bromegrass on soil health were evaluated through comparing soil nutrients, enzyme activities, microbial community, and forage yield in alfalfa–grass mixtures and corresponding monocultures after seven years of establishment. Mixtures significantly increased forage dry matter yield by 61.39% and 1188.29% in the alfalfa–timothy mixture compared with alfalfa and timothy monocultures, respectively, and by 54.36% and 736.38% in the alfalfa–smooth bromegrass mixture compared with alfalfa and smooth bromegrass monocultures, respectively. Mixtures enhanced soil organic carbon, total nitrogen, nitrate nitrogen and ammonium nitrogen contents, and urease activity, but reduced microbial alpha diversity. Beneficial taxa, such as Bacillus, Paenibacillus, and Mortierella, were enriched. Soil nitrate nitrogen was identified as a key driver influencing bacterial functional composition, while soil organic carbon, ammonium nitrogen, water, alkaline phosphatase, and sucrase exhibited significant effects on fungal functional composition. This study demonstrated that alfalfa–grass mixtures enhance system productivity by improving soil physicochemical properties and reconstructing soil microbial community. It provides a theoretical basis from the viewpoint of soil health for establishing and managing sustainable cultivated grasslands. Full article

This study evaluated combinations of defoliation frequencies and intensities to identify grazing strategies that optimize forage accumulation and morphological composition in mixed pastures of Marandu palisadegrass (Urochloa brizantha cv. Marandu) with the legume Macrotyloma axillare. Treatments consisted of pre-grazing heights of 30 and 40 cm (defining defoliation frequency) combined with post-grazing heights of 15 and 20 cm (defoliation intensity), in a 2 × 2 factorial randomized block design with four repetitions. Forage accumulation rate, morphological component mass, and leaf area index (LAI) were evaluated under rotational stocking. The highest forage accumulation rates of grass and its stems occurred at a pre-grazing height of 30 cm. A taller pre-grazing height (40 cm) resulted in greater pre-grazing forage mass, leaf and stem mass of Marandu palisadegrass and LAI, but it also increased the amount of dead material and post-grazing stem mass. The greatest Macrotyloma forage accumulation occurred under grazing strategies of 30–20 cm and 40–15 cm. Lenient defoliation (20 cm post-grazing height) favored post-grazing leaf mass, whereas severe defoliation (15 cm) favored stem mass. Marandu palisadegrass showed higher LAI at 40 cm pre-grazing height (4.7) than at 30 cm (3.6), with slightly greater values under 20 cm (4.3) than 15 cm (4.1) post-grazing height, while Macrotyloma axillare exhibited low LAI. Across all grazing strategies, the legume mass decreased over time. Therefore, future studies should explore alternative grazing strategies and periodic reseeding of Macrotyloma axillare to maintain its presence in mixed tropical pastures. Full article

Identifying the plant species comprising a pasture, among other aspects, is crucial for assessing its nutritional value for grazing animals and facilitating its effective management. Traditionally, it requires labor-intensive visual inspection. Artificial Intelligence (AI) offers a solution for automatic classification, yet robust datasets for training such models in natural, uncontrolled environments are scarce. This data descriptor presents a dataset of 741 images collected in pasture lands in the Centre of Portugal using standard cameras at a height of 50 cm. A semi-automated annotation pipeline was employed, utilizing a Faster R-CNN model followed by manual verification and refinement. The dataset contains 1744 annotations across four categories: ‘Shrubs’, ‘Grasses’, ‘Legumes’, and ‘Others’. It includes diverse morphological variations and captures real-world challenges such as occlusion and lighting variability. This dataset serves as a benchmark for training object detection models in agricultural settings, facilitating the development of automated monitoring systems for precision agriculture. Such a mechanism could be incorporated into a mobile application, mounted on a drone, or embedded in an animal-worn device, enabling automated sampling and identification of the plant composition within a pasture. Full article

