Extraction Method Research Articles

Tomato Waste as a Sustainable Source of Antioxidants and Pectins: Processing, Pretreatment and Extraction Challenges

Tomato processing waste (TPW), a byproduct of the tomato processing industry, is generated in significant quantities globally, presenting a challenge for sustainable waste management. While traditionally used as animal feed or fertilizer, TPW is increasingly recognized for its potential as a valuable raw material due to its high content of bioactive compounds, such as carotenoids, polyphenols and pectin. These compounds have significant health benefits and are in growing demand in the pharmaceutical and cosmetic industries. Despite this potential, the broader industrial utilization of TPW remains limited. This review explores the influence of various processing, pretreatment and extraction methods on the concentration and stability of the bioactive compounds found in TPW. By analyzing the effects of these methodologies, we provide insights into optimizing processes for maximum recovery and sustainable utilization of TPW. Additionally, we address the major challenges in scaling up these processes for industrial application, including the assessment of their ecological footprint through life cycle analysis (LCA). This comprehensive approach aims to bridge the gap between scientific research and industrial implementation, facilitating the valorization of TPW in line with circular economy principles.

A low-temperature process for lithium extraction from lithium-bearing mineral: Conversion behavior and mechanisms

Lithium extraction from lithium-bearing clay mineral (LiBC) has received significant attention due to the increasing demand of lithium for the advanced renewable energy industry. However, the low contents of valuable elements and stable physiochemical properties of LiBC result in high energy consumption and low efficiency in extracting lithium from LiBC. This study demonstrates a low-temperature strategy using (NH4)2SO4 as an additive to effectively extract lithium from LiBC. In details, the thermodynamic analysis verifies that Li, Al, and Fe can be converted to sulfates at 250–450 °C during thermal treatment, indicating the possibility for extraction of Li under low-temperature conditions. Subsequently, the leaching behavior of lithium under different roasting temperatures and water leaching conditions was investigated. The results show that 83.43 % of Li can be extracted under optimized conditions. The mechanism study was carried out through a number of characterization techniques including 3D microscope, TG-DSC, XRD, FTIR, and SEM. It reveals that formation of liquidus phase of molten salt is the key to achieve low-temperature roasting and transfer and reactions at the interface of molten salt and LiBC can be significantly enhanced that can easily breakdown the interlayer structures. Consequently, it offers distinct advantages, since the roasting temperature can be significantly decreased with minor impurity ions being leached into the solutions. This research therefore provides an efficient and environmentally friendly method for lithium extraction from minerals.

Association between forensic DNA and odontology in human identification during mass disaster: a systematic review

BACKGROUND: According to the literature, forensic odontology is one of the most effective and affordable scientific techniques for identifying victims of mass disasters. This research methodically reviews the role and function of forensic odontologists in several global mass disasters. Forensic DNA in odontology is associated with the importance of its application in the identification of humans of mass disasters. As the crime rate continues to rise, the field of forensic medicine has evolved significantly. Forensic dentists play a pivotal role in various areas of crime scene investigations, thereby helping solve innumerable mysteries. AIM: The study aimed to increase the body of knowledge for future research on forensic odontology by conducting a systematic review search to investigate possible forensic DNA in odontology associated with the importance of its application in the identification of humans of mass disasters. MATERIALS AND METHODS: Six databases, including Google Scholar, PubMed, Scopus, Embase, Web of Science, and ScienceDirect, were analyzed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) quality scale. The literature search, conducted until February 2024, informed important research choices. RESULTS: A total of 16 (100%) studies related to forensic DNA of mass disasters were identified. Of these, only seven (43.75%) articles related to dental DNA were included in this review. Of the 4,808 articles obtained, 138 duplicates or irrelevant articles were eliminated. Following a full-text review, seven studies were selected based on eligibility criteria. The highest percentage of victims was identified using dental DNA. In a few studies, some samples were insufficient for complete DNA profiling due to factors such as the method of DNA extraction. CONCLUSION: Forensic odontology has played a significant role in the identification of victims of several mass disasters around the world. Although teeth are an excellent source of DNA for humans, future studies with larger sample sizes, appropriate control groups, and standardized techniques of DNA extraction need to be conducted.

