Effective Extraction Technique Research Articles

Extraction of Lactic Acid from Whey of Yoghurt by Solvent Extraction Technique

The aim of this paper is to investigate the possibility to recover lactic acid (LA) from the whey of yoghurt by easy and effective solvent extraction technique using tri-n-octylamine, tri-n-butyl phosphate, and their mixtures as extractant. All parameters affecting the transfer of lactic acid to the organic phase were investigated including: time of stirring, tri-n-butyl phosphate and tri-n- octylamine concentrations, organic to aqueous phase ratio, temperature, NaCl concentration as a salting out agent, and number of contacts. The maximum yield of LA extraction can be obtained by using the following operation conditions: 0.8M TOA+11% TBP, Vorg/Vaq = 4/1, t = 30 oC, [NaCl] = 2M. Complete stripping of LA from loaded organic phase can be done in 2 stages using double distilled water at 60oC and Vaq/Vorg = 20/1.

AgFlow: fast model selection of penalized PCA via implicit regularization effects of gradient flow

Principal component analysis (PCA) has been widely used as an effective technique for feature extraction and dimension reduction. In the High Dimension Low Sample Size setting, one may prefer modified principal components, with penalized loadings, and automated penalty selection by implementing model selection among these different models with varying penalties. The earlier work (Zou et al. in J Comput Graph Stat 15(2):265–286, 2006; Gaynanova et al. in J Comput Graph Stat 26(2):379–387, 2017) has proposed penalized PCA, indicating the feasibility of model selection in \(\ell _2\)-penalized PCA through the solution path of Ridge regression, however, it is extremely time-consuming because of the intensive calculation of matrix inverse. In this paper, we propose a fast model selection method for penalized PCA, named approximated gradient flow (AgFlow), which lowers the computation complexity through incorporating the implicit regularization effect introduced by (stochastic) gradient flow (Ali et al. in: The 22nd international conference on artificial intelligence and statistics, pp 1370–1378, 2019; Ali et al. in: International conference on machine learning, 2020) and obtains the complete solution path of \(\ell _2\)-penalized PCA under varying \(\ell _2\)-regularization. We perform extensive experiments on real-world datasets. AgFlow outperforms existing methods (Oja and Karhunen in J Math Anal Appl 106(1):69–84, 1985; Hardt and Price in: Advances in neural information processing systems, pp 2861–2869, 2014; Shamir in: International conference on machine learning, pp 144–152, PMLR, 2015; and the vanilla Ridge estimators) in terms of computation costs.

Residue level and health risk assessment of organophosphorus pesticides in eggplant and cauliflower collected from Dhaka city, Bangladesh

Residue levels of seven organophosphorus pesticides in two vegetables (eggplant and cauliflower) collected from major markets of Dhaka city, Bangladesh were analysed. The collected samples were analysed using a modified Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS) extraction technique by Gas Chromatography coupled with Flame Thermionic Detector (GC-FTD). Among the 50 analysed samples of the eggplant 12% samples contained residues of chlorpyrifos (0.384~0.980 mg/kg), 6% samples contained residue of dimethoate (0.052~0.132 mg/kg) and 2% samples contained residue of diazinon (0.01 mg/kg). Whereas, among the 50 samples of cauliflower, 12% samples contained residues of chlorpyrifos (0.056~0.540 mg/kg), 8% samples contained residues of diazinon (0.033~0.42 mg/kg) and 2% samples contained residues of quinalphos (0.06 mg/kg). The chlorpyrifos was found as the most frequently detected organophosphorus pesticide. Among the 21 contaminated samples, 20 were above EU-MRL. Short and long-term health risk assessment based on ARfD and ADI indicates that the intake risks of eggplant and cauliflower were in the acceptable range. Nevertheless, establishing strong monitoring and traceability system together with controlling pre-harvest interval needed to ensure food safety, consumer confidence and promote vegetable export from Bangladesh.

