Identification Index Research Articles

Uniseriate ray characteristics for wood identification and quality indices of six Korean oak species

Uniseriate ray characteristics for wood identification and quality indices of six Korean oak species

Leafiness-LiDAR index and NDVI for identification of temporal patterns in super-intensive almond orchards as response to different management strategies

The use of super-intensive orchards is a growing trend in fruit production. The present study aims to improve management of these cropping systems by focusing on how agronomic decisions impact orchard dynamics in the short to medium term and by providing a decision-support approach based on stable temporal patterns from previous seasons. A multitemporal study using remote sensing and LiDAR was conducted in a commercial almond orchard over four growing seasons (2019–2022) to determine the optimal timing of image acquisition for variable pre-harvest treatments. A model-based clustering (mclust) was applied to optimal Sentinel-2 NDVI maps and apparent soil electrical conductivity (ECa) data, interpolated to the pixel centroids of Sentinel-2 image grids, to delineate potential management zones (PMZs). The leafiness-LiDAR index (LLI), a leaf area index (LAI) estimator, was obtained as ground truth after summer pruning and before harvesting, showing a significant influence of fertigation and pruning on the LAI, with summer pruning particularly influencing orchard dynamics. The optimal time for NDVI mapping was found to be two months after summer pruning in productive years and two weeks after in unproductive years. The delineated PMZs were consistent across seasons and corresponded to significant LAI differences. This method could contribute to improving resource management and sustainability in super-intensive commercial orchards.

Evaluation of Grain Moisture Content at Maturity and Screening for Identification Indexes of Maize Inbred Lines

The grain moisture content of maize inbred lines at maturity is one of the most important indicators for mechanical harvesting of kernels. In this study, 116 maize inbred lines from a wide range of sources were used as research materials and 30 traits of grain moisture content were analyzed using multivariate statistical analysis. The results showed that all 30 traits had some correlations. Principal component analysis downscaled the 30 traits into 10 principal component factors, reflecting 77.674% of the information in the original traits. Cluster analysis categorized the 116 inbred lines into 5 major groups containing 26, 29, 31, 16 and 14 inbred lines. Based on the D value of the overall evaluation, discriminant analysis reclassified the maize inbred lines by principal component scores and 98 maize inbred lines were correctly discriminated with a probability of 84.48%, which can be regarded as a relatively reliable clustering result. The stepwise regression method was further used to screen seven traits: GMC2, GDR1, HMC3, NH, GDR2, CD and EL and to establish a comprehensive evaluation model for the grain moisture content of maize inbred lines. Among 116 maize inbred lines, 14, represented by H21 and MS71, had the lowest grain moisture content at maturity.

Evolution Trend of Water Quality in the Inner Mongolia Section of the Yellow River from 2003 to 2020

The aim of this study was to comprehensively understand the water environment quality status and its change trend in the Inner Mongolia section of the Yellow River Basin. To analyze the water quality in recent years,the water quality data in the Yellow River basin from 2003 to 2020 were firstly collected from five typical monitoring stations．Various data analysis methods, including principal component analysis, cluster analysis, and a long short-term memory model, were used along with an improved comprehensive water quality identification index to explore the spatiotemporal characteristics of water quality in the Yellow River Basin. The results showed that the overall water quality in the basin has improved and stabilized over time. In terms of temporal variation, there was a distinction between the wet season and dry season, with a better status observed during the wet season due to increased agricultural irrigation and higher water volume. Spatially, the five monitoring sections could be divided into three categories based on strong natural factors that maintained their temporal characteristics during the wet season； however, significant differences were observed during the dry season due to urban water usage patterns. Analysis using LSTM models revealed that ammonia nitrogen will continue to decline and have a decreasing impact on the comprehensive water quality. These findings provide valuable insights for the comprehensive management of water quality in Inner Mongolia's Yellow River Basin.

