Screening Design Research Articles

Analysis of Ultrasonic Vibration-Assisted Ball Burnishing Process on the Tribological Behavior of AISI 316L Cylindrical Specimens.

In this study, we analyzed the effects of vibration assistance, combined with a ball burnishing process, in terms of topology, residual stresses, and tribological properties on 316L shafts. The burnishing variables consisted of the variation of the input force, the number of passes, and the activation of the vibration assistance, which is based on a 40 kHz frequency and 8 μm of vibration amplitude, derived in a screening design of three factors. The results show that the medium-high level of burnishing force, high level of the number of passes, and the activation of the vibration assistance are the best options in order to improve the average roughness, the microstructure, the increase in the compressive residual stresses, and the wear enhancement, besides all variables being significant in the p-value analysis through ANOVA. Statistically, the vibration-assisted ball burnishing improved the average roughness by 2.9%, enlarged the von Mises stress on the surface by 11.5% and enhanced the wear resistance of a 316L shaft and WC-Co ball contact up to 7.3%.

I-Cubid: a nonlinear cubic graph-based approach to visualize and in-depth browse Flickr image results.

The existing image search engines allow web users to explore images from the grids. The traditional interaction is linear and lookup-based. Notably, scanning web search results is horizontal-vertical and cannot support in-depth browsing. This research emphasizes the significance of a multidimensional exploration scheme over traditional grid layouts in visually exploring web image search results. This research aims to antecedent the implications of visualization and related in-depth browsing via a multidimensional cubic graph representation over a search engine result page (SERP). Furthermore, this research uncovers usability issues in the traditional grid and 3-dimensional web image search space. We provide multidimensional cubic visualization and nonlinear in-depth browsing of web image search results. The proposed approach employs textual annotations and descriptions to represent results in cubic graphs that further support in-depth browsing via a search user interface (SUI) design. It allows nonlinear navigation in web image search results and enables exploration, browsing, visualization, previewing/viewing, and accessing images in a nonlinear, interactive, and usable way. The usability tests and detailed statistical significance analysis confirm the efficacy of cubic presentation over grid layouts. The investigation reveals improvement in overall user satisfaction, screen design, information & terminology, and system capability in exploring web image search results.

Disease Bundling or Specimen Bundling? Cost- and Capacity-Efficient Strategies for Multidisease Testing with Genetic Assays

Problem definition: Infectious disease screening can be expensive and capacity constrained. We develop cost- and capacity-efficient testing designs for multidisease screening, considering (1) multiplexing (disease bundling), where one assay detects multiple diseases using the same specimen (e.g., nasal swabs, blood), and (2) pooling (specimen bundling), where one assay is used on specimens from multiple subjects bundled in a testing pool. A testing design specifies an assay portfolio (mix of single-disease/multiplex assays) and a testing method (pooling/individual testing per assay). Methodology/results: We develop novel models for the nonlinear, combinatorial multidisease testing design problem: a deterministic model and a distribution-free, robust variation, which both generate Pareto frontiers for cost- and capacity-efficient designs. We characterize structural properties of optimal designs, formulate the deterministic counterpart of the robust model, and conduct a case study of respiratory diseases (including coronavirus disease 2019) with overlapping clinical presentation. Managerial implications: Key drivers of optimal designs include the assay cost function, the tester’s preference toward cost versus capacity efficiency, prevalence/coinfection rates, and for the robust model, prevalence uncertainty. When an optimal design uses multiple assays, it does so in conjunction with pooling, and it uses individual testing for at most one assay. Although prevalence uncertainty can be a design hurdle, especially for emerging or seasonal diseases, the integration of multiplexing and pooling, and the ordered partition property of optimal designs (under certain coinfection structures) serve to make the design more structurally robust to uncertainty. The robust model further increases robustness, and it is also practical as it needs only an uncertainty set around each disease prevalence. Our Pareto designs demonstrate the cost versus capacity trade-off and show that multiplexing-only or pooling-only designs need not be on the Pareto frontier. Our case study illustrates the benefits of optimally integrated designs over current practices and indicates a low price of robustness. Funding: This work was supported by the National Science Foundation [Grant 1761842]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0296 .

