Extraction Process Research Articles

Optimization of phosphorus wet acid extraction from sewage sludge ashes: Detailed process insight via multi-variate statistical techniques

To tackle the issue of phosphorus (P) supply, Sewage Sludge Ash (SSA) is a promising secondary source. The goal of this research is the optimization of the wet P extraction process in the view of providing valuable insights for the process scale-up. While most of the studies relied on the “one-variable-changed-at-a-time” approach, this work applied a statistical optimization model based on the Design of Experiments technique for investigating the influence of most relevant operating conditions of extraction process on Phosphorus Extraction Efficiency (PEE) with two types of SSA characterized by different levels of alkalinity. Experimental results highlighted the importance of ash characteristics, making some SSA not suitable for cost-effective phosphorus recovery due to the high acid dosage required in extraction process. Type of acid and contact time become significant factors only for Ca-rich ashes, especially when using H2SO4 as extracting agent. Optimal operating conditions (CH2SO4 = 1.3 N, L/S = 20, t = 2 h and CHCl = 2.0 N, L/S = 10, t = 2 h for Ash#1 and CH2SO4/HCl = 0.8 N, L/S = 10 for Ash#2) resulting in high PEE (80–94%) were identified for extraction performed with H2SO4 and HCl as a function of ash characteristics.

Advances in Extraction Protocols, Degradation Methods, and Bioactivities of Proanthocyanidins

Proanthocyanidins, natural polyphenolic compounds abundantly present in plants, exhibit diverse bioactivities, including antioxidative, anti-inflammatory, and antibacterial effects. These bioactivities are intricately linked to the degree of polymerization of these compounds. Through a comprehensive analysis of recent domestic and international research, this article synthesizes the latest advancements in the extraction process, degradation methods, as well as the biological activities and underlying mechanisms of proanthocyanidins. Furthermore, future research endeavors should prioritize the refinement of extraction techniques, the elucidation of bioactive mechanisms, and the development of formulations with enhanced potency. This will maximize the utilization of proanthocyanidins across diverse applications.

Research on moving object tracking with a large number of outliers based on TRESAC++ algorithm

In contrast to the method based on motion equations, image registration proves effective for tracking moving objects in missions where establishing a motion model is unfeasible. However, in cases where the object is captured at varying imaging angles or against a similar background, a large number of outliers may arise during the process of image feature extraction. Consequently, when confronted with a large number of outliers, image registration methods exhibit a drawback in accurate outlier filtering, especially when spatial constraints on feature matching pairs are constrained. Ultimately, these factors can render object tracking inaccurate or even unattainable. In light of the aforementioned circumstances, this paper proposes TRESAC++, which based on a triplet relation feature matching method to effectively filter outliers. To enhance the operational efficiency of the algorithm, Principal Component Analysis is employed for dimensionality reduction, aiming to decrease the incidence of triple matches and subsequently mitigate execution time. To fortify the algorithm's robustness, a triplet relation linked with an initial data subset selection strategy is additionally proposed. Experimental results on five challenging experiments show that TRESAC++ rivals current state-of-the-art techniques in terms of computational cost, while the implementation exhibits better outlier filtering. Additionally, Experiment 4 and Experiment 5 use moving object datasets to confirm TRESAC++'s superior capability in precise object tracking.

Production of Camellia oleifera Abel Seed Oil for Injection: Extraction, Analysis, Deacidification, Decolorization, and Deodorization

Camellia seed oil (CSO), as a nutrient-rich edible oil, is widely used in foods, cosmetics, and other fields. In this work, the extraction, deacidification, decolorization, and deodorization processes of CSO were respectively optimized for meeting injectable oil standards. The results showed that the CSO extraction rate reached the highest level of 94% at optimized conditions (ultrasonic time, 31.2 min; reaction pH, 9.2; and reaction time, 3.5 h). The physicochemical indexes of CSO and 10 other vegetable oils were evaluated by the principal component analysis method, and the overall scores of vegetable oils were ranked as camellia seed oil > olive oil > rice oil > peanut oil > sesame oil > corn oil > soybean oil > sunflower oil > rapeseed oil > walnut oil > flaxseed oil. The physicochemical indicators of CSO were the most ideal among the 11 vegetable oils, which means that CSO is suitable as an injectable oil. Through the optimized processes of the deacidification, decolorization, and deodorization, the CSO acid value was reduced to 0.0515 mg KOH/g, the decolorization rate reached a maximum of 93.86%, and the OD430 was 0.015, meeting the requirement (≤0.045 of OD430) of injectable oil. After the deodorization process, these parameters of the refractive index, acid value, saponification value, iodine value, absorbance, unsaponifiable, moisture and volatiles, fatty acid composition, and heavy metal limits all met the pharmacopoeia standards of injectable oil in many countries and regions. The possibility of CSO as an injectable oil was first verified through refining-process optimization and nutritional index analysis, providing an important technical reference for the high-value utilization of vegetable oil.

