Search Results (188)

A field experiment was conducted in 2019–2020 and 2020–2021 at Rogoza, Fala, and Brežice in Slovenia to examine the biological viability of a mixed intercropping system and the effect of winter catch crops (WCCs) on maize growth parameters. The experiment included Italian ryegrass (IR) in pure stands, fertilized with nitrogen (N) in spring (70 kg N ha⁻¹), mixtures of crimson clover and red clover 50:50 (C), and intercropping between IR and C (IR+C). Neither mixture was fertilized with N in spring. We evaluated different competition indices and biological efficiency. Relative crowding coefficient (RCC) and actual yield loss (AYL) exceeded 1, indicating a benefit of IR+C intercropping. The IR in intercropping was more aggressive, as indicated by positive aggressivity (A) and a competitive ratio (CR) > 1, and it dominated over C in IR+C (that had negative A values and CR < 1). The competitive balance index (Cb) differed from zero, the relative yield total (RYT) was 2.24, the land equivalent coefficient (LEC) exceeded 0.25, the area–time equivalent ratio (ATER) exceeded 1, and land use efficiency (LUE) exceeded 100%. IR+C exhibited the highest total aboveground dry matter yield of maize (29.22 t ha⁻¹), the highest nitrogen content in dry matter grain yield of maize (206.35 kg ha⁻¹), the highest nitrogen and potassium content in maize stover (105.7 and 105.7 kg ha⁻¹, respectively), and the highest nitrogen and potassium content in the total aboveground dry matter of maize (312 and 267.3 kg ha⁻¹, respectively). The C/N ratio in dry matter yield of IR was 45.35, and in IR+C it was 33.43, which means that the mixture had a positive effect on nutrient release in maize. The ryegrass–clover mixture, according to the calculated biological indices, had advantages over pure stands and had a positive effect on maize yield. Full article

The North China Plain, a major grain production base in China, is facing the chronic threat of climate-change-induced delays in winter wheat sowing, with late sowing constraining yields by shortening the pre-winter growth period, and soil moisture at sowing potentially serving as a key factor to alleviate late-sowing losses. However, previous studies have mostly independently analyzed the effects of sowing time or water stress, and there is still a lack of systematic quantitative evaluation on how the interaction effects between the two determine long-term yield potential and risk. To fill this gap, this study aims to quantify, in the context of long-term climate change, the independent and interactive effects of different sowing dates and baseline soil moisture on the growth, yield, and production risk of winter wheat in the North China Plain, and to propose regionally adaptive management strategies. We selected three representative stations—Beijing (BJ), Wuqiao (WQ), and Zhengzhou (ZZ)—and, using long-term meteorological data (1981–2025) and field trial data, undertook local calibration and validation of the APSIM-Wheat model. Based on the validated model, we simulated 20 management scenarios comprising four sowing dates and five baseline soil moisture levels to examine the responses of phenology, aboveground dry matter, and yield, and further defined yield-reduction risk probability and expected yield loss indicators to assess long-term production risk. The results show that the APSIM-Wheat model can reliably simulate the winter wheat growing period (RMSE 4.6 days), yield (RMSE 727.1 kg ha⁻¹), and soil moisture dynamics for the North China Plain. Long-term trend analysis indicates that cumulative rainfall and the number of rainy days within the conventional sowing window have risen at all three sites. Delayed sowing leads to substantial yield reductions; specifically, compared with S1, the S4 treatment yields about 6.9%, 16.2%, and 16.0% less at BJ, WQ, and ZZ, respectively. Moreover, increasing the baseline soil moisture can effectively compensate for the losses caused by late sowing, although the effect is regionally heterogeneous. In BJ and WQ, raising the baseline moisture to a high level (P85) continues to promote biomass accumulation, whereas in ZZ this promotion diminishes as growth progresses. The risk assessment indicates that increasing baseline moisture can notably reduce the probability of yield loss; for example, in BJ under S4, elevating the baseline moisture from P45 to P85 can reduce risk from 93.2% to 0%. However, in ZZ, even the optimal management (S1P85) still carries a 22.7% risk of yield reduction, and under late sowing (S4P85) the risk reaches 68.2%, suggesting that moisture management alone cannot fully overcome late-sowing constraints in this region. Optimizing baseline soil moisture management is an effective adaptive strategy to mitigate late-sowing losses in winter wheat across the North China Plain, but the optimal approach must be region-specific: for BJ and WQ, irrigation should raise baseline moisture to high levels (P75-P85); for ZZ, the key lies in ensuring baseline moisture crosses a critical threshold (P65) and should be coupled with cultivar selection and fertilizer management to stabilize yields. The study thus provides a scientific basis for regionally differentiated adaptation of winter wheat in the North China Plain to address climate change and achieve stable production gains. Full article