Vegetation in desert ecosystems is strongly affected by seasonal climatic fluctuations and soil physical and chemical properties. Rawdat Nourah is a natural watershed depression within the King Abdulaziz Royal Reserve in Saudi Arabia. It is colonized by grasses, herbs, and shrubs. Climatic variability and soil heterogeneity are influencing the vegetation dynamics and regeneration patterns in this ecosystem. Based on the literature review, no previous study analyzed and determined either the vegetation composition or the soil seed-bank of Rawdat Nourah. So, the general objective of this study is to examine the vegetation composition and its relationships with soil physicochemical properties and soil seed-bank composition across Rawdat Nourah across different seasons. Floristic analyses, vegetation composition, soil properties, and soil seed-bank were performed within two seasons (winter–spring and summer–fall seasons) of 2023–2024. The obtained data were analyzed using multivariate and statistical approaches. Six plant associations were identified: winter–spring (WVG I: Zilla spinosa–Malva parviflora; WVG II: Rhazya stricta–Zilla spinosa; WVG III: Cynodon dactylon–Convolvulus pilosellifolius) and summer–fall (SVG I: Calotropis procera–Pulicaria undulata; SVG II: Cynodon dactylon–Zilla spinosa; SVG III: Rhazya stricta–Schismus arabicus). Species richness was higher in winter–spring (2.4 species stand⁻¹) than in summer–fall (1.66 species stand⁻¹), while the seed-bank densities were 633.9 and 575.1 seeds m⁻², respectively. Vegetation responded strongly to marked seasonal contrasts in temperature and moisture (~15 °C, 11 mm vs. ~36 °C, 3 mm). Moderate human activity enhanced vegetation cover, whereas prolonged grazing exclusion reduced diversity through the dominance of a few species. The response of vegetation structure and species richness to climatic factors varies greatly depending on the increase in water availability, and moisture content during the mild weather Winter–Spring season (mean temperature is 15 °C and rainfall is 11 mm), compared to the Summer–Autumn season (mean temperature is 36 °C and rainfall is 3 mm). The richness and cover of the plants were generally affected by human activity, where long-term grazing will reduce species richness and increase competition between species, making one or two species dominant. Although above-ground vegetation exhibited clear seasonal and spatial shifts in species composition and abundance, these changes were not reflected in the soil seed-bank. This relation suggests that above-ground communities and seed-banks are regulated by different ecological processes under arid conditions. The data of the present study showed low correlation between the current vegetation and the soil seed bank, which reflects a degradation in this region. Therefore, these findings suggest that sustained protection of the King Abdulaziz Royal Reserve is essential for enhancing seed-bank persistence, vegetation recovery, and ecosystem resilience under arid conditions. Full article

The quality of beef fat depends on both intramuscular fat (IMF) content and fatty acid (FA) composition, which can be modulated by finishing diets. This study evaluated the effects of silage type and feeding intensity on IMF deposition, FA profile, desaturase indices, and lipid quality indices in finishing Holstein–Friesian bulls. Thirty-two bulls were assigned to a 2 × 2 factorial design (n = 8/group) and fed total mixed rations for 120 days based on grass silage or maize silage, under intensive (≈50:50 forage:concentrate, DM basis) or semi-intensive feeding (≈70:30). FA composition of longissimus lumborum lipids was determined by GC-FID, and lipid quality indices were calculated, including the atherogenic index (AI), thrombogenic index (TI), and the hypocholesterolemic/hypercholesterolemic ratio (h/H). Feeding intensity increased IMF content (p = 0.001) and the absolute amounts of major FA classes (g/100 g meat). Silage type primarily affected FA composition by increasing n-3 PUFA and lowering the n-6/n-3 ratio in grass silage diets (p = 0.042). Several FAs showed silage type × feeding intensity interactions (p < 0.05), indicating that the response to dietary energy supply depended on the forage base. Overall, feeding intensity mainly regulated lipid deposition, whereas silage type modulated the nutritional profile of intramuscular fat. Full article

