Determination Of Content Research Articles

Accurate determination of high sulfur content in sulfide samples: an optimized ICP-OES method

Determination of high sulfur content in sulfide minerals is crucial for various applications, including geochemistry, mining, and environmental monitoring. While inductively coupled plasma optical emission spectrometry (ICP-OES) is the preferred method for sulfur analysis, conventional sample preparation techniques often fall short when dealing with high sulfur concentrations. This study investigated optimized digestion conditions for accurate sulfur determination in sulfide minerals using ICP-OES. We employed anti-corrosion acid digestion bombs, an aqua regia–hydrofluoric acid system, and a digestion temperature of 180 °C, achieving exceptional results. Certified reference material recoveries ranged from 99.9 to 100.5%, with relative standard deviations between 0.42 and 0.84%. These results demonstrate the high accuracy and precision of the method. The optimized digestion protocol presented in this study provides a robust and reliable approach for accurate sulfur analysis in sulfide minerals, particularly for high concentrations.

Assessment of Quality Control parameters under Accelerated Stability Conditions for Manasamitra Vatakam; A Herbo Mineral Formulation

Accelerated Stability Studies predicts the stability data and significantly explains the drug decision process. In the present study, Manasamitra Vatakam, a Herbo mineral formulation was subjected to stability conditions at 40°C ± 2°C /75%± 5% RH for 06 months. Control and stability samples were determined for parameters like Weight variation, Moisture content, Marker content determination, and Disintegration test, Dissolution study with different mediums, Friability and Hardness test. The phytomarker analysis showed decrease assay value for β-sitosterol, Vitexin, Kampferol and Withaferin. The dissolution studies were performed for the major biomarker Berberine in 0.1N HCl, pH 4.5 acetate and pH 6.8 phosphate buffer in which pH 6.8 buffer showed maximum release of 66.82% at 04 hours. The other Quality control parameters showed minimal difference under acceptance criteria. The study explains the need of stability analysis in polyherbal formulations and developed method can be used for routine analytical studies in various formulation containing berberine. Keywords: Berberine, HPLC, Manasamitra Vatakam, Quality Control, Stability.

Determination of Trace Elements Content of a Popular Traditional Herbal Medicine Used for Internal Hemorrhoids Treatment in Katsina State, Nigeria

Study’s Excerpt/Novelty Assessment of toxic metal concentrations of a widely used traditional herb in Katsina state, was carried out. Flame atomic absorption spectrophotometry and descriptive statistical analysis was employed in the research. Pb, Cr, and As were found to be beyond WHO/FAO thresholds. Full Abstract There has been an increase in the utilization of traditional herbal drugs for different medications and health care in Katsina state. This is possibly due to the growing need for complementary disease treatment, relative cheapness, availability, and wider distribution. Raw samples of a popularly used traditional herb (locally named - Dan Lambar Rimi) were purchased from local markets, prepared, and analyzed using a flame atomic absorption spectrophotometer for Pb, Cr, As, Co, Ni, and Cd concentrations. The obtained concentrations were then summarized using descriptive statistics in SPSS Version 27. The results for the elements analyzed were Ni (0.83 ± 0.15), Cd (0.20 ± 0.01), Pb (21.5 ± 6.63), As (2.10 ± 0.70), Cr (2.36 ± 0.37), and Co (1.15 ± 0.22) ppm. Cr, Pb and As concentrations were greater than the WHO/FAO threshold limits for herbal medicines, while that of Cd was within the recommended threshold. Furthermore, the concentrations of these metals (As, Cr, and Pb) were greater than the WHO/FAO acceptable threshold in 50% of the herbal samples analyzed. Therefore, these metals can pose a threat to public health, especially considering the conventional way in which this herbal medicine is used. With deliberate improvement in hygiene during its preparation prior to consumption, the risk will be brought to a minimal. Future studies should perform a detailed chemical risk assessment, especially when we look at the increase in the number of diseases of unknown etiology in the region.