Long-term storage for reanalysis purposes: A stability study of extracts from post-explosion/burning residues of fuel-oxidizer explosive mixtures

Post-explosion residue analysis is vital in forensic chemistry, providing valuable insights into incidents involving explosives. One significant challenge in this field is preserving samples for long-term storage for reanalysis. Presently, many laboratories conducting post-explosion analyses worldwide do not retain samples for reanalysis purposes, since the extraction process for sample preparation often necessitates the complete consumption of the scarce material. Even in cases where a portion of the material remains, such as a swab, it is difficult to ensure its representativeness and select a specific portion for preservation. One possible solution to overcome this challenge is to consider preserving the extracts used in the analyses for potential reanalysis. However, the stability characteristics of these extracts are currently unknown. The results presented in this article provide valuable insights into the feasibility of long-term storage for samples containing target analytes in extracts from post-explosion/burning residues of frequently encountered fuel-oxidizer explosive mixtures, such as flash powder, explosive emulsion, and black powder. These results shed light on the potential viability of preserving such extracts for future reanalysis, offering promising prospects for enhancing forensic investigations in this field. Based on the current findings, it has been demonstrated that the aqueous extracts can be effectively preserved as long-term storage samples for a minimum of 24 months, encompassing all the studied explosives. Only cyanate ion showed significant degradation among the 27 compounds studied. Additionally, the organic extract, specifically in the case of emulsion explosive, can be maintained for at least 12 months.

Correlation of Fourier transform infrared spectroscopy data for optimizing Gramicidin production in corn kernel aqueous stream

In this work, an aqueous corn kernel stream (CKS) fermented in the presence of Aneurinibacillus aneurinilyticus was subjected to an extraction process with phosphate buffer saline (PBS) to evaluate the conditions that promote the production of Gramicidin (GR) in this aqueous stream. To do so, a fast and simple technique was used based on Fourier Transform Infrared Spectroscopy (FTIR) analysis combined with a statistical correlation treatment of the spectra in comparison with a standard spectrum of Gramicidin A (GR-A) and Gramicidin S (GR-S). The correlation analysis employed made it possible to obtain a similarity index using Pearson (PP) and Spearman (PS) coefficients for pairs of FTIR transmittance spectra, associated to different fermentation conditions. More favorable PPand PS similarity indices were obtained for pairs with GR-S rather than GR-A when compared with the samples under evaluation, observing that production of GR-S was promoted under high concentration of CKS (400 g/L) with similarity index of 0.752 and 0.813 for PPand PS, respectively, considering the FTIR spectra between 400 and 4000 cm−1, whereas low concentration of CKS (100 g/L) provided non favorable correlation factors (PP similarity indices lower than 0.4). The same behavior was observed when the study was considered between 1450 and 1750 cm−1 corresponding with the interval absorbance of amide I, amide II, and ammonium dominate bands in GR-S. Finally, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) corroborated this correlation study, proving that FTIR could be an interesting tool for establishing the optimal conditions of biotechnological processes.

FACNN: fuzzy-based adaptive convolution neural network for classifying COVID-19 in noisy CXR images.

COVID-19 detection using chest X-rays (CXR) has evolved as a significant method for early diagnosis of the pandemic disease. Clinical trials and methods utilize X-ray images with computer and intelligent algorithms to improve detection and classification precision. This article thus proposes a fuzzy-based adaptive convolution neural network (FACNN) model to improve the detection precision by confining the false rates. The feature extraction process between the successive regions is validated using a fuzzy process that classifies labeled and unknown pixels. The membership functions are derived based on high precision features for detection and false rate suppression process. The convolution neural network process is responsible for increasing detection precision through recurrent training based on feature availability. This availability analysis is verified using fuzzy derivatives under local variances. Based on variance-reduced features, the appropriate regions with labeled and unknown features are used for normal or infected classification. Thus, the proposed FACNN improves accuracy, precision, and feature extraction by 14.36%, 8.74%, and 12.35%, respectively. This model reduces the false rate and extraction time by 10.35% and 10.66%, respectively.

