Nitrogen Management Research Articles (Page 1)

Optimizing fertilizer management is essential for reducing salinity-related risks and improving nutrient efficiency in ornamental plant production. Fertilization enhances plant performance; however, excessive nutrient inputs can disrupt substrate chemistry, elevate salinity, and promote nitrogen leaching—particularly in containerized systems with limited rooting volume. This study evaluated the growth, physiological performance, and soil–plant nutrient dynamics of Sabal palmetto (cabbage palm) cultivated under six fertilization regimes over 180 days in a subtropical shade-house environment. Treatments ranged from a single baseline application of 15 g per plant (T0) to a cumulative 75 g (T5) using granular slow-release fertilizer. Morphological traits (plant height: 26–70 cm; leaf number: 4–18) and physiological indices (atLEAF+: 34.3–66.4; NDVI: 0.26–0.77) were monitored every 30 days. Substrate nitrogen and carbon concentrations increased from 0.57% and 41.78% at baseline to 1.24% and 42.94% at 180 days, while foliar nitrogen ranged from 1.46% to 2.57%. Fertilization significantly influenced all parameters (p < 0.05). Higher fertilization levels elevated electrical conductivity, salinity, and nitrogen leaching, with principal component analysis revealing strong positive associations among total nitrogen, electrical conductivity, and salinity. Moderate fertilization (T2 = 45 g) maintained favorable substrate chemistry, high foliar nitrogen, and balanced canopy growth with minimal nutrient losses. Sensor-based chlorophyll indices (atLEAF+ and NDVI) correlated strongly (r = 0.71, p < 0.001), confirming their reliability as non-destructive diagnostics for nitrogen management. These findings demonstrate that integrating optical monitoring with adaptive fertilization mitigates substrate salinization, sustains ornamental quality, and promotes the sustainable cultivation of Sabal palmetto in urban horticultural systems.

Baby corn is a high nitrogen (N) demanding exhaustive crop. Weed infestation causes 39 % loss in yield under rainfed condition. An experiment comprising four weed management practices viz., W1: Atrazine 1.0 kg ha-1 (pre-emergence), W2: Tembotrione 90 g ha-1 + 2,4-D 400 g ha-1 (post emergence), W3 : W1 + manual weeding at 21 days after sowing (DAS), W4: Hoeing and weeding at 21 DAS allocated to main plots and five N management practices i.e. N1:100 % soil test-based N from chemical source (C100 % STN), N2: C75 % STN + farmyard manure (FYM) 25 % STN, N3: C75 % STN + vermicompost (VC)25 % STN, N4: C75 % STN + FYM12.5 % STN + vermicompost12.5 % STN and N5: C50 % STN + FYM25 % STN + vermicompost25 % STN allocated to sub plots were tried in split plot design with three replications at Bhubaneswar, India during kharif 2022 and 2023. The treatment combination W3N1 produced the maximum dehusked baby cob (2.38 t ha-1), keeping W3N3 and W3N4 at par whereas, W3N3 produced the maximum green fodder yield (27.48 t ha-1), keeping W3N1 and W1N3 at par. The treatment combination W3N1 recorded the maximum net return of 225.10 × 103 ₹ ha-1 and return per rupee investment of 3.89 as against 188.11 × 103 ₹ ha-1 and 3.20 with W3 and 189.74 × 103 ₹ ha-1 and 3.43, respectively with N1. Both baby cob and green fodder yield exhibited significant negative correlation with weed density and biomass. The treatment W3N1 gave the maximum productivity and profitability, but W3N3 with similar yield is recommended considering productivity and long-term sustainability.

In Canada, beneficial management practices (BMP) are being used to reduce agricultural greenhouse gas emissions, manage environmental risks, and contribute to national climate goals. A key component of BMP is effective nitrogen (N) fertilizer management, which is essential for improving both soil health and economic profitability and reducing environmental risk. This research employed a modelling approach to evaluate the potential adoption of BMPs related to nitrogen fertilizer management in canola production on agricultural lands on the Mistawasis Nêhiyawak First Nation (MNFN) reserve in central Saskatchewan. The MNFN lands have a unique historical and cultural perspective, where systemic barriers to modern agricultural adoption have limited participation of local farmers and shifted agricultural decision making to non-Indigenous farmers who rent Indigenous governed lands—a common arrangement across most First Nations in the region. The modelling exercise serves as a starting point for engaging with tenant farmers on future nitrogen management strategies that more closely reflect community values and desired outcomes for their lands, including the balance of economic viability with environmental stewardship. Two distinct fertilizer application scenarios were simulated: inorganic nitrogen fertilizer and the integrated use of organic and inorganic fertilizers as BMP for canola yield. Results indicate that the combined approach within the context of the integrated nitrogen management regime could increase crop yields. The economic evaluation highlighted the financial viability of nitrogen management BMPs, leading to higher net present values (NPV). Sensitivity analysis revealed the impact of market fluctuations on economic indicators, particularly prices and costs, indicating that BMPs offered greater resilience against price volatility and rising input costs. This study contributes to ongoing efforts to improve nitrogen fertilizer practices in the region and to facilitate adoption of BMPs, particularly on First Nation reserves in Canada, with spillover benefits for the Canadian agricultural sector.