Fast and robust super-resolution DOA estimation for UAV swarms

Unmanned aerial vehicle (UAV) swarms have shown great potentials in civilian and military applications. Consequently, there is a high demand for accurate UAV swarms detection. In response to resolve the closely spaced UAVs, we propose three super-resolution direction of arrival (DOA) estimation algorithms, i.e., frequency-selective reweighted atomic-norm minimization (FSRAM), fast Fourier transform (FFT)-reweighted atomic-norm minimization (FFT-RAM) and FFT-FSRAM. These proposed three algorithms take full account of advantages of prior knowledge, effective information extraction and gridless sparse technique, i.e., i) the use of prior knowledge can improve the accuracy of DOA estimation; ii) the effective information extraction can improve the signal-to-noise ratio to enhance the robustness and reduce the computational complexity; iii) the gridless sparse technique is insensitive to signal correlations. Complexity analysis and numerical simulations are performed to demonstrate that, compared with the Beamforming method, multiple signal classification (MUSIC) and reweighted atomic-norm minimization (RAM), the proposed three algorithms are insensitive to signal correlations and the FFT-RAM and FFT-FSRAM are more robust and faster for super-resolution DOA estimation of UAV swarms under the noisy environment. Additionally, the real experiment with C-band radar is also conducted to verify the effectiveness of the proposed super-resolution DOA estimation algorithms.

An extensive clean-up method for extraction of 17β-estradiol from eel aquaculture waste solids for quantitation via high-performance liquid chromatography tandem-mass spectrometry

The use of 17β-estradiol (E2) in aquaculture feed increases growth and promotes feminization in freshwater eels. E2 and its metabolites (estrone (E1) and estriol (E3)) must be accurately measured in solid and liquid waste streams to ensure proper management. For reliable quantitation of estrogens in complex aquaculture waste solids, a rigorous clean-up method is imperative. The focus of this study was to assess, optimize, and validate a quick, easy, cheap, effective, rugged, and safe (QuEChERS) technique for extraction of estrogens from aquaculture waste solids and quantitation via liquid chromatography tandem-mass spectrometry (LC-MS/MS). Waste solids were collected from a recirculating aquaculture system containing American eels. Waste solids samples (2 g) were spiked to 50 μg kg−1 of E1, E2, and E3 and processed using 800 mg magnesium sulfate (MgSO4) and 400 mg of sodium acetate (NaOAc) as extraction salts. Two dispersive solid phase extraction (dSPE) steps were implemented to achieve optimal E2 recovery efficiency (RE (%)) in preliminary experiments (RE (%) = 102%; RSD = 5%). RE (%) for E1 and E3 were 87% (RSD = 54%) and 60% (RSD = 83%), respectively. Method performance characteristics were further assessed for E2 only and included specificity, linearity, accuracy (RE (%) and process efficiency (PE (%))), precision (intra-day precision, and inter-day precision), matrix effects, method detection limit (MDL), and limit of quantitation (LOQ). MDL and LOQ values for E2 were 0.7 and 2.3 μg kg−1, respectively. PE (%) and RE (%) were excellent (99–101% and 99–100%, respectively) and matrix effects were minimal (99 and 101%). The results of this study indicate that this method can be used for quantitation of E2 in aquaculture waste solids.

Fabricating a heavy oil viscosity reducer with weak interaction effect: Synthesis and viscosity reduction mechanism

We synthesized a copolymer with strong hydrophilicity and low surface and interfacial activity, which reduced the viscosity of heavy oil by interacting with asphaltenes or resins via hydrogen bonding. Water-soluble terpolymers (PAMD) were synthesized by the copolymerization of acryloyl morpholine, maleic anhydride with N, N-dimethylacrylamide in pure water. The copolymer showed low surface and interfacial activity, as well as the ability to weakly interact with heavy oil to form oil-in-water emulsions under stirring, but reducing the viscosity of the heavy oil by more than 90%. Under the condition of weak interaction between polymer and heavy oil, the oil-in-water emulsions dehydrated within 1 h to form oil and aqueous phases, which could be reused for the viscosity reduction at least five times. Therefore, this novel heavy oil viscosity reducer to provide a convenient and effective technique for oil extraction and reduce the burden of economic costs.

Optimization of Ultrasonic Cellulase-Assisted Extraction and Antioxidant Activity of Natural Polyphenols from Passion Fruit.