Regional traffic congestion coordination control based on critical links

Critical links have the characteristics of carrying large traffic flow and quickly affecting the operational performance of the road network. Existing regional traffic congestion coordination control methods do not consider the impact of critical links. To solve this issue, this paper proposes a regional traffic congestion coordination control method based on critical links. First, the median, gravitational index, and traffic sharing ratio are selected as the identification indexes of critical links in urban networks. Second, the road network vulnerability is assessed, and road link criticality is calculated based on joint entropy theory and multi-scale factor synthesis of multi-metric identification results. Then, the regional signal control range is determined, and a multi-stage signal control optimization model is developed. Finally, the optimal traffic signals for intersections are obtained by minimizing the pressure at the maximum phase of the road link and maximizing the capacity of critical links. To demonstrate the effectiveness of the proposed methods, two benchmarks (i.e., the MAXBAND method and existing traffic signals) are compared. The results show that (1) in terms of boundary control, the average vehicle delay at the boundary intersection of the road network is 34.62 s, an increase of 7.49 s and 5.03 s compared to the benchmark methods, respectively. (2) In terms of internal control, the average delay of the road network based on the proposed method is 87.54 s, which is reduced by 16.38 % and 28.73 % compared with the benchmark methods, and the queue lengths of the critical links are reduced by 21.47 % and 34.15 %, respectively. (3) The control process of the proposed method enables the number of vehicles within the road network to be maintained near the optimal carrying capacity, which gives the road network an efficient operating efficiency.

Spatiotemporal characteristics and potential pollution factors of water quality in the eastern route of the South-to-North Water Diversion Project in China

The eastern route of the South-to-North Water Diversion Project (SNWDP-ER) in China, an open-channel cross-basin project, is exposed to multiple potential pollution sources and has changing hydrodynamic conditions between diversion and non-diversion periods. After a decade of pollution control efforts, it is imperative to perceive the water quality conditions and identify potential pollution factors for further maintenance. Combining the water quality identification index (WQII) and multivariate statistical techniques (MSTs), this study conducted an exploratory analysis in SNWDP-ER, based on the monitoring data in 2020–2021. The monitoring and WQII results show that the overall water quality in SNWDP-ER is satisfactory and meets the Class III requirements in China Environmental Quality Standard for Surface Water, except for total nitrogen (TN) which falls into Class V or even worse. The periodic alternations of flow direction between diversion and non-diversion periods tend to deteriorate water quality, particularly in the initial stage of alternations. Water quality appears more stable during the diversion period, and impounding lakes along the project are crucial to water environment restoration in this period. Due to the positive influence brought by the self-purification and environmental carrying in the Luoma Lake, Nansi Lake, and Dongping Lake, water quality exhibits an enhancing trend from upstream to downstream in the Lianghu and Jiaodong reaches. Besides, the monitoring stations in Shandong reach exhibit significant divisional heterogeneity under hierarchical cluster analysis (HCA) with the Nansi Lake and Dongping Lake as the demarcation points, and the results of factor analysis/principal component analysis (FA/PCA) further identified the contributions of mining, shipping, and land use to each section. Based on the findings, the study recommends implementing wastewater discharge control, abandoned mines remediation, and continued water quality monitoring for further maintenance and improvement in SNWDP-ER.

Evaluating the clinical utility of small airway function assessment for early diagnosis of GOLD stage 0 chronic obstructive pulmonary disease

Objective To investigate the clinical utility of small airway function indices for early identification of GOLD stage 0 chronic obstructive pulmonary disease (COPD). Methods This retrospective study enrolled 137 participants at our institution between January 2017 and December 2018, comprising 40 healthy controls, 46 individuals with GOLD stage 0 COPD, and 51 patients with established COPD. Pulmonary function was assessed using the PowerCube spirometry system (GANSHORN, Germany). Parameters evaluated included forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1), FEV1/FVC ratio, and small airway function indicators. Results The COPD cohort exhibited significantly lower values across all lung function measures compared to the other two groups, particularly for dynamic lung volume parameters such as FEV1%predicted and FEV1/FVC%. Small airway function indices, including FEV3%predicted, FEF75%predicted, FEF50%predicted, FEF25%predicted, and MMEF%predicted, were markedly decreased in the COPD group (all p-values <0.001). Receiver operating characteristic (ROC) curve analysis demonstrated that MMEF/FVC% and FEV3/FVC% had high diagnostic accuracy for COPD, with MMEF/FVC% exhibiting the optimal sensitivity and specificity. Conclusion Small airway function indices, especially MMEF/FVC%, can serve as effective tools for early identification of GOLD stage 0 COPD. Incorporation of these findings into clinical practice may facilitate early diagnosis and intervention, thereby improving treatment outcomes and patient quality of life.