Extraction method for characterizing microcracks on Si3N4 ceramic bearings rolling element with contour segmentation

AbstractAiming at the fuzzy diffusion characteristics of microcrack regions in Si3N4 ceramic bearing rolling elements, an adaptive region segmentation method is proposed to achieve precise extraction of microcrack features. The fuzzy diffusion effect of the microcrack region is analyzed, and a structural complexity matrix is defined to represent the degree of structural variation in the image. A threshold point is determined through histogram analysis, and the matrix dispersion rate is calculated using a box plot to update the correction factor, optimizing the overlap of noise in the microcrack image. The causes of distortion in the microcrack region are analyzed, and pixel points are assigned based on spatial metrics and LAB color features. The fuzzy boundaries and overlapping regions are segmented using the fuzzy C‐means clustering algorithm. A grid search algorithm is embedded to quantitatively evaluate the optimal combination of hyperparameters, enabling comprehensive extraction of microcrack features in Si3N4 ceramic bearing rolling elements. The optimized image achieves an average peak signal‐to‐noise ratio of 39.3, an information fidelity criterion of 7.9328, and an average extraction accuracy of approximately 0.92, effectively overcoming the impact of the fuzzy diffusion effect on the accuracy of microcrack feature extraction in Si3N4 ceramic bearing rolling elements.

Plant species modulate wildfire effects on soil phosphorus fractions in alpine forest of Eastern Tibetan Plateau

Global wildfires occurring with ever escalating frequency and intensity profoundly disrupt soil phosphorus (P) cycling in forest ecosystems. The impact of plant species on post-fire soil P transformation, particularly in alpine forests, remains largely unexplored. This study addressed this gap by investigating both bulk soils (BS) and root-zone soils (RS) across three plant species (shrub: Sophora davidii and Quercus aquifolioides, tree: Pinus densata) in the alpine forest of the eastern Tibetan Plateau, three years after a wildfire event. We examined variations in soil P fractions under varying wildfire intensities using the modified Hedley sequential extraction method. Compared to unburned soils, the burned soils exhibited significantly reduced organic P (Po) but increased inorganic P (Pi) concentrations in BS. However, both Pi and Po concentrations decreased in the burned RS, particularly for S. davidii and P. densata, indicating the effects of biological P utilization. The increased specific phosphatase activity and the ratio of carbon to Po suggested increased P limitation in the post-fire environment. Notably, the N2-fixer S. davidii primarily reduced labile P fractions through direct plant P uptake, while conifer tree species P. densata tended to deplete all extractable P fractions, probably through diverse P utilization strategies. Conversely, Q. aquifolioides did not significantly alter soil P fractions, likely due to its fire-resistant properties. These species-dependent impacts on post-fire P fractions were further corroborated by their distinct influences on soil and microbial traits. Our findings underscore the critical roles of functional-specific plant species in post-fire soil P dynamics in alpine forests, with conifer trees exhibiting the best P mining and utilization capacity.

Road Boundary Extraction Method from Mobile Laser Scanning Point Clouds

Abstract With the rapid development of mobile laser scanning (MLS) technology, high-precision three-dimensional point cloud data has shown great potential in different fields such as topographic mapping, road asset management and smart city construc-tion. Three-dimensional point cloud data contains not only position information, but also the shape and attributes of the target, which is very convenient for obtaining road information. Accurate extraction of the road boundary is a basic task for obtaining road infrastructural data, which can support the generation of high-precision maps, vehicle navigation and auton-omous driving. However, road boundary extraction in urban environments is easily occluded such as vehicles and pedestri-ans on the road, which leads to problems such as difficulty and incomplete extraction of MLS point cloud road boundaries. To address this problem, this study proposes a road boundary extraction method that integrates pavement edge information, accurately considers the position of the road boundary from two dimensions, eliminates false boundaries, and completes the missing boundary through the extracted boundary spatial relationship. First, grid elevation filtering is used to remove high-level non-ground points. Then the pavement edges and curb stone points are extracted from the preprocessed point cloud, and they are superimposed to remove false boundary points to obtain accurate road boundaries. Finally, based on the spatial relationship of road boundaries, missing parts are detected and repaired to obtain complete road boundaries. Experimental results show that the accuracy on real road scenes exceeds 98%, the completeness rate is above 91%, and the extraction quality is above 90%, which verifies the effectiveness and accuracy of this method.

