Different Concentrations Of Urea Research Articles

Optimization of an Alternative Culture Medium for Phycocyanin Production from Arthrospira platensis under Laboratory Conditions.

Arthrospira platensis, known as spirulina, is a cyanobacterium with multiple nutritional benefits, as it contains substantial amounts of proteins, fatty acids, and pigments. However, the production of this microalga has faced significant challenges, primarily related to the cost and composition of the required culture medium for its optimal growth. This study focused on optimizing two nitrogen sources (urea and potassium nitrate) to maximize the growth of A. platensis and the production of phycocyanin, a photosynthetic pigment of significant commercial value. Optimization was performed using the response surface methodology (RSM) with a central composite design (CCD). Analysis of variance (ANOVA) was employed to validate the model, which revealed that the different concentrations of urea were statistically significant (p < 0.05) for biomass and phycocyanin production. However, potassium nitrate (KNO3) showed no significant influence (p > 0.05) on the response variables. The RSM analysis indicated that the optimal concentrations of KNO3 and urea to maximize the response variables were 3.5 g L-1 and 0.098 g L-1, respectively. This study offers valuable perspectives for the efficient production of A. platensis while reducing production costs for its cultivation on a larger scale.

Urea reduces the sustainability of soil Cd immobilization by upregulating the expression of AmSTOP1 and AmMATE genes in edible amaranth roots

After cadmium (Cd) immobilization remediation in contaminated farmland soil, which forms of nitrogen fertilizer should be implemented to keep its sustainability? Urea and nitrate were used to compare for their effects on the remobilization of stabilized Cd in the rhizosphere soil of edible amaranth at nitrogen concentrations of 60, 95, and 130 mg kg−1. The results showed that compared to nitrate nitrogen, the Cd content in shoots increased by 76.2%, 65.6%, and 148% after applying three different concentrations of urea, and the total remobilization amount of Cd also increased by 16.0%, 24.9%, and 14.0% respectively. Urea application promotes root secretion of citric acid, malic acid, pyruvate, and γ-aminobutyric acid, crucial in remobilizing stable Cd. The application of urea promoted the expression of genes involved in sucrose transport, glycolysis, the TCA cycle, amino acid secretion, citric acid efflux, and proton efflux. Arabidopsis heterologous expression and yeast one-hybrid assays identify critical roles of AmMATE42 and AmMATE43 in citric acid and fumaric acid efflux, with AmSTOP1 activating their transcription. Inhibition of SIZ1 expression in urea treatment reduce AmSTOP1 SUMOylation, leading to increased expression of AmMATE42 and AmMATE43 and enhanced organic acids efflux. Using edible amaranth as a model vegetable, we discovered that urea is not beneficial to preserving the sustainability of stabilized Cd during the reuse of remediated farmlands contaminated with Cd.

Urease-Powered Black TiO2 Micromotors for Photothermal Therapy of Bladder Cancer.

Urease-powered nano/micromotors can move at physiological urea concentrations, making them useful for biomedical applications, such as treating bladder cancer. However, their movement in biological environments is still challenging. Herein, Janus micromotors based on black TiO2 with urease asymmetric catalytic coating were designed to take benefit of the optical properties of black TiO2 under near-infrared light and the movement capability in simulated bladder environments (urea). The black TiO2 microspheres were half-coated with a thin layer of Au, and l-Cysteine was utilized to attach the urease enzyme to the Au surface using its thiol group. Biocatalytic hydrolysis of urea through urease at biologically relevant concentrations provided the driving force for micromotors. A variety of parameters, such as urea fuel concentration, viscosity, and ionic character of the environment, were used to investigate how micromotors moved in different concentrations of urea in water, PBS, NaCl, and urine. The results indicate that micromotors are propelled through ionic self-diffusiophoresis caused by urea enzymatic catalysis. Due to their low toxicity and in vitro anticancer effect, micromotors are effective agents for photothermal therapy, which can help kill bladder cancer cells. These promising results suggest that biocompatible micromotors hold great potential for improving cancer treatment and facilitating diagnosis.

Fabrication of multinuclear copper cluster-based coordination polymers as urease inhibitors.