This study aimed to address the limited infiltration capacity of the double ridge–furrow mulching system (DRFM) under heavy rainfall on the Loess Plateau, which exacerbates surface runoff and mid-summer soil water deficits in semi-arid rainfed areas. By incorporating infiltration holes to optimize the system, we evaluated their effects on soil water storage, maize growth, and water use efficiency (WUE). A two-year field experiment (2021–2022) comprised four treatments: conventional flat planting (CK), the traditional ridge-furrow system (CWC), the double ridge-furrow system (DWC), and the double ridge-furrow system with infiltration holes (DWCR). The experimental periods represented a normal precipitation year (2021, 410 mm) and a dry year (2022, 270 mm). Results indicated that the DWCR treatment established preferential flow pathways, significantly enhancing deep soil water storage and its utilization efficiency during critical phenological stages, particularly under drought. This improved deep water accelerated crop growth and boosted yield. Compared to the CK, CWC, and DWC treatments, the DWCR treatment significantly increased plant height, aboveground dry matter (ADM), yield, and WUE. Specifically, the DWCR treatment improved yield and WUE by 0.24–20.04% and 2.75–26.27%, respectively. In the dry year, the yield of the DWC treatment increased by 12.72% compared to its yield in the normal year, whereas the DWCR treatment achieved a greater increase of 19.18%. Root analysis confirmed that the DWCR treatment significantly increased root weight density in the 20–60 cm soil layer under drought, optimizing root spatial distribution and thereby enhancing deep water uptake and drought resistance. In conclusion, incorporating infiltration holes into the DRFM is an effective strategy for optimizing soil water distribution, improving crop drought tolerance and WUE, and promoting sustainable semi-arid rainfed agriculture. Full article

To investigate the adaptability and efficacy of biogas residue soil conditioner in conjunction with other commercially available soil conditioners in arid conditions, a study was conducted using dryland maize as the experimental crop. Five treatments were implemented based on the “dry sowing and wet emergence” method for Xinjiang cotton: T1 with traditional fertilization, T2 with biogas residue soil conditioner, T3 with biogas residue soil conditioner and endophytic arbuscular mycorrhizal bacteria, T4 with commercial Fuli Bang soil conditioner, and T5 with commercial Tianji soil conditioner. Results indicated that the combined use of biogas residue particulate soil conditioner and arbuscular mycorrhizal fungi (T3) had the most positive effects. T3 treatment reduced soil bulk density, increased soil organic matter content, and enhanced rhizosphere microbial diversity. Compared to T1, T3 led to a decrease in soil bulk density by 8.89%, higher microbial diversity indices, and significant increases in plant height, stem diameter, and yield by 6.25%, 15.48%, and 37.43%, respectively. Moreover, T3 showed elevated antioxidant enzyme activities (SOD and POD) and lower malondialdehyde content, indicating enhanced stress resilience and root activity. T3 showed ideal balance in yield, aboveground growth, and root stress resilience. It also improved soil organic matter levels and structure, highlighting the significant potential of combining biogas residue soil conditioner and endophytic arbuscular mycorrhizal fungi to alleviate spring drought stress. Full article

