The development of low-carbon binders requires optimized formulations that balance mechanical performance, durability, and environmental impact. This study investigates the multi-criteria optimization of slag-based geopolymer mortars incorporating ground granulated blast furnace slag (GBFS), cement kiln dust (CKD), and glass powder (GP) as ternary precursors. A multifactorial Central Composite Design (CCD) coupled with Response Surface Methodology (RSM) was employed to evaluate the individual and interactive effects of CKD and GP (0–30%) on fresh, mechanical, dimensional, microstructural, and environmental properties. Nine formulations were produced and tested for flow spread, compressive strength (7 and 28 days), open porosity, drying shrinkage (56 days), mass loss, and carbon footprint. The developed statistical models showed high reliability (R² = 0.94–0.97; p < 0.01). Incorporation of 15% GP reduced open porosity from 14.23% to 11.1% and increased 28-day compressive strength by 20.3%. In contrast, 30% CKD increased porosity to 17.85% and drying shrinkage above 1.10‰. GP at 30% minimized shrinkage to 0.82‰ and reduced mass loss to 3.2%. Multi-response optimization identified an optimal composition of 17.91% CKD and 25.34% GP, achieving 47.67 MPa at 28 days, 185.26 mm flow spread, 13.86% porosity, 962 µm/m shrinkage, and a carbon footprint of 143.8 kg CO 2 /m 3 . Microstructural analyses (XRD, DTG, SEM–EDX) confirmed the formation of hybrid C-(N)-A-S-H gels responsible for matrix densification. The novelty of this work lies in the integrated mechanical–microstructural–dimensional–environmental optimization of a ternary geopolymer system through a statistically validated multi-response framework, providing a comprehensive methodology for sustainable construction materials design. • Ternary geopolymer mortars based on GBFS, CKD, and GP were optimized using CCD. • Synergistic CKD–GP interactions improved strength and matrix densification. • ∼15% GP increased compressive strength and reduced porosity and shrinkage. • Alkaline activators dominated the environmental footprint.

Efficient elimination of amoxicillin and methylene blue dye from wastewater by ultrasonic-assisted adsorption using walnut shells-derived sulfonated adsorbent: Optimization by response surface methodology.

This study examines the mechanical properties and flexural behavior of fly ash–based geopolymer concrete (GPC) for sustainable structural applications. A two-factor Central Composite Rotatable Design (CCRD) was employed to optimize NaOH molarity and the activator-to-fly ash ratio, yielding a reliable regression model for compressive strength (R² = 0.94). Heat-cured GPC (60 °C for 24 h) achieved 28-day compressive strengths of 40–60 MPa with elastic moduli of 27–32 GPa. The elastic modulus increased with compressive strength and was slightly lower than OPC predictions, while the flexural tensile strength was 7–27% higher than that of OPC at equivalent compressive strength. Nine under-reinforced GPC beams tested under four-point bending exhibited typical three-stage flexural behavior and ductile failure after steel yielding, with ultimate load increasing by up to 56% as the reinforcement ratio increased. Finite element simulations using the Concrete Damaged Plasticity model accurately reproduced the experimental response, with deviations within 5–10%. The results demonstrate that fly ash–based geopolymer concrete can provide structural performance comparable to OPC while offering environmental benefits.

Metabolomic profile of barnyard millet (Echinochloa Esculenta) and its application in white carrot-based dairy product (kheer) preparation.

Chitin-rich organic wastes in aquatic environments provide ecological niches for chitinolytic microorganisms capable of converting chitin into chitosan, a high-value biopolymer with applications in agriculture, biotechnology, and environmental management. Microbial chitosan production represents a sustainable alternative to conventional chemical extraction; however, its efficiency is strongly influenced by environmental and physicochemical process parameters. This study investigated the occurrence, chitinolytic potential, and chitosan-producing capacity of indigenous microorganisms isolated from freshwater and sediment samples in Minna, Niger State, Nigeria, and optimised production under controlled fermentation conditions. Physicochemical characteristics of water bodies were determined, followed by the isolation and characterisation of bacterial and fungal chitinolytic strains. Selected isolates were screened for chitinase activity and subjected to fermentation-based chitosan production. Process optimisation was performed using a five-factor central composite design to assess the effects of temperature, pH, glucose level (5-20g L⁻¹), nitrogen source concentration (1-5g L⁻¹), and incubation time, with response surface methodology applied for model development and interaction analysis. Low dissolved oxygen and moderate temperatures favoured chitinolytic genera, including Aspergillus, Bacillus, and Fusarium, with Aspergillus niger exhibiting the highest chitosan yield. Incubation time was the most significant factor (p < 0.001), while temperature, pH, and substrate concentration showed strong interaction effects. Initial batch fermentations yielded up to 0.20g L⁻¹ chitosan from selected isolates, while response surface optimisation with Aspergillus niger increased production to 1.46g L⁻¹ at 32.8°C, pH 5.12, 15.3g L⁻¹ glucose, 2.45g L⁻¹ yeast extract, and 5.2 days incubation. The optimised product exhibited a high degree of deacetylation, indicating suitability for agricultural and environmental applications. These findings highlight inland aquatic ecosystems as valuable reservoirs of chitinolytic microorganisms and provide an optimised, environmentally benign framework for scalable microbial chitosan production.