Optimization of the Crystallization Process of TFA-MOD ErBCO Films on IBAD-Substrate Under Low-Pressure Conditions via DSD Approach

Crystallization in a sub-atmospheric reactor could achieve higher production rate while dramatically reducing the flow rate of high-purity carrier gas. Due to enhanced supersaturation conditions at low total pressure, it is necessary to find the optimum processing window to avoid misoriented growth. This is extensive and incomplete when using one-factor-at-a-time experiments as significant parameters are often correlated. <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">We prepared ErBa₂Cu₃O_7-<i>_δ</i> (ErBCO) films by the TFA-MOD route with low-fluorine solutions on technical IBAD template with CeO₂ top buffer layer in an industrial reel-to-reel furnace. We used a novel design-of-experiment (DOE) technique, the Definitive Screening Design (DSD), to identify significant factors for improving critical temperature and microstructure of the films. Within the investigated range, lower crystallization temperature as well as lower total pressure are beneficial. With the new process window, the self‑field critical current density at 77 K was successfully increased from almost zero to 1 MA/cm². This shows that DSD is an attractive approach to optimize the CSD process under low-pressure conditions to enhance the growth rate or possibly achieve a reduction of carrier gas flow rate by a factor <i>p</i>_tot/<i>p</i>_atm of 3.3 for equal output as the atmospheric reactor. Further improvement of <i>J</i>_c is necessary and possible.

Penerapan Metode Design Thinking untuk Perancangan UI/UX Sistem E-Marketplace Berbasis Website

E-Marketplace is an application that allows users to enjoy a shopping experience with a minimalist design. A systematic manufacturing process using design thinking empathize, define, ideate, prototype and test methodologies. The author hopes to create an ideal website for various marketing platforms. The design thinking method can also work smoothly if UI and UX (User Interface and User Experience) can be created. Using the usability test method as a prototype reference and using the Google Form to determine the best design for the TOP 5 marketplaces and using Preview Figma to solicit different opinions at the Emphatize stage by collecting data from 105 Shopee, Lazada, Blili, Bukalapak and Tokopedia users to use Google's market solutions. The purpose of this research is that this prototype can be accepted by the community, especially active market users. After going through different stages, the final result of this research is the creation of a homepage according to the components of the system design. Received user test data About 99% of the 105 data collected, of which 54.3% women and 45.7% men used the marketing platform and presented their assumptions about the header design obtained from the screen design which received 58.1% of the 105 users who chose SHOPEE. In the final stage, FGD (Forum Group Discussion) and expert judgment were carried out to determine whether the prototype created was ideal and able to compete in the virtual world market. can be interpreted as a conclusion that this prototype can be accepted in the community, considering that it still needs significant improvement and development according to user feedback.

Optimization and synthesis of a novel sorbent composite based on magnetic chitosan-amine-functionalized bimetallic MOF for the simultaneous dispersive solid-phase microextraction of four aflatoxins in real water, herbal distillate, and food samples.

Aflatoxins (AFs), an important category of pollutants, are formed in many foods and adversely affect human health. Therefore, their determination is critical to ensuring human food health. An efficient dispersive solid-phase microextraction technique was developed as a simple and straightforward sample preparation technique for determination of four aflatoxins using a high-performance liquid chromatography (HPLC) fluorescence detector. A novel efficient, green sorbent for extracting AFs was synthesized based on hydrothermal and chemical strategies. The amounts of three sorbent components were optimized using a mixture design (simplex lattice design), including 14 experiments. The optimal amount of amino-bimetallic Fe/Ni-MIL-53 nanospheres, chitosan, and magnetic Fe3O4 nanoparticles as sorbent components was 0.87, 0.67, and 0.47 g, respectively. Also, various factors affecting the process of AF determination were studied and optimized in two successive experimental designs, including the definitive screening design and the Box-Behnken design. Under optimal conditions, the linear ranges for measuring aflatoxin B1, aflatoxin B2, aflatoxin G1, and aflatoxin G2 were 0.05-82.6, 0.07-86.4, 0.08-85.7, and 0.07-89.5 ng mL-1, respectively. The relative standard deviations under inter-day and intra-day conditions for measuring AFs at three analyte concentrations were determined in triplicate analysis and were in the ranges of 3.7-4.6% and 4.9-6.1% for water sample analysis, respectively. The qualitative detection limits for determining AFs were between 0.01 and 0.05 ng mL-1. The pre-concentration factor of the method for measuring AFs ranged from 739.7 to 802.1. The proposed method was used for determining AFs in several real samples, including herbal distillate, black tea, corn, and real water samples. The relative recovery and standard deviation were 87.8-97.8% and 4.10-6.82%, respectively.