Curcuma Longa: Nutraceutical Use and Association with Nanotechnology.

Curcumin is a natural product found in the rhizome of Curcuma longa (L) and other Curcuma spp. As a lipophilic molecule, it has greater affinity for polar, non-polar, alkaline or extremely acidic organic solvents. Several studies indicate that curcumin has several benefits for human health, for example, against degenerative diseases, cancer and infectious diseases. To obtain a quality product with nutraceutical properties, it is necessary to know its physicochemical characteristics and preserve it from cultivation until ingestion by the human. However, its low solubility leads to low absorption, in this context, nanotechnological systems can contribute to increase curcumin bioavailability. This review aims to highlight important issues in all stages that curcumin goes through: from aspects related to its extraction, to its association with nanotechnology. Although curcumin extraction process is already well established, it is possible to observe that more and more research focused on increasing yield and being more environmentally friendly. Furthermore, curcumin's low absorption is notable due to its physicochemical characteristics, mainly due to its low aqueous solubility. However, its association with nanotechnology has shown to be promising and an increasingly growing trend, since the use of this "Indian solid gold" is the hope of many patients. This article is protected by copyright. All rights reserved.

Methodology to Increase the Efficiency of the Mineral Water Extraction Process

The most important source of human life support is water. During the development of mineral water fields, unsustainable patterns of production and consumption have been observed, which could lead to environmental damage and the deterioration of mineral water quality and sources. In this work, a procedure for determining the modified link’s parameters, replacing the static and dynamic indicators of the hydrodynamic process, is proposed. Recording the parameters at the different filtration coefficients along the spatial coordinates allows the environmental safety of aquifers to be increased and the pressure of the reservoir to be stabilized. The presented approach allows the accuracy of the process used to control the reservoir’s pressure to be increased.

Design tungsten oxides hole transport layers (HTLs) to modify the back interface in all-inorganic carbon-based CsPbBr3 solar cells

To enhance the inferior photovoltaic performance of all-inorganic carbon-based perovskite solar cells (C-PSCs) caused by inefficient charge extraction and transport processes of the CsPbBr3/carbon back interface, three types of tungsten oxides (WO3, WO2.72, WO2) are synthesized as low cost and stable hole transport layers (HTLs) to modify the back interface by tunning the energy level alignment. Among the three kinds of tungsten oxides, WO3 shows the best hole extraction and transport capability and the C-PSCs using WO3 HTL generates a power conversion efficiency (PCE) of 7.90% with a high open circuit voltage (Voc) of 1.307 V, indicating a great PCE enhancement of 43.9%, as compared with the device without HTL (5.49%). Meanwhile, WO2.72 and WO2 also are also proved to be qualified HTLs and the devices show PCE values of 7.57% and 6.24%, respectively. Importantly, WO3 and WO2.72 based device show excellent stabilities with PCE retention over 90% of the initial PCE values under ambient conditions for 60 days.

To prompt or not to prompt: Navigating the use of Large Language Models for integrating and modeling heterogeneous data

Manually integrating data of diverse formats and languages is vital to many artificial intelligence applications. However, the task itself remains challenging and time-consuming. This paper highlights the potential of Large Language Models (LLMs) to streamline data extraction and resolution processes. Our approach aims to address the ongoing challenge of integrating heterogeneous data sources, encouraging advancements in the field of data engineering. Applied on the specific use case of learning disorders in higher education, our research demonstrates LLMs’ capability to effectively extract data from unstructured sources. It is then further highlighted that LLMs can enhance data integration by providing the ability to resolve entities originating from multiple data sources. Crucially, the paper underscores the necessity of preliminary data modeling decisions to ensure the success of such technological applications. By merging human expertise with LLM-driven automation, this study advocates for the further exploration of semi-autonomous data engineering pipelines.