The industrial demand for cost-effective and eco-friendly enzyme production has prompted the exploration of microbial systems utilizing agro-industrial residues. This study aimed to optimize amylase production by Bacillus wiedmannii SPPU 4 using statistical experimental designs and low-cost substrates. A total of seven agro-industrial wastes-wheat bran, rice bran, corn steep liquor (CSL), molasses, groundnut cake, sugarcane bagasse, and whey-were screened using Plackett-Burman Design (PBD) to identify the most influential components for amylase synthesis. Subsequent optimization was performed using Central Composite Design (CCD) under Response Surface Methodology (RSM), focusing on the top three substrates: wheat bran (A), CSL (B), and molasses (C). PBD analysis revealed CSL as the most potent factor (p/=/0.001), followed by molasses (p/=/0.002), wheat bran (p/=/0.011), whey (p/=/0.017), and groundnut cake (p/=/0.024). The highest amylase activity (129.8/U/mL) was achieved in PBD Run 4, where all seven substrates were at their high levels. CCD-based modelling yielded a second-order polynomial regression equation with high significance (F/=/93.32, p/&lt;/0.0001, R²/=/0.9917). Maximum activity (121.2/U/ml) was observed when wheat bran and molasses were at +1 level, and CSL at center point. ANOVA confirmed significant linear and quadratic contributions, while interaction terms were statistically insignificant. This study establishes Bacillus wiedmannii SPPU 4 as a promising amylase producer and highlights the value of integrating agrowaste valorization with statistical optimization. The findings offer a scalable and sustainable strategy for industrial enzyme production.

This study presents the design and optimization of a laboratory-scale bubble column bioreactor (BCB) for bioethanol fermentation. Python-based simulations in Google Colab were employed to analyze mass transfer dynamics, hydrodynamic behavior, and reactor scale-up strategies under varying aeration rates. Although ethanol production is an anaerobic process, oxygen transfer analysis was conducted to characterize reactor performance and establish oxygen-limited conditions suitable for Saccharomyces cerevisiae fermentation, incorporating mass transfer modeling, reaction kinetics, process control, and sparger design to enhance fermentation efficiency. To further enhance fermentation efficiency, Response Surface Methodology (RSM) was applied following a two-stage optimization approach. A working volume of 500 mL was defined using fermentation kinetics, including an oxygen uptake rate of 1.1 g O₂/g cells, biomass yield of 0.5 g/g glucose, and kLa of 50 h⁻¹. A perforated plate sparger with six 1.2 mm orifices achieved a gas velocity of 90.3 m/s and 2.68 mm bubble size. Aeration was dynamically controlled to maintain 0.002 g/L dissolved oxygen, while pH was regulated at 5.0–5.5 using NaOH dosing. These conditions yielded 44.3% ethanol. A full factorial design identified Time, Air Flow Rate, Cell Loading, and Bead Mass as significant factors. RSM with Central Composite Design confirmed a significant quadratic model (F = 14.14, p &lt; 0.0001; R² = 0.9601, Adjusted R² = 0.9201). Cell Loading (F = 48.48) and Bead Mass (F = 26.53) had the strongest effects. Optimal conditions yielded 47.9% ethanol at 52.70 h, 1.55 L/min air, 1.51 g/L cells, and 47.20 g beads, with 0.84% prediction error. Copyright © 2026 by Authors, Published by Universitas Diponegoro and BCREC Publishing Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0).

