Central Composite Experiment Research Articles

Parkinson biomarker determination with an Au microflower-enhanced electrochemical immunosensor using non-Faradaic capacitancemeasurements.

This work comprehends the development and characterization of a carbon black-based electrode modified with Au microflowers to increase its effect as a capacitance biosensor for the determination of PARK7/DJ-1. Due to its high surface-to-volume ratio and biocompatibility, Au particles are suitable for antibody binding, and by monitoring surface capacitance, it is possible to identify the immune-pair interaction. Au microflowers allowed the adequate immobilization of Parkinsonian-related proteins: PARK7/DJ-1 and its antibody. The protein is associated with several antioxidant mechanisms, but its abnormal concentrations or mutations can be the cause of the loss of dopaminergic neurons, leading to Parkinson's disease. The device was characterized by scanning electron microscopy and cyclic voltammetry, revealing the flower-like structures and the electrochemically-interest enhancements they provide, such as increased heterogeneous electron transfer rate coefficient and electroactive area. The self-assembled monolayers of different molecules were optimized with the aid of 22 central composite experiments and a linear calibration curve was obtained between 0.700 and 120ngmL-1 of PARK7/DJ-1, with a limit of detection of 0.207ngmL-1. The data confirms that the addition of Au microflowers enhanced the electrochemical signal of the device, as well as allowed for the determination of an early stage Parkinson's disease biomarker with appreciable analytical performance.

Iterative eigenvalue method coupled with RSM for structural acoustic analysis and optimization of the CLD-damped orthotropic steel deck

In the present work, an iterative eigenvalue method (IEM) is proposed and combined with the boundary element method (BEM) to perform the structural acoustical analysis of the orthotropic steel deck (OSD) damped with constrained layer damping (CLD), through which the frequency-dependent properties of the viscoelastic core can be accurately considered. Then, a series of hammer tests are carried out in a semi-anechoic chamber to verify the acoustic prediction method. It shows that the simulated structural noises basically agree with the test results, and the overall deviations at the field points M2 and M8 are merely 2.4 and 2.3 dB, respectively. Subsequently, taking the thicknesses of the damping layer and the constraining layer, as well as the material properties of the constraining layer as design variables, a central composite experiment is designed and combined with response surface methodology (RSM) to fit the relationship between analysis objectives and design variables. With the objective of minimizing the acoustic radiation power, a program for finding the optimal values of design variables is developed based on the interior penalty function method. Through iterative computations, the optimal points are numerically determined as t 1 = 2.3 mm and t 2 = 0.3 mm for the thicknesses of the damping layer and the constraining layer, respectively. Steel alloy is found to be the optimal material for the constraining layer. After optimizing CLD treatment, the overall acoustical power level can be reduced from 97.7 dB to 93.1 dB and the overall sound pressure levels (SPLs) at the field points M2 and M8 can be reduced from 89.2 dB to 83.5 and 76.9 dB to 70.3 dB, respectively, indicating that the optimization of CLD design parameters can significantly improve acoustic performance of the CLD-damped structures.

Medium Formulation and Optimisation of Fermentation Condition Enhancing γ-aminobutyric Acid (GABA) Biosynthesis by Lactiplantibacillus plantarum B7

Extensive studies on γ-aminobutyric acid (GABA) over decades highlight its significant physiological and pharmacological effects on humans. GABA produced using microbe is favoured compared to enzymatic and chemical methods due to operational ease and reduced harmful pollutant formation. This study focused on increasing γ-aminobutyric acid (GABA) biosynthesis from Lactiplantibacillus plantarum B7, employing a multi-step optimisation strategy. An unoptimised cultivation approach yielded a maximum GABA of 11.68 ± 0.04 g/L and viable cell count of 10.47 ± 0.01 log CFU/mL at 48 h. A nutrient-rich medium was developed through single-parameter optimisation, comprising 1%, 2.5% and 0.0002% of glucose, yeast extract and each trace element (CaCO3, KI, and Tween 80) respectively. Temperature, pH, incubation period, initial concentration of monosodium glutamate (MSG) and pyridoxal-5’-phosphate (PLP) demonstrated significant contributions towards GABA production and cell growth as determined using a two-level factorial design. Steepest ascent identified optimal conditions (36°C, pH 5.5, 370 mM MSG, and 0.7 mM PLP), resulting in 30.50 g/L GABA and 11.51 log CFU/mL at 60 h. Further refinement via a central composite experiment yielded optimal conditions (temperature-35.6°C, pH-5.66, initial MSG concentration-335.61 mM, PLP concentration-0.723 mM) with improved GABA production (32.18 g/L) and cell growth (11.52 log CFU/mL) over 63.66 h. Therefore, this approach utilising lactic acid bacteria capable of GABA synthesis holds promise for mass-produced, enhanced-functional foods.