This study focused on the design and synthesis of two Cu-based coordination polymers, [Cu2(4-dpye)(5-HSIP)(μ3-O)(H2O)2]·3H2O (Cu-CP-1) and [Cu(4-dpye)0.5(BCA)2] (Cu-CP-2), where 4-dpye = N,N'-bis(4-pyridinecarboxamide)-1,2-ethane, 5-H3SIP = 5-sulfoisophthalic acid, and HBCA = benzoic acid, by using a hydrothermal method. Single-crystal X-ray diffraction (SCXRD) study revealed that by adding various auxiliary ligands, the architectures of the Cu-CPs could be altered, yielding two distinct multinuclear Cu clusters. Moreover, the Cu-CPs can be used as urease inhibitors (UIs). In vitro experiments showed that the Cu-CPs had good urease inhibition effects with IC50 values of 0.53 ± 0.01 μM for Cu-CP-1 and 1.44 ± 0.01 μM for Cu-CP-2 and 98.48% (Cu-CP-1) and 96.27% (Cu-CP-2) inhibition of urease was achieved at a concentration of 100 μM, respectively. Furthermore, the inhibition effect of the tetranuclear Cu-CP was better than that of the binuclear Cu-CP. To better understand the potential mechanism of inhibition of the two copper complexes, we performed kinetic analysis using Lineweaver-Burk (L-B) plots in the presence of different concentrations of urea and different concentrations of inhibitors, and both Cu-CP-1 and Cu-CP-2 showed a non-competitive mode of inhibition. In addition, molecular docking analysis showed that the Cu-CPs were able to enter well into the urease binding pocket, thus interacting with key amino acid residues of urease to different degrees. Both kinetic and molecular docking studies theoretically explain and demonstrate the inhibition effect of both Cu-CPs on urease activity in vitro, which is expected to provide reasonable guidance and effective strategies for the development of novel, efficient, stable and safe CP-based UIs.

Development and Characterization of a Paper-Based Sensor for Colorimetric Urea Detection in Artificial Urine

Toxic nitrogen, which is formed as a result of the breakdown of proteins, is converted into nontoxic urea by the enzymes in the "urea cycle". While a small part of the produced urea is eliminated with sweat, a large part is removed from the body by the kidneys with urine. Therefore, urea determination in blood and urine provides important information about kidney functions. In this study, a colorimetric paper based sensor was developed and characterized for use in urea detection. Basically, urea measurement was carried out by immobilization of urease enzyme on pH sensitive papers. The determination of urea was made by observing the changes in pH caused by ammonia with basic properties, which is formed as a result of the destruction of urea by urease. In the presence of different concentrations of urea, the colorimetric changes on the sensor were visualized with a camera and analyzed with the ImageJ program in the computer environment. In the first stage, a calibration curve showing the relationship between urea concentration and color intensity was obtained, and then the detection limit and sensitivity of the system were determined from this curve. Finally, the selectivity of the sensor was demonstrated by testing the different molecules involved.

Multifunctional Cu:ZnS quantum dots for degradation of Amoxicillin and Dye Sulphon Fast Black-F and efficient determination of urea for assessing environmental aspects

This work is particularly aimed at the preparation of ZnS and Cu doped ZnS (Cu:ZnS) QDs by facile and easy technique, chemical precipitation method for the degradation of water pollutants and a simple scheme was proposed to prepare the urea-sensing system. The morphological and optical properties of the synthesized QDs was studied using high resolution transmission and scanning electron microscopes, X-ray diffraction, energy dispersive X-ray analysis, fluorescence and ultraviolet–visible spectroscopy, differential thermal and thermogravimetric analyses, Brunauer–Emmett–Teller analysis. The photocatalytic performance was systematically assessed by the photodegradation of an important pharmaceutical water pollutant, Amoxicillin (AMX) and a dye Fast Sulphon Black F (SFBF) in aqueous medium under UV light irradiation. Also, a very sensitive system was prepared by depositing the dots over an indium-tin-oxide (ITO) glass substrate for the sensing of biologically active molecule urea as it is an important monitor of public health in water and soil productivity. The results illustrated excellent photocatalytic efficiency (86.46% for AMX and 99.41% for SFBF) with stability up to four cycles of degradation reaction. The optimal photocatalyst dosage for achieving maximum removal of AMX was found to be 70 mg at a pH of 9.5, with a treatment time of 40 min. Similarly, for SFBF, the optimal photocatalyst dosage was determined to be 60 mg at pH 9, with a treatment time of 60 min. Further, the electrochemical analysis was done by fabricating Urease enzyme (UR)/Cu:ZnS QDs/ITO bioelectrode and then the fabricated bioelectrode, was utilized to determine the different concentrations of urea by cyclic voltammetry. Thus, the obtained limit of detection and sensitivity of the fabricated biosensing device for urea detection was obtained to be 0.0092 μM and 12 μA μM−1cm−2, respectively; under the optimized experimental conditions. Hence, it is anticipated that Cu:ZnS QDs can also successfully be applied as a promising material for fabrication of novel bioelectrode for urea determination and the biosensing platform is desirable and viable.