Biodiesel production and selected fuel qualities from prospective non-edible oils: Hevea brasiliensis, Madhuca longifolia, Azadirachta indica, and Gossypium hirsutum

ABSTRACT Biodiesel predominantly originates from edible oil. Exploring non-edible oil resources is crucial to biodiesel manufacturing’s commercial viability and food security. This study examines four non-edible seed oils Hevea brasiliensis, Madhuca longifolia, Azadirachta indica, and Gossypium hirsutum as biofuel feedstocks. This study optimized reaction parameters to improve base-catalyzed transesterification, oil extraction and biodiesel synthesis. The produced esters were identified by nuclear magnetic resonance, Fourier transform infrared, and gas chromatography mass spectrometry. Elements composition was determined using inductively coupled plasma-optical emission spectrometry and elemental analyzer. The biofuel’s physicochemical properties met American Society for Testing and Materials and European standards. The maximum amount of crude oil was seen in Hevea brasiliensis using the soxhlet extraction process, ranging from 52-63%. This was followed by Madhuca longifolia 38-55%, Azadirachta indica 24-33%, and Gossypium hirsutum with 19-27%. The density of the plant sources exhibited a range of 0.88-0.90 g/cm3 @ 15 °C, while the kinematic viscosity showed a range of 3.2-4.1 mm2/s. The elemental composition of biodiesel, expressed as percentages of carbon, hydrogen, nitrogen, and oxygen, varied between the ranges of 70.52-76.30, 11.25-14.02, 1.18-2.75, and 9.11-13%, respectively. Since they may be grown in infertile and unproductive settings, these non-consumable seeds are cost-effective for renewable energy. They also help solve the energy situation by boosting biodiesel production..

Damage Severity Assessment of Multi-Layer Complex Structures Based on a Damage Information Extraction Method with Ladder Feature Mining.

Multi-layer complex structures are widely used in large-scale engineering structures because of their diverse combinations of properties and excellent overall performance. However, multi-layer complex structures are prone to interlaminar debonding damage during use. Therefore, it is necessary to monitor debonding damage in engineering applications to determine structural integrity. In this paper, a damage information extraction method with ladder feature mining for Lamb waves is proposed. The method is able to optimize and screen effective damage information through ladder-type damage extraction. It is suitable for evaluating the severity of debonding damage in aluminum-foamed silicone rubber, a novel multi-layer complex structure. The proposed method contains ladder feature mining stages of damage information selection and damage feature fusion, realizing a multi-level damage information extraction process from coarse to fine. The results show that the accuracy of damage severity assessment by the damage information extraction method with ladder feature mining is improved by more than 5% compared to other methods. The effectiveness and accuracy of the method in assessing the damage severity of multi-layer complex structures are demonstrated, providing a new perspective and solution for damage monitoring of multi-layer complex structures.

In vitro toxicity evaluation in A549 cells of diesel particulate matter from two different particle sampling systems and several resuspension media.

In urban areas, inhalation of fine particles from combustion sources such as diesel engines causes adverse health effects. For toxicity testing, a substantial amount of particulate matter (PM) is needed. Conventional sampling involves collection of PM onto substrates by filtration or inertial impaction. A major drawback to those methodologies is that the extraction process can modify the collected particles and alter their chemical composition. Moreover, prior to toxicity testing, PM samples need to be resuspended, which can alter the PM sample even further. Lastly, the choice of the resuspension medium may also impact the detected toxicological responses. In this study, we compared the toxicity profile of PM obtained from two alternative sampling systems, using in vitro toxicity assays. One system makes use of condensational growth before collection in water in an impinger - BioSampler (CG-BioSampler), and the other, a Dekati® Gravimetric Impactor (DGI), is based on inertial impaction. In addition, various methods for resuspension of DGI collected PM were compared. Tested endpoints included cytotoxicity, formation of cellular reactive oxygen species, and genotoxicity. The alternative collection and suspension methods affected different toxicological endpoints. The water/dimethyl sulfoxide mixture and cell culture medium resuspended particles, along with the CG-BioSampler sample, produced the strongest responses. The water resuspended sample from the DGI appeared least toxic. CG-BioSampler collected PM caused a clear increased response in apoptotic cell death. We conclude that the CG-BioSampler PM sampler is a promising alternative to inertial impaction sampling.