Comparative studies on modeling and optimization of fermentation process conditions for fungal asparaginase production using artificial intelligence and machine learning techniques

The L-asparaginase is commercial enzyme used as chemotherapeutic agent in cancer treatment and food processing agent in backed and fried food industries. In the present research work, the artificial intelligence and machine learning techniques were employed for modeling and optimization of fermentation process conditions for enhanced production of L-asparaginase by submerged fermentation of Aspergillus terreus. The experimental L-asparaginase activity obtained using central composite experiment design was used for optimization. The Random Forest algorithms machine learning techniques was found best based on the analysis of regression coefficient of ANN model and metric score values of machine learning algorithms. The experimental L-asparaginase activity of 41.58 IU/mL was obtained at the Random Forest algorithm predicted fermentation process conditions of temperature 31 °C, initial pH 6.3, inoculum size 2% (v/v), agitation rate 150 rpm and fermentation time 66 h.

Size optimization design of the driving shaft of the track robot

Abstract In the traditional mechanical design, the design of the drive shaft of the tracked robot requires a certain amount of engineering and practical experience, rather than based on scientific analysis and calculation, resulting in conservative design, long design cycle, and poor reusability. A response surface optimization design method was proposed, and the influence of multiple design variables on the performance of the drive shaft was investigated by a central composite experiment. The least square method was used to fit the approximate points, and the response surface model of the design variables and the performance of the drive shaft was established. The optimal size of the shaft diameter of each drive shaft was solved by a multi-objective genetic algorithm, and finally, three groups of optimization schemes were obtained. After optimization, the maximum equivalent stress, the maximum deformation, and the weight of the drive shaft are improved.

Optimizing the performance of TPCB/SCA composite-modified asphalt using improved response surface methodology

Abstract A composite-modified asphalt was developed by incorporating tire pyrolytic carbon black (TPCB) with a silane coupling agent (SCA) to enhance its ductility and storage stability. The functional binding between asphalt and TPCB was improved by the addition of SCA. The gray correlation comprehensive evaluation method is incorporated into the response surface methodology (RSM), leading to an improved RSM. The improved RSM was employed to optimize the content of the modifier and the preparation process to enhance overall performance. A central composite design-based experiment was conducted to optimize the penetration, softening point, 10°C ductility, Brookfield rotational viscosity, and storage stability indicators of modified asphalt. The response surface of the gray comprehensive evaluation value of the evaluation indicators was calculated using the gray correlation analysis method, and a second-order regression model was established between independent variables such as TPCB, SCA content, and shear time factor and the gray comprehensive evaluation value. This model analyzed the impact of a single variable and variable interaction on the performance of the TPCB/SCA composite-modified asphalt. The optimized model results showed that the preparation parameters that optimize the expected comprehensive performance of the composite-modified asphalt are 9.2% TPCB content, 2.1% SCA content, and a shear time of 56.3 min. Finally, the TPCB/SCA composite-modified asphalt prepared with the improved RSM exhibited the highest gray comprehensive evaluation value and the best overall performance, indicating the feasibility of the optimized preparation parameters with the improved RSM.

Utilizing discarded face masks to fabricate sustainable high-performance panels for enhanced building thermal and acoustic comfort