In this paper, ultrasonic cellulase extraction (UCE) was applied to extract polyphenols from passion fruit. The extraction conditions for total phenol content (TPC) and antioxidant activity were optimized using response surface methodology (RSM) coupled with a Box-Behnken design (BBD). The results showed that the liquid-to-solid ratio (X2) was the most significant single factor and had a positive effect on all responses. The ANOVA analysis indicated quadratic models fitted well as TPC with R2 = 0.903, DPPH scavenging activity with R2 = 0.979, and ABTS scavenging activity with R2 = 0.981. The optimal extraction parameters of passion fruit were as follows: pH value of 5 at 30 °C for extraction temperature, 50:1 (w/v) liquid-to-solid ratio with extraction time for 47 min, the experimental values were found matched with those predicted. Infrared spectroscopy suggested that the extract contained the structure of polyphenols. Furthermore, three main polyphenols were identified and quantified by HPLC. The results showed the content of phenolic compounds and antioxidant activity of the optimized UCE were 1.5~2 times higher than that determined by the single extraction method and the Soxhlet extraction method, which indicates UCE is a competitive and effective extraction technique for natural passion fruit polyphenols.

Optimizing the ultrasonic-assisted extraction of antioxidants from Ulva lactuca algal biomass using factorial design

Ultrasonic-assisted extraction (UAE) is increasingly emerging as a highly effective extraction technique. This extraction technique is affected by several experimental factors. The present work aimed to optimize the ultrasonic-assisted extraction of antioxidants from Ulva lactuca (sea lettuce), widespread macroalgae growing along the Mediterranean coast. In this respect, a full-factorial design (23) was employed to assess the effect of three different factors at two levels and their interactions on the extraction of antioxidants from sea lettuce algal biomass. The studied factors were extraction solvent, time of extraction, and temperature. The two levels chosen for extraction solvent were 100% ethanol and 50% ethanol, for the sonication time (1 h and 3 h) and temperature (25 °C and 40 °C). All experiments were done using an ultrasonic bath, and the biomass to solvent ratio was kept at 1:5. Total antioxidant capacity and quercetin concentration were set as the two responses for optimum output. The results showed that the temperature and solvent were the dominating factors that significantly affect the extraction process. The optimum extraction parameters were extraction time of 1 h, 50% ethanol, and temperature of 25 °C. Under these conditions, the maximum value for TAA was calculated as 2166.51 mg of ascorbic acid equivalent per gram (mg/g of AAE), and quercetin showed a maximum calculated value of 42.5 mg/g with combined desirability of 0.91 for the two responses. The present study results indicate that U. lactuca can be used as a source of antioxidants and phenolic compounds that can be applied in food and medicine at optimum extraction conditions.Graphical abstract

Integrated technique of segmentation and classification methods with connected components analysis for road extraction from orthophoto images

Road networks are one of the main urban features. Therefore, road parts extraction from high-resolution remotely sensed imagery and updated road database are beneficial for many GIS applications. However, owing to the presence of various types of obstacles in the images, such as shadows, cars, and trees, with similar transparency and spectral values as road class, achieving accurate road extraction using different classification and segmentation methods is still difficult. This paper proposes an integrated method combining segmentation and classification methods with connected components analysis to extract road class from orthophoto images. The proposed technique is threefold. First, multiresolution segmentation method was applied to segment images. Then, the main classification methods, namely, decision trees (DT), k-nearest neighbors (KNN), and support vector machines (SVM), were implemented based on spectral, geometric, and textural information to classify the obtained results into two classes: road and non-road. Three main accuracy evaluation measures, such as recall, precision, and F1-score, were evaluated to determine the performance of the proposed method, with respective average values of 87.62%, 89.71%, and 88.61%, respectively, for DT; 86.61%, 88.17%, and 87.30%, respectively, for KNN; and 89.83%, 89.52%, and 89.67%, respectively, for SVM. Finally, connected components labelling was used to extract road component parts, and morphological operation was employed to delete non-road parts and noises and improve the performance. These results were also compared with other prior works, which confirmed that the integrated method is an effective road extraction technique.

Comparative Study on the Essential Oils from Five Wild Egyptian Centaurea Species: Effective Extraction Techniques, Antimicrobial Activity and In-Silico Analyses.