Effect of Concentrations of Biocementation Solution on Enzyme Induced Calcium Carbonate Precipitation (EICP)

Abstract: The need to accommodate a growing global population has become major concern in many societies and has pushed human inventiveness to new levels. There is an increase in need for engineering technologies to improve the mechanical properties of the ground. Mostly soil strengthening is done by applying cement or chemical products to enhance the mechanical properties of soil. However, the usage of those products can possibly disturb improved soil and the production process of cement and chemical products can create harmful products. Enzyme Induced Calcium Carbonate Precipitation (EICP) is one sustainable method where calcium carbonate precipitation occurs via hydrolysis of urea (ureolysis) catalysed by plant-extracted urease enzyme for soil improvement . This study analysed the effect of different concentrations of urea- CaCl2 (0.5M, 1M, 1.5M) and urease enzyme (5 g/l) which forms the biocementation solution on the mechanical properties of soil. Direct Shear test is done to analyse the shear strength parameters. The optimum EICP treatment solution was obtained as urea- CaCl2 (1 M) at urease enzyme (5 g/l). It was observed that there was an increase in cohesion (0.16kg/cm2 ) and angle of internal friction (35º) at 7 days was to cohesion(0.18kg/cm2 ) and angle of internal friction (36º) at 14 days .

Advanced Urea Precursors Driven NiCo2O4 Nanostructures Based Non-Enzymatic Urea Sensor for Milk and Urine Real Sample Applications

The electrochemical performance of NiCo2O4 with urea precursors was evaluated in order to develop a non-enzymatic urea sensor. In this study, NiCo2O4 nanostructures were synthesized hydrothermally at different concentrations of urea and characterized using scanning electron microscopy and X-ray diffraction. Nanostructures of NiCo2O4 exhibit a nanorod-like morphology and a cubic phase crystal structure. Urea can be detected with high sensitivity through NiCo2O4 nanostructures driven by urea precursors under alkaline conditions. A low limit of detection of 0.05 and an analytical range of 0.1 mM to 10 mM urea are provided. The concentration of 006 mM was determined by cyclic voltammetry. Chronoamperometry was used to determine the linear range in the range of 0.1 mM to 8 mM. Several analytical parameters were assessed, including selectivity, stability, and repeatability. NiCo2O4 nanostructures can also be used to detect urea in various biological samples in a practical manner.

Experimental study on the calcium carbonate production rates and crystal size of EICP under multi-factor coupling

The production and microstructure of calcium carbonate are the fundamental indicators to evaluate the effectiveness of Enzyme-induced Carbonate Precipitation (EICP). Soybean urease is extracted, and the urease activity is controlled by the soybean powder concentration in this study. The urease reacts with the cementation solution with different concentrations of urea and calcium ions at different temperatures to determine the calcium carbonate production rates (RCC). The crystal sizes of calcium carbonate (SCC) are investigated by scanning electron microscopy (SEM) and image processing method. The RCC increase and subsequently decrease with increasing calcium ion concentration and peak at 0.75 M. A lower urea concentration is more favourable to the formation of CaCO3. Increased urease activity and temperature will lead to an increased RCC and SCC. Some crystals appear as capsules when the temperature goes up. The SCC decreases slightly with increasing calcium ion concentration under low urease activity and increases under high urease activity. The SCC increases first and subsequently decreases with increasing urea concentration under high urease activity, while the effect of urea concentration under low urease activity is not significant. XRD test results show that the calcium carbonate produced in this study is dominated by calcite crystals. The study provides additional data, a useful base to move forward toward a better understanding of the method of stabilization and its applications, for example, the treatment of different soils.