In this study, the chemical leaching and bioleaching behaviors of a complex carbonate-rich sphalerite ore were statistically evaluated using Response Surface Methodology (RSM) based on Central Composite Design (CCD) and the effects of process parameters on Zn and Fe recovery were assessed. The maximum Zn recovery obtained in the chemical leaching process was 59.16%, while the maximum Zn recovery in the biological leaching process was determined to be 37.26%. Statistical analyses showed that the solid-to-liquid ratio and leaching time had a significant effect on chemical leaching performance, while the effect of Fe(II) concentration on biological leaching performance was limited. During biological leaching, pH increases occurred due to the ore’s carbonate-rich structure, and periodic sulfuric acid adjustments were made to maintain suitable biological leaching conditions. The findings indicate that carbonate-rich mineral structures significantly influence both chemical and biological leaching behavior, and that this effect must be taken into account in the processing of complex sphalerite ores.

ABSTRACT To address the limited research on glass curtain wall prestressed cable net structures and the challenges in achieving accurate cable force measurements, this study explores frequency correction and cable force optimisation using the response surface methodology. A central composite design and regression analysis were utilised to establish the frequency response surface function of the cable net’s finite element model. By optimising key structural parameters based on measured frequency values, boundary conditions and finite element models were significantly improved, enabling the correction of cable forces calculated via the frequency method. The findings reveal that interaction and quadratic terms, such as cross-sectional area and density, substantially influence the vibration characteristics of the cable net. Following optimisation, the finite element model demonstrates a frequency error of less than 0.5%, and the accuracy of cable force calculations using string theory and beam theory improves by at least 14.39%. This study offers valuable insights for structural health monitoring and performance optimisation of prestressed glass curtain wall cable net systems.

Development and in vivo evaluation of novel bioresponsive nanocubosomal in-situ gelling system for ophthalmic delivery of Amphotericin B.

Conventional ulcerative colitis (UC) therapies suffer from limited efficacy and toxicity. Although physcion (PHY) has multi-target anti-inflammatory activity, its poor solubility and lack of targeting restrict clinical use. To overcome these issues, we developed folate receptor (FR)-targeted DSPE-PEG liposomes encapsulating PHY using thin-film hydration and central composite design optimization. The resulting liposomes showed uniform size (approximately 160 nm, PDI < 0.18), high entrapment efficiency (>92%), and good stability. In vitro release was significantly improved, and cellular uptake was enhanced in inflammatory EC cells via FR-mediated endocytosis. Pharmacokinetic studies revealed prolonged half-life and increased bioavailability, while tissue distribution confirmed colon-specific enrichment. In DSS-induced UC mice, targeted liposomes repaired colonic mucosa, reduced fibrosis, suppressed pro-inflammatory cytokines (IL-1β, IL-6, TNF-α), and alleviated oxidative stress through coordinated NF-κB/Nrf2 regulation, with efficacy superior to conventional liposomes and positive controls. Safety assessments showed no notable cytotoxicity to normal cells. This work offers a promising FR-targeted nanocarrier to overcome PHY’s clinical limitations and provides a foundation for targeted UC therapy.

Gamma-Poly Glutamic Acid (γ-PGA) is an eco-friendly biopolymer that is biodegradable and water soluble and has been used in different industries such as foods, pharmaceuticals, agriculture, and environment. Unlike other artificial polymers, γ-PGA is a natural polymer that can be obtained through microbial fermentation. Various strains have been employed to obtain the desired polymer but Bacillus subtilis has been the most common one studied so far. In the current study, the possibility of using soybean extracts to produce γ-PGA in both solid state fermentation and submerged state fermentation was examined. Of all the strains, white and black soybeans yielded the highest amount in SSF and SBF respectively at 347.67 mg (1.390%) and 935 mg (3.116%). To eliminate concerns regarding external glutamate addition, only a trace amount of monosodium glutamate (MSG) was used in the seed culture, and no glutamate was added during fermentation, indicating that γ-PGA was produced predominantly through production without external glutamate supplementation during fermentation. The initial screening showed that black soybean waste could be used as an inexpensive substrate for optimization via SBF. A Central Composite Design (CCD) design with four factors and five levels, with response surface methodology consisting of 30 different experiments, was conducted to determine the influence of the substrate concentration, pH, temperature, and inoculum amount. The optimized parameters for the maximum γ-PGA production, namely 6% substrate, pH of 6.0, 35 °C temperature, and 3% inoculum, resulted in γ-PGA production equaling 7.5 g/L, which is close to the predicted value of 7.48 g/L. The study highlights that substrate selection and statistical optimization are equally critical for enhancing γ-PGA production, positioning black soybean waste as a promising low-cost substrate with potential for future scale-up and sustainable γ-PGA bioprocess development following further pilot-scale and techno-economic validation.