This study aims to design, fabricate, and optimize fibrous panels made of discarded polypropylene face masks (FMs) for application in sound absorption and thermal insulation. The discarded FMs were shredded and transformed into a fibrous mass using a Garnet machine. The resulting fibers, after being mixed with a bio-based binder, were molded based on an experimental design using response surface methodology in conjunction with the central composite experiment design (RSM-CCD) with five different thicknesses, densities, and blending ratios of spunbond to meltblown fabrics. The average of the sound absorption coefficients for the twelve one‐third‐octave bands from 200 to 2500 Hz (SAA) and effective thermal conductivity (Keff) of the panels were measured as the dependent parameters. These values were calculated within the ranges of 0.28–0.53 and 0.031–0.056 W/(mK), respectively. Additionally, the interactive effects of input variables on SAA and Keff of the manufactured panels were discussed. The quadratic and two-factor interaction models were proposed for optimizing the values of SAA and Keff, respectively. The optimal conditions were determined to achieve the maximum SAA and minimum Keff in a thickness of 26.7 mm, density of 135 kg/m3, and blending percentage of 32.4 %. Under these conditions, the measured values of SAA and Keff were 0.534 and 0.0279 W/mK, respectively. Finally, three fibrous panels were manufactured under optimal conditions, and their acoustic and thermal properties were measured. It was observed that excellent agreement exists between the model results and the experimental data with a 95% confidence level. The bending properties of the optimally designed panels were also investigated and the panels exhibited an impressive flexural strength of 2.1 MPa. Additionally, the fire performance of the panels was examined and all panels showed self-extinguishing properties. These findings suggest that panels made of discarded FMs hold promise as an eco-friendly and sustainable construction material for manufacturing acoustic and thermal insulation panels. Moreover, the frequency-dependent absorption coefficients of the panels were predicted using the Johnson-Champoux-Allard model.

Substantiation of the technology of treatment of flushing water of water treatment facilities with subsequent return to the technological cycle

The paper lists the existing technological schemes for the purification of flushing water of water treatment facilities; shows the results of a multifactorial central composite planning experiment with the obtained second-order correlation and regression analysis equations describing the dependence of the residual content of suspended solids on the initial content, sedimentation duration, coagulant dose when using various reagents; the recommended technological scheme for the purification of flushing water with technological calculation of the main structure.

ПОВЫШЕНИЕ ЭНЕРГОЭФФЕКТИВНОСТИ СИСТЕМЫ ОБРАБОТКИ ПОБОЧНЫХ ПРОДУКТОВ ЖИВОТНОВОДСТВА, ОСНОВАННОЙ НА ИХ АНАЭРОБНОЙ БИОКОНВЕРСИИ

One of the anaerobic bioconversion process’s significant disadvantage at organic waste and animal by products’ treatment is the limiting stage, namely hydrolysis existing. A number of wellknown methods of livestock organic waste and by products before methane fermentation’s pretreatment are described. To eliminate this disadvantage and hydrolysis process accelerating, it was proposed to use an improved vortex layer apparatus with an integrated ferromagnetic core located coaxially in the apparatus vortex layer’s working chamber pretreatment system using. This system allows to accelerate not only hydrolysis, but also to introduce additionally iron particles into the substrate, which are a catalyst for methanogenesis using. In addition, the iron particles anaerobic oxidation products are nutrients for methanogenic microorganisms. At the same time, it is known that the vortex layer apparatus consumed energy significant part into waste heat, that can be disposed by a pump’s compression heat using is converted. An experimental installation was developed and created, and its operation’s description is given. The energy consumption’s investigated system structure for animal by products processing based on their anaerobic bioconversion was also determined. By the response surface methodology using, key factors’ influence was studied, namely, of the initial substrate’s pumping rate, the vortex layer apparatus cooling system for pumps’ circulation supply and electromagnetic field in the vortex layer apparatus’ coil frequency on the coolants’ temperatures in the heat pump’s compression evaporator and condenser and the initial substrate’s temperature’s changing and, as a result, the energy efficiency process preprocessing. By the central composite experiment’s design using, these factors’ optimal values with an electricity coefficient conversion into heat optimized value based on previously defined optimization’s criteria were found. The obtained experimental data allow to talk about in both the electricity conversion’s coefficient spent on the ABC operation and the energy system’s efficiency as a whole increasing.

Comparative characteristics of different methods for electrophoretic determination of mono- and disaccarides using derivatization

The following variants of electrophoretic determination of sugars with prior derivatization are considered in the article: reductive amination using p-aminobenzoic acid ethyl ester (ABEE) and condensation with 1-phenyl-3-methyl-5-pyrazolone (PMP). Derivatization products were separated using capillary electrophoresis in both zone and micellar modes, and comparative estimate characteristics were obtained. The best efficiency (ca. 650 thousand theoretical plates), selectivity (2.1–2.4), and LOD (0.8–2.9 μg/mL) was observed for the separation of reductive amination products using micellar electrokinetic chromatography (MEKC). Optimization of derivatization conditions was performed for the reductive amination using the central composite experiment design. Additionally, LOD was lowered by the sample intracapillary concentration in sweeping mode, and sample enhancement factors (SEF) of 13–19 were achieved. A proof-of-concept possibility of the intracapillary reductive amination ensuring electrophoretic mobility of the derivatization reagent using detergent micelles as carrying agents was demonstrated. Both derivatization methods were applied for the analysis of baby food.