The genus Centaurea is recognized in folk medicine for anti-inflammatory, anti-itch, antitussive, purgative, astringent, and tonic activities. To study the chemical determinant for antimicrobial activity essential oils (EOs), five Centaurea species were analyzed including: C. scoparia, C. calcitrapa, C. glomerata, C. lipii and C. alexandrina. Conventional hydro-distillation (HD) and microwave-assisted extraction (MAE), as new green technologies, were compared for the extraction of essential oils. GC/MS analysis identified 120 EOs including mostly terpenoid except from C. lipii and C. alexandrina in which nonterpenoids were the major constituents. Major terpenoids included spathulenol, caryophyllene oxide and alloaromadendrene oxide-2. To probe antibacterial activity, potential EO inhibitors of a bacterial type II DNA topoisomerase, DNA gyrase B were screened via an in silico molecular docking approach. Spathulenol and alloaromadendrene oxide-2 possessed the best binding affinity in the ATP- binding pocket of Gyrase B enzyme. Principal component analysis and agglomerative hierarchical clustering were used for sample classification and revealed that sesquiterpenes contributed the most for accessions classification. In vitro antimicrobial activity against Staphylococcus aureus, Escherichia coli and Aspergillus niger for all EOs were also evaluated. EOs from C. lipii, C. glomerata and C. calcitrapa exhibited significant MIC against S. aureus with an MIC value of 31.25 µg/mL.

Recent progress in extraction/transesterification techniques for the recovery of oil from algae biomass

Exploration of alternative and sustainable sources of fuel production has become vital for a couple of decades because of the increase in demand, shortages in inexpensive fossil fuel production, and environmental pollution caused by their derivatives. Although a variety of renewable energy alternatives are currently available, energy derived from natural microalgae associated with bacteria seems promising because it flourishes in all natural environments, along with contributing to the carbon cycle. Lipid extraction from different microalgae cells is a significant boundary for the biofuel business because of the multifaceted nature of the procedure and cell structure of the microalgae. Although the current existing dry extraction methods for lipid extraction from algae are in use, the drying of microalgae is consuming more energy than the extraction itself. There is still lack of technology to optimize the extraction of biodiesel from microalgae in a cost-effective and quick way. Studies show that eliminating the drying step and extracting lipids in one step can be optimal by adding mechanisms like supercritical method, ionic liquids, Eutectic solvents, and transesterification. A major constraint in this process is effective lipid extraction technique. Fuel production from wet microalgae biomass is significantly desirable because it would eliminate at least two lengthy processes (dewatering and drying) that consume much energy. In this study, wet extraction techniques are comprehended. For implementing and optimizing this application, further research and exploration are much needed.

An Analysis of the Extraction Technologies: Fruit Peel Waste

Abstract Advances in technology over the past few years have allowed us to evolve from waste to value. Food waste has been an increased recognition that more attention needs to be paid to this area. With this concern, research on fruit waste valorization into medicinal products has a rich background. This paper approaches the problem with a broader perspective by introducing the fruit waste valorization pathway. The key idea in this paper is to use the multi-criteria analysis method to choose the best essential oil extraction technique from fruit waste. The performance of four different extraction methods i.e., steam distillation, cold-pressing, solvent extraction, and hydro distillation compared in the approach, considering the environmental, economic, social, and technical criteria. The methodology was developed with two scenarios, by using the Analytic hierarchy process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods. Our research highlighted that cold-pressing extraction is the most effective technique for essential oil extraction in both scenarios.

Effect of accelerated solvent extraction conditions on the isolation of bioactive compounds from fennel (Foeniculum vulgare Mill.) seeds

This study focused to establish the optimal conditions of accelerated solvent extraction (ASE), i.e., temperature, static extraction time and number of extraction cycles, for the isolation of fennel (Foeniculum vulgare Mill.) seeds phenols and pigments using 96% ethanol as an extraction solvent. Hence, extraction conditions of temperature (80 and 110 °C), static extraction time (5 and 10 min) and number of extraction cycle (1, 2, 3 and 4) were varied. Obtained extracts were spectrophotometrically analyzed for the content of total phenols (TP), total chlorophylls (TCHL) and total carotenoids (TCAR). Applied extraction conditions had a significant (p<0.01) influence on the yields of analyzed compounds, except for static extraction time on TCAR (p=0.11). Based on the results of statistical analysis, the highest levels of TP and TCHL were achieved at the most invasive conditions (110 °C/10 min/4 cycles), while shorter period was sufficient to reach the highest TCAR yield (110 °C/5 min/3 cycles). In summary, ASE demonstrated to be effective extraction technique for the isolation of fennel seeds hydrophilic and lipophilic bioactive compounds.

