This article provides a detailed analysis and summary of the comparison between FZ/T 73078—2024 "Artificial leather-style knitted leggings" and FZ/T 73029—2019 "Knitted leggings". The similarities and differences between the two standards and their reasons are explained, and corresponding suggestions are proposed for the precautions to be taken in the implementation and labeling process of the standards.

This article is based on the two standards, GB/T 14272—2021 and FZ/T 73053—2025, and conducts a comparative analysis of the technical indicators differences between woven and knitted down jacket clothing. Combined with the recent national and local supervision and inspection data, it reveals the existing quality problems and their causes in the industry. The two standards have significant differences in color fastness, seam performance, feathering and pilling, residual metal needles, post-washing appearance and specification size assessment, etc. Essentially, this reflects the different adaptability of the characteristics of woven and knitted fabrics to quality requirements. Through comparative analysis, this article aims to address the confusion faced by enterprises, testing institutions and consumers regarding the selection of standards and the determination of quality, and to clarify the types of products applicable to different standards as well as the key points of assessment. The woven down jacket standard focuses on evaluating seam splits, needle spacing density and color fastness; while the knitted down jacket standard mainly assesses seam strength, feather shedding and balling, evaluates the post-washing appearance using a gentle washing procedure, has more flexible sizing settings, and adds safety indicators such as fluorescent color definition and residual metal needles. Both standards maintain consistency in down quality requirements. Relevant parties should correctly select standards based on the actual fabric type of the product and pay attention to the difference items to promote the improvement of industry quality.

To better implement the FZ/T 73053—2025 standard for "Knitted down garments", this article comprehensively analyzes the core differences between the old and new standards from dimensions such as scope of application, normative referenced documents, and technical requirements, while proposing strategies and recommendations based on industrial production and market demand.

This paper provides a systematic interpretation of GB/T 17685—2026 "Down and feather" from four aspects: changes in main technical requirements, technical index comparison, key points of testing and inspection, and quality control measures, and conducts a comprehensive comparison with the previous standard. The GB/T 17685—2026 standard classifies down and feather according to life cycle and processing degree, specifying quality indicators for different product categories. It helps promote green and low-carbon transformation in the down industry, improve the circular utilization system, and impose higher requirements on testing and inspection. Enterprises need to further strengthen classified quality management of down.

The new national standard GB 18383—2025 "General technical requirements for products with filling materials" was issued on December 2, 2025, and will officially take effect on July 1, 2026. This article analyzes and compares the new and old standards for thermal lining fiber products, providing technical references for manufacturers, testing institutions, and consumers.

By conducting a statistical analysis of the implementation of the GB 31701—2015 "Safety technical code for infants and children textile products" standard, we aim to understand the implementation status of the standard in the field of infant and children’s clothing products in China. We summarize and analyze the five aspects of standard implementation: enforceability, applicability, coordination, implementation constraints, and implementation effectiveness. Through this analysis, we identify issues that arise during the implementation of the standard and propose countermeasures and suggestions.

With the expanding application of glass fiber cloth in industrial filtration, composite materials and other fields, differential-pressure air permeability testers serve as critical metrological instruments for evaluating the air permeability of materials. The accuracy and reliability of their measurements directly affect product quality assessment. Currently, the industry lacks targeted and systematic technical standards for calibration, leading to inconsistent calibration procedures and potential measurement deviations. Therefore, it is urgent to develop scientific and standardized calibration methods. This study strictly complies with national fundamental metrological specifications including JJF 1001—2011 and JJF 1071—2010, taking the calibration requirements specified in JJF (Textile) 037—2023 "calibration specification for fabric air permeability testers" as core references, it integrates the test principle of air permeability described in GB/T 5453—1997 "textiles-determination of the permeability of fabrics to air" and conducts technical research for JJF (Lu) 208—2025 supported by substantial experimental data. Following the principles of scientific rationality, practicality and easy popularization, this paper defines the calibration items, environmental conditions and detailed operating procedures for differential-pressure glass fiber cloth air permeability testers, and establishes a complete set of calibration specifications. The research outcomes can provide standardized and implementable calibration references for metrological institutions at all levels, manufacturers and end-users, standardize instrument calibration procedures, ensure consistent measurement values and credible test results for glass fiber cloth air permeability, and offer technical support for industrial quality control and metrological traceability.

In order to standardize the work process of notarized inspection of fresh mulberry silkworm cocoons and strengthen whole-process management, the China Fiber Quality Monitoring Center issued the "Technical specification for official classification of fresh mulberry silkworm cocoons (trial)" in 2026. This specification is the first operational technical document specifically targeting the notarized inspection of fresh mulberry silkworm cocoons, supporting the revised national standard GB/T 15268—2024 "mulberry silkworm fresh cocoons". Starting from the background and significance of the specification, this paper systematically reviews its technical requirements in core links such as lot definition, on-site inspection, weighing and sampling, laboratory testing, data and sample management. Combined with relevant regulations and standards, it provides an in-depth analysis of key points, difficulties, and error-prone aspects in implementation, aiming to serve as a reference for accredited inspection agencies to accurately understand and strictly implement the technical specification.