Determination of antioxidant capacity and phenolic content of haskap berries (Lonicera caerulea L.) by attenuated total reflectance-Fourier transformed-infrared spectroscopy

The total phenolic content (TPC) and antioxidant capacity (TAC) of haskap berries cultivated in various locations across Alberta were analyzed using attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy. The Folin–Ciocalteu assay was used to determine TPC, while TAC was quantified by 2,2-diphenyl-1-picrylhydrazl radicals (DPPH) assay and oxygen radical absorbance capacity (ORAC) assay. Three tenfold cross-validated partial least-squares regression (PLSR) models and three fivefold cross-validated deep learning models were developed separately based on FT-IR spectra collected from 22 haskap berry samples and their corresponding reference values determined through Folin-Ciocalteu, DPPH, and ORAC assays. The deep learning models (R2 = 0.95, 0.93, and 0.90 for Folin-Ciocalteu, DPPH, and ORAC assays, respectively) demonstrated better prediction capability compared to the PLSR models (R2 = 0.74, 0.72, and 0.66 for Folin-Ciocalteu, DPPH, and ORAC assays, respectively). In addition, PLS loading plots indicated that phenolic contents and polysaccharides in haskap berries could contribute to their antioxidant capacity. Using ATR-FTIR to estimate the TPC and TAC of fruits offers a rapid alternative to the conventional chemical assays.

Determination of Ethanol Content in Alcoholic Products by LF-NMR

Determination of Ethanol Content in Alcoholic Products by LF-NMR

Examination of the reliability of X‐ray powder diffraction analysis to determine mineral composition of soils

AbstractX‐ray powder diffraction (XRPD) is an effective technique for identifying and quantifying mineral types in soil. However, few studies have compared quantitative values based on XRPD with those from conventional wet chemical methods (WCMs). Here, we determined the primary mineral content in artificial mineral mixtures and 79 agricultural soils from across Japan using WCMs and two XRPD‐based quantitative methods: the mineral intensity factor (MIF) and the full‐pattern summation (FPS) methods performed with the powdR package for R. For artificial mixtures, the accuracy of mineral content determination (i.e., micas, quartz, K‐feldspar, and plagioclase) followed the order: WCMs > FPS > MIF. For Japanese agricultural soils, the contents of each mineral were highly similar between WCMs and FPS, based on mean absolute differences and correlation coefficients. Alternatively, MIF displayed lower similarities with WCMs, likely due to preferred orientation and peak shift or overlap issues. Using the FPS method, the mica and amorphous phase contents were positively and significantly correlated with nonexchangeable K content and cation exchange capacity, respectively. Additionally, the plagioclase content was negatively and significantly correlated with clay content. Thus, the powdR‐based FPS method is recommended for determining the mineral composition of soils, as it allows for a clearer and more quantitative demonstration of the relationship between individual minerals and soil properties.

MoistNet: Machine vision-based deep learning models for wood chip moisture content measurement

Quick and reliable measurement of wood chip moisture content is an everlasting problem for numerous forest-reliant industries such as biofuel, pulp and paper, and bio-refineries. Moisture content is a critical attribute of wood chips due to its direct relationship with the final product quality. Conventional techniques for determining moisture content, such as oven-drying, possess some drawbacks in terms of their time-consuming nature, potential sample damage, and lack of real-time feasibility. Furthermore, alternative techniques, including NIR spectroscopy, electrical capacitance, X-rays, and microwaves, have demonstrated potential; nevertheless, they are still constrained by issues related to portability, precision, and the expense of the required equipment. Hence, there is a need for a moisture content determination method that is instant, portable, non-destructive, inexpensive, and precise. This study explores the use of deep learning and machine vision to predict moisture content classes from RGB images of wood chips. A large-scale image dataset comprising 1,600 RGB images of wood chips has been collected and annotated with ground truth labels, utilizing the results of the oven-drying technique. Two high-performing neural networks, MoistNetLite and MoistNetMax, have been developed leveraging Neural Architecture Search (NAS) and hyperparameter optimization. The developed models are evaluated and compared with state-of-the-art deep learning models. Results demonstrate that MoistNetLite achieves 87% accuracy with minimal computational overhead, while MoistNetMax exhibits exceptional precision with a 91% accuracy in wood chip moisture content class prediction. With improved accuracy (9.6% improvement in accuracy by MoistNetMax compared to the best baseline model ResNet152V2) and faster prediction speed (MoistNetLite being twice as fast as MobileNet), our proposed MoistNet models hold great promise for the wood chip processing industry to be efficiently deployed on portable devices, such as smartphones.