Efficient optimization approaches for microwave assisted extraction of high-quality antioxidant compounds from Salvia officinalis L.: UHPLC-HRMS differential analysis of phenolic profiles obtained by ultrasound and microwave extraction

The study aims to optimize MAE of total phenolic compounds (TPC) and antioxidant capacity from Salvia officinalis L. leaves using a definitive screening design (DSD) and I-optimal design. UHPLC-HRMS analysis was used to identify and compare the composition of MAE and UAE optimal extracts. The results showed that DSD and I-optimal design were successfully applied for the optimization of MAE targeting phenolics and other antioxidants from S. officinalis L. with the following optimum conditions: 60% ethanolic solvent, time of 4.75 min, power of 600 W, and L/S ratio of 50 mL g−1. The UHPLC-MS analysis results allowed the identification of more than 80 compounds, and the differential analysis indicated that the MAE yielded a higher level of 181 substance peaks, while the UAE yielded a higher level of 87 substance peaks. This study provides valuable information for selecting the appropriate extraction technique when targeting specific compounds.

Optimizing the Functional Properties of Starch-Based Biodegradable Films.

A definitive screening design was used in order to evaluate the effects of starch, glycerol and montmorillonite (MMT) concentrations, as well as the drying temperature, drying tray type and starch species, on packaging film's functional properties. Optimization showed that in order to obtain films with the minimum possible thickness, the maximum elongation at break, the maximum tensile strength, as well as reduced water vapor permeability and low opacity, a combination of factors should be used as follows: 5.5% wt starch concentration, 30% wt glycerol concentration on a dry starch basis, 10.5% wt MMT concentration on a dry starch basis, 45 °C drying temperature, chickpea as the starch species and plexiglass as the drying tray type. Based on these results, starch films were prepared, and fresh minced meat was stored in them for 3 days. It was shown that the incorporation of MMT at 10.5% wt on a dry starch basis in the packaging films led to a decreased mesophilic and psychrotrophic bacteria growth factor compared to commercial packaging. When assessed for their biodegradability, the starch films disintegrated after 10 days of thermophilic incubation under simulated composting conditions. Finally, to prove their handling capability during industrial production, the starch films were rewound in a paper cylinder using an industrial-scale rewinding machine.

Use Straw in the Removal of Petroleum Hydrocarbons from Industrial Wastewater for South Refinery Company in Basrah Province

In this study, a straw was employed at the coagulation and flocculation of total petroleum hydrocarbons from industrial wastewater in the refinery oil company in Basra province, using the design of experiments approach using the method of (analyzing screening designs). Independent factors in the experiments (pH, dose of the substance used for removal, and time of the experiment). Furthermore, the link between the test's independent variables and their impact on the elimination process. As previously stated, the results revealed that the square model is the optimum model in this study, and the maximum removal was 100% at PH (3), dose (2) g, and time (30) minutes, and a comparison was made between the experimental design DOE and the multiple linear regression MLR to determine the effectiveness of the system used, which proved its great effectiveness. MLR was too distant from the real consequences of DOE removal when there was a strong convergence between the real and expected impacts of DOE removal.

African locust bean (Parkia biglobosa) seed coat: A source of phenolic compounds

Parkia biglobosa is a versatile plant species used extensively by local communities in arid Africa. The seeds of this plant are valued for their high polyphenol content, highlighting their therapeutic antioxidant, and anti-inflammatory, antimicrobial, antidiabetic and antihypertensive properties. The aim of this study was to optimize the conditions for the extraction of the polyphenol content of the seed coat of P. biglobosa. Five extraction factors, namely solvent concentration, time, temperature, solid-liquid ratio, and pH, were optimized using the response surface technique. The optimization screening design results showed that temperature, time and solvent concentration were the most important variables with significant effects on polyphenol yield in a two-stage Placket-Burman design (p0.05). Box Behnken and Response Surface Analysis were applied to further investigate the mutual interactions between these variables and determine the ideal values that give the highest possible phenolic yield. The results showed the following ideal extraction conditions: 45 °C temperature, 240 min extraction time and 47.5 % solvent concentration. The TPC value obtained under the ideal extraction conditions was 54.023 ± 2.05 mg GAE /g. The antioxidant activity results of the concentrates showed 72.389 % inhibition of 2, 2-diphenyl-2-picrylhydrazyl hydrate and antioxidant capacity of 80.96 ± 1.16 mg AA /g. The results of the study show that the model is suitable for maximizing polyphenol extraction from the dried seed coat of P. biglobosa, as there is good agreement between the laboratory experiments and the estimated values