Nitrogen (N) is the most widely used nutrient in agriculture in the form of urea, yet it is one of the least efficient in terms of application due to losses through volatilization and leaching. The combination of urea with micronutrient sources, especially in the form of nanoparticles, is a promising technology for reducing these losses. Two greenhouse experiments were conducted with the objective of evaluating the influence of coating urea with zinc oxide nanoparticles (NPZnO) and iron oxide nanoparticles (NPFe₂O₃), associated with elemental sulfur (S°), on the leaching of mineral nitrogen and the production of dry mass and accumulation of N in young corn plants. The coating (0.26% w/w) of urea with elemental sulfur (S°) and NPZnO and NPFe₂O₃ reduced N losses through leaching (−21.3%) and delayed the nitrification process of N in the soil (−71.8%). This coating increased the efficiency of nitrogen fertilization in young corn plants, boosting the production of dry mass in leaves (+39.4%), stems (+68.8%), and roots (+61.6%), as well as the absorption of N in the above-ground biomass (+64.1%), compared to conventional urea. The use of urea coated with NPZnO and NPFe₂O₃ associated with S° is an environmentally sound solution for supplying N and micronutrients such as Fe and Zn in a more efficient and sustainable manner, especially in sandy soils with low organic matter content, which are common in the semi-arid region of Brazil. Full article

As critical reservoirs of biodiversity and providers of ecosystem services, wetland ecosystems play a pivotal role in maintaining global ecological balance. They not only serve as habitats for diverse aquatic and terrestrial organisms but also play substantial roles in water purification, carbon sequestration, and climate regulation. However, intensified anthropogenic activities—including drainage, fertilization, invasion by alien species, grazing, and urbanization—pose unprecedented threats, leading to profound alterations in the functional traits of wetland plants. This review synthesizes findings from peer-reviewed studies published between 2005 and 2024 to elucidate the mechanisms by which human disturbances affect plant functional traits in wetlands. Drainage was found to markedly reduce plant biomass in swamp ecosystems, while mesophyte and tree biomass increased, likely reflecting altered water availability and species-specific adaptive capacities. Mowing and grazing enhanced aboveground biomass and specific leaf area in the short term but ultimately reduced plant height and leaf dry matter content, indicating potential long-term declines in ecological adaptability. Invasive alien species strongly suppressed the growth of native species, reducing biomass and height and thereby threatening ecosystem stability. Eutrophication initially promoted aboveground biomass, but excessive nutrient inputs led to subsequent declines, highlighting ecosystems’ vulnerability to shifts in trophic state. Similarly, fertilization played a dual role: moderate inputs stimulated plant growth, whereas excessive inputs impaired growth performance and exacerbated eutrophication of soils and water bodies. Urbanization further diminished key plant traits, reduced habitat extent, and compromised ecological functions. Overall, this review underscores the profound impacts of anthropogenic disturbances on wetland plant functional traits and their cascading effects on ecosystem structure and function. It provides a scientific foundation for conservation and management strategies aimed at enhancing ecosystem resilience. Future research should focus on disentangling disturbance-specific mechanisms across different wetland types and developing ecological engineering and management practices. Recommended measures include rational land-use planning, effective control of invasive species, and optimized fertilization regimes to safeguard wetland biodiversity, restore ecosystem functions, and promote sustainable development. Full article