Impact of different food-grade protein extraction methods on the proteomic profile and potential allergenicity of Spirulina (Arthrospira platensis)

Various optimized methods for cell disintegration and protein extraction of algae have been reported, but there is a lack of information regarding the proteomic characterization of the extracted proteins; thus, systematic verification of the protein profiles to find potentially exploitable proteins, while minimizing allergenicity risks, is profitable. The method described in this study was developed to thoroughly investigate the proteome characterization of A. platensis following aqueous protein extraction by high-shear homogenization and pH shift. Liquid chromatography-tandem mass spectrometry was applied to assess the proteome obtained from four protein extraction methods using data-dependent proteome analysis. Overall, 699 proteins were identified; however, each extraction method identified unique proteins. The maximum number of exclusive proteins was observed using a combination of high-shear homogenization and acidic pH. The evaluation of protein abundance revealed a clear distinction between proteins isolated from pH 2 treatment compared to those obtained via neutral or basic pH treatment. The applied extraction methods affected the in silico computed physicochemical properties of the proteins. Using the AllerCatPro database, 12 putative allergenic proteins were detected, the most predominant of which were related to the C-phycocyanin beta subunit (P72508). This study demonstrated that extraction methods affect the detection, physicochemical properties, and potential allergenicity of the obtained proteins. Hence, the extraction methods used to obtain novel proteins must consider these aspects before using them as functional foods.

Optimization of Cell Membrane Purification for the Preparation and Characterization of Cell Membrane Liposomes.

Cell membrane nanoparticles have attracted increasing interest in nanomedicine because they allow to exploit the complexity of cell membrane interactions for drug delivery. Several methods are used to obtain plasma membrane to generate cell membrane nanoparticles. Here, an optimized method combining nitrogen cavitation in isotonic buffer and sucrose gradient fractionation is presented. The method allows to obtain cell membrane fractions of high purity from both suspension and adherent cells. Comparison with other common methods for membrane extraction, where mechanical lysis using cell homogenizers is performed in isotonic or hypotonic buffers, shows that the optimized procedure yields high purity membrane in a robust and reproducible way. Procedures to mix the purified membrane with synthetic lipids to obtain cell membrane liposomes (CMLs) are presented and indications on how to optimize these steps are provided. CMLs made using crude membrane isolates or the purified membrane fractions show different uptake by cells. The CMLs made with the optimized procedure and liposomes of the same composition but without cell membrane components are thoroughly characterized and compared for their size, zeta potential, bilayer and mechanical properties to confirm membrane protein inclusion in the CMLs. Cell uptake studies confirm that the inclusion of membrane components modifies liposome interactions with cells.

Comparative Analysis of Water Body Extraction Accuracy Based on Thresholding Method

Abstract. With the continuous development of remote sensing technology, various methods for land water body extraction based on satellite remote sensing have emerged. The thresholding method, as a commonly used image segmentation technique, possesses advantages such as high efficiency and wide applicability, making it widely employed in water body extraction research. In this thesis, utilizing SPOT4 imagery, we conducted experimental comparisons of water body extraction using the Iteration thresholding algorithm, Kittler-Illingworth (KI) thresholding algorithm, and Otsu thresholding algorithm. The experimental results demonstrate that all three thresholding methods exhibit good performance in water body extraction, with the Kittler-Illingworth (KI) thresholding algorithm achieving the highest relative accuracy.

To date or not to date? A comparison of different 14C pretreatment methods applied to archeological marine shells from Vale Boi (Portugal)

Abstract Mollusk shells are often found in archeological sites, given their great preservation potential and high value as a multipurpose resource, and they can often be the only available materials useful for radiocarbon (14C) dating. However, dates obtained from shells are often regarded as less reliable compared to those from bones, wood, or charcoals due to different factors (e.g., Isotope fractionation, reservoir effects etc.). The standard acid etching pretreatment for mollusk shells is the most used in many 14C laboratories, although another protocol known as CarDS (Carbonate Density Separation) was introduced just over a decade ago. We compare these two methods with two newly proposed methods for intracellular organic matrix extraction. We applied all four methods to samples selected from different archeological layers of the well-known Upper Paleolithic site of Vale Boi, rich in mollusk specimens throughout the stratigraphic sequence. Here we compare our results to previous dates to determine which of these pretreatment methods results in the most reliable 14C dates. Based on the results of this study, all four methods gave inconsistent ages compared to previous dates and the stratigraphic attribution.