Fermentation broth of a novel endophytic fungus enhanced maize salt tolerance by regulating sugar metabolism and phytohormone biosynthesis or signaling

Soil salinization is a major environmental factor that severely affects global agriculture. Root endophytes can enter root cells, and offer various ecological benefits, such as promoting plant growth, improving soil conditions, and enhancing plant resistance. Su100 is a novel strain of endophytic fungus that was characterized from blueberry roots. In this study, we focused on evaluating the effects of Su100 secretion on maize growth. The results demonstrated that maize treated with Su100 fermentation broth (SFB) exhibited significantly stronger salt tolerance than the control. It is worth mentioning that the treated root system not only had an advantage in terms of biomass but also a change in root structure with a significant increase in lateral roots (LRs) compared to the control. Transcriptome analysis combined with hormone content measurements indicated that SFB upregulated the auxin signaling pathway, and also caused alterations in brassinosteroids (BR) and jasmonic acid (JA) biosynthesis and signaling pathways. Transcriptome analyses also indicated that SFB caused significant changes in the sugar metabolism of maize roots. The major changes included: enhancing the conversion and utilization of sucrose in roots; increasing carbon flow to uridine diphosphate glucose (UDPG), which acted as a precursor for producing more cell wall polysaccharides, mainly pectin and lignin; accelerating the tricarboxylic acid cycle, which were further supported by sugar content determinations. Taken together, our results indicated that the enhanced salt tolerance of maize treated with SFB was due to the modulation of sugar metabolism and phytohormone biosynthesis or signaling pathways. This study provided new insights into the mechanisms of action of endophytic fungi and highlighted the potential application of fungal preparations in agriculture.

On the determination of charge and nitrogen content in cellulose fibres modified to contain quaternary amine functionality

Research interest in quaternization of cellulose fibres has increased considerably over the past decades. However, there is little or no consensus regarding how to characterize the material in terms of degree of substitution (DS), and the literature suggests a range of different methods focusing on charge determination as well as nitrogen content quantification. This work aims to fill the knowledge gap regarding how the different methods perform in relation to each other, and for what cellulosic systems each method has advantages, disadvantages and even potential pitfalls. FT-IR and NMR measurements are used to establish successful modification and determine the relative number of substituent groups. Another six methods are compared for the determination of the DS of cellulosic fibres and nanofibrils. The methods include Kjeldahl measurements, nitrogen determination by chemiluminescence, determination of molecular nitrogen by the Dumas method, colloidal titration, conductometric titration and polyelectrolyte adsorption. It can be concluded that most techniques investigated are reliable within certain ranges of DS and/or when using appropriate post-treatment of the quaternized material and suitable sample preparation techniques. The results from the present work hence provide recommendations to make an educated choice of method, and experimental protocol, based on the technique at hand.

Escherichia coli alcohol dehydrogenase YahK is a protein that binds both iron and zinc.

Previous studies have highlighted the catalytic activity of Escherichia coli alcohol dehydrogenase YahK in the presence of coenzyme nicotinamide adenine dinucleotide (NAD) and metal zinc. Notably, competitive interaction between iron and zinc ligands has been shown to influence the catalytic efficiency of several key proteases. This study aims to unravel the intricate mechanisms underlying YahK's catalytic action, with a particular focus on the pivotal roles played by metal ions zinc and iron. The purified YahK protein from E. coli cells cultivated in LB medium was utilized to investigate its metal-binding properties through UV-visible absorption measurements and determination of metal content. Subsequently, the effects of excess zinc and iron on the metal-binding ability and alcohol dehydrogenase activity of the YahK protein were explored using M9 minimal medium. Furthermore, site-directed mutagenesis technology was employed to determine the iron-binding site location within the YahK protein. Polyacrylamide gel electrophoresis was conducted to examine the relationship between iron and zinc with respect to the YahK protein. The study confirmed the presence of iron and zinc in the YahK protein, with the zinc-bound form exhibiting enhanced catalytic activity in alcohol dehydrogenation reactions. Conversely, the presence of iron appears to play a pivotal role in maintaining overall stability of the YahK protein. Furthermore, experimental findings indicate that excessive zinc within M9 minimal medium can competitively bind to iron-binding sites on YahK, thereby augmenting its alcohol dehydrogenase activity. The dynamic binding of YahK to iron and zinc unveils its intricate regulatory mechanism as an alcohol dehydrogenase, thereby highlighting the possible physiological role of YahK in E. coli and its significance in governing cellular metabolic processes. This discovery provides a novel perspective for further investigating the specific impact of metal ion binding on YahK and E. coli cell metabolism.