Toxic trace metals such as lead (Pb), cadmium (Cd), and arsenic (As) represent persistent environmental contaminants associated with significant human health risks. Reliable and rapid analytical strategies are therefore essential for toxicological surveillance of consumer and environmental matrices. In this study, a green and process-intensified ultrasonic extraction method was developed for the efficient recovery and determination of Pb, Cd, and As from complex matrices including herbal materials, cosmetic products, beverages, and wastewater, using Atomic Absorption Spectrometry. The approach utilizes ultrasonic cavitation to accelerate metal desorption and mass transfer, enabling rapid extraction under mild conditions with reduced reagent consumption. Galangal was selected as a representative plant matrix to establish and validate the analytical framework. A rotatable central composite design based on response surface methodology was applied to evaluate the influence of nitric acid concentration (0.40-1.20 M), ultrasonic time (5-15 min), and acid volume (20-40 mL) on metal recovery. The statistical model demonstrated strong predictive capability and identified acid concentration and solvent volume as significant factors influencing extraction performance (p < 0.05). Ultrasonic irradiation significantly enhanced metal release from the matrix through cavitation-induced disruption and accelerated diffusion processes. The optimized extraction conditions (0.68 M HNO3, 11 min ultrasonic time, and 32 mL acid volume) yielded predicted recoveries of 97.13%, 102.09%, and 103.26% for Pb, Cd, and As, respectively, with corresponding experimental recoveries of 95.17 ± 2.37%, 97.50 ± 5.13%, and 98.63 ± 0.25%. The developed method showed a very low matrix effect. The relative expanded uncertainty of metal extraction under optimized conditions ranged from 5.60 to 10.36%, which is within the acceptable criteria (≤15%). Based on the evaluation of trueness through comparison with results obtained from homogeneous proficiency testing (PT) materials, the developed method exhibited acceptable trueness for the quantitative determination of all trace metals, with z-scores less than 2. Application of the method to real samples demonstrated consistent analytical performance across seven galangal varieties and multiple complex matrices, with recoveries ranging from 87.00 to 109.00% (% RSD = 0.08-6.82). These findings demonstrate that ultrasonic processing can provide a rapid, low-reagent, and environmentally responsible extraction strategy for toxic trace metal determination. The developed protocol offers a practical analytical platform for toxicological monitoring, contaminant surveillance, and safety assessment of natural and industrial products.

Pharmaceutical pollutant, such as amoxicillin was selected because it is one of the most widely consumed antibiotics worldwide and is frequently detected in hospital and municipal wastewater. Its high excretion rate in active form and persistence in aquatic environments make it an important target contaminant for water treatment studies. To address this issue, we developed a dendrimer-functionalized graphene quantum dot-mesoporous silica hybrid (GQDs@mSiO2@Dend.G3) as an effective and reusable adsorbent. AMX is an ideal model contaminant for studying adsorption mechanisms and evaluating the performance of this advanced hybrid material. Mechanistic interpretation suggests that hydrogen bonding, π-π, and electrostatic interactions collectively contribute to antibiotic binding at the hybrid interface. The nanoadsorbent was characterized using XRD, TGA, FTIR, BET-BJH, FE-SEM, EDX, and zeta potential measurements. Response surface methodology with a central composite design was used to optimize and validate the removal efficiency, yielding statistically significant results. The drug removal efficiency of 96% was achieved under the following optimal conditions: pH 6, temperature of 35 °C, and contact time of 45 min. The kinetics followed the pseudo-second-order model (R2 = 0.9979) and the equilibrium fit the Langmuir isotherm (R2 = 0.9657-0.9675) confirming monolayer physisorption onto uniform active sites. Thermodynamics showed that the process was spontaneous and endothermic (ΔH° = 8562.589 J mol-1, ΔS° = 155.530 J mol-1 K-1, and ΔG° = -37.808 to -40.919 kJ mol-1). The nanoadsorbent showed consistently high removal efficiency in real water samples. It retained over 70% of its original performance after multiple regeneration cycles. This indicates that GQDs@mSiO2@Dend.G3 is a promising and reusable solution for reducing pharmaceutical pollution in environment samples.