Critical nitrogen concentration (Nc) and accumulation (Na) throughout the entire growth period are key indicators for diagnosing N status and implementing precision N management in cut chrysanthemum. However, direct measurement of these two parameters is both time-consuming and destructive, and establishing accurate predictive models is fundamental to their practical application. From May 2021 to July 2022, five N-gradient experiments (ranging from 14 to 574 mgf·plant⁻¹) were conducted on the cut chrysanthemum cultivar ‘Nannong Xiaojinxing’. Predictive models for Nc and Na were developed using environmental light and temperature data during growth as driving variables. The results showed that the aboveground dry matter (DM) prediction model, which utilized the cumulative photo-thermal effect (PTE) derived from these environmental factors, demonstrated superior accuracy compared to models relying on conventional driving variables. Subsequently, the Nc and Na prediction models were established with DM as the driving variable. These models indicated that at a DM level of 1 g·plant⁻¹, Nc and Na values were 4.53% and 45.30 mg·plant⁻¹, respectively. The Na reached a maximum of 236.50 mg·plant⁻¹ at the flower harvesting stage, representing the minimum N accumulation required for optimal floral quality. Using the dry matter model as a process-based model, we successfully developed predictive models for Nc and Na driven by PTE. Validation using independent experimental data confirmed the models’ high predictive accuracy, with coefficients of determination of 0.9378 and 0.9612, and low errors—root mean square errors of 0.2736% and 19.18 mg·plant⁻¹, and normalized RMSE of 10.79% and 14.94%, respectively. These models provide a foundation for implementing precision N management and reducing fertilizer application in cut chrysanthemum production. Full article

This study employs an integrated framework that combines field-based measurements, remote sensing, and Geographic Information Systems (GISs) to monitor vegetation dynamics and assess the suitability of a steppe range reserve for livestock grazing. Forty-three surface and subsurface soil samples were collected in April and November 2021 to capture seasonal variations. Above-ground biomass (AGB) measurements were recorded at five sampling locations across the reserve. Six Sentinel-2 satellite imageries, acquired around mid-March 2016–2021, were processed to derive time-series Normalized Difference Vegetation Index (NDVI) data, capturing temporal shifts in vegetation cover and density. The GIS-based Multi-Criteria Decision Analysis (MCDA) was employed to model the suitability of the reserve for livestock grazing. The results showed higher salinity, total dissolved solids (TDSs), and nitrate (NO₃) values in April. However, the percentage of organic matter increased from approximately 7% in April to over 15% in November. The dry forage productivity ranged from 111 to 964 kg/ha/year. On average, the reserve’s dry yield was 395 kg/ha/year, suggesting moderate productivity typical of steppe rangelands in this region. The time-series NDVI analyses showed significant fluctuations in vegetation cover, with lower NDVI values prevailing in 2016 and 2018, and higher values estimated in 2019 and 2020. The grazing suitability analysis showed that 13.8% of the range reserve was highly suitable, while 24.4% was moderately suitable. These findings underscore the importance of tailoring grazing practices to enhance forage availability and ecological resilience in steppe rangelands. By integrating satellite-derived metrics with in situ vegetation and soil measurements, this study provides a replicable methodological framework for assessing and monitoring rangelands in semi-arid regions. Full article

Soil contamination with petroleum-derived substances, including petrol, is one of the most serious environmental issues of the modern era. These products are characterised by their durability and stability in the environment, their capacity for bioaccumulation and their toxicity to many organisms, including plants. This study aimed to evaluate the impact of petrol contamination on trace element content in the above-ground parts of oats (Avena sativa L.) and to determine the effectiveness of in situ stabilisation methods using compost, bentonite and calcium oxide in reducing bioaccumulation of these elements. Petrol contamination of the soil significantly altered the biomass yield and the concentration of trace elements in the plants. It caused a decrease in the dry matter yield and an increase in the content of most trace elements in the above-ground parts of oats. The most pronounced effects were observed for Cd, Ni, Fe, Co, Cr and Mn, whose concentrations in the plants increased across the entire range of petrol doses. Petrol had a similar effect on Zn and Pb content in the above-ground parts of oats, but only up to a medium level of contamination (5 cm³ kg⁻¹). In contrast to the aforementioned elements, soil contamination with petrol contributed to a decrease in the copper content of the above-ground parts of oats. The materials applied to the soil had a beneficial effect on the biomass and the concentration of certain trace elements in plants. The compost and especially calcium oxide had a positive influence on plant yield. Compared to the series without their application to the soil, all materials reduced the content of Cr, Fe, Cd and, especially, Mn in the above-ground parts of plants. Compost also reduced the content of Pb, while bentonite and calcium oxide reduced the content of Co. Calcium oxide also reduced the content of Cu in the above-ground parts of oats. However, bentonite had a weaker effect than compost and calcium oxide. Changes in the content of other elements in plants after application of the aforementioned materials were often opposite (and dependent on the type of material), with the clearest effect being on nickel content. The materials used in the study produced good results in limiting the impact of minor soil contamination with petrol on the content of certain trace elements in plants. Full article