Development of probiotic-loaded calcium alginate-maltodextrin microparticles based on electrohydrodynamic technique

Maintaining the viability of probiotic bacteria in food products for intestinal delivery remains a challenge. Consequently, the objective of this study was to encapsulate Lactobacillus rhamnosus (NCDC 18) in calcium alginate–maltodextrin hydrogel systems by combining electrospraying and freeze-drying techniques. The microparticles were produced using varying concentrations of sodium alginate (SA) (2, 3, and 4%) in conjunction with maltodextrin (MD) (0, 2, and 4%). A definitive screening design (DSD) was used to design experiments and explain the effect of independent variables (concentrations of SA, calcium chloride, and MD and electrospraying voltage) on the response variables: loss of viability, encapsulation efficiency, drying yield, Carr's index, and Hausner ratio. The obtained microparticles were characterized by employing Scanning Electron Microscopy (SEM), Fourier Transform Infrared Spectroscopy (FTIR), and Differential Scanning Calorimetry (DSC). The addition of MD significantly increased encapsulation efficiency up to 75.19% and decreased viability loss up to 2.539 log CFU/mL in microparticles. The morphological analysis revealed the particle surface structure and variation in porosity in response to varying variables. The FTIR spectra confirmed that the addition of SA, MD, and probiotics caused synergistic changes in the functional bonding. The XRD analysis could further elucidate the interactions of SA with MD in the microcapsules. Our study could confirm that MD acted as a cryoprotectant and decreased the concavities and pores on the surface of the microparticles, thereby enhancing their probiotic-related properties.

The synergetic effect from the combination of different adsorption resins in batch and semi-continuous cultivations of S. Cerevisiae cell factories to produce acetylated Taxanes precursors of the anticancer drug Taxol.

In situ product recovery is an efficient way to intensify bioprocesses as it can perform adsorption of the desired natural products in the cultivation. However, it is common to use only one adsorbent (liquid or solid) to perform the product recovery. For this study, the use of an in situ product recovery method with three combined commercial resins (HP-20, XAD7HP, and HP-2MG) with different chemical properties was performed. A new yeast strain of Saccharomyces cerevisiae was engineered using CRISPR Cas9 (strain EJ2) to deliver heterologous expression of oxygenated acetylated taxanes that are precursors of the anticancer drug Taxol ® (paclitaxel). Microscale cultivations using a definitive screening design (DSD) were set to get the best resin combinations and concentrations to retrieve high taxane titers. Once the best resin treatment was selected by the DSD, semi-continuous cultivation in high throughput microscale was performed to increase the total taxanes yield up to 783 ± 33 mg/L. The best T5α-yl Acetate yield obtained was up to 95 ± 4 mg/L, the highest titer of this compound ever reported by a heterologous expression. It was also observed that by using a combination of the resins in the cultivation, 8 additional uncharacterized taxanes were found in the gas chromatograms compared to the dodecane overlay method. Lastly, the cell-waste reactive oxygen species concentrations from the yeast were 1.5-fold lower in the resin's treatment compared to the control with no adsorbent aid. The possible future implications of this method could be critical for bioprocess intensification, allowing the transition to a semi-continuous flow bioprocess. Further, this new methodology broadens the use of different organisms for natural product synthesis/discovery benefiting from clear bioprocess intensification advantages.

Optimization of biodiesel production, engine exhaust emissions, and vibration diagnosis using a combined approach of definitive screening design (DSD) and artificial neural network (ANN).