Abstract The growing demand for sustainable energy and stringent emission regulations necessitate the development of cleaner alternative fuels for diesel engines. This study investigates the performance and emission characteristics of a binary biodiesel blend derived from Garcinia gummi-gutta (GGG) and Garcinia indica (GI) doped with CaO·Al₂O₃ nanoparticles (NPs) in a compression-ignition engine. Biodiesel is produced via microwave-assisted transesterification, with a yield of 98.9%, and is characterized according to ASTM standards. A Central Composite Design (CCD) is employed to examine the effects of blend ratio (10–30%), nanoparticle concentration (60–180 ppm), compression ratio (14–18), and engine load (40–100%) on brake thermal efficiency (BTE), brake specific fuel consumption (BSFC), and emissions (CO, UHC, and NOx). A hybrid multi-response optimization framework integrating the Desirability Function Approach (DFA), the Grey Wolf Optimizer (GWO), and the Starfish Optimization Algorithm (SFOA) is implemented to determine optimal engine conditions. Results indicate that nanoparticle doping enhances combustion efficiency by improving catalytic activity and oxygen availability. The optimal single-objective conditions yield a maximum BTE of 34.8%, minimum BSFC of 0.172 kg/kW·h, and reduced emissions (CO: 0.031 vol.%, UHC: 13.82 ppm, NOx: 92 ppm). Multiobjective optimization yields a composite desirability value of 0.938, and experimental validation confirms its predictive accuracy, with an average absolute deviation of 5.85%. The addition of CaO.Al₂O₃ NPs increases the BTE by 11.86% and reduce BSFC, CO, and UHC by 1.72%, 38.89%, and 26.80%, respectively. However, NOx emissions increase slightly by 7.49%, attributed to improved combustion behaviour resulting from higher oxygen content, air–fuel ratio, and calorific value. The study demonstrates that GGG-GI biodiesel blends doped with CaO·Al₂O₃ nanoparticles, combined with a hybrid statistical-AI optimization framework, offer a viable pathway to enhance diesel engine efficiency and reduce emissions, supporting sustainable biofuel deployment.

Instant-pounded yam flour (poundo flour) provides a convenient and time-saving alternative to the traditional yam pounding method. This study explores the optimization of processing conditions for poundo flour production from precooked sweet potato tubers, aiming to enhance its functional properties for improved quality and efficiency in food applications. Response surface methodology, incorporating a central composite rotatable design, was adopted to evaluate the effects of slice thickness (1-5 mm), precooking time (5-25 min), and drying temperature (40-80 °C) on bulk density (BD), swelling capacity (SC), water absorption capacity (WAC), oil absorption capacity (OAC), and gelatinization temperature (GT). High coefficients of determination (R2 values) were obtained, indicating strong relationships between the processing variables and response parameters. During optimization, BD, SC, and WAC were maximized, while OAC and GT were minimized to improve hydration, swelling and thickening behaviour, reduce oil retention, and lower energy requirements during cooking. The optimal processing conditions were identified as slice thickness of 4 mm, precooking time of 10 min, and drying temperature of 53.27 °C. The predicted values of BD, SC, WAC, OAC, and GT, under these conditions, were 0.930 g cm-3, 0.33 g g-1, 0.138 g g-1, 0.376 g g-1 and 63.92 °C, respectively. Experimental validation yielded corresponding values of 0.915 g cm-3, 0.34 g g-1, 0.140 g g-1, 0.370 g g-1 and 63.50 °C, with percentage errors below 3% for all responses. The close agreement between predicted and experimental results confirms the adequacy and reliability of the developed models for predicting and optimizing the functional characteristics of the poundo flour. © 2026 Society of Chemical Industry.

In this study, a hydrophilicity-switchable deep eutectic solvent (HS-DES) was prepared by combining nonanoic acid (C9) with tetrabutylammonium bromide (TBAB) and applied as an efficient extraction medium for the ultrasound-assisted liquid-phase microextraction (UALPME) of verapamil from human plasma samples prior to spectrofluorimetric determination. The hydrophilicity-hydrophobicity transition of the HS-DES was controlled by pH adjustment using NaOH or HCl solutions, enabling reversible phase switching and facilitating effective separation of verapamil from the biological matrix. Key experimental parameters influencing the extraction efficiency were systematically investigated, and further optimization was performed using a central composite design coupled with a desirability function approach. The developed HS-DES-based UALPME (HS-DES-UALPME) method provides a tunable, environmentally friendly, and effective strategy for the preconcentration of verapamil from complex biological samples. The method showed wide linear range (200-2000 ng/mL), a good limit of detection (62.16 ng/mL), and extraction recovery (59.55%). To assess the method's sustainability, the AGREE tool was applied, clearly demonstrated the overall greenness of the developed procedure. A comparison of the analytical performance of the method with previously reported methods demonstrated its superiority or, at minimum, its comparability in key analytical parameters.