Climate change is expected to increase the frequency of extreme soil moisture events, such as winter waterlogging followed by spring drought, particularly in temperate regions of Europe, North America and Northeast China. While N2O emissions from paddy soils under waterlogging and subsequent drainage have been widely studied, knowledge of upland arable soils under wheat cultivation remains limited. We hypothesized that: (1) in upland soils, combined waterlogging and drought reduces N2O emissions compared to continuous waterlogging, and (2) plant presence mitigates soil nitrate accumulation and N2O emissions across different moisture regimes. A greenhouse experiment was conducted using intact upland soil cores with and without wheat under four moisture treatments: control (60% water-holding capacity, WHC), drought (30% WHC), waterlogging, and waterlogging followed by drought. Daily and cumulative N2O fluxes, soil mineral nitrogen (NH4+-002DN and NO3−-N), and total nitrogen uptake by wheat shoots were measured. Prolonged waterlogging resulted in the highest cumulative N2O emissions, whereas the transition from waterlogging to drought triggered a sharp but transient N2O peak, particularly in soils without plants. Wheat presence consistently reduced N2O emissions, likely through nitrate uptake, which limited substrate availability for incomplete denitrification. Moisture regimes strongly affected nitrate dynamics, with drought promoting nitrate accumulation and waterlogging enhancing nitrate loss. These findings highlight the vulnerability of upland soils in regions prone to seasonal moisture extremes. Effective management of soil moisture and nitrogen, including the promotion of plant growth, is essential to mitigate N2O emissions and improve nitrogen use efficiency under future climate scenarios.

Chlorophyll quantification in summer maize (Zea mays L.) leaves is the focus of this research, specifically at the jointing phenological stage. Based on field experiments and the correlation between canopy spectral characteristics and chlorophyll during typical growth stages, the spectral reflectance of corn leaf samples was determined using an ASD FieldSpec Pro spectrometer with a wavelength range of 350-2500 nm. Variations in spectral reflectance patterns were examined across different chlorophyll concentrations. The reflectance spectra underwent Savitzky-Golay 9-point smoothing, followed by preprocessing with MSC and SNV. Subsequently, first-derivative, second-derivative, and reciprocal logarithmic transformations were applied. PLSR was employed to establish optimal spectral estimation models for chlorophyll. The results provide a theoretical foundation and technical guidance for non-destructive crop growth monitoring and precision nitrogen management. Reflectance spectra processed with Savitzky-Golay 9-point smoothing combined with different transformations significantly improved the signal-to-noise ratio. Derivative transformations enhanced the correlation between spectral data and corn leaf chlorophyll content. Using highly correlated combination bands substantially improved model stability and predictive capability. For PLSR models, the optimal approach involved MSC processing of smoothed spectra followed by second-derivative transformation, achieving Rc²=0.9799, RMSEC=3.3027, and SEC=3.3225. The prediction models developed using various analytical approaches exhibited robust consistency and precise performance, facilitating efficient chlorophyll level assessment in large-scale maize fields. Bangladesh J. Bot. 54(3): 875-883, 2025 (September) Special

To bolster food security in the Loess Plateau, the Chinese government initiated a land expansion program (2013-2017) targeting a 337.80 km2 increase in cultivated area through integrated ditch management and reclamation. Given the region’s reliance on rain-fed agriculture, optimizing production under climate change is critical for evidence-based policymaking. This study evaluates climate and fertilization impacts on spring maize yields using the APSIM model under two Shared Socioeconomic Pathways SSP1-2.6 (sustainable low-emission development) and SSP5-8.5 (fossil-fueled high-emission development). Baseline simulations (1980-2014) revealed substantial yield gains with elevated nitrogen application: compared to the 90 kg N/ha control, treatments of 150 kg N/ha and 200 kg N/ha increased yields by 1,263 kg/ha and 1,326 kg/ha, respectively, during the 2030-2100 projection period. Climate-driven yield variability exhibited marked spatiotemporal heterogeneity, with annual mean increases under 90 kg N/ha fertilization reaching 1,111 kg/ha (SSP1-2.6) and 1,018 kg/ha (SSP5-8.5) relative to baseline conditions. These findings highlight the dual role of adaptive nitrogen management and climate-resilient land-use planning, providing actionable insights to maximize the ecological and agricultural returns of soil-water conservation initiatives while safeguarding long-term food security in this vulnerable agroecosystem. Bangladesh J. Bot. 54(3): 841-853, 2025 (September) Special