In this study, definitive screening design (DSD) optimization and artificial neural network (ANN) modelling techniques are applied for the production of palm oil biodiesel (POBD). These techniques are implemented to examine the vital contributing factors in achieving maximum POBD yield. For this purpose, seventeen experiments are conducted randomly by varying the four contributing factors. The results of DSD optimization reveal that a biodiesel yield of 96.06% is achieved. Also, the experimental results are trained in ANN for predicting the biodiesel yield. The results proved that the prediction capability of ANN is superior, with a high correlation coefficient (R2) and low mean square error (MSE). Furthermore, the obtained POBD is characterized by significant fuel properties and fatty acid compositions and observed within the standards (ASTM-D675). Finally, the neat POBD is examined for exhaust emissions and engine cylinder vibration analysis. The emissions results confirm a significant drop in NOx (32.46%), HC (40.57%), CO (44.44%), and exhaust smoke (39.65%) compared to diesel fuel at 100% load. Likewise, the engine cylinder vibration measured on top of the cylinder head reveals a low spectral density with low amplitude vibrations observed for POBD at measured loads.

RNA crystal improvement with definitive screening designs

RNA crystal improvement with definitive screening designs

Specific Clearance of Lipopolysaccharide from Blood Based on Peptide Bottlebrush Polymer for Sepsis Therapy.

Lipopolysaccharide (LPS) is the primary bacterial toxin that is vital to the pathogenesis and progression of sepsis associated with extremely high morbidity and mortality worldwide. However, specific clearance of LPS from circulating blood is highly challenging because of the structural complexity and its variation between/within bacterial species. Herein, a robust strategy based on phage display screening and hemocompatible peptide bottlebrush polymer design for specific clearance of targeted LPS from circulating blood is proposed. Using LPS extracted from Escherichia coli as an example, a novel peptide (HWKAVNWLKPWT) with high affinity (KD < 1.0 nм), specificity, and neutralization activity (95.9 ± 0.1%) against the targeted LPS is discovered via iterative affinity selection coupled with endotoxin detoxificationscreening. A hemocompatible bottlebrush polymer bearing the short peptide [poly(PEGMEA-co-PEP-1)] exhibits high LPS selectivity to reduce circulating LPS level from 2.63 ± 0.01 to 0.78 ± 0.05 EU mL-1 in sepsis rabbits via extracorporeal hemoperfusion (LPS clearance ratio > 70%), reversing the LPS-induced leukocytopenia and multiple organ damages significantly. This work provides a universal paradigm for developing a highly selective hemoadsorbent library fully covering the LPS family, which is promising to create a new era of precision medicine in sepsis therapy.

Design, development, and assessment of a High-Throughput Screening (HTS) system for the macroscopic root water uptake modeling

Climate change is responsible for the increasing frequency and intensity of abiotic stresses generating water scarcity conditions. There is a need to breed plants adapted to future environmental conditions and resistant to water stress. This study presents a High-Throughput Screening (HTS) system for continuously and simultaneously monitoring plant stress response to drought in a semi-controlled environment. The HTS system combines a gravimetric weighing system with soil moisture and atmospheric sensors. In operative terms, the system was tested on the Sage (Salvia officinalis L.) under two soil water deficit treatments managed according to a feedback control irrigation scheduling.The system was able to model the sage water stress function following the root water uptake macroscopic approach. The threshold of soil water status below which crop water stress occurred was also identified. The gravimetric-based daily evapotranspiration (ETa) and the time domain reflectometry (TDR)-based root water-uptake (RWU) rates showed a high correlation during the drying when the evaporation flux is minimal. Moreover, the effects of soil bulk density on the root density and the plant biomass were evaluated, indicating the importance of carrying out a homogeneous procedure of the pot-filling process.

Preferential Contamination in Electroadhesive Touchscreens: Mechanisms, Multiphysics Model, and Solutions

AbstractElectroadhesive surface haptic touchscreens can help augment user experiences by providing tactile effects. The electrode layout in current commercialized designs has separated electrodes for the sensing and actuating functions. During regular use, it is observed that fingerprint residue preferentially deposits on the actuating electrodes far more than the sensing electrodes, which makes the underlying electrode pattern apparent and is highly undesirable for touchscreen users. To address this issue, various physical phenomena (electrohydrodynamic deformation, capillary bridge stabilization, electrowetting, and electrophoretic deposition) are investigated to understand the mechanism. Through experimentation, multiphysics modeling, and surface characterization, it is found that the root cause can be attributed to two mechanisms occurring in the actuating regions: 1) electrohydrodynamic deformation of sebum droplets attached to the finger valleys leading to the formation of additional capillary bridges and residual droplets on the screen surface after their rupture, and 2) electric field‐induced stabilization of sebum capillary bridges existing between the finger ridges and the screen, leading to the coalescence and formation of larger‐sized droplets. The developed model can then be used to address the issue during the screen design process. An example of using the model to explore the impact of changes in screen oleophobicity is shown.