Biodepolymerization of poly(ethylene terephthalate) (PET) plastics using microorganisms has emerged as a promising and sustainable approach for mitigating pollution caused by PET waste. In this study, Glutamicibacter mysorens ASR14, a mesophilic bacterium isolated from Kodungaiyur dumpyard (Chennai, India), showed 27.6% PET biodepolymerization in terms of weight loss in 30 d. A customized screening of 20 trials was designed using JMP statistical software to evaluate the influence of various variables. Furthermore, a Central Composite Design (CCD) of Response Surface Methodology (RSM) was adopted and validated using four variables at five levels, with 25 trials, to correlate the relationship for enhanced PET biodepolymerization. A maximum PET weight loss of 75.6% was achieved in 60 d, representing a 2.73-fold improvement compared to that under unoptimized conditions. Enzymatic assays confirmed the involvement of esterase (5,690 U/mL) and lipase (962 U/mL) activities in accelerating the breakdown of PET. The analytical characterization techniques revealed significant surface erosion, reduction in crystallinity, and high yield of terephthalic acid (TPA), which also holds potential value for biorefinery applications. This work represents the first comprehensive report on process optimization for PET biodepolymerization using G. mysorens ASR14 as a whole-cell biocatalyst. The findings establish G. mysorens ASR14 as a promising candidate for developing scalable, green bioremediation strategies.

Ferrofluids represent a class of functional materials that combine the flow characteristics of liquids with the magnetic responsiveness of solid magnetic substances. In this study, a novel low-viscosity hydrophobic deep eutectic solvent (HDES) based ferrofluid for vortex-assisted liquid-liquid microextraction (HDES-FF-VA-LLME) technique is proposed for simultaneous extraction of UV filters and parabens from environmental water samples. The ferrofluid was composed of poly(dopamine) modified magnetic nanoparticles and fatty acid based low-viscosity HDESs. The key experimental factors influencing the extraction performance were first screened using a Plackett-Burman design and subsequently optimized through a central composite design. Under the optimized experimental conditions, the method provided limits of detection ranging from 0.05 to 0.25 µg L-1 and limits of quantification between 0.2 and 1.0 µg L-1. The intra-day (n = 5) and inter-day (n = 5) relative standard deviations were both below 3.3%, while enrichment factors varied from 22 to 29. Following the extraction process, the ferrofluid phase could be rapidly isolated by applying an external magnetic field, which eliminates the need for conventional phase-separation procedures and significantly reduces separation time. The extraction mechanism was further investigated using density functional theory calculations. Coupled with high-performance liquid chromatography equipped with an ultraviolet detector, the proposed method was successfully applied to the simultaneous determination of UV filters and parabens in environmental water samples, achieving recoveries in the range of 94.4-107.7%. Overall, the developed approach provides a rapid, straightforward, cost-effective, and environmentally friendly microextraction strategy, showing promising potential for applications in environmental monitoring.

Effective weed management in faba bean (Vicia faba L.) requires precise adjustment of herbicide dose and application timing to achieve effective weed suppression while maintaining crop growth and yield. This study employed response surface methodology (RSM) to quantify and optimize the interactive effects of imazethapyr rate and application timing on weed biomass, morphophysiological traits, and yield of faba bean under field conditions in western Iran during a single 2024-2025 growing season.Imazethapyr (Pursuit® 10% SL) was applied at rates ranging from 0 to 1000 mL ha⁻¹ at pre-plant incorporated, pre-emergence, and post-emergence stages using a central composite design. Leaf area index, plant height, number of pods per plant, 100-seed weight, biological yield, grain yield, and weed dry weight were modeled using quadratic and cubic RSM functions. Strong nonlinear dose by timing interactions were observed for all responses. Intermediate imazethapyr rates (250-500 mL ha⁻¹) applied from pre-planting to early post-emergence (3-10 days after sowing) maximized canopy development, reproductive performance, biological yield, and grain yield while minimizing weed biomass. Higher rates (≥ 750 mL ha⁻¹) or late post-emergence applications reduced crop performance despite improved weed suppression, indicating phytotoxic effects. Model diagnostics showed high predictive accuracy, particularly for leaf area index, 100-seed weight, and weed dry weight. Multi-response desirability analysis identified a favorable management range balancing weed control and yield performance, indicating the value of RSM as a decision-support framework for precision herbicide management in faba bean.