Analysis Of Chemical Components Research Articles

Correlation Analysis of Chemical Components and Rheological Properties of Asphalt After Aging and Rejuvenation

Correlation Analysis of Chemical Components and Rheological Properties of Asphalt After Aging and Rejuvenation

Noninvasive and simultaneous quantitative analysis of multiple human blood components based on the grey analysis system

Noninvasive detection of human blood components is the dream of human beings and the goal of clinical detection. From the perspective of mathematical analysis, based on the grey analysis system, the principle of spectral chemical quantitative analysis and the solution method of multivariate linear equation, this paper pioneers the spectrum elimination method, and obtains a complete, high-precision, synchronous and noninvasive detection system for a variety of human blood components. The spectral elimination method applies the principle of elimination method in mathematics to the noninvasive quantitative analysis of human blood components by spectral method, reduces the influence of non-target components on the detection of target components, and improves the accuracy of noninvasive quantitative analysis of human blood components. To demonstrate the effectiveness of the method, taking the analysis of the contents of seven blood components (hemoglobin, red blood cell count, neutrophils, lymphocytes, monocytes, eosinophils and basophils) in blood as an example, fourteen models were established by two different methods. From the comparison of modeling results, it can be concluded that when the seven models established by spectral elimination method predict the corresponding seven components of all samples, the predicted correlation coefficients are more than 0.9500. The experimental results show that the spectral elimination method and non-invasive detection system proposed can predict the content of human blood components with high accuracy. This paper studies a high-precision, simultaneous and noninvasive quantitative analysis system of multiple human blood components for the first time, which not only makes great progress in the non-invasive chemical quantitative analysis of human blood components by spectroscopy, but also has great application value for clinical medical treatment and disease diagnosis.

Discriminating Geographical Origin of Cashew Nuts Based on the Combination of Multi-elements and Chemical Component Analysis

This study aims to distinguish Indonesian cashew nuts’ geographical origin based on their elemental profiles and chemical composition. Nine elements and five chemical components of cashew nut samples were analyzed. The profiles of four micro-elements, Zn, Cu, Mn, Cr, and five macro elements, K, Ca, Mg, Fe, Na, of Indonesian cashew nuts were determined using Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES). Simultaneously, the chemical components of moisture, ash, total protein, total fat, and carbohydrate contents were measured using the AOAC standard. The combination of elemental profiles was then analyzed with a scatterplot matrix diagram and a multivariate statistical technique, Canonical Discriminant Analysis (CDA). Inter-region discrimination among four major Indonesian cashew nuts producers was achieved by applying CDA. Sodium (Na), calcium (Ca), potassium (K), manganese (Mn), zinc (Zn), and total protein were the best descriptors for cashew nuts origin. According to the findings, the most abundant element in cashew nuts is potassium (K), followed by magnesium (Mg), and calcium (Ca) (Ca). Fat is the most abundant chemical composition in cashew nuts at the same time. Potassium (K), magnesium (Mg), and calcium (Ca) concentrations showed major regional variations. On the other hand, zinc (Zn) and manganese (Mn) are two micro-elements that may help identify the origin of cashew nut samples. The use of a Canonical Discriminant Analysis scatters plot to visualize the origin of Indonesian cashew nut samples was less successful based on micro-element concentrations. The CDA scatter plot application based on macroelements, and the CDA scatter plot application based on a mixture of micro- and macro-elements produced better results than the CDA scatter plot application based on micro-elements. Furthermore, the best visual separation was achieved using a CDA scatter plot based on a combination of elemental profiles and protein concentration. For a complete characterization of cashew nuts, further research with a large number of samples is needed.