ABSTRACT Transitional drylands are anthropogenically fragile and climate‐susceptible land surfaces situated across sub‐humid, arid and semi‐arid ecosystems worldwide. Understanding land use dynamics is essential for food security and soil conservation, particularly in ecologically vulnerable ecosystems such as transitional drylands. Maintaining optimal soil nitrogen (N) fertility is a major challenge in intensive land use scenarios on these drylands. At the same time, understanding how soil N and associated soil functions respond to different land‐use changes is crucial for developing sustainable nitrogen management strategies. This study investigates the changes in soil N fertility and associated key ecosystem functions in topsoil (0–15 cm) and subsoil (15–30 cm) by comparing three land‐use systems along 5‐, 10‐ and 18‐year chronosequences: (i) groundnut (native land use), (ii) olive without cover crop (olive − CC) and (iii) olive with cover crop (olive + CC). Our results showed that long‐term integration of olive + CC, particularly after 18 years, led to the most noticeable decrease in soil pH and bulk density (BD). In contrast, we observed significantly higher water extractable organic carbon (WEOC), pentose (plant derived‐C), hexose (microbe derived‐C) and soil enzyme activities (i.e., dehydrogenase, urease and protease) in olive + CC compared to either groundnut or olive − CC. For total N stocks, the olive − CC showed a consistent decline (≈30% in topsoil; 27% in subsoil from 5 to 18 years), indicating progressive N depletion without organic inputs. In contrast, olive + CC restored soil N fertility with the highest N stocks after 18 years, including total N (131.58 kg N ha −1 in topsoil; 222.10 kg N ha −1 in subsoil), greater soil NO 3 ‐N and NH 4 + ‐N stocks at all depths, and a significant increase in organic N and microbial biomass nitrogen (MBN), especially in subsoil after 18 years. Regardless of soil depth, the mineral N stock under olive + CC increased steadily over 18 years, whereas changes under olive − CC were not significant. Furthermore, the regressions highlight the importance of both the quantity and quality of WEOC, which decisively influence soil N multifunctionality, especially through the additive effects of olive + CC. Overall, our study provides empirical evidence that long‐term diversification of olive orchards with cover crops is a practical, time‐dependent strategy to restore and improve soil nitrogen fertility in transitional drylands.

Reducing chalkiness and enhancing quality and yield in hybrid indica rice at the middle panicle position through optimal water and nitrogen management.

Optimizing nitrogen management cooperates yield stability and environmental nitrogen balance from the perspective of continuous straw incorporation

ABSTRACT Nitrogen (N), typically supplied through fertilisers, is essential for enhancing agricultural productivity, but over‐fertilisation—particularly in soils with high initial soil mineral nitrogen (N ISM )—can lead to nutrient pollution of both soil and water. In regions with shallow groundwater, optimising N application is essential yet understudied, particularly in balancing environmental protection and yield maximisation. To address this gap, field experiments were conducted in China's Mu Us Sandy Land in 2019 and 2021, with a pause in 2020. The 2019 study evaluated the effects of a 200 kg N ha −1 fertilisation rate on soil water dynamics, N behavior, and spring maize growth, whereas the 2021 drip‐irrigated trial tested a base rate of 73 kg N ha −1 supplemented with six additional N rates (0, 100, 150, 200, 250, and 300 kg N ha −1 ). Using the collected field data, a WHCNS soil‐crop model was developed, calibrated with 2019 data—including soil moisture, soil N concentration, and leaf area index—from the 200 kg N ha −1 treatment, and validated across all 2021 treatments. The model, highly sensitive to crop parameters, was further optimised using PEST to improve accuracy and then used to simulate the impacts of various water and N management strategies on water use, N fate, and crop growth under shallow groundwater conditions. Simulations revealed that high N ISM levels reduced the benefits of additional N for maize yield and resource use efficiency, whereas low N ISM conditions responded positively to increased N applications. An optimal N application rate of 200–250 kg N ha −1 , paired with a total water input of 473–516 mm, was identified as the most effective for maximising yield while minimising water and N losses.

Anammox in nature-based systems for urban water management: A review and Bayesian assessment of environmental drivers.

Changes in lysine content in rice caryopses during grain filling and in response to mid-season nitrogen management

Induced photosynthesis significantly influences biomass in Betula platyphylla seedlings compared to steady-state photosynthesis under different nitrogen forms.