Constructing hydroxyoxime-functionalized ionic liquid [BHIB][NTf2] for the separation of Mo(VI) from U(VI)

We describe here a hydroxyoxime-functionalized ionic liquid, 1-butyl-3-(4-hydroxy-3-((hydroxyimino)methyl)benzyl)-1H-imidazol-3-ium bis((trifluoromethyl)sulfonyl)amide ([BHIB][NTf2]), for the isolation and purification of 99Mo from 235U. This material exhibits remarkable extraction efficiency for Mo(VI) from 0.1 to 2 M HNO3 and can effectively distinguish Mo(VI) from U(VI). The attained highest separation factor (SF) of Mo(VI) over U(VI) exceeds 104, thus setting a new record for their separation. Additionally, the extracted Mo(VI) can be efficiently recovered using either NH4OH or the mixture of NH4OH and (NH4)2CO3. This excellent extraction performance is sustained even after five cycles. The extraction efficiency remains stable following exposure to 150 kGy gamma irradiation, thus providing robust experimental support for potential engineering applications. Slope analysis and EXAFS results indicate that [BHIB][NTf2] forms a 2:1 complex with Mo(VI) during the extraction process primarily driven by a cation exchange mechanism. When one equivalent of Mo(VI) migrates from the aqueous phase to the organic phase, each of two equivalents [BHIB][NTf2] remove one of H+ and migrate to the aqueous phase to maintain charge balance. This investigation introduces a highly efficient and environmentally benign method for separation, alongside providing novel insights into ligand design for the efficacious differentiation of Mo(VI) and U(VI) under HNO3 conditions, potentially streamlining current methodologies.

Use of di-(2-ethylhexyl)-orthophosphoric acid for the extraction of lanthanum, neodymium, samarium and yttrium from nitric acid solutions

The process of separating rare-earth elements into individual components is considered the most important problem in rare-earth technology because of the similarity in their physical and chemical properties. Currently in the world dialkyl phosphate compounds are widely used as effective extractors for rare earths. However, most extraction processes have been studied from hydrochloric acid or perchlorate solutions. In Russia, tributyl phosphate has long been used to extract rare earths from nitric acid solutions, but the distribution coefficients of the elements are not high, and the process must be repeated multiple times. In this study di-(2-ethylhexyl)-orthophosphoric acid was used for the extraction of lanthanum, neodymium, samarium, and yttrium from nitric acid solutions. When the concentration of nitric acid increased, distribution coefficient of elements gradually decreased to minimum (in the range of 1 to 5M) then increased backward. However, when the concentration was too high (C > 5M), nitric acid was extracted to the organic phase due to the properties of the phosphoryl group. Moreover, the study of dependence of solvation number of neodymium on the concentrations of nitric acid shows that rare earths in the organic phase can be extracted as Re(HA2)3 (C < 1M) or Re(NO3)3«3HA (C > 5M).

Enhancing Cutin Extraction Efficiency from Industrially Derived Tomato Processing Residues by High-Pressure Homogenization.

This study primarily aimed to enhance the extraction of cutin from industrial tomato peel residues. Initially, the conventional extraction process was optimized using response surface methodology (RSM). Subsequently, high-pressure homogenization (HPH) was introduced to improve extraction efficiency and sustainability. The optimization process focused on determining the optimal conditions for conventional extraction via chemical hydrolysis, including temperature (100-130 °C), time (15-120 min), and NaOH concentration (1-3%). The optimized conditions, determined as 130 °C, 120 min, and 3% NaOH solution, yielded a maximum cutin extraction of 32.5%. Furthermore, the results indicated that applying HPH pre-treatment to tomato peels before alkaline hydrolysis significantly increased the cutin extraction yield, reaching 46.1%. This represents an approximately 42% increase compared to the conventional process. Importantly, HPH pre-treatment enabled cutin extraction under milder conditions using a 2% NaOH solution, reducing NaOH usage by 33%, while still achieving a substantial cutin yield of 45.6%. FT-IR analysis confirmed that cutin obtained via both conventional and HPH-assisted extraction exhibited similar chemical structures, indicating that the main chemical groups and structure of cutin remained unaltered by HPH treatment. Furthermore, cutin extracts from both conventional and HPH-assisted extraction demonstrated thermal stability up to approximately 200 °C, with less than 5% weight loss according to TGA analysis. These findings underscore the potential of HPH technology to significantly enhance cutin extraction yield from tomato peel residues while utilizing milder chemical hydrolysis conditions, thereby promoting a more sustainable and efficient cutin extraction process.