Determination and safety evaluation of metal element contents of Oviductus Ranae produced from <i>Rana dybowskii</i> by pond culture–forest grazing relay model in Heilongjiang Province, China

The aquatic products of grazing ecological culture exhibit a strong reliance on the production environment system, which may result in heavy metal contamination. In this study, 24 elements (Ag, Al, As, Ba, Cd, Co, Cr, Cs, Cu, Fe, Ga, K, Mg, Mn, Na, Ni, Pb, Rb, Se, Sr, Tl, U, V, Zn) were determined for Oviductus Ranae (OR) from more than 1,000 individuals of Rana dybowskii produced by pond culture–forest grazing relay mode from six major production areas in Heilongjiang Province, China. Furthermore, we assessed the associated health risks. Our findings indicate that most of these 24 metal elements were detected in OR at a detection rate of 100%, with the exceptions being As (98.0%), Ga (98.0%), Co (98.0%), V (94.0%), Cd (89.0%), Pb (76.0%), Cs (74.0%), Tl (35.0%), and U (not detectable). Variations in element concentrations were significant across the six sampling sites, with characteristic elements identified to account for spatial differences. The total target hazard quotient was determined to be 0.152 in Heilongjiang Province, thereby suggesting a relatively low health risk associated with consuming OR from this region’s production systems according to existing standards and guidelines. Nevertheless, special attention is needed for monitoring the habitat environments of R. dybowskii from two sampling locations showing heightened pollution levels.

Determination of leaf nitrogen content in apple and jujube by near-infrared spectroscopy

The nitrogen content of apple leaves and jujube leaves is an important index to judge the growth and development of apple trees and jujube trees to a certain extent. The prediction performance of the two samples was compared between different models for leaf nitrogen content, respectively. The near-infrared absorption spectra of 287 apple leaf samples and 192 jujube leaf samples were collected. After eliminating the outliers by Mahalanobis distance method, the remaining spectral data were processed by six different preprocessing methods. BP neural network (BP), random forest regression (RF), least partial squares (PLS), K-Nearest Neighbor (KNN), and support vector regression (SVR) were compared to establish prediction models of nitrogen content in apple leaves and jujube leaves. The results showed that the determination coefficient (R2), root mean square error (RMSE) and residual prediction deviation (RPD) of the models established by different combined pretreatment methods were compared among the five methods. Compared with the performance of the other four models, the modeling method of SG + SD + CARS + RF was suitable for the prediction of nitrogen content in apple leaves, and its modeling set R2 was 0.85408, RMSE was 0.082188, and RPD was 2.5864. The validation set R2 is 0.75527, RMSE is 0.099028, RPD is 2.1956. The modeling method of FD + CARS + PLS was suitable for the prediction of nitrogen content in jujube leaves. The modeling set R2 was 0.7954, RMSE was 0.14558, and RPD was 2.4264; the validation set R2 is 0.81348, RMSE is 0.089217, and RPD is 2.4552.In the prediction modeling of apple leaf nitrogen content in the characteristic band, the model quality of RF was better than the other four prediction models. The model quality of PLS in predictive modeling of nitrogen content of jujube leaves in characteristic bands is superior to the other four predictive models, These results provide a reference for the use of near-infrared spectroscopy to determine whether apple trees and jujube trees are deficient in nutrients.

Rapid determination of oil content of single peanut seed by near-infrared hyperspectral imaging

Oil content is a crucial indicator for evaluating the quality of peanuts. A rapid and non-destructive method to determine oil content of individual peanut seed can provide robust technical support for breeding high-oil-content peanut varieties. In this study, we established a rapid determination method using near-infrared hyperspectral imaging and chemometrics to assess the oil content of single peanut seed. After selecting key wavelengths through competitive adaptive reweighted sampling (CARS), uninformative variable elimination (UVE), and random frog (RF), we constructed an oil content calibration model based on partial least squares regression for single peanut seed. Validation results demonstrated that the correlation coefficient was 0.8393 with a root mean square error of 1.7771 in the calibration set, while it was 0.7915 with a root mean square error of 2.2943 in the independent prediction set. Most samples exhibited relative errors below 5%, confirming the reliability of this model in predicting oil content of single peanut seed.