Tolerance indices based evaluation of wheat (Triticum aestivum) genotypes under terminal heat stress conditions

Present study was carried out during winter (rabi) seasons of 2021–22 and 2022–23 at Crop Research Centre, Sardar Vallabhbhai Patel University of Agriculture and Technology, Meerut, Uttar Pradesh to evaluate the terminal heat tolerance ability of 30 wheat (Triticum aestivum L.) genotypes using 8 heat stress tolerance indices. The results indicate that 12 genotypes showed low yield reduction as compared to average yield reduction. The stress susceptibility index (SSI) was observed as robust indicator for identifying heat-tolerant genotypes. Stress tolerance index (TOL) was observed crucial which reflects genotype's ability to maintain grain yield under terminal heat stress. Analysis of correlation revealed positive relationships between grain yield under normal and stress conditions, suggesting that best-performing genotypes under normal conditions also perform well under terminal heat stress conditions. Principal component analysis and biplot analysis further confirmed the importance of studied tolerance indices for identification of heat tolerance genotypes. PC1 was associated with yield potential and heat tolerance, while PC2 was associated with stress susceptibility. Based on analysis, genotypes, viz. DBW14, DBW90, HD2864, HD2932, HD2985, HS375, HUW234, RAJ4083, WH1021, WH1124, DBW71 and PBW757 exhibited higher terminal heat stress tolerance. Cluster analysis revealed two major clusters, cluster I contained 12 heat tolerant genotype while cluster II was consisting 18 heat susceptible genotypes. The SSI and TOL index were found promising indices for identification of heat tolerant genotypes of wheat.

Multi-trait stability index for identification of stable green gram (Vigna radiata (L.) Wilczek) genotypes with MYMV resistance

Multi-environment trials (MET) are crucial for selecting genotypes that are well-suited to different environmental conditions. Incorporating multiple traits in the analysis can provide more reliable recommendations for selecting genotypes with desirable traits, including resistance to the Mungbean Yellow Mosaic Virus (MYMV) and high yield potential. The use of a Multi-Trait Stability Index (MTSI) is a good approach for analyzing the stability of genotypes across multiple traits under MYMV stress. In the present investigation, the performance of thirteen green gram genotypes were evaluated for traits such as yield, plant height, number of branches per plant, and resistance to MYMV. The main objective of the study is to identify highly productive and stable mung bean genotypes resistant to MYMV. MTSI can be calculated by combining information on the performance of genotypes across multiple traits and environmental conditions to provide a single index that indicates the overall stability of genotypes across traits and environments. The results helped to identify two green gram genotypes (Yadadri and JNG-18) that were high-yielding with stable resistance to MYMV stress across multiple environmental conditions. This can provide useful information to breeders for the development of suitable genotypes against MYMV in the affected areas.

Bottleneck identification and transfer prediction for automated production lines based on FNN

Abstract In a re-entrant production system, the throughput of the whole system depends on the capacity of the bottleneck machine. In this study, a new definition of bottleneck is proposed for a precision forging blade shop. The reinforcement learning algorithm is used to optimize the production scheduling to determine the most suitable scheduling scheme, which lays the foundation for bottleneck identification. Subsequently, the bottleneck identification index system was established according to the optimization objective, and the bottleneck identification problem was transformed into a multi-attribute decision-making problem. Finally, a fuzzy neural network is used for training, and the basic scheduling examples of each flow shop are utilized for bottleneck identification and prediction to verify their effectiveness.

The composite drought index incorporated solar-induced chlorophyll fluorescence enhances the monitoring capability of short-term drought

Understanding the response of vegetation to drought is significant for socio-economic development and biodiversity conservation. However, due to the complexity of drought, relying only on one approach, such as the surrounding physical environmental conditions or specific vegetation characteristics, does not yield precise results. To address this challenge, composite drought indices incorporating Normalized Difference Vegetation Index (NDVI) and other multiple variables, have been developed and shown promising effectiveness in drought detection. Compared to NDVI, solar-induced chlorophyll fluorescence (SIF) decreases due to the increased non-photochemical quenching and reduced photosynthesis during short-term drought stress. This indicates a direct association between SIF and vegetation photosynthesis, offering advantages over NDVI in capturing drought effects. Nevertheless, SIF has not yet been fully integrated into composite drought indices. Therefore, this study focused on assessing the advantages of SIF for short-term drought monitoring by constructing a new composite drought index (CPDI) using the Principal Component Analysis (PCA) method. Subsequently, CPDI was employed to forecast future drought conditions. Overall, CPDI performs exceptionally well as a composite drought index in drought trend analysis and drought event identification, indeed advancing the monitoring capability for short-term drought. Furthermore, the incorporation of SIF in CPDI, obtained from various data sources provides more timely monitoring of drought events, while the CPDI with NDVI reflects the cumulative effect of drought conditions over a longer period. In the future, it is potential to utilize the benefits of SIF in constructing drought indices or combine it with NDVI for comprehensive drought characterization.