Evaluation of physicochemical changes of Nopal (Opuntia ficus-indica) at different steam cooking times

The objective was to evaluate and schematically characterize the physicochemical changes of nopal (Opuntia ficus-indica) due to steam cooking at different times. Cladodes were cut into pieces (25 x 30 x 15 mm) and mixed to obtain four samples of 1250 g each on a fresh basis and randomly assigned to each treatment: T1 or Control; T2, cooking for 4 min; T3, for 7 min; and T4, for 10 min. After cooking, samples were dehydrated, and then a proximal chemical analysis was performed. The data were analyzed through a fixed-effect model, and the differences between treatments were obtained by least-squares means. Correlation analysis of chemical components was conducted. T2, T3, and T4 showed higher values of protein (?16.0/ 100 g DM), lipids (?1.3 g/100 g DM), and nitrogen-free extract (?20.2 g/100 g DM) than T1; whereas dietary fiber (? 33.6 g/100 g DM) and insoluble fiber (? 22.0 g/100 g DM) in these were lower than T1. Soluble fiber decreased in T3 and T4 (5.9 and 5.5 g/100 g DM, respectively) but increased in T2 (14.5 g/100 g DM). In this study, steam cooking at 100 °C modified the chemical composition of nopal (O. ficus-indica) suggesting that cooking for 4 min might help to preserve cladode components.

Blood chemical components analysis of honeysuckle and formulation of xanthan gum/starch-based (PVA-co-AA) hydrogels for controlled release

Honeysuckle is a commonly used Chinese medicine for treating intestinal inflammation and other diseases. Compounds that are absorbed into the blood produce pharmacodynamic effects. However, it is still unclear which compounds in honeysuckle are absorbed into the blood. Thus, the purpose of this study was to investigate the composition and in vivo absorption of active components in honeysuckle in male Sprague-Dawley rats, and develop a controlled release hydrogel system. UPLC-LTQ-Orbitrap-MS was used to determine the active ingredients of honeysuckle in vitro and in vivo. A total of 80, out of which 42 components were found to be absorbed into the blood, which includes flavonoids, iridoids, organic acids and other compounds. FTIR analysis confirmed crosslinking between hydrogel content and drug loading, and TGA and DSC analysis indicated a high thermal stability. XRD analysis showed a decrease in crystallinity following crosslinking, and SEM revealed an irregular and hard surface. The maximum swelling and drug release were observed at pH 7.4 as compared to pH 1.2. The identified blood components can be used to determine Q-markers, while the prepared hydrogels can serve as an effective and promising carrier for the controlled release of honeysuckle extracts.

Isolation and Analysis of Chemical Components of Garlic (Allium sativum L.) Tuber Essential Oil As Well As Antibacterial and Antioxidant Activity Tests

The essential oil from garlic tubers (Allium sativum L) was isolated by hydrodistillation method using the Stahl apparatus. Garlic tubers were distilled for 4 to 5 hours to produce as much oil as 0.05% (w/ w). The chemical components of essential oil of garlic tubers were analyzed using GC-MS spectroscopy. The GC-MS results showed that there were 11 components with 5 main components, namely diallyl disulfide (44.98%), 1,3-diallyl tri sulfane (13.63%), allyl sulfide (13.06%), methyl allyl disulfide (11.87%), and methyl allyl trisulfide (4.84%). The antibacterial activity of essential oil of garlic tubers with diffusion method to use concentration variation of 5%, 10%, and 15% have strong antibacterial activity against Gram-positive bacteria like Staphylococcus aureus and have a medium to strong antibacterial activity against Gram-negative bacteria like Escherichia coli. The antioxidant activity of the essential oil of garlic tubers with DPPH (2,2-diphenyl-1-picrylhydrazil) showed an IC50 value was 22.863 mg/L and a very strong antioxidant group.

Utilization of corncob hydrolysate enables 2,3-butanediol production in Enterobacter cholerae

2,3-Butanediol (2,3-BDO) is an important industrial diol that could function in various fields. Currently, there are many substrates used for 2,3-BDO biosynthesis, but studies using green carbon sources such as corncob hydrolysate as a substrate are lacking. As a widely distributed waste lignocellulose-derived substrate, corncob hydrolysate is nutrient-rich and cost-effective. The present study evaluated 2,3-BDO production via an Enterobacter cholerae strain using corncob hydrolysate as carbon source. Chemical component analysis showed that concentrated corncob hydrolysate contained 233 g/L total sugar and showed no inhibitory effect, but it was beneficial for 2,3-BDO synthesis. Optimization experiments for fermentation resulted in a titer of 47.23 g/L 2,3-BDO with a yield of 0.30 g/g and a productivity rate of 0.66 g/L•h. This study is expected to provide insights for large-scale bioproduction of bulk chemicals utilizing corncob hydrolysates.