Ultrasound-assisted aqueous two-phase extraction of synephrine, naringin, and neohesperidin from Citrus aurantium L. fruitlets

The ultrasound-assisted aqueous two-phase extraction (UA-ATPE) was first employed to develop an effective technique for simultaneous extraction and preliminary purification of synephrine, naringin, and neohesperidin from Citrus aurantium L. fruitlets. Five types of ethanol/salts of aqueous two-phase system (ATPS) were investigated and then the extraction conditions were further optimized using single-factor experiments and response surface methodology (RSM) via Box–Behnken Design (BBD). The optimum process parameters were concluded as follows: 20.60% (w/w) K2CO3, 27% (w/w) ethanol, solvent-to-material ratio of 45.17:1 (g:g), 120-mesh particle size of fruitlets powder, extraction temperature of 50 °C, extraction time of 30 min, and ultrasonic power of 80 W. Under these conditions, the extraction yields of synephrine, naringin, and neohesperidin were up to 11.17 mg/g, 7.39 mg/g, and 89.27 mg/g, respectively. The yield of neohesperidin extracted by the optimal UA-ATPE was over eight times higher than that extracted by the ultrasound-assisted extraction (UAE) using conventional solvents, and the total yield of target compounds was over twice higher while the impurity content in the extract was much lower. Therefore, UA-ATPE appeared to be a highly effective and promising approach for the extraction of synephrine, naringin, and neohesperidin from C. aurantium fruitlets.

Comprehensive Strategies for Polychlorinated biphenyls Quantitative Analysis Specialized in Foodstuffs

Food matrices are naturally complex and many ingredients such as lipids, proteins, pigments and others are co-extracted with PCBs. So, reliable and effective analytical techniques are needed to determine PCBs in foodstuffs at low concentration. This review is exploring and summarizes the current available techniques for extraction, clean-up, and separation techniques to quantify the PCBs in different foods. Several extraction approaches have been improved to overcome the issues associated with regular techniques involves large amount of solvent and time consuming. Accelerated solvent extraction is a promising and effective extraction technique using reasonable amount of solvents. Acidified silica gel alone or in combination with alumina is succeeded to purify most extract matrices. Besides, gel permission chromatography is widely used to eliminate large size molecules and other co-extracted impurities. As a reference technique GC-HRMS is the most effective technique for quantification of dioxins and dioxin-like PCBs. As alternative techniques, GC coupling with tandem MS is optimized to analysis dioxin and PCBs in foodstuffs and represent a cost effectiveness technique compared to GC-HRMS. GCxGC-HRTOF-MS is evaluated and validated to examine dl-PCBs and indicator PCBs and the obtained results were satisfactory well equivalent to those results obtained by GC-HRMS.

A Deep Regression Model with Low-Dimensional Feature Extraction for Multi-Parameter Manufacturing Quality Prediction

Manufacturing quality prediction can be used to design better parameters at an earlier production stage. However, in complex manufacturing processes, prediction performance is affected by multi-parameter inputs. To address this issue, a deep regression framework based on manifold learning (MDRN) is proposed in this paper. The multi-parameter inputs (i.e., high-dimensional information) were firstly analyzed using manifold learning (ML), which is an effective nonlinear technique for low-dimensional feature extraction that can enhance the representation of multi-parameter inputs and reduce calculation burdens. The features obtained through the ML were then learned by a deep learning architecture (DL). It can learn sufficient features of the pattern between manufacturing quality and the low-dimensional information in an unsupervised framework, which has been proven to be effective in many fields. Finally, the learned features were inputted into the regression network, and manufacturing quality predictions were made. One type (two cases) of machinery parts manufacturing system was investigated in order to estimate the performance of the proposed MDRN with three comparisons. The experiments showed that the MDRN overwhelmed all the peer methods in terms of mean absolute percentage error, root-mean-square error, and threshold statistics. Based on these results, we conclude that integrating the ML technique for dimension reduction and the DL technique for feature extraction can improve multi-parameter manufacturing quality predictions.

An Overview: Analysis of ultrasonic-assisted extraction’s parameters and its process

Previously, there were many extraction methods that had been done on extracting the oil such as centrifugation, chilling and thawing, hot and cold extraction, on seeds, waste products and plants. Based on those oil extraction methods (OEM), further study is needed to develop more effective processes as most of the methods were having many disadvantages in term of time, cost, quality and safety. Ultrasonic-assisted extraction (UAE) is used in this project as it is a rapid and effective extraction technique that uses ultrasound to generate rapid movement of solvents, resulting in a higher mass transfer speed as well as acceleration of extraction. Compared to other advanced extraction techniques, UAE is more economic, eco-friendly, and convenient by the reduction of time consumption, higher oil quality and cost reduction. The principle of acoustic cavitation ultrasound which is explained by a series of compression and rarefaction waves induced in the molecules of the medium and the collapse of the bubble during the process of UAE may be discussed. Parameters involved also play the important role in the extraction such as extraction time (ET), extraction temperature (ETem), solvent to material ratio (S/M Ratio) and type of solvent selected. Thus, the paper discusses the application of UAE on oil extraction.