Optimization of shallow buried drip irrigation and nitrogen management for spring maize in the sandy land of Northwest China

Global synthesis of nitrogen management in sugarcane systems: Decoding climate-soil-management drivers of Brazil-China contrasts

Real-time nitrogen management in rice using leaf color chart (LCC): A review

Biochar-based fertilizers have attracted increasing attention as sustainable soil amendments due to their potential to enhance nitrogen (N) retention and mitigate N losses. However, their effects on N dynamics in tea orchard soils remain inadequately understood. This study investigated the impact of biochar-based fertilizer (BF) on N migration and transformation into acidic tea orchard soils through controlled laboratory experiments comprising nine treatments, including sole urea (U) applications and various combinations of BF and U. The results showed that ammonia (NH3) volatilization peaked within seven days after application. Compared with urea-only treatments, the application of BF at 15 t·ha−1 combined with a low U application rate (0.72 t·ha−1) significantly reduced NH3 and total dissolved nitrogen losses by up to 22.33% and 33.56%, respectively, while higher BF rates increased these losses. BF applications markedly improved soil N sequestration, as evidenced by increases in total nitrogen, ammonium nitrogen (NH4+-N), nitrate nitrogen (NO3−-N), and the NH4+-N/NO3−-N ratio. Additionally, soil organic carbon, urease activity, and pH were significantly enhanced. Random forest analysis identified soil pH and organic carbon as the primary predictors of NH3 volatilization and soil N retention. Partial least squares path modeling revealed that the BF-to-urea ratio governed N dynamics by directly influencing N transformation and indirectly modifying soil physicochemical properties. BF applied at ≤15 t·ha−1 with low U inputs exhibited potential for improving N use efficiency and sustainability, pending further field validation.

Effects of long-term nitrogen application and irrigation on soil organic nitrogen fractions and soluble nitrogen in Populus tomentosa plantations in the North China Plain.

Introduction Field chilling stress during the maturation phase significantly impairs tobacco productivity and leaf quality. Nitrogen (N) management is a crucial agronomic approach for enhancing leaf quality and curing attributes; however, its specific role under chilling stress conditions remains poorly understood. Methods Field demonstrations employed ‘Honghuadajinyuan’ tobacco cultivar under varying N fertilization rates, i.e., T1 (18.9 kg N ha -1 ), T2 (27 kg N ha -1 , conventional rate), and T3 (35.1 kg N ha -1 ) with uniform basal application of 15,000 kg ha⁻¹ composted farmyard manure. This study evaluated the quality characteristics of fresh and cured tobacco leaves, as well as the curing process, by integrating physical and chemical analysis with multivariate statistical approaches, including principal component analysis and multiple linear stepwise regressions. Results Fresh tobacco quality, such as leaf tissue integrity, chloroplast pigment content, and antioxidant enzyme activities as well as curing characteristics (leaf moisture regulation capacity, pigment conversion efficiency, and antioxidant system stability) exhibited gradient pattern of T3 > T2 > T1, respectively. This trend was also reflected in carbon-nitrogen metabolic accumulation, economic traits, and sensory quality of cured tobacco leaves. T3 treatment application enhanced tobacco yield (7.35%) and economic value (43.97%) as compared to T2 treatment. Principal component analysis and multiple linear stepwise regressions revealed covariance structures among economic traits, sensory quality, and principal components F1 and F2 (R 2 =0.87, P <0.05). F1 (60.53% variance explanation rate) loaded predominantly on N fertilization rates and chloroplast pigments, whereas F2 (23.75%) exhibited strong factor loading with nicotine content, total N, and neochlorogenic acid content. Conclusions Increasing N fertilization by 30% above the conventional rate mitigates the adverse effects of field chilling stress, leading to significant improvements in yield and quality of mature tobacco.

Abstract Limiting nitrogen pollution from crop production is essential for mitigating greenhouse gas emissions (GHG) and protecting aquatic ecosystems while maintaining food security. Precision nitrogen management (PNM) provides a conceptual framework for achieving yield goals while maintaining nitrogen pollution within planetary boundaries by matching fertilizer rates to specific production conditions. Nevertheless, PNM strategies for smallholder contexts like India, a global nitrogen pollution hotspot, have proven costly to implement and are often ineffective. By combining field survey data of production practices from 8,705 wheat with digital soil mapping, we develop a novel PNM strategy that ‘learns from landscapes’ to generate and evaluate novel decision logic for nitrogen management. With this approach, ex-ante simulations indicate that reductions of 9% in nitrogen use and 16% in N2O emissions can be achieved without compromising yields, saving US$ 28 million per year in subsidies for the Indian state of Bihar alone. In contrast, conventional soil test-based recommendations are estimated to increase nitrogen use by 5% without corresponding yield gains. Our method that leverages large-n survey data and predictive modelling may provide a scalable pathway for PNM in similarly complex crop production environments where field and management heterogeneity is high.