Experimental investigation and optimization of morphological characteristics in mechanically agitated aluminium 6061‐fly ash cenosphere composite

AbstractThe current work examines the results of an experimental study for the liquid casting of an aluminum‐6061‐5 weight % fly ash cenosphere composite by employing stir casting. The studies were conducted using the response surface methodology (central composite design L16 experiments) with three process factors (stirring temperature, stirring speed, and stirring time) at three different levels. An attempt has been made to determine the impact of process variables on the degree of sphericity and particle size. The optimal processing conditions for the best degree of sphericity (0.765) and particle size (93.227 μm) are identified as A−1, B+1, and C+1, corresponding to a stirring temperature of 670 °C, a stirring speed of 600 min−1, and 15 min stirring time. Based on the analysis of variance analysis, the degree of sphericity and particle size evolution is significantly influenced by stirring time followed by temperature and speed. Additionally, a mathematical model for the evaluation of the degree of sphericity and particle size in the primary‐aluminium phase has been developed and it shows good consensus with the experiments.

Super-high interface adhesion through silver/polyimide heterojunction

Metallized polymer film is becoming increasingly common in cutting-edge technology fields, and interface adhesion is the key factor affecting service performance. In this article, we used all-wet process to prepare Ag/Polyimide composite film with ultra-high interface adhesion (Over 25 N/cm). The influence of etching and reduction on interface adhesion was analyzed using central composite experiments and response surface methodology. Microcracks on polyimide (PI) surface were the basis for the formation of mechanical interlocks. And combined with SEM, EDS, and XPS data, the effect of Ag structure and composition on interface adhesion during reduction was summarized. The role of Ag aggregations at interface was explained, and concluded the detachment of Ag aggregations during peeling and high temperature was the main reason of failure. RFID tag, Circuit, and Cu/Ag/PI film (Resistivity: 9.3 × 10−6 Ω·cm) were made, which confirmed the compatibility and usability of Ag/PI film.

Optimization of the Transdermal Delivery System in Astilbin Microemulsion with Improved Stability and Anti-psoriatic Activity.

Astilbin is a promising candidate drug for psoriasis. However, the poor solubility and stability limited its clinical application. The present work aimed to develop a stable microemulsion of astilbin formulation and evaluate its effect in vitro and in vivo. Oil phase, surfactants, and cosurfactants were screened using solubility and stability of astilbin as the index. The central composite experiment design and response surface methodology analysis were adopted to optimize microemulsion parameters. The particle size, zeta potential, polydispersity index, viscosity, drug content, encapsulation, transmission electron microscopy (TEM), and stability of the optimized microemulsion were evaluated. Then, the drug release and anti-psoriasis effects were evaluated in a mouse model induced by imiquimod. The optimum formulation contained Labrafil M 1944 Cs (10.12%), Polyoxyethylene Castor Oil 35 (37.41%), propylene glycol (12.47%), water (40%), and gallic acid (2.9%), and the average particle size was 14.71 nm. The permeability of astilbin from the optimized astilbin-gallic acid microemulsion in 24 hr was 4.39 times higher compared with the astilbin's microemulsion. The content of astilbin in astilbin-gallic acid microemulsion remained unchanged after being stored at 25°C for 4 months compared with astilbin aqueous (3 h) and astilbin microemulsion (185 h). Compared with the model group, the optimized formulation decreased the PASI score and Baker score by 49% and 73%, respectively, which showed a favorable anti-psoriasis effect. Moreover, there was no difference in the anti-psoriasis effect between the optimized group and the positive control. These results indicated that the astilbin-gallic acid microemulsion might be a potential topical drug used for the treatment of psoriasis.

Willingness-to-pay experimental model for Stackelberg dual channel pricing decision