A robust superhydrophobic and oleophobic coating with short chain perfluoroalkyl group and flower-shaped SiO2 nanoparticles

Low-surface-energy fluorocarbon-based materials are widely used in superhydrophobic and oleophobic coatings. The fabrication of oil-repellant coatings, however, is particularly challenging due to the low surface tension of oils and the nondegradable of long-fluorocarbon compounds (CnF2n+1, n ≥ 8). In this work, superhydrophobic and oleophobic functional nanoparticles were prepared based on flower-shaped silica and environmentally friendly short chain perfluoroalkyl group. The experimental results show that a low-surface-energy coating surface (water contact angle of 152.5 ± 0.4°, oil contact angle of 142.2 ± 0.8°) can be obtained by using triethoxy(1H,1H,2H,2H-nonafluorohexyl)silane (CH3CH2O)3SiCH2CH2(CF2)3CF3 (C4FTES) and methyltriethoxysilane (MTES) to co-modified flower-shaped SiO2 nanoparticles (flower-shaped MF-SiO2). The analysis of morphology and chemical components of flower-shaped MF-SiO2 displayed a synergistic effect by providing a multi-scale rough structure of flower-shaped SiO2 which minimize contact at the liquid/solid interface, and promotes the distribution and accumulation of the outermost -CF3 groups of nanoparticles as evidenced by the angle-resolved X-ray photoelectron spectrum (AR-XPS) tests. Furthermore, flower-shaped MF-SiO2 nanoparticles have good mechanical stability under the action of adhesive, which means the flower-shaped MF-SiO2 nanoparticles as a promising candidate for superhydrophobic and oleophobic coating materials.

Changes in Chemical Composition of Betung Bamboo (Dendrocalamus asper) after Alkali Immersion Treatment under Various Immersion Times

This research aimed to analyze the change in chemical composition of the betung bamboo (Dendrocalamus asper) strands after alkali immersion treatment under various immersion times. The bamboo culms were converted into strands with the target length, width, and thickness of 70, 25, and 0.5 mm, respectively. Strands were alkali immersion-treated with 1% NaOH solution for 1, 2, and 3 h. Preparation of powder for chemical component analysis refers to the Technical Association of the Pulp and Paper Industry (TAPPI) standard T 264 cm-07 regarding the preparation of wood test samples for chemical analysis. Structural and non-structural bamboo strand chemical components such as holocellulose, alpha-cellulose, hemicellulose, klason lignin, and extractives were analyzed. The results showed that alkali immersion treatment decreased the hemicellulose content from 21.55% before treatment to 20.30% after 3 h immersion. Thus, it changed the holocellulose and alpha-cellulose composition. Alkali immersion treatment also changed the extractive substances dissolved in cold water, hot water, 1% NaOH, and ethanol-benzene solution. The decrease in hemicellulose, molecular weight lignin, and extractive substances would be beneficial for bamboo-oriented strand board manufacture to improve strand adhesion, dimensional stability, mechanical properties, and durability against biological agents attack. Keywords: alkali immersion times, alkali immersion treatment, bamboo, chemical components, pre-treatment

Seaweed Oligosaccharide Synergistic Silicate Improves the Resistance of Rice Plants to Lodging Stress under High Nitrogen Level