The global feed gap, driven by seasonal shortages and climate change, highlights the need for novel forage resources. Vicia faba (Faba bean) produces substantial above-ground biomass as residue after fresh pod harvest, which remains underutilized. This study comprehensively evaluated the forage potential of faba bean leaves and stems across three growth stages: flowering (S1), pod development (S2), and ripening (S3). Dry matter content peaked at S2 in both tissues, while crude protein and fat content were highest at S1; carbohydrate levels increased progressively with maturation. Significant mineral concentrations, particularly K, Ca, and Mg, were detected, with leaves at S2 showing higher ash (i.e., mineral) content. Bioactive compounds (L-dopa, flavonols, total phenolics, and flavonoids) and antioxidant activities were most abundant at S1, with strong positive correlations between phenolics and antioxidant activities. Overall, faba bean residues offer proximate nutritional profiles comparable to traditional forages such as alfalfa and clover, while providing superior antioxidant potential. Their incorporation into animal feed systems before S3 could help mitigate seasonal forage shortages and enhance the nutritional quality of livestock diets. Full article

The APSIM (Agricultural Production Systems Simulator)-Wheat model has been widely used to simulate wheat growth, but the sensitivity characteristics of the model parameters at different soil moisture levels in arid regions are unknown. Based on 2023~2025 winter wheat field data from the Changji Experimental Site, Xinjiang, China, this study conducted a global sensitivity analysis of the APSIM-Wheat model using Morris and EFAST methods. Twenty-one selected parameters were perturbed at ±50% of their baseline values to quantify the sensitivity of the aboveground total dry matter (WAGT) and yield to parameter variations. Parameters exhibiting significant effects on yield were identified. The calibrated APSIM model performance was evaluated against field observations. The results indicated that the order of influential parameters varied slightly across different soil moisture levels. However, the WAGT output was notably sensitive to accumulated temperature from seedling to jointing stage (T1), accumulated temperature from the jointing to the flowering period (T2), accumulated temperature from grain filling to maturity (T4), and crop water demand (E1). Meanwhile, yield output showed greater sensitivity to number of grains per stem (G1), accumulated temperature from flowering to grain filling (T3), potential daily grain filling rate during the grain filling period (P1), extinction coefficient (K), T1, T2, T4, and E1. The sensitivity indices of different soil moisture levels under Morris and EFAST methods showed highly significant consistency. After optimization, the coefficient of determination (R²) was 0.877~0.974, the index of agreement (d-index) was 0.941~0.995, the root mean square error (RMSE) was 319.45~642.69 kg·ha^–1, the mean absolute error (MAE) was 314.69~473.21 kg·ha^–1, the residual standard deviation ratio (RSR) was 0.68~0.93, and the Nash–Sutcliffe efficiency (NSE) was 0.26~0.57, thereby enhancing the performance of the model. This study highlights the need for more careful calibration of these influential parameters to reduce the uncertainty associated with the model. Full article