PurposeThis study proposes and demonstrates a novel approach to analyzing customer channel preferences and willingness-to-pay (WTP) in the dual sales channel (DSC) system involving direct online channels and conventional offline retailers, and to how the pricing decisions are made under specific game competition.Design/methodology/approachQuestionnaire survey based on central composite experiment design was utilized to obtain primary data. The model for customer channel preferences and WTP was then built by using multinomial logistic regression. The propensity of a customer to make purchases in either channel estimated by using the logit model was inserted in the bilevel programming model to formulate and solve for the Stackelberg competition where the conventional retailer acted as a leader.FindingsThe study found that channel prices have nonlinear impacts on WTP and channel preference. The empirical results complement the mathematical formulation well where high-order own-price and cross-price effects on channel selection are generally not analytical tractable. Under the Stackelberg competition, the traditional retailer (as the leader) still achieves higher profits than the online facility.Practical implicationsThe proposed framework provides an empirical approach that can easily address the competition model in the sales channel when complicated own-price or cross-price effects are present.Originality/valueThe present work provides a novel approach to analyze customer preference and WTP of the DSC systems. This alternative method simplifies the procedure for investigating and estimating price sensitivity, especially when the online and offline prices affect customer WTP and channel preferences nonlinearly. This model is also utilized in the game competition to facilitate data-driven price decision making to better formulate and understand real-world DSC problems.

Optimization and Experiment of Fertilizer-Spreading Device for Wheat Wide-Boundary Sowing Planter under Full Rice Straw Retention

When sowing with a wide boundary under full rice straw retention in the rice–wheat rotation area of China, conventional fertilization methods have some problems, such as a low fertilizer utilization rate, heap soil around a buried fertilizer device, or blocked fertilizing orifice. Firstly, combined with theoretical analysis, discrete element numerical simulation technology, and central composite test method, the wide-boundary fertilization device for wheat wide-boundary sowing was designed. Then, with the coefficient of variation for particle uniformity (CVPU) as the response value, the central composite experiment was carried out on the key structural parameters (focal length coefficient, lateral span, tilt angle, and ground clearance) of the wide-boundary fertilization device by EDEM software. Finally, the influential rules of core factors of the device on the CVPU were analyzed by Design-Expert software; then, the optimal parameter combination was determined and verified by a field test. The results showed that all factors had significant effects on the CVPU. The primary and secondary factors affecting the CVPU were the tilt angle, lateral span, focal length coefficient, ground clearance, tilt angle × ground clearance, and lateral span × ground clearance, in which there were certain interactions between the tilt angle and ground clearance and lateral span and ground clearance. When the focal length coefficient, lateral span, tilt angle, and ground clearance were 1.5, 60 mm, 30°, and 192 mm, respectively, the lateral was minimum. In this case, the theoretical value and field test value were 14.11% and 17.63%, respectively. The field test value is consistent with the theoretical calculation value. This study could provide references for the design of a fertilizer-spreading device with a wide boundary.

Repurposing levocetirizine hydrochloride loaded into cationic ceramide/phospholipid composite (CCPCs) for management of alopecia: central composite design optimization, in- silico and in-vivo studies

Levocetirizine hydrochloride (LVC) is an antihistaminic drug that is repurposed for the treatment of alopecia. This investigation is targeted for formulating LVC into cationic ceramide/phospholipid composite (CCPCs) for the management of alopecia. CCPCs were fabricated by ethanol-injection approach, through a central composite experiment. CCPCs were evaluated by inspecting their entrapment efficiency (EE%), polydispersity index (PDI), particle size (PS), and zeta potential (ZP). The optimum CCPCs were additionally studied by in-vitro, ex-vivo, in-silico, and in-vivo studies. The fabricated CCPCs had acceptable EE%, PS, PDI, and ZP values. The statistical optimization elected optimum CCPCs composed of 5 mg hyaluronic acid, 10 mg ceramide III, and 5 mg dimethyldidodecylammonium bromide employing phytantriol as a permeation enhancer. The optimum CCPCs had EE%, PS, PDI, and ZP of 88.36 ± 0.34%, 479.00 ± 50.34 nm, 0.377 ± 0.0035, and 20.20 ± 1.13 mV, respectively. The optimum CCPC maintained its stability for up to 90 days. It also viewed vesicles of tube shape via transmission electron microscope. The in-silico assessment resulted in better interaction and stability between LVC and vesicle components in water. The ex-vivo and in-vivo assessments showed satisfactory skin retention of LVC from optimum CCPCs. The histopathological assessment verified the safety of optimum CCPCs to be topically applied. Overall, the optimum CCPCs could be utilized as a potential system for the topical management of alopecia, with a prolonged period of activity, coupled with reduced LVC shortcomings.