Background: Chrysopogon zizanioides (L.) Roberty (vetiver) is a perennial medicinal grass with deep aromatic roots traditionally used for several ailments. Its root essential oil (CZEO) is rich in phytochemicals with documented antimicrobial, anti-inflammatory, and antioxidant activities. Although its anticancer potential remains underexplored, the complex phytochemical profile of CZEO positions it as a promising multi-target therapy, particularly for colorectal (CRC) and lung cancers where resistance and pathway redundancy often limit conventional treatments. Therefore, this study aimed to investigate the phytochemical composition and antiproliferative activity of CZEO from Qatar against colorectal (HCT-116) and lung (A549) cancer cells and to elucidate its molecular targets and mechanisms of action in CRC and lung cancer using network pharmacology and in silico approaches. Methods: CZEO was extracted by steam distillation and characterized using GC–MS. In vitro proliferation assays with HCT-116 colorectal and A549 lung cancer cells were conducted using the Alamar Blue assay. The ten most abundant phytochemicals identified by GC–MS were assessed for drug-likeness and ADMET properties and further analyzed through network pharmacology, molecular docking, and molecular dynamics (MD) simulations to elucidate the molecular targets and mechanisms underlying CZEO’s anticancer activity. Results: GC-MS profiling identified 40 compounds, predominantly sesquiterpenoids (93%), including khusimol, β-eudesmol, α-vetivone, and rosifoliol. CZEO inhibited cancer cell viability in a dose-dependent manner, with IC₅₀ values of 62.95 ± 2.19 µg/mL for HCT-116 and 167.82 ± 6.51 µg/mL for A549 cells, demonstrating greater potency against colorectal cancer. CZEO did not affect the growth of normal human neonatal fibroblasts (HDFn), suggesting potential selectivity for cancerous cells. ADMET predictions indicated favorable pharmacokinetics and low toxicity of CZEO’s top 10 abundant compounds (TACs). Network pharmacology revealed 373 and 394 overlapping gene targets between TACs and lung and colorectal cancer, respectively. The overlapping genes were used to construct a protein–protein interaction (PPI) network to identify hub genes. STAT3 and AKT1 consistently emerged as common top-scoring hub genes in both cancers. Molecular docking of TACs showed strong binding affinities of rosifoliol and α-vetivone to AKT1 (−6.20 and −5.93 kcal/mol, respectively) and STAT3 (−5.19 and −5.09 kcal/mol, respectively), surpassing reference inhibitors. MD simulations confirmed stable ligand–protein interactions and structural stabilization, particularly with α-vetivone. Conclusions: CZEO from Qatar exhibits potent antiproliferative activity against colorectal and lung cancer cells, supported by a sesquiterpenoid-rich phytochemical profile. Integrative computational analyses highlight AKT1 and STAT3 as key molecular targets, with rosifoliol and α-vetivone emerging as promising lead compounds. These findings support CZEO as a natural, multi-target anticancer agent, warranting further mechanistic and in vitro and in vivo validation. Full article

Disparities in root fungal endophyte (RFE) communities are well documented among plant species, yet differences among plant functional groups (PFGs) remain unclear. Given that RFE community structure is influenced by host plant abundance and species-specific root functional traits, and that PFGs exhibit divergent relative abundances and root traits, we hypothesize that PFGs harbor unique RFE communities, potentially aligned with their functional traits. We investigated RFE communities in 45 alpine meadow species representing four PFGs (grasses, legumes, dicot forbs, and monocot forbs), using high-throughput sequencing. Ascomycota dominated all groups (>50%) except monocot forbs (38.9%). Distinct differences in the RFE community species composition were found among PFGs. In particular, the differences were significant between dicot forbs and monocot forbs, and between monocot forbs and grasses, which contradicted with conventional PFG classification that combined monocot and dicot forbs as a single PFG. Moreover, marker operational taxonomic units (OTUs) with symbiotic lifestyles were more abundant in legumes, and their functional composition differed significantly from grasses. Roots’ nitrogen concentration was the strongest predictor of RFE variation, followed by root length, biomass, and species abundance. These results emphasize the importance of integrating microbial partners into understanding plants’ functional diversity and ecosystem resilience in alpine environments. Full article

Silage additives formulated with lactic acid bacteria (LAB) are commonly applied to enhance fermentation efficiency and aerobic stability. However, comparative evaluations across different forage species are still scarce. This in vitro experiment assessed the influence of eleven commercial silage inoculants containing various combinations of homo- and heterofermentative LAB on fermentation dynamics, nutrient conservation, and aerobic stability of medium-wilted alfalfa (Medicago sativa L.), perennial ryegrass (Lolium perenne L.), and red clover/perennial ryegrass silages. Experimental silages were prepared in 3 L laboratory silos and stored for 90 days. All inoculated treatments exhibited significantly lower pH values at both 3 and 90 days of ensiling compared with the untreated control (p < 0.05). LAB application increased the concentration of total fermentation acids and lactic acid in all forage types, although responses varied depending on inoculant composition. Inoculants containing Lentilactobacilllus buchneri produced the greatest acetic acid concentrations and resulted in a marked enhancement of aerobic stability. Compared with the control, silage inoculation significantly decreased dry matter losses by 35–64% and ammonia-N proportion by 20–37%, leading to an additional dry matter recovery of 1.29–2.87%. Control silages showed the lowest aerobic stability (97.2 h), while inoculated silages ranged from 126.0 to 200.4 h, with the extent of improvement differing among forage species and LAB formulations. In conclusion, commercial silage inoculants incorporating diverse LAB strains effectively improve fermentation quality, limit nutrient degradation, and enhance aerobic stability of legume and grass silages under controlled experimental conditions. Full article