EFFECT OF UREA IN THE ELECTROLESS BATH ON THE PLATING RATE, PHOSPHORUS CONTENT AND CORROSION RESISTANCE OF THE Ni–P DEPOSITS

Proper selection of bath additives is critical to the plating rate, phosphorus content and corrosion resistance of the nickel–phosphorus (Ni–P) alloy deposits. In this work, electroless Ni–P alloy deposition from an acidic bath using sodium hypophosphite as the reducing agent at relatively low temperatures (30°C and 60°C) was carried out in the presence and absence of urea additives. The effects of different concentrations of urea on plating rate and phosphorus content of the Ni–P deposits were studied. The results showed that the plating rate and the phosphorus content of the Ni–P deposits were largely dependent on the concentration of urea in the bath. The corrosion resistance of the Ni–P deposits was evaluated in aerated 3.5 wt.% sodium chloride (NaCl) solution using potentiodynamic polarization curves. It was found that the corrosion resistance of the deposits obtained from the bath solution containing 1 g/L of urea was the highest. In addition, cyclic voltammetry techniques were used to study the mechanism of electroless Ni–P alloy deposition in the bath. The results revealed that the addition of urea to the bath promoted the concentrations of adsorbed atomic hydrogen and sodium hypophosphite on mild steel surface, which markedly increased the phosphorus content of the Ni–P deposits. This work offers a new way that highlights the relation between the urea additives and phosphorus content.

Measurement of the NOx reduction effect on food wastewater during waste incineration.

Incineration is the most effective method for reducing the increasing waste volume. However, as the pollutants generated during incineration may cause secondary pollution, blocking them in advance is necessary. During incineration, prevention facilities are operated to reduce the amount of pollutants. Conventional selective non-catalytic reduction (SNCR) reduces nitrogen oxides (NOx) by injecting ammonia and urea as reducing agents. In this study, the NOx reduction effect on food wastewater (FW) was examined. In addition, the removal efficiency was compared at different concentrations of urea mixed with FW. When different concentrations of urea were injected in SNCR facilities A, B and C, NOx removal efficiencies of up to 75% were observed; with FW injection only, removal efficiency was 56%; and when both urea and FW were injected, removal efficiency was up to 79%. Although FW showed a lower NOx removal efficiency than urea, injecting both increased the efficiency. In addition, when air pollutant emissions and the incinerator temperature were analysed, we found that they could be managed without exceeding the allowed limits. However, for the injection and incineration of reducing agents, the characteristics of the incineration facility and reducing agents must be considered.

Comparative estimation of nitrogen in urea and its derivative products using TKN, CHNS and hand-held refractometer

In this paper, a comparative analysis between the hand-held refractometer and other methods (TKN and CHNS) was accomplished for the estimation of nitrogen percentage (N%) in urea, nano urea fertilizer, and diesel exhaust fluid (DEF) solution. In order to compare the performance of all methods/devices, the detection of N% in different concentrations of urea, nano urea, and DEF were evaluated in terms of their linearity. The most important finding of this study was that the refractometer-based device revealed a good linear coefficient up to 40% urea solution (R2 = 0.99918) among other approaches, which means the estimation of N% is more close to the theoretical value. Moreover, the refractometer has detected the urea, nano urea, and DEF samples within 3 s which were quite fast as compared to other tested methods and no requirement of any chemicals during the sample preparation and analyses. Thus, the finding of this study suggests that a hand-held urea refractometer-based portable device can be used for onsite N% determination by the fertilizer and DEF manufacturing industries and their customers due to its low cost, low power requirement, reliable estimation, rapid N% detection, and its environmental suitability.

Probing the Interactions Responsible for the Structural Stability of Trypanothione Reductase Through Computer Simulation and Biophysical Characterization.

With the necessity to develop antileishmanial drugs with substrate specificity, trypanothione reductase (TryR) has gained popularity in parasitology. TryR is unique to be present only in trypanosomatids and is functionally similar to glutathione in mammals. It protects against oxidative stress exerted by the host defense mechanism. The TryR enzyme is essential for the survival of Leishmania parasites in the host as it reduces trypanothione and aids in neutralizing hydrogen peroxide produced by the host macrophages during infection. Henceforth, it becomes vital to decipher their functional stability and behaviour in the presence of denaturants. Our study is focused on structural, functional and behavioural stability aspects of TryR with different concentrations of Urea, Guanidinium chloride, alcohol based compounds followed by extensive molecular dynamics simulations in a lipid bilayer system. The results obtained from the study reveal an interesting insight into the possible mechanisms of modulation of the structure, function and stability of the TryR protein.