Optimization of Shearer Drum Based on Multi-Objective Bat Algorithm with Grid (MOBA/G)

The shearer drum undertakes the main function of coal falling and loading, and picks distributed on it have a great impact on the performance of the drum. However, few studies have optimized the pick and drum at the same time. In this paper, parameters of pick and drum are considered as design variables, and the response functions of design variables are established based on the central composite experiment method. The optimal structural and working parameters of the pick and the drum of MG500/1130-WD shearer are obtained by using the multi-objective bat algorithm and multi-objective bat algorithm with grid, respectively. Comparing results of the two algorithms, the multi-objective bat algorithm with grid is more effective in improving the comprehensive performance of the drum. According to the optimized design variables, a coal mining test is carried out to verify the optimization effect of the algorithm. The result provides some theoretical references for the design and production of the drum and has some engineering application value.

Numerical study and multi-objective optimization of flexible screening process of flip-flow screen: A DEM-FEM approach

Vibrating flip-flow screens are widely used in deep screening processes. However, in-depth studies on flexible screening processes and the optimization of their operating parameters are limited. This study combines the discrete element method (DEM) and finite element method (FEM) to establish a coupled DEM–FEM model for simulating flexible screening processes. The reliability of the model was experimentally verified. Single-factor and central composite experiments were conducted to analyze the effects of y-direction amplitude, relative amplitude, installation angle, and frequency on particle speed, screening efficiency, and sieve plate stress. Finally, multi-objective optimization was implemented. The results revealed the dynamic response of the amplitude and stress on the flexible screen surface under the impact of materials. Moreover, a mathematical fitting model was derived to describe the relationship between the evaluation index and vibration parameters. Accordingly, a foundation for effectively improving the performance and reliability of flexible screening was established.

Research on the Operational Modal Prediction of Dry Gas Seal System Based on Response Surface Method

The cross power spectrum function is used to realize the operational modal analysis and identification of the dry gas seal device system through the multi-reference point least squares complex frequency domain method. The steady state diagram and mathematical indicators MAC, MPD, MPC, MOV and MIF are used to verify the modal results. At the same time, based on the response surface method, with two different operating conditions of medium pressure and rotating speed, modal direction and modal order as the response surface variables, a time-varying modal recognition model is established. Through the Full Factorial experiment design, Box-Behnken experiment design and Central Composite experiment design, the suitable variable sample points are formed. A complete quadratic polynomial response surface model of the system operational modal parameters is established. The complex correlation coefficient, the modified complex correlation coefficient and the root mean square error are used to verify the effectiveness of the response surface model. It provides new method and technical support for realizing time-varying modal identification in this paper.

Optimization of operating parameters of seeding device in plot drill with seeding control system

Plot drill has a significant impact on field breeding by replacing manual seeding. However, the seeding performance of plot drill needs to be further improved as the mechanical transmission method cannot work under the optimal combination of operating parameters. In this study, a cone compartment tray of sowing device was evaluated under the laboratory conditions, using a self-designed seeding control system to adjust the operating parameters. Among them, a plot seeding control system was involved that could set operating parameters through an Android terminal, which effectively reduced the difficulty of parameters adjustment. The method of central composite experiment design was employed to conduct experiments and explore the effects of experiment factors such as lifting height of storage tube (LHST), rotation speed of cone compartment tray (RSCCT), and rotation speed seed distributor (RSSD) on the seeding uniformity coefficient of variation among rows (SUCVR) and the rate of damaged seeds (RDS). For SUCVR of wheat, the results showed that the importance order of main factors from high to low was RSSD, RSCCT and LHST. And for SUCVR of buckwheat, RSCCT had the largest influence, followed by RSSD, and LHST had the smallest influence. For RDS of wheat and buckwheat, only RSSD had a very significant effect among the main factors. The experiments data of wheat indicated that when operated at 27.2 mm for LHST, 4.5 r/min for RSCCT and 1169 r/min for RSSD, the sowing performance of wheat was optimal, with SUCVR and RDS values of 5.02% and 0.117%, respectively. The buckwheat seeding performance was found to be optimal when the LHST, RSCCT and RSSD were 26.5 mm, 3.9 r/min and 711 r/min, and SUCVR and RDS were 4.74% and 0.113%. The seeding control system realized the electromechanical control of the seeding equipment, was convenient for parameter setting and stepless adjustment, and could be operated under an optimized combination of operating parameters. The research results could provide a reference for the performance improvement and application of plot drill. Keywords: plot drill, seeding device, seeding control system, seeding performance, parameter optimization DOI: 10.25165/j.ijabe.20211403.6218 Citation: Cheng X P, Li H W, He J, Wang Q J, Lu C Y, Wang Y B, et al. Optimization of operating parameters of seeding device in plot drill with seeding control system. Int J Agric & Biol Eng, 2021; 14(3): 83–91.