The objective of this study was to determine the effect of seaweed oligosaccharide synergistic silicate (Si) fertilizer (SOSSiF) on rice resistance to lodging stress. The results showed that a spraying SOSSiF decreased apparent lodging index and enhanced rice yield significantly under a high N level. The spraying test indicated that the apparent lodging rate of rice was the lowest when SOSSiF was sprayed for four times, and the dosage was 45 kg/ha each time. Morphological and anatomical analysis indicated that SOSSiF decreased plant height and the lower internode length of ZCSM and increased culm cross-sectional area and wall thickness of JNSM significantly compared with the control. Furthermore, SOSSiF enhanced bending strength of rice culm by 38.8% to 63.6%, and reduced lodging index by 36.8% to 42.6%. Chemical component analysis found that SOSSiF elevated the contents of soluble sugar, cellulose, Si, and lignin in the culms of ZCSM and JNSM. Correlation analysis revealed that the lodging index was positively correlated with the length of the lower internode, and was negatively correlated with culm bending strength and culm thickness. The above results suggested that spraying SOSSiF elevates culm contents of Si and lignin and enhances bending strength, thus improving rice lodging resistance and production.

Quantitative Analysis of Routine Chemical Constituents of Tobacco Based on Thermogravimetric Analysis.

As the most basic indexes to evaluate the quality of tobacco, the contents of routine chemical constituents in tobacco are mainly detected by continuous-flow analysis at present. However, this method suffers from complex operation, time consumption, and environmental pollution. Thus, it is necessary to establish a rapid accurate detection method. Herein, different from the ongoing research studies that mainly chose near-infrared spectroscopy as the information source for quantitative analysis of chemical components in tobacco, we proposed for the first time to use the thermogravimetric (TG) curve to characterize the chemical composition of tobacco. The quantitative analysis models of six routine chemical constituents in tobacco, including total sugar, reducing sugar, total nitrogen, total alkaloids, chlorine, and potassium, were established by the combination of TG curve and partial least squares algorithm. The accuracy of the model was confirmed by the value of root mean square error for prediction. The models can be used for the rapid accurate analysis of compound contents. Moreover, we performed an in-depth analysis of the chemical mechanism revealed by the result of the quantitative model, namely, the regression coefficient, which reflected the correlation degree between the six chemicals and different stages of the tobacco thermal decomposition process.

Detoxification mechanism of vinegar-processed Kansui revealed by systematic phytochemical analysis using ultrahigh-performance liquid chromatography diode array detection tandem mass spectrometry, ultrahigh-performance liquid chromatography high-resolution mass spectrometry and in silico drug target identification.

The dried roots of Euphorbia kansui L., known as Kansui, are used to treat ascites and edema in traditional Chinese medicine. However, the toxicity of this herb has seriously restricted its clinical application. A unique vinegar-processing method has been used to reduce its toxicity since the time of ancient China. However, the detoxification mechanism underlying such vinegar processing has not been fully revealed. To find the answer, the process-induced changes in components should be carefully investigated. We performed a systematic analysis of chemical components in raw and vinegar-processed Kansui using ultrahigh-performance liquid chromatography (UHPLC) diode array detection tandem mass spectrometry and UHPLC high-resolution mass spectrometry. Thirty-one chemical components in raw and vinegar-processed Kansui were found, the chemical structures of 28 components among them were proposed and the process-induced changes in components were then investigated. A comprehensive conclusion about the process-induced chemical change was drawn. It was found that jatrophane-type diterpenoids decreased markedly after vinegar processing, while ingenane-type diterpenoids were retained during vinegar processing. In silico drug target identification gave hints that jatrophane-type diterpenoids, which decreased markedly during vinegar processing, may have more intense toxicity involving cholinesterase and mitogen-activated protein kinases, while ingenane-type diterpenoids, which were retained during vinegar processing, may have a more intense therapeutic effect involving carbonic anhydrase. The possible detoxification mechanism of vinegar-processed Kansui is presented. The research has significance for the therapeutic/toxic chemical basis of Kansui. Also, it has significance for drug discovery from terpenoids within the herb.