Soil Urea Analysis Using Mid-Infrared Spectroscopy and Machine Learning

Urea is the most common fertilizer used by the farmers. In this study, the variation of mid-infrared transmittance spectra with addition of urea in soil was studied for five different concentrations of urea. 150 gm of soil is taken and dried in a hot air oven for 5 h at 80°C and then samples are prepared by adding urea and water to it. The spectral signature of soil with urea is obtained by using an Infrared Spectrometer that reads the spectra in the mid infra-red region. The analysis is done using Partial Least Square Regression and Support Vector Machine algorithms by applying Savitzky Golay filter and Gaussian filter. The score plot, prediction and reference plots are used in the analysis using PLSR. RMSE and R-squared value are obtained from the analysis. It is evident that the detection accuracy was appropriate for Gaussian filter compared to Golay filter for both the PLSR and SVM models. The RMSE for PLSR is 0.8% and for SVM is 16%. The results show that Support vector machine model has higher accuracy compared to Partial least square regression model considering the prediction for which R square value is 0.99 with and without filters. SVM model gives better prediction without filters.

Machine learning and RSM models for prediction of compressive strength of smart bio-concrete

In recent years, bacteria-based self-healing concrete has been widely exploited to improve the compressive strength of concrete using different bacterial species. However, both the identification of the optimal involved reaction parameters and theoretical framework information are still limited. In the present study, both experimentally and numerical modelling using machine learning (ANN and ANFIS) and response surface methodology (RSM) were implemented to evaluate and optimse the evolution of bacterial concrete strength. Therefore, a total of 58 compressive strength tests of the concrete incorporating new bacterial species were designed using different concentrations of urea, cells concentration, calcium, nutrient and time. Based on the results, the compressive strength of the bacterial concrete improved by 16% due to the decrement of the pore percentage in the concrete skin; specifically, 5 mm from the concrete surface, compared to that of the control concrete. In the same context, both machine the learning and RSM models indicated that the optimal range of urea, calcium, nutrient and bacterial cells were (18-23 g/L), (150-350 mM), (1-3 g/L) and 2×107 cells/mL, respectively. Based on the statistical analysis, RMSE, R2, MPE, RAE and RRSE were (0.793, 0.785), (0.985, 0.986), (1.508, 1.1), (0.11, 0.09) and (0.121, 0.12) from both the ANN and ANFIS models, respectively, while; the following values (0.839, 0.972, 1.678, 0.131 and 0.165) was obtained from RSM model, respectively. As such, it can be concluded that a high correlation and minimum error were obtained, however, machine learning models provided more accurate results compared to that of the RSM model.

The denatured state of HIV-1 protease under native conditions.

The denatured state of several proteins has been shown to display transient structures that are relevant for folding, stability, and aggregation. To detect them by nuclear magnetic resonance (NMR) spectroscopy, the denatured state must be stabilized by chemical agents or changes in temperature. This makes the environment different from that experienced in biologically relevant processes. Using high‐resolution heteronuclear NMR spectroscopy, we have characterized several denatured states of a monomeric variant of HIV‐1 protease, which is natively structured in water, induced by different concentrations of urea, guanidinium chloride, and acetic acid. We have extrapolated the chemical shifts and the relaxation parameters to the denaturant‐free denatured state at native conditions, showing that they converge to the same values. Subsequently, we characterized the conformational properties of this biologically relevant denatured state under native conditions by advanced molecular dynamics simulations and validated the results by comparison to experimental data. We show that the denatured state of HIV‐1 protease under native conditions displays rich patterns of transient native and non‐native structures, which could be of relevance to its guidance through a complex folding process.

Influence of creams with different urea concentrations on plantar skin hydration

IntroductionThe skin is the body's outermost organ, and one of its main functions is to provide protection against potential infections. Hydration is related to the proper functioning of the skin, hindering the appearance of wounds or cracks which could lead to the occurrence of infections or other dermatological alterations. The skin of the foot is thicker than that of the rest of the body due to the load it supports, and it is more complicated to maintain. The intention of this study was to evaluate the efficacy of different concentrations of urea (5% and 20%) in hydrating the foot compared to a placebo cream. MethodsThe study was carried out with 60 subjects of ages from 20 to 35 years in age. The experimental protocol was initiated by creating three randomized groups (1:1:1), each being treated with a different cream: placebo, 5% urea cream, and 20% urea cream. The examination was carried out using a non-invasive instrument (Corneometer CM 825®) that detects the skin surface hydration. ResultsAnalysis of the hydration of the different study zones according to the cream used showed no significant differences between the placebo and 5% urea for the first MTH and heel, but a significant difference for the fifth MTH. There were significant differences in all study areas between the placebo and 20% urea creams, but none between the 5% urea and 20% Discussion/ConclusionThe conclusion drawn was that skin hydration was greater with the 20% urea cream versus the placebo, but there were no differences found when comparing either the 20% and 5% urea creams or the placebo and 5% urea creams.