Theoretical and Experimental Investigations of Identifying Bridge Damage Using Instantaneous Amplitude Squared Extracted from Vibration Responses of a Two-Axle Passing Vehicle

Identifying bridge damage using a movable test vehicle is highly regarded for its mobility, cost-effectiveness, and broad monitoring coverage. Previous studies have shown that the residual contact-point (CP) response between connected vehicles is free of the impact of vehicle self-vibrations and road roughness, making it particularly suitable for the indirect extraction of bridge modal properties. However, most experimental campaigns regarding contact-point (CP) responses focus on a single-axle testing vehicle within a non-moving state. This study aims to theoretically and experimentally identify bridge damage using the instantaneous amplitude squared (IAS) extracted from the residual CP response of a two-axle passing vehicle. First, the closed-form solution of the residual CP acceleration was derived for a two-axle vehicle interacting with a simply supported beam. The IAS index was constructed from the driving frequency of the residual CP acceleration. Then, numerical investigations using finite element simulation were conducted to validate using the IAS index for indirect bridge damage identification. The application scope of the approach under various vehicle speeds and road roughness grades was examined. Finally, a laboratory vehicle–bridge interaction system was tested to validate the approach. Numerical studies demonstrated that bridge damage could be directly determined by observing the IAS abnormalities, which were baseline-free. The IAS from the residual CP response outperformed the IAS from CP responses in identifying bridge damage. However, it was better to use the IAS when the vehicle speed was no greater than 2 m/s and the grade of the road surface roughness was not high. Laboratory tests showed that it was possible to identify bridge damage using the IAS extracted from the residual CP acceleration under perfect road surfaces. However, it fell short under rough road surfaces. Hence, further experiments are required to fully examine the capacity of the IAS for bridge damage identification in practical applications.

Mapping long-term Transformation of Wetlands and Annual Rainfall Variability in Madhubani District (1975-2022).

In addition to supporting a rich biodiversity, wetlands serve as ecosystems that connect aquatic and terrestrial settings. They also play a critical ecological role by providing essential supplies. According to the National Wetland Atlas (2010), Bihar has a total of 21,988 wetlands with a total area of 4,03,209 hectares. These wetlands exhibit great range of floral and faunal diversity with large number of endemic species. The present paper endeavors to map the natural wetlands of Madhubani district of North Bihar and assess their evolving hydro-physiographic characteristics. The study area is endowed with numerous small wetlands as it receives high average annual rainfall in Bihar. This study primarily emphasizes on identification of wetlands and their spatial-temporal assessment during the period 1975-2022 by utilizing datasets from various sources like topographical maps, satellite imageries, and other ancillary data. It uses geospatial tool like Arc Hydro and indices like Topographic Wetness Index (TWI) and Normalized Difference Wetness Index (NDWI) for identification and spatial-temporal assessment of wetlands during pre-monsoon and post-monsoon season. The study finds that despite being one of the rainiest districts of Bihar, the annual rainfall trends in Madhubani is decreasing. This has impacted upon the water quality, productivity, biodiversity and annual recharge of wetlands of Madhubani. Its entire geographic region has thus been significantly reduced as a result. Other important factors like accelerated anthropogenic intervention, land use changes and process of urbanization have contributed towards rapid transformation of floodplains of Madhubani District. These changes may affect future water potential of the region and thus threaten sustainability in the region.