Determination of Opium Alkaloid Content in Poppy Seeds Using Liquid Chromatography Coupled with a Mass Spectrometer with a Time-of-Flight Analyzer (UPLC-TOF-HRMS).

Opium poppy is a plant used in both the pharmaceutical and food industries. Substances found on the surface of dry poppy seeds belong to the group of opium alkaloids. However, the presence of these substances in food products poses a risk to consumer health, which is why new permissible levels for both substances in poppy seeds and derivative products have been introduced in Regulation (EU) 2023/915. This research aimed to analyze the content of all six opium alkaloids in poppy seeds provided directly by producers as well as those available on the local market in Poland. The research confirmed the presence of morphine in all examined poppy seed samples. The alkaloid content ranged from 12.46 to 102.86 mg/kg for seeds purchased in local markets and from 1.1 to 110.1 mg/kg for seeds obtained directly from producers. Both groups showed similar levels of morphine content as well as other OAs, which significantly exceeded the permissible limit of 20 mg/kg set by the European Commission (EU) 2023/915. These results indicate that the presence of morphine and other opium alkaloids in poppy seeds exceeds permissible levels, posing a serious health issue and necessitating further research and improvement in processing methods.

Comparison of various test methods to quantify the deterioration degree of archaeological leather

Quantifying the degree of deterioration is crucial for developing prevention strategies for archaeological leather. In this work, the morphology, chemical compositions, and physical properties of artificially aged leather samples were analyzed using a series of test methods to determine non-destructive or micro-destructive technologies for quantifying the degree of deterioration in archaeological leather. Results show that the hydroxyproline (Hyp) content of leather decreases with the increase of deterioration degree because deterioration leads to the gradual destruction of the collagen fiber network of leather. Moreover, the Hyp content of leather can be micro-destructively determined by high-performance liquid chromatography with fluorescence detection. Therefore, the determination of Hyp content is recommended to quantify the degree of deterioration in archaeological leather.

Facile Determination of Aluminum Content in Industrial Brine by Investigating the Effects of Buffer Systems.

The aluminum content of concentrated (27 wt%) sodium chloride solutions could be crucial for large-scale chlor-alkali-based industries applying membrane cell electrolysis. Thus, a facile method which enables a fast and reliable protocol to determine the Al content of these solutions on ppb scale in industrial environments is fundamentally important. It was demonstrated that the increased sensitivity of colorful Al-ECR (eriochrome cyanine R) complex by the use of a cationic surfactant and specific biological buffers could effectively indicate the Al content in an extended pH interval of a concentrated saline medium under industrial conditions. The dependence of the analytical protocol on pH, temperature, time, wavelength, and the salinity of the medium was investigated. It was shown that the absorbance-based measurements of the solution should be performed at least 2-4 h after its preparation. By applying the selected two Good's buffers (HEPES: 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid, MOPS: 3-(N-morpholino)-propanesulfonic acid) and Tris (tris(hydroxymethyl)aminomethane), 32.8-38.1 % increase in the sensitivity was achieved for saturated NaCl solutions. Moreover, the limits of detection and quantification (LOD, LOQ) were also lowered by 19.0-29.8 %, and the salinity dependence of the calibration was also reduced.

Determination of Proximate Content and Phytochemical Analysis of Some Selected Grains, Fruits and Vegetables Commercially Sold in Eke Awka Market, Awka, Anambra State, Nigeria

Six samples from cucumber (Cucumis sativus), apple (Malus domestica), cabbage (Brassica oleracea), Tigernuts (Cyperus esculentus), Beans (Phaseolus vulgaris), Green peas (Pisum sativum) were purchased from Eke Awka market, Awka in Anambra state, and evaluated for their proximate composition and phytochemicals content using the standard procedures as described by Association of Official Analytical Collaboration International, (1995). The study revealed that moisture content of cucumber was significantly high, followed by cabbage, apple and then tiger nuts. The outcome of Phytochemical analysis showed that Alkaloids, Flavonoid Phenol and Oxalate levels were highest in cabbage; Saponin and Tannin were highest in tiger nuts while Steroids and Phytate were highest in cucumber. The fruits and vegetables analyzed contain appreciable amounts of phytochemicals and relatively high food value thus making them valuable nutraceutical sources and very useful for nutritional and medicinal purposes Keywords: Proximate composition, Phytochemical analysis, Grains, Fruits, Vegetables