Harnessing the Power of AI in Pharmacokinetics and Pharmacodynamics: A Comprehensive Review

Personalized medicine, medication discovery, and development might all benefit greatly from AI’s incorporation into pharmacokinetics and pharmacodynamics. Target identification, therapeutic effectiveness prediction, drug design optimization, obstacles, and future possibilities are all explored in this survey of AI applications in these areas. An overview of pharmacokinetics and pharmacodynamics is presented first, stressing the significance of knowing how drugs are absorbed, distributed, metabolized, and excreted and the correlation between drug concentration and pharmacological effect. The article then looks into the function of AI in target identification, exploring how machine learning algorithms and data integration may be used to discover new drug targets and enhance the design of existing ones. Classification and regression methods are also investigated for their potential use in the prediction of therapeutic efficacy using AI. Patient data, molecular interaction data, and clinical response data are just a few examples of the types of data that may be used to fuel the creation of predictive models that might assist in dosage and efficacy optimization. Metrics and procedures for validating these models are addressed to evaluate their efficacy. Additionally, de novo drug design, virtual screening, and structure-based drug design are all discussed in relation to the use of AI in optimizing drug development. The paper provides examples of how AI has been applied successfully in different settings, demonstrating its potential to hasten the drug discovery process and enhance treatment outcomes. We examine data availability, interpretability, and ethical implications as challenges and limits of AI in pharmacokinetics and pharmacodynamics. To guarantee these technologies’ proper and ethical use, we also discuss the regulatory elements and rules for applying AI in drug research. Possibilities and prospects for the use of AI in pharmacokinetics and pharmacodynamics are discussed as a conclusion to the review. It stresses the significance of regulatory standards and clinical translation, as well as the incorporation of multiomics data, deep learning methods, real-time monitoring, explainable artificial intelligence, collaborative networks, and more.

The effects of mobile applications’ passive and interactive loading screen types on waiting experience

ABSTRACT The loading screen is unavoidable to smartphone users, and the waiting experience influences the success of a mobile application. Providing visual feedback during waiting time is an effective way to increase the waiting experience. This study is the first to examine the effects of interactive loading screens on the waiting experience compared to a passive loading screen on mobile phones across varying waiting times. The rotating ring, which has been used in loading screens widely, was chosen in our experiments. Participants compared a passive animation with grey-scale and colour-changed interactive animations. The results indicated that the duration of waiting time has a significant impact on the selection of the loading screen type. The studies also demonstrate that colour can act as an essential design factor to improve the waiting experience when designing the interactive loading screen. Furthermore, it was found that perceived time was shorter when an interactive loading screen was used, leading to higher user satisfaction compared to a passive loading screen, especially for the long waiting time. The findings obtained in the experiments provide a reference and guidelines for loading screen design to improve users` waiting experience.

Application of the Plackett-Burman design for screening and optimisation of factors affecting the aqueous extract for total anthocyanin content of broken riceberry rice

The aim of the present work was to identify the key factors that influence the total anthocyanin content of the aqueous extract of broken riceberry rice (BRR). The eight-run Plackett-Burman design was used to evaluate four factors (BRR particle size, BRR powder/water ratio, extraction temperature, and time). As revealed by the results, the BRR powder/water ratio, extraction temperature, and time had a significant influence on the total anthocyanin content. As a consequence, single-factor tests were conducted using a completely randomised design (CRD), considering BRR powder/water ratio (1:2.5, 1:5, 1:7.5, and 1:10 g/mL), extraction temperature (50, 55, 60, 65, and 70°C), and time (50, 60, 70, 80, and 90 min). Based on the results, the criteria for yield optimisation were a BRR particle size of 60 mesh, BRR powder/water ratio of 1:5, extraction temperature of 60°C, and time of 70 min. With these parameters, the total anthocyanin concentration of the extract was 9.71 mg C3G/g dry material.