Analysis of Detailed Chemical and Bioactive Components of Yığılca Honeybee Propolis and Determination of Antioxidant Potential

Analysis of Detailed Chemical and Bioactive Components of Yığılca Honeybee Propolis and Determination of Antioxidant Potential

Kandungan Minyak Esensial Sebagai Bahan Baku Obat-Obatan dari Tanaman Gaharu (Gyrinops versteegii) pada Kondisi Lahan Berbeda

Content of Essential Oils as Raw Materials for Medicine from Agarwood Plants (Gyrinops versteegii) in Various Soil Conditions. Essential oil is one of the processed agarwood (Gyrinops versteegii) which is useful in the basic ingredients of perfume, cosmetics, and medicines. The purpose of this study was to determine the volume and chemical composition of essential oils in agarwood plants in different land conditions. This research was conducted through a hydrodestillation process and chemical component analysis using a Gas Chromatography Mass Spectrophotometer (GCMS). The materials used are samples of agarwood from different lands, namely: A (agarwood on land with Regosol in Klungkung Regency) and B (agarwood on land with Latosol in Tabanan Regency). The specimens of agarwood consisted of: (1) Sapwood, (2) Kemedangan. The results showed that the essential oil content of the sapwood and kemedangan agarwood from Tabanan was higher than that of the sap and kemedangan agarwood from Klungkung. The composition of the compounds contained in sapwood includes: 9-Octadecenoic acid, Trans-13-Octadecenoic acid, Eugenol, 1-Nonadecene, Propanedioic acid, phenyl-; 2-propanol, 1,1'-oxybis-; 1-Propanol, 2- (2-hydroxypropoxy); Cyclopentadecanone, 2-hydroxy-and Oleic acid.

A comparative performance of machine learning algorithms on laser‐induced breakdown spectroscopy data of minerals

AbstractThe exploration and analyses of chemical components in (extra‐)terrestrial geological materials (such as asteroids and meteorites) are insightful in modern research. Laser‐induced breakdown spectroscopy (LiBS) is a popular method for analyzing the chemical attributes of geologic samples—which scientists use to study and understand planetary bodies and their complex histories. In the literature, several machine learning models that produce high‐accuracy predictions have been proposed. In our work, we compared the performances of such models in predicting elemental abundances on a certain spectroscopic dataset. Models included partial least squares (PLS), extreme gradient boost machines (XGB), neural networks, and linear models. In our results, we showed how PLS and XGB are superior in terms of high predictive power, their ability to generalize, and their reasonably efficient runtimes. In addition, we proposed Ensemble models that aggregate predictions of top‐tier models and observed that they can be desirable. We intend to gain better understanding of how these models perform in predicting elemental compositions on specific spectrum (LIBS) datasets.

A Long Short-Term Memory Neural Network Based Simultaneous Quantitative Analysis of Multiple Tobacco Chemical Components by Near-Infrared Hyperspectroscopy Images

Near-infrared (NIR) spectroscopy has been widely used in agricultural operations to obtain various crop parameters, such as water content, sugar content, and different indicators of ripeness, as well as other potential information concerning crops that cannot be directly obtained by human observation. The chemical compositions of tobacco play an important role in the quality of cigarettes. The NIR spectroscopy-based chemical composition analysis has recently become one of the most effective methods in tobacco quality analysis. Existing NIR spectroscopy-related solutions either have relatively low analysis accuracy, or are only able to analyze one or two chemical components. Thus, a precise prediction model is needed to improve the analysis accuracy of NIR data. This paper proposes a tobacco chemical component analysis method based on a neural network (TCCANN) to quantitatively analyze the chemical components of tobacco leaves by using NIR spectroscopy, including nicotine, total sugar, reducing sugar, total nitrogen, potassium, chlorine, and pH value. The proposed TCCANN consists of both residual network (ResNet) and long short-term memory (LSTM) neural network. ResNet is applied to the feature extraction of high-dimension NIR spectroscopy, which can effectively avoid the gradient-disappearance issue caused by the increase of network depth. LSTM is used to quantitatively analyze the multiple chemical compositions of tobacco leaves in a simultaneous manner. LSTM selectively allows information to pass through by a gated unit, thereby comprehensively analyzing the correlation between multiple chemical components and corresponding spectroscopy. The experimental results confirm that the proposed TCCANN not only predicts the corresponding values of seven chemical components simultaneously, but also achieves better prediction performance than other existing machine learning methods.