Prediction of Total Soluble Solids Content Using Tomato Characteristics: Comparison Artificial Neural Network vs. Multiple Linear Regression

Tomatoes are among the world’s most significant vegetables, both in terms of production and consumption. Harvesting takes place in tomato production when the important quality attribute of total soluble solids content reaches its maximum possible level. Tomato total soluble solids content (TSS) is among the most crucial attribute parameters for assessing tomato quality and for tomato commercialization. Determination of total soluble solids content by conventional measurement methods is both destructive and time-consuming. Therefore, the tomato processing industry needs a rapid identification method to measure total soluble solids content (TSS). In this study, we aimed to estimate how much soluble solids there are in beef tomato fruit by Artificial Neural Networks (ANN) and Multiple Linear Regression (MLR) methods. The models were assessed using the Coefficient of Determination (R2), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE) metrics. The training data set results of the MLR model established to estimate the amount of brix in tomato fruit, calculated as MAE: 0.2349, RMSE: 0.3048, R2: 0.8441, and MAPE: 5.5368, while, according to the ANN model, MAE: 0.0250, RMSE: 0.031, R2: 0.9982 and MAPE: 0.5814. According to the metric outcomes, the ANN-based model performed better in both the training and testing parts.

Studies on Quantitative Determination of Polyphenols in Seven Harvesting Times of Salvia deserta Schang Leaves and its Stability Evaluation

Introduction: Leaves of Salvia deserta Schang at seven harvesting times in the same year were collected as the materials. Method: The polyphenols were determined by the Folin–Ciocaileu method and High-Performance Liquid Chromatography (HPLC) to compare the quality of samples. The stability of polyphenols was studied under different conditions (light, temperature, pH, common additives). Results: The results showed that the established method is fast, simple and reliable, which is fully validated in terms of outstanding validation data. High Performance Liquid Chromatography (HPLC) for the determination of total polyphenol content can be quickly and accurately detected, reducing the error of manual determination of the content. The study of polyphenol stability was carried out using a UV spectrophotometer (UV) in order to explore the potential factors affecting polyphenol stability as much as possible and to make the study as scientific and rigorous as possible. The results of quantitative determination showed that there are obvious differences in the content of polyphenols in seven samples. The contents of total polyphenols, rosmarinic acid (RA) and caffeic acid (CA) in the samples harvested in July reached the highest level of 41.37, 26.73 and 1.05 mg/g. Conclusion: The results of the stability assay found that light could damage the stability of polyphenols in samples, especially UV light. Polyphenols are quite sensitive to high temperatures. While polyphenols are less stable when exposed to high alkali conditions and salt treatment, they are much more stable when subjected to low concentrations of redox agents, carbohydrates, and preservatives. The developed methods and stability evaluation provide valuable basis information for quality evaluation and the following use of polyphenols in S. deserta Schang leaves.

Heat-dependent properties of methane diffusion in coal: an experimental study and mechanistic analysis.

Coalbed methane thermodynamic extraction, as an emerging ECBM recovery method, can effectively improve gas recovery rates. And clarifying methane diffusion and migration law in coal under thermal stimulation is crucial for the selection of its process parameters. Based on laboratory methane adsorption-release experiments, the evolution law of methane diffusion characteristics with temperature and pressure was studied, and the control mechanism of heat-dependent methane diffusion behavior was explored. The results show that both thermal stimulation and high adsorption pressure accelerated the methane diffusion rate in coal. Adsorption pressure had little effect on methane diffusion percentage, but thermal stimulation promoted a significant increase in diffusion percentage and improved the net methane yield. The influence mechanisms of adsorption pressure and thermal stimulation on methane diffusion characteristics are elucidated in relation to the amount and proportion of methane-activated molecules in the diffusion process. The constant diffusion coefficient of methane is heat-dependent, based on which a diffusion model is derived to accurately predict the methane release process in coal. Additionally, temperature has a more important effect on transient diffusion coefficient than pressure. Thermal stimulation leads to a net increase rather than a decrease in diffusion coefficient in the early diffusion stages and can also accelerate the attenuation of diffusion coefficient, with this intensifying effect becoming more pronounced at higher temperatures. The research results can provide some reference for the determination of coal seam gas content and the selection of heat injection process parameters.