The effect of different washing methods assisted by ultrasound on the removal of cypermethrin and spirotetramat residues in apples

AbstractThe simplest way to remove pesticide residues from fruits and vegetables is to wash them with tap water. However, this method is not effective enough. In this study, the effectiveness of different washing methods assisted by ultrasound on pesticide removal was investigated. For this purpose firstly, apples were soaked in a cypermethrin (CYP) and spirotetramat (SPI) solution, which are frequently used as insecticides. Subsequently, the apples were washed in solutions prepared with vinegar, lemon juice, and baking soda at different concentrations (0.5%, 1% and 2%) and assisted by ultrasound (2.5–5 min). The residues in the medicated and washed samples were analysed on an LC-MS/MS instrument after extraction using the QuEChERS extraction method. The results of the analysis showed that acidic vinegar and lemon juice were more effective than baking soda. Moreover, the application of ultrasound significantly increased this effect. When a 0.5% vinegar solution was assisted by ultrasound, 62% of the cypermethrin residue was removed and 82% of the spirotetramat residue was removed. These values were 51.5% and 49.6% higher than tap water, respectively. In conclusion, acidic solutions such as vinegar, which we can easily prepare at home, are highly effective in removing pesticide residues when assisted by ultrasound.

A morphological and high throughput sequencing workflow to identify Australian ants (Hymenoptera, Formicidae): a new tool for biosecurity and biodiversity

Ants are often the most ubiquitous and ecologically influential components of terrestrial systems, exhibiting an exceptionally high level of endemic diversity. Simultaneously, exotic ants can be amongst the most environmentally and economically devastating biological invaders. Distinguishing between exotic and related natives is essential for early detection and to reduce the chance of establishment, but at the species-level there remains a great deal of uncertainty among several of the most diverse, widespread and ecologically dominant genera. This taxonomic impediment negatively impacts the use of molecular techniques relying on reference databases, due to the poor state of ant DNA sequences in publicly available repositories, with many species not represented at all and others incorrectly identified. As a result, biosecurity screening for targeted exotic ants and assigning ant species-level identifications for biodiversity remain two separate areas of focus in Australia. Here we propose a workflow for the identification of ants that enables simultaneous processing of large numbers of “bulk” ant samples each containing many individuals, increasing resolution for taxonomic assignment, and generating a curated database linked to voucher specimens. We use a non-destructive DNA extraction method and compare two high throughput sequencing (HTS) metabarcoding platforms – MiSeq (Illumina) and MinION (Oxford Nanopore Technologies) – processing up to 180 bulk mixed ant samples per run. This approach allowed for the acquisition of curated DNA sequences from voucher specimens morphologically examined by expert taxonomists. This work highlights the advantages and current limitations of DNA-based identifications, the needs for standardisation, as well as the importance of a taxonomy-based curation of DNA database for both biodiversity and biosecurity.

Remote Sensing LiDAR and Hyperspectral Classification with Multi-Scale Graph Encoder–Decoder Network

The rapid development of sensor technology has made multi-modal remote sensing data valuable for land cover classification due to its diverse and complementary information. Many feature extraction methods for multi-modal data, combining light detection and ranging (LiDAR) and hyperspectral imaging (HSI), have recognized the importance of incorporating multiple spatial scales. However, effectively capturing both long-range global correlations and short-range local features simultaneously on different scales remains a challenge, particularly in large-scale, complex ground scenes. To address this limitation, we propose a multi-scale graph encoder–decoder network (MGEN) for multi-modal data classification. The MGEN adopts a graph model that maintains global sample correlations to fuse multi-scale features, enabling simultaneous extraction of local and global information. The graph encoder maps multi-modal data from different scales to the graph space and completes feature extraction in the graph space. The graph decoder maps the features of multiple scales back to the original data space and completes multi-scale feature fusion and classification. Experimental results on three HSI-LiDAR datasets demonstrate that the proposed MGEN achieves considerable classification accuracies and outperforms state-of-the-art methods.