Identification Leaves of Ulmus pumila L., Tilia cordata Mill. and Acer campestre L. Using Vegetation Indices

The aim of the research was to identify a group of vegetation indices (VIs) for species identification. The objects of research were leaves of Ulmus pumila L., Tilia cordata Mill. and Acer campestre L. Hyperspectral imaging (HSI) was carried out under artificial lighting in laboratory conditions using a Cubert UHD-185 hyperspectral camera. A technique was developed for the automated selection of pure spectral profiles from hyperspectral images by setting a double barrier specified by intervals of PSSR and NDVI VIs. A total of 80 VIs was calculated. A statistical analysis of the data was carried out for their representativeness. To determine VIs, the value of which is most dependent on the species characteristics of trees, analysis of variance (ANOVA) and principal component analysis (PCA) methods were used. Research has shown that the PCA method is effective and sufficient to identify the group of VIs characterized by the greatest dispersion in relation to tree species. The PCA carried out for pairs of tree species made it possible to identify a group of vegetation indices, the value of which to the greatest extent depends on species characteristics. These are Carter2, CI2, CRI4, GMI2, mSR2, NDVI2, OSAVI2, SR1, Carter4, Datt2, SR6, Datt, DD, Maccioni, MTC.

Comparative study of dynamic parameters for damage identification of carbon fiber reinforced polymer tube

AbstractThe primary objective of the paper is the numerical and experimental investigation related to the damage recognition effects for CFRP tubes of four dynamic parameters. Four damage identification indexes consisting of natural frequency‐based index, Mode Shape‐based index (MS), Mode Shape Curvature‐based index (MSC), and Modal Flexibility Curvature‐based index (MFC) are established by analyzing the dynamic parameter data obtained before and after damage occurs. The performances of dynamic parameters are thoroughly discussed in the context of numerical simulations and experiment. The results indicate that the effect of natural frequency is not as significant as that of mode shape. MFC has the most notable effectiveness out of the four indexes. The simulation peak index pair is predicted to rise from 0.3 to 0.6 as the damage in the simulation model increases by 25% from 12.5%, indicating that MFC can feedback the damage degree. Moreover, the circumferential curvature index exhibits superior performance compared to the axial curvature index. To enhance the accuracy of the axial curvature index, it is proposed to increase the number of measuring sites along the tube's long direction.Highlights Damage identification indexes of four dynamic parameters are established. Discuss the identification ability of dynamic parameters by simulation and test. Two numerical models of CFRP tube with delamination damage are established. Impact and modal tests are executed to study the ability of four indexes.

Augmented reality presentation system of skeleton image based on biomedical features

Aimed at limitations in the description and expression of three-dimensional (3D) physical information in two-dimentsional (2D) medical images, feature extraction and matching method based on the biomedical characteristics of skeletons is employed in this paper to map the 2D images of skeletons into a 3D digital model. Augmented reality technique is used to realize the interactive presentation of skeleton models. Main contents of this paper include: Firstly, a three-step reconstruction method is used to process the bone CT image data to obtain its three-dimensional surface model, and the corresponding 2D–3D bone library is established based on the identification index of the 2D image and the 3D model; then, a fast and accurate feature extraction and matching algorithm is developed to realize the recognition, extraction, and matching of 2D skeletal features, and determine the corresponding 3D skeleton model according to the matching result. Finally, based on the augmented reality technique, an interactive immersive presentation system is designed to achieve visual effects of the virtual human bone model superimposed and rendered in the world scenes, which improves the effectiveness of information expression and transmission, as well as the user's immersion and embodied experience.

An Observational Multi-Center Study Protocol for Distribution of Pattern Identification and Clinical Index in Parkinson’s Disease

Objectives: This study investigated the pattern identification (PI) and clinical index of Parkinson’s disease (PD) for personalized diagnosis and treatment.Methods: This prospective observational multi-center study recruited 100 patients diagnosed with PD from two Korean medicine hospitals. To cluster new subtypes of PD, items on a PI questionnaire (heat and cold, deficiency and excess, visceral PI) were evaluated along with pulse and tongue analysis. Gait analysis was performed and blood and feces molecular signature changes were assessed to explore biomarkers for new subtypes. In addition, unified PD rating scale II and III scores and the European quality of life 5-dimension questionnaire were assessed.Results: The clinical index obtained in this study analyzed the frequency statistics and hierarchical clustering analysis to classify new subtypes based on PI. Moreover, the biomarkers and current status of herbal medicine treatment were analyzed using the new subtypes. The results provide comprehensive data to investigate new subtypes and subtype-based biomarkers for the personalized diagnosis and treatment of PD patients. Ethical approval was obtained from the medical ethics committees of the two Korean medicine hospitals. All amendments to the research protocol were submitted and approved.Conclusions: An objective and standardized diagnostic tool is needed for the personalized treatment of PD by traditional Korean medicine. Therefore, we developed a clinical index as the basis for the PI clinical evaluation of PD.