Chemical Composition and Biological Activities of Extracts from Pomelo Peel By-Products under Enzyme and Ultrasound-Assisted Extractions

Enzyme-assisted extraction (EAE) and ultrasound-assisted extraction (UAE) were popular methods used to extract bioactive compounds from citrus peels, by-products of fruit processing industry. In this study, the total phenolic content (TPC), total flavonoid content (TFC), naringin and hesperidin contents, and antioxidant and antimicrobial activities of the extracts from pomelo peels using the combined enzyme and ultrasound-assisted extraction (E-UAE) or ultrasound and enzyme-assisted extraction (U-EAE) technique were investigated and compared with those extracted using the EAE and UAE. The optimal EAE conditions were as follows: enzyme concentration of 2%, water-solid ratio of 40 ml/g, incubation temperature of 50°C, and extraction time of 60 min, whereas the optimal UAE conditions were ultrasonic energy of 40 kHz, water-solid ratio of 40 ml/g at room temperature, and extraction time of 60 min. The results indicate that the total phenolics, total flavonoids, naringin, and hesperidin contents of the extracts significantly increased in the following order of the extraction techniques: UAE < EAE < U-EAE < E-UAE (p<0.05). The combined E-UAE technique was the most effective technique for bioactive compound extraction with the highest antioxidant and antimicrobial activities. The results also indicate that chemical composition and antioxidant and antimicrobial activities of the extracts were different depending on the pomelo species.

Maximising extraction yields of gallic acid and hesperetin from lemon myrtle (Backhousia citriodora) leaf using microwave assisted extraction

Lemon myrtle (Backhousia citriodora) is native to Australia and is well-known for its lemon aroma and traditional uses in foods and as a medicine. The leaves are rich in phenolics, and gallic acid and hesperetin are the major phenolic compounds. Microwave-assisted extraction (MAE) is known as an effective extraction technique for phenolics from plant materials. This study aimed to investigate the individual and interaction effects of microwave on the isolation of gallic acid and hesperetin from lemon myrtle leaf and quantify the part in total phenolic compound. This study also optimized the MAE conditions. Extraction solvent was acetone (50%) in water and extraction time, microwave power and sample to solvent ratio were tested for their optimal conditions. The results showed that extraction time and microwave power had a positive significant effect on gallic acid, but not on hesperetin; whereas, the sample to solvent ratio had a negative significant impact on both gallic acid and hesperetin. The optimal MAE conditions were 6 min, 630 W, and 2 g/100 mL. Under these conditions, 43.32 mg gallic acid and 21.51 mg hesperetin could be obtained from a gram of dry sample. These account for approximately 42% and 21% of extracted total phenolic and flavonoid content, respectively. The optimized MAE conditions are recommended for recovery of gallic acid and hesperetin from lemon myrtle leaves for further applications.

Salt-assisted aqueous extraction combined with Span 20 allow the obtaining of a high-quality and yield walnut oil

To develop an effective and eco-friendly technique for walnut oil extraction, surfactant and salt-aided aqueous extraction (SSAE) method was used to break the emulsion. The optimal extraction parameters obtained by single-factor experiments (i.e., extraction time, 60min; extraction temperature, 85 °C; concentration of sodium chloride solution, 1.2 mol/L; liquid-to-material ratio, 5:1; concentration of Span 20, 1.7 g/100 g). The new aqueous extraction processing (AEP) procedure that was finally developed in this study recovered 91.2% walnut oil with high quality. Span 20 is effective in destabilizing the emulsions and improving oil recovery, which may be due to the fact that Span 20 could effectively replace the position of the oleosin to destabilize the emulsion. In addition, walnut protein has not been denatured after extraction of walnut oil by SSAE and can be reclaimed. Therefore, the discovery of Span 20 as an available demulsifier provides a new insight into the development of AEP of walnut.