Feature extraction and classification of microstructure and magnetic tomography images of an advanced Nd-Fe-B sintered magnet

Abstract Although the microstructure and magnetic tomography images of an advanced Nd-Fe-B sintered magnet were previously reported [Takeuchi, SO., NPG Asia Mater. 14, 70 (2022)], the relationship between these three-dimensional images has not been well analyzed. In this work, a feature extraction method of histogram of oriented gradients and a classification method of uniform manifold approximation and projection are employed for this issue. The microstructural features with superimposing the information of magnetic domain structure are classified into two groups depending on the external magnetic field, resulting in the different microstructural features for the different magnetization states are successfully classified. These differences of the microstructural features are difficult to be found by human recognition. Further detailed analysis of these microstructural features may clarify the key microstructures for the nucleation of reversed domains and their propagations.

Applying nanopore sequencing technology in Paracoccidioides sp.: a high-quality DNA isolation method for next-generation genomic studies.

Paracoccidioidomycosis is a severe systemic endemic mycosis caused by Paracoccidioides spp. which mainly affects individuals in Latin America. Progress in Paracoccidioides genomics has been slow, as evidenced by the incomplete reference databases available. Next-generation sequencing is a valuable tool for epidemiological surveillance and genomic characterization. With the ability to sequence long reads without the need for prior amplification, Oxford Nanopore Technology (ONT) offers several advantages, but high-quality and high-quantity DNA samples are required to achieve satisfactory results. Due to the low concentration of Paracoccidioides DNA in clinical samples and inefficient culture isolation methods, DNA extraction can be a significant barrier to genomic studies of this genus. This study proposes a method to obtain a high-coverage de novo genome assembly for Paracoccidioides using an improved DNA extraction method suitable for sequencing with ONT. The assembly obtained was comparable in size to those constructed from available data from Illumina technology. To our knowledge, this is the first genome assembly of Paracoccidioides sp. of such a large size constructed using ONT.

Cultivated Land Information Extraction and Spatial Pattern Analysis in Beijing Based on Deep Learning

Abstract. Cultivated land is the basic resource and material condition for human survival, providing the necessary material basis for agricultural development and agricultural modernization (Tian and Shi, 2024). For this reason, this paper takes Beijing as an experimental area to study the cultivated land extraction method and analyze the distribution pattern of cultivated land and the degree of fragmentation. The results show that (1) the extraction results are evaluated by using confusion matrix and Kappa coefficient, and the Kappa coefficient is obtained to be 0.8358.(2) The cultivated land in Beijing is mainly distributed in the southeast as well as the northwest of the local area of gentle terrain, and the The range of the extremely high value of cultivated land kernel density in 2017–2022 is significantly reduced, the slope of the area with the smallest reduction in the proportion of cultivated land is less than 5°, the reduction in the area of cultivated land in water resource-rich areas is small, and the reduction in the proportion of cultivated land in road-intensive areas is large. (3) Due to various natural factors and human activities, the degree of cultivated land fragmentation in Beijing is increasing, the boundary shape of cultivated land patches tends to be irregular.

Impact of PM2.5 filter extraction solvent on oxidative potential and chemical analysis