Biodiversity of Costus speciosus Phylloplane Fungi in Baturaden Botanical Gardens and Antagonist Testing against Fusarium oxysporum

Indonesia has an abundant biodiversity of natural resources, one of which is phylloplane fungi. This abundant phylloplane mold needs further investigation to utilize its potential as an antagonistic agent. This study aims to prove the existence and to determine the types of phylloplane fungi species found on the leaf surface of pacing tawar (sweet ginger or crepe-ginger) plants, to analyze and determine the level of diversity and dominance of phylloplane, and to determine the types of phylloplane fungi species that have the antagonistic ability of the phytopathogenic mold Fusarium oxysporum. This research method includes isolating crepe-ginger phylloplane fungi using a contact plate, isolates purification, macromorphological and micromorphological identification, diversity and dominance index calculation, and antagonist test using a dual culture method. This study used a descriptive analysis research design. The isolation results obtained 57 species of crepe-ginger plants leaf phylloplane molds consisting of eight genera (Alternaria, Aspergillus, Cladosporium, Curvularia, Fusarium, Mucor, Penicillium, and Trichoderma). The results of the diversity index calculation with a value of 2.02 showed that the diversity of phylloplane fungi was moderate. The result of the dominance index calculation, with a value of 0.1521, shows no tendency for phylloplane fungi species to dominate. The results of the antagonist test showed that 15 isolates could antagonize the F. oxysporum with an inhibitory proportion of up to 82% obtained from T. viride isolates with code FD5B3.2

Microplastic contamination in the Chanthaburi estuarine ecosystem, Eastern part of Thailand

Aim: The prevalence of plastic particles has become a global crisis for the environment pollution and human life. This study aimed to investigate the contamination of microplastics (MPs) in marine environments and to determine the relationships between MPs pollution and types of land use. Methodology: Two invertebrate species (Anadara granosa and Litopenaeus vannamei) and sediment samples were collected for the analysis of MPs accumulation in the Chanthaburi estuarine ecosystem. The microplastics contamination and pollution were determined with visual identification and environmental index, respectively. The abundance and the land use type of MPs in Chanthaburi Province were compared by a Geographic Information System (GIS). Results: The MPs contamination in the white shrimps were higher than the cockles. The black filamentous type of MPs was a major characteristic which ranged between 0.43–0.85 mm, 0.45–0.65 mm and 1.25 – 3.05 mm in A. granosa, L. vannamei and sediment, respectively. The MPs pollution index (PLI and BCF) showed low levels in the hazardous category. The Chanthaburi land use analysis showed variation in the land use change and a strong correlation between green areas and the MPs contamination. Interpretation: The statistical analysis suggested differences between MPs abundance in our samples.The utilization of agriculture and forest land use types could relieve the impact of MPs accumulation.This study also demonstrated the need for managing MPs pollution in Thai marine ecosystems. Key words: Anadara granosa, Chanthaburi, Estuarine ecosystem, Litopenaeus vannamei, Microplastics

Identification of plugging types and their formation mechanism based on production curves of coalbed methane wells

Taking the production curves of coalbed methane (CBM) wells in Shizhuang south block in south-central Qinshui Basin (Shanxi Province, China) as a research subject, evaluation indices for the identification of plugging types of pulverized coal were constructed according to changes in daily water production and daily gas production. Four plugging types were classified based on the identification indices’ critical values. The results show when the proportion of soft coal in coal seam segments is not greater than 30%, mid-remote wave-shaped plugging is likely to occur. If the proportion of soft coal in coal seam segments is in the range of 30–50% and the daily water production or daily gas production is large, near-wellbore wave-shaped plugging occurs readily. Under the same proportion of soft coal, mid-remote complete plugging is liable to develop if the daily rates of water and gas production are low. Once soft coal accounts for a proportion equal to and greater than 50% in coal seam segments, near-wellbore regions are likely to be completely plugged. The research provides a method and reference for identifying the types of CBM well de-plugging and formulating de-plugging measures.