Analysis of Key Chemical Components in Aqueous Extract Sediments of Panax Ginseng at Different Ages.

Panax ginseng beverages have been some of the most popular plant drinks among consumers in recent years, but they become turbid and sediment are easily formed during production and marketing, these are some of the key issues that affect the quality of the beverages. In this study, we analysed the physicochemical properties of sediments in aqueous extracts of 3- to 6-year-old ginseng, and by tracing the sediment formation process from 0–40 days, we observed that the sediment was gradually beginning on day 10. The solid content of ginseng aged 5 and 6 years was significantly higher than that of ginseng aged 3 and 4 years. There was no significant difference in the sediment amount sediment in the extracts of ginseng of different ages. The light transmittance of the extracts after centrifugation was significantly higher than before centrifugation. Colour-difference analysis found that there was a significant positive correlation between ginseng age and colour-difference value (ΔE). Chemical composition analysis showed that total sugar and proteins were the main components of the sediment. In addition, ginsenosides, amino acids and minerals were also involved in sediment formation to different degrees. A stepwise regression model was established through principal component analysis (PCA), and the regression equation for predicting the sediment amount was obtained as follows: sediment amount (mg/mL) = 2.906 − 0.126 × CTotal saponins − 0.131 × CFree amino acids.

Discussion on Medicinal Value of Honeysuckle and Analysis of Main Chemical Components

Discussion on Medicinal Value of Honeysuckle and Analysis of Main Chemical Components

Effect of altitude on polysaccharide and lignin contents of brutian pine (Pinus brutia Ten.) wood and kraft pulp

This study investigated the chemical properties of Brutian pine (Pinus brutia Ten.) wood samples collected at altitudes of 800 m, 900 m, and 1000 m and the behaviors of the chemical components of the same materials during kraft pulping. Chemical component analysis indicated that the wood and pulp sample from 1000 m contained higher quantities of holocellulose and α-cellulose, and a lower quantity of lignin. For both wood and pulp samples, a continuous increase in holocellulose and α-cellulose contents and a continuous decrease in lignin content were observed with increasing altitude. Gas chromatography analysis of monosaccharides determined that the highest cellulose and hemicellulose contents were obtained from the wood and pulp sample from 1000 m. Quantity of these components increased with increasing altitude. Lastly, kraft pulping degraded 14.10-15.70% of cellulose, 56.49-61.35% of galactoglucomannan, 65.75-69.61% of arabinoglucoronoxylan, and 92.42-93.48% of lignin in the samples.

Groundwater discharge tracing for a large Ice-Covered lake in the Tibetan Plateau: Integrated satellite remote sensing data, chemical components and isotopes (D, 18O, and 222Rn)

It has been known that groundwater-lake water interaction plays an important role in mass exchange between land and lakes. However, most of the lakes in the world freeze during the winter, and few studies of groundwater and surface water interaction (groundwater discharge tracing) focus on ice-covered lakes. This study investigated groundwater discharge into a large ice-covered lake, Xiao Qaidam Lake in the Tibetan Plateau (TP), using satellite remote sensing and chemical and isotopic tracing. Analysis of chemical components, stable isotopes (D, 18O) and 222Rn revealed that groundwater discharge occurred in the western and southern portions of Xiao Qaidam Lake. Remote sensing data (the distribution of and variation in lake surface temperature, LST) revealed these locations of groundwater discharge and indicated additional groundwater discharge in areas of springs. Based on the regression model between LST and 222Rn activity in lake water and 222Rn mass balance model, the groundwater discharge into Xiao Qaidam Lake was estimated to be (2.77 ± 0.26) × 105 m3/d, which is slightly higher than river water input at summer. In addition, this study also suggests that ice melting process should be considered when tracing groundwater discharge into an ice-covered lake, and that the LST distribution during the icing period is better than the LST variation for tracing groundwater discharge because the ice eliminated noise from wind and surface water. The study provides insight into the tracing of groundwater discharge into large ice-covered lakes in the TP and elsewhere.