From Field to Waste Valorization: A Preliminary Study Exploring the Impact of the Wine Supply Chain on the Phenolic Profile of Three Sardinian Pomace Extracts.

The winemaking process generates an annual global production of about 10 million tons of waste consisting of stalks, skin, and seeds. The possible reutilization of wine pomace is strictly linked to its chemical composition. In this preliminary study, three different Sardinian white grapes (Malvasia, Vermentino and Nasco) grown in the same area were evaluated through a whole wine production chain. To reduce environmental impact, all the grapes were treated following the integrated production practice (IPP) strategies. The adopted agronomic methods and the main physico-chemical parameters of the fresh fruits and musts were evaluated. A fully qualitative and quantitative characterization of the phenolic fraction of the pomace extracts was performed by HPLC-DAD after a post-winemaking process. Water and ethanol were utilized as green solvents in the extraction process. Additionally, the entire pomace post-winemaking process was carried out within the winery facilities to reduce energy loss and road transportation. The findings demonstrated that large amounts of beneficial polyphenols are present in pomace extracts, and that the type of grape used, agronomic practices, and winemaking method all influence the quantity and quality of the extracts. The polyphenol concentrations in the Vermentino (28,391.5 ± 7.0 mg/kg) and Malvasia pomace (11,316.3 ± 6.5 mg/kg) were found to be the highest and lowest, respectively.

Phase behaviour and internal mechanism of action of two solvents for the separation of butanol isomers from industrial wastewater

Industrial wastewater usually contains large amounts of butanols which form azeotropic mixtures with water. Efficiently and cleanly separating these azeotropes while saving energy is an urgent problem to solve. This study used two types of solvents to measure the ternary liquid-liquid equilibrium (LLE) data for extracting n-butanol, sec-butanol, and tert-butanol from water at 298.2 K and 101.3 kPa. The obtained data was correlated with NRTL and UNIQUAC models to obtain relevant binary interaction parameters. The reliability of the binary interaction parameters was verified using a Gibbs energy topology-based mixture surface analysis method. The root mean square deviations of the two models were less than 0.0061 and 0.0072, respectively, indicating that both the NRTL and UNIQUAC models could correlate the experimental data well. The extraction performance was evaluated using the distribution coefficient (D) and the separation factor (S). Isopentyl acetate showed better extraction performance, and the differences in the molecular structures of butanols also showed regularity during the extraction process. Combined with quantum chemistry calculations, the hydrogen bond donors and acceptors between six ternary systems were analyzed using the COSMO-SAC method. The intermolecular interaction energies were calculated using the Dmol3 module. Finally, through IGMH and AIM analysis, it was proved that the difference in hydrogen bond strength between isopentyl acetate/ethyl acetate and butanols with different molecular structures is the reason for this difference. This study provides basic data and parameters for the design of butanols extraction processes through a combination of experiments and quantum chemistry calculations.

Study on the Optimization, Extraction Kinetics and Thermodynamics of the Ultrasound-Assisted Enzymatic Extraction of Tremella fuciformis Polysaccharides.

In this study, Tremella fuciformis polysaccharides (TFPs) were extracted by ultrasound-assisted enzymatic extraction (UAE) at different extraction parameters in order to explore the potential of ultrasound in intensifying the extraction yield. The effects of experimental conditions on the extraction yields were optimized using response surface methodology, with the optimal ultrasonic power of 700 W, temperature of 45 °C and time of 50 min. The kinetic analysis revealed that UAE significantly promoted the dissolution, diffusion and migration with the maximum yield of 26.39%, which was enhanced by 40.45% and 156.96% compared with individual ultrasonic extraction (UE) and enzymatic extraction (EE). According to the modified Fick's second law of diffusion, the extraction process of TFPs illustrated a good linear correlation (R2 ≥ 0.9), and the rate constant gradually elevated as the temperature increased from 25 to 45 °C, while the presence of ultrasound exerted a vital role in extracting TFPs. Regarding to the thermodynamic results, the positive values of ΔH and ΔG demonstrated that UAE, UE and EE were endothermic and unspontaneous processes. This study provides a theoretical basis for polysaccharide extraction processing.