Water scarcity and spatial variability in soil fertility are key constraints to stable grain production in the Huang-Huai-Hai Plain. However, the interaction mechanisms between regulated deficit irrigation and soil fertility influencing yield formation and water-nitrogen use efficiency in winter wheat remain unclear. In this study, a two-year field experiment (2022–2024) was conducted to investigate the effects of two irrigation regimes—regulated deficit irrigation during the heading to grain filling stage (D) and full irrigation (W)—under four soil fertility levels: F1 (N: P: K = 201.84: 97.65: 199.05 kg ha⁻¹), F2 (278.52: 135: 275.4 kg ha⁻¹), F3 (348.15: 168.75: 344.25 kg ha⁻¹), and CK (no fertilization). The results show that aboveground dry matter accumulation, total nitrogen content, pre-anthesis dry matter and nitrogen translocation, and post-anthesis accumulation significantly increased with fertility level (p < 0.05). Regulated deficit irrigation promoted the contribution of post-anthesis dry matter to grain yield under the CK and F1 treatments, but suppressed it under the F2 and F3 treatments. However, it consistently enhanced the contribution of post-anthesis nitrogen to grain yield (p < 0.05) across all fertility levels. Higher fertility levels prolonged the grain filling duration by 18.04% but reduced the mean grain filling rate by 15.05%, whereas regulated deficit irrigation shortened the grain filling duration by 3.28% and increased the mean grain filling rate by 12.83% (p < 0.05). Grain yield significantly increased with improved fertility level (p < 0.05), reaching a maximum of 9361.98 kg·ha⁻¹ under the F3 treatment. Regulated deficit irrigation increased yield under the CK and F1 treatments but reduced it under the F2 and F3 treatments. Additionally, water use efficiency exhibited a parabolic response to fertility level and was significantly enhanced by regulated deficit irrigation. Nitrogen partial factor productivity (NPFP) declined with increasing fertility level (p < 0.05); Regulated deficit irrigation improved NPFP under the F1 treatment but reduced it under the F2 and F3 treatments. The highest NPFP (41.63 kg·kg⁻¹) was achieved under the DF1 treatment, which was 54.81% higher than that under the F3 treatment. TOPSIS analysis showed that regulated deficit irrigation combined with the F1 fertility level provided the optimal balance among yield, WUE, and NPFP. Therefore, implementing regulated deficit irrigation during the heading–grain filling stage under moderate fertility (F1) is recommended as the most effective strategy for achieving high yield and efficient resource utilization in winter wheat production in this region. Full article

Excessive fertilization is a widespread issue in onion (Allium cepa L.) production in Southwest China. This practice not only leads to environmental pollution but also decreases the marketable yield and fertilizer productivity of onions. Identifying an optimal fertilization rate is crucial for promoting high-yield and highly efficient onion cultivation. The objective of this research is to determine the appropriate amount of fertilizer by investigating the effects of different fertilization rates on the growth characteristics and bulb yield of onion. The study was conducted over two consecutive growing seasons utilizing a randomized complete block design, which included six treatments: local routine fertilizer application (F1), a 20% reduction from F1 (F2), a 40% reduction from F1 (F3), a 60% reduction from F1 (F4), an 80% reduction from F1 (F5), and no fertilizer application (F0). The results show that, at the mature stage, aboveground dry matter quantity and its accumulation rate of onion under treatment F2 were found to be the highest among all other treatments across both growing seasons. Following the onset of bulbing, dry matter accumulation initially increased but subsequently decreased with reduced fertilizer supply; notably, it was greater under treatment F2 compared to other treatments. Compared with F1, the PFPN (partial factor productivity of nitrogen fertilizer) under treatment F2 increased by 35.2% and 32.0%, and the marketable bulb yield under treatment F2 increased by 8.4% and 5.8% during the 2022–2023 and 2023–2024 growing seasons, respectively. The marketable bulb yield demonstrated extremely significant positive correlations with aboveground dry matter and the dry matter accumulation rate throughout all growth periods in both growing seasons. Furthermore, marketable bulb yield exhibited extremely significant positive correlations with dry matter translocation before the onset of bulbing and dry matter accumulation following bulbing initiation. It was concluded that the appropriate fertilizer application (F2), characterized by a fertilization rate of 339-216-318 kg ha⁻¹ for N-P₂O₅-K₂O, enhanced onion bulb yield and nitrogen fertilizer productivity by promoting post-bulbing dry matter accumulation. This study emphasizes the significance of optimizing the fertilization rate as a crucial factor in achieving high-yield and highly efficient onion cultivation by enhancing dry matter accumulation. Full article