ABSTRACT Fine particulate matter (PM2.5) is hypothesized to induce oxidative stress, and has been linked to acute and chronic adverse health effects. To better understand the risks and underlying mechanisms following exposure, PM2.5 is collected onto filters but prior to toxicological analysis, particles must be removed from filters. There is no standard method for filter extraction, which creates the possibility that the methods of extraction selected can alter the chemical composition and ultimately the biological implications. In this study, comparisons were made between extraction solvents (methanol (MeOH), dichloromethane (DCM), 0.9% saline, and Milli-Q water) and the results of oxidative potential and elemental concentration analysis of PM2.5 collected across sites in Arkansas, USA. Significant differences were observed between solvents, with DCM having significantly different results compared to all other extraction solvents (p ≤ 0.001). Significant correlations between element, black carbon, and PM2.5 concentrations and oxidative potential were observed. The observed correlations were extraction solvent dependent. For example, in saline extracted samples, oxidative potential had significant negative correlations with: Ba, Cd, Ce, Co, Ga, Mn and significant positive correlations with: Cr, Ni, Th, U. While in MeOH extracted samples, significant positive correlations were only between oxidative potential and Ga, U and significant negative correlations with V. This indicates that PM2.5 samples extracted with different solvents will yield different conclusions about the causal components. This study highlights the importance of filter extraction methods in interpretation of oxidative potential results and comparisons between studies. Implications While there is no standard method for PM2.5 filter extraction, variation of extraction methods impact analytical results. This project identifies that extraction method variation, particularly extraction solvent selection, leads to discrepancies in chemical and toxicological analysis for PM2.5 collected on the same filter. This work highlights the need for methods standardization to support accurate comparisons between PM2.5 research studies, thus providing better understanding of PM2.5 across the globe.

Quality Results of Cotton Fabric Coloring with Mangsi (Phyllanthus Reticulatus) Fruit Extract

The research was done to analyze the quality of the coloring result of mangsi (phyllanthus reticulatus) fruit extract as natural dyes in cotton fabric dyeing. Extraction method was carried out through maceration process using some solvents namley water, ethanol, acidic ethanol, methanol, and acidic methanol in a ratio of 1:10 with pre-mordanting and fixation using mordant alum, calcium carbonate, and ferrous sulphate. The conducted observations included color direction test, color opacity test and color fastness to soap washing test. The result of color direction was brown to yellow-orange and blue to dark blue. The value of color opacity on cotton fabrics was in the “medium” to “very opaque” color category. The resulting value of color fastness to soap washing test was in the “good” to “poor” category. The dyeing results on cotton fabric generated an even color.

Ultrasound-assisted extraction vs. microwave-assisted extraction for sustainable development goals: Selecting the ideal lipid extraction and fatty acid profile

The objective of this study was to compare the efficiency of ultrasound-assisted extraction (UAE) and microwave-assisted extraction (MAE) methods for extracting lipids from the green microalga Chlorococcum novae-angliae. This study specifically focused on the fatty acid profiles of the extracted lipids, using ethanol as the solvent and wet biomass as the starting material. Ultrasound-assisted extraction yielded a maximum of 0.026 ± 0.001 g lipid/g wet biomass at a biomass ratio of 1:25 for 2 min with a 1-second cycle at 180 W and 20 kHz, which was 21% higher than that of microwave-assisted extraction conducted at a ratio of 1:30 for 2 min at 300 W and 35 °C. Ultrasound-assisted extraction enhanced saturated fatty acids (SFAs), which were 1.5 times higher than to microwave-assisted extraction, while microwave-assisted extraction significantly increased polyunsaturated fatty acids (PUFAs) by 4.4 times. The findings suggest that ultrasound-assisted extraction is more suitable for applications requiring high SFA content, such as in the fuel industry, whereas microwave-assisted extraction is preferable for sectors focused on fatty acid quality, such as food and health. This comparative analysis contributes to the literature by highlighting the impact of extraction methods on fatty acid profiles and supports sustainable development goals (SDGs), particularly SDG 12, by promoting environmentally friendly extraction techniques.

Factors Affecting the Extraction Components of Artemisia Argyi Volatile Oil

The main components of Artemisia argyi volatile oil include eucalyptol, camphor, pinene, camphene, borneol, and other active substances. These components exhibit various pharmacological effects such as antibacterial, anticancer, choleretic, antiasthmatic, analgesic, hemostatic, and anti-allergic properties. However, due to variations in Artemisia species, growth environments, and extraction methods, the main components and their concentrations in Artemisia argyi volatile oil can vary. This paper systematically summarizes the factors affecting the composition and content of Artemisia argyi volatile oil, detailing how factors such as the source of Artemisia, harvest time, storage methods, plant parts, and extraction methods influence the essential oil components, providing theoretical references for research on extraction processes and high-value utilization of Artemisia argyi.