Responses of bimetallic Ag/ZnO alloy nanoparticles and urea on morphological and physiological attributes of wheat.

Wheat (Triticum aestivum L.) is the most important staple food crop globally. According to economic survey 2018‐19, agriculture sector of Pakistan grew by 0.85%, with wheat accounting for 8.9% of agriculture and 1.6% of GDP, and its production fell short of the target by 4.9%. Wheat requires beneficial ties to improve its efficiency with the help of modern technology. Nanotechnology modifies conventional agricultural practices as these are stimulating agents for plant growth. Green bimetallic Ag/ZnO alloy nanoparticles (NPs) synthesised from salts reduced by Moringa oleifera and characterised by UV‐visible spectroscopy, scanning electron microscopy, and energy‐dispersive X‐ray spectroscopy are studied herein. Different concentrations of urea and Ag/ZnO alloy NPs were applied exogenously to wheat plants (Pakistan‐13 and Galaxy13). A significant effect of 100 mg/L urea and 75 ppm Ag/ZnO alloy NPs was observed on the morphology of wheat, with a maximum increase of 58% plant length, 85% leaf area, 89% plant fresh weight and 76% plant dried weight. In physiological parameters, relative water content and membrane stability index have shown maximum increases of 39% and 77%, while chlorophyll a, b, and total chlorophyll content (TCC) showed maximum increases of 92%, 71%, and 84% respectively. Evidence of the morpho‐physiological responses of urea and green synthesised alloy NPs on wheat varieties are reported on.

Chemometric model for rapid detection of urea and hydrogen peroxide in milk

A simple and cost effective method has been developed for determination of adulteration in milk with urea and hydrogen peroxide by using chemometric modeling with Fourier Transform Infrared (FTIR) spectroscopic data. Milk samples were purchased from a dairy farm (South Banasree, Dhaka, Bangladesh) and spiked at different concentrations of urea and hydrogen peroxide. Spectral data of all samples were collected using ATR-FTIR spectrophotometer. After acquisition of spectral data, they were preprocessed with transformation techniques such as multiplicative scatter correction (MSC) and savitzky-golay derivative. The predictive performance of principal component regression (PCR) and partial least-square regression (PLSR) methods were assessed by relative prediction errors and recoveries (%) were compared . PLSR shows better prediction efficiencies over PCR with R2 value 99% for urea and 95% for hydrogen peroxide.Six brands of commercial milk samples have been evaluated by this method and the samples contain 21.66-44.73 mg urea and 1.62-2.86 mg hydrogen peroxide in 100 ml milk. This method can be easily used in the quality assessment of milk.&#x0D; Bangladesh J. Sci. Ind. Res.56(1), 1-8, 2021

Fenoxaprop combined with urea improves photosynthesis, weed control, and yield of potato

AbstractThis study aimed to evaluate the effects of combined application of fenoxaprop (fenoxaprop‐p‐ethyl) and urea on potato (Solanum tuberosum L.) photosynthesis, weed control, and yield. The optimal sequence and dosage of the urea and fenoxaprop combination on potato production was investigated using different concentrations of urea (0, 1, 2, 4, and 8 g L−1) and fenoxaprop (0, 1.33, 2.66, 5.32, and 7.98 ml L−1) in a randomized block experiment. Potato plant photosynthesis levels, weed control efficacy, and potato yield were explored through the analysis of chlorophyll content index (CCI), photosynthetic parameters, weed‐related statistics, and polynomial regression. The results showed fenoxaprop stress not only reduced indices such as the CCI and net photosynthetic rate (Pn) but also decreased the activity, maximum photochemical efficiency, and quantum efficiency of Photosystem II, and the photochemical quenching coefficient. Urea at concentrations of 1–4 g L−1 antagonized the toxicity of fenoxaprop, whereas 8‐g L−1 urea aggravated herbicide toxicity. Compared with fenoxaprop treatment alone, the combination of 4‐g L−1 urea and 1.33‐ml L−1 fenoxaprop significantly increased the Pn of potato plants, weed control efficacy, and potato tuber yield by 36.12, 11.35, and 11%, respectively. Furthermore, treatment with urea first, followed by fenoxaprop, displayed greater efficacy in weed control than fenoxaprop followed by urea. Taken together, urea at concentrations of 1–4 g L−1 may alleviate the side effects of fenoxaprop on potato seedlings. Meanwhile, urea treatment (4 g L−1) followed by fenoxaprop (1.33 ml L−1) may be the optimal combination for potato production.