Potatoes, as the world’s fourth-largest staple crop, are vital for global food security. Efficient methods for assessing yield and quality are essential for policy-making and optimizing production. Traditional yield assessment techniques remain destructive, labor-intensive, and unsuitable for large-scale monitoring. While remote sensing has offered a promising alternative, current approaches largely depend on empirical correlations rather than physiological mechanisms. This limitation arises because potato tubers grow underground, rendering their traits invisible to aboveground sensors. This study investigated the mechanisms underlying hyperspectral remote sensing for assessing belowground yield traits in potatoes. Field experiments with four cultivars and five nitrogen treatments were conducted to collect foliar biochemistries (chlorophyll, nitrogen, and water and dry matter content), yield traits (tuber yield, fresh/dry weight, starch, protein, and water content), and leaf spectra. Two approaches were developed for predicting belowground yield traits: (1) a direct method linking leaf spectra to yield via statistical models and (2) an indirect method using structural equation modeling (SEM) to link foliar biochemistry to yield. The SEM analysis revealed that foliar nitrogen exhibited negative effects on tuber fresh weight (path coefficient b = −0.57), yield (−0.37), and starch content (−0.30). Similarly, leaf water content negatively influenced tuber water content (0.52), protein (−0.27), and dry weight (−0.42). Conversely, chlorophyll content showed positive associations with both tuber protein (0.59) and dry weight (0.56). Direct models (PLSR, SVR, and RFR) achieved higher accuracy for yield (R² = 0.58–0.84) than indirect approaches (R² = 0.16–0.45), though the latter provided physiological insights. The reduced accuracy in indirect methods primarily stemmed from error propagation within the SEM framework. Future research should scale these leaf-level mechanisms to canopy observations and integrate crop growth models to improve robustness across environments. This work advances precision agriculture by clarifying spectral–yield linkages in potato systems, offering a framework for hyperspectral-based yield prediction. Full article

In integrated crop–livestock systems (ICLSs), grazing intensity and crop rotation influence residue dynamics, making it essential to assess shoot and root contributions to soil carbon (C) and nitrogen (N) inputs. This study aimed to assess the shoot and root biomass of Italian ryegrass, soybean, and maize; the distribution of roots within the soil profile; and the contributions of shoot and root biomass to soil C and N under varying winter grazing intensities and summer crop rotations. The experiment was conducted within a long-term (12-year) field protocol, arranged in a randomized complete block design with split plots and four replicates. Grazing intensity was defined as the following: (i) moderate grazing—forage allowance equivalent to 2.5 times the potential dry matter intake of sheep, and (ii) low grazing—forage allowance equivalent to 5.0 times the intake potential. Grazing intensities (moderate and low) were allocated to the main plots, while cropping systems—monoculture (soybean/soybean) and crop rotation (soybean/maize)—were assigned to the subplots. Soil depth layers (0–10, 10–20, 20–30, and 30–40 cm) were treated as sub-subplots. Root samples of Italian ryegrass, soybean, and maize were collected using the soil monolith method. Low grazing intensity (8.6 Mg ha⁻¹) promoted greater aboveground biomass production of Italian ryegrass compared to moderate intensity (6.6 Mg ha⁻¹). Maize exhibited a higher capacity for both root and shoot biomass accumulation, with average increases of 85% and 120%, respectively, compared to soybean. Root biomass was primarily concentrated in the surface soil layer, with over 70% located within the top 10 cm. Italian ryegrass showed a more uniform root distribution throughout the soil profile compared to soybean and maize. Carbon inputs were higher under crop rotation (17.2 Mg ha⁻¹) than under monoculture (15.0 Mg ha⁻¹), whereas nitrogen inputs were greater in soybean monoculture (0.23 Mg ha⁻¹) than in crop rotation (0.16 Mg ha⁻¹). Low grazing intensity in winter and summer crop rotation with high-residue and quality species enhance the balance between productivity and soil C and N inputs, promoting the sustainability of ICLSs. Full article