This paper collates, compares and analyzes the index data of national notarial inspection items for cashmere (dehaired cashmere, raw cashmere) and wool under notarial inspection in the Inner Mongolia Autonomous Region in 2025. Through listing, comparing and analyzing the inspection index data, the general situation of the quantity and quality of cashmere and wool in Inner Mongolia Autonomous Region in that year can be clearly understood.

Based on test data from the MC101 raw cotton impurity rapid analyzer, this paper systematically analyzes the correlation and variation patterns between the weight of impurities after the first combing (M1) and the weight of impurities after the second combing (M2). Through statistical analysis of 90 samples across low (<1.0%), medium (1.5%~2.5%), and high (>2.5%) three impurity rate levels, it was found that the relationship between M1 and M2 exhibits a distinct interval-dependence characteristic. Specifically, the low and high impurity rate groups showed a highly significant positive correlation, while the medium impurity rate group demonstrated a highly significant negative correlation. These findings deepen the understanding of the mechanical combing process for raw cotton impurity removal. They also provide a data reference for monitoring the reasonableness of individual impurity rate test results and evaluating equipment operational stability using the relationship between M1 and M2.

As a major country in cotton production and consumption, the cotton industry plays a crucial role in the national economy. Cotton quality directly determines the industrial competitiveness, and impurities are the primary restrictive factor. Cotton impurities include various non-cotton fiber substances such as sand, insect corpses, and sterile seeds. They not only reduce cotton grades and market prices, affect color, hand feel, and spinnability, but also cause equipment wear, yarn defects, and other problems in all links of textile processing. The generation of impurities is affected by multiple factors including nature, planting, harvesting, and processing. Climate conditions, soil fertility, and plant diseases/insect pests increase impurities at the source. Improper use of defoliants, non-standard operations in manual and mechanical harvesting, and backward ginning technology further raise the impurity content. Therefore, it is necessary to reduce impurities through measures such as selecting high-quality varieties, optimizing field management, standardizing harvesting operations, and improving processing technology. In the future, intelligent detection technology, breeding of new impurity-resistant varieties, and green impurity removal methods will become research priorities, contributing to the high-quality and sustainable development of the cotton industry.

Textile testing is a critical link in product quality control. With the growth of testing demand and intensifying market competition, laboratory operation efficiency has become an important factor affecting core competitiveness. From a management perspective, this paper analyzes the existing management problems in the current testing process, such as low sample circulation efficiency, unbalanced task allocation, and scattered quality control nodes, and proposes management strategies including process reengineering, optimization of personnel performance appraisal, and improvement of the quality management system. By establishing standardized operating procedures, implementing refined personnel management, and constructing a whole-process quality control mechanism, the testing cycle has been effectively shortened and the testing quality has been steadily improved. Practice shows that the optimized management model has shortened the average sample testing cycle by 32%, increased personnel work efficiency by 28%, and customer satisfaction rate reaches 96%.

To investigate the influencing factors of testing the anti-mosquito performance of textiles via the repellent tester method, this study conducted experiments in accordance with GB/T 30126—2013, using Aedes albopictus as the test mosquitoes, standard cotton adjacent fabrics as the control samples, and 50 anti-mosquito finished textile samples as the test specimens. It analyzed the influence rules of the hole positions of the repellent tester, the characteristics of volunteers and the color of textiles on the test results. The results showed that the hole positions of the repellent tester were an extremely significant influencing factor, with the 4th hole having the highest number of mosquito stays, and the combination of hole positions directly determining the repellency rate results; individual physiological differences among volunteers were the main factor leading to poor repeatability of test results, while the differences between the left and right hands and gender characteristics were secondary interfering factors; the color value of textiles had a significant impact—low value fabrics were prone to attracting mosquitoes, with most of their anti-mosquito grades below Grade C, whereas high value fabrics were more likely to show high-grade anti-mosquito effects in tests. This study clarified the interference mechanisms and influence degrees of various factors, proposed control measures for standardized testing, and provided a scientific basis for improving the anti-mosquito testing standards for textiles and guiding the R&D and production of anti-mosquito textiles.

A method for determining acetaldehyde content in leather by liquid chromatography-tandem mass spectrometry (LC-MS/MS) with ultrasonic extraction was established. After ultrasonic extraction, the sample were derivatized using 2,4-dinitrophenylhydrazine (DNPH) as the derivatization reagent. The resulting solution was analyzed by LC-MS/MS to determine the retention time for quantitative analysis and external standard method for qualitative analysis. The experimental results show that the ultrasonic extraction conditions are as follows: 2.0% phosphoric acid solution as extraction reagent, the extraction temperature is 50 ℃, the extraction time is 30 min, the extraction volume is 10.0 mL, 2,4-dinitrophenylhydrazine (DNPH) solution as the derivatization reagent, the derivatization temperature is 40 ℃, the derivatization time is 30 min. The method detection limit (LOD) is 3.0 μg/kg. The linear correlation coefficient R2 of the method within the mass concentration range of 0.2 μg/L~20.0 μg/L is 0.9996, the recovery rates ranging is 83.1%~95.2%, the relative standard deviation (RSD) is 2.7%~3.9% (n=6). This method offers the advantages of simple operation, high sensitivity, excellent recovery rates, and good precision, making it suitable for determining acetaldehyde content in leather.

The mesh density of carded cotton wadding is a core indicator for evaluating its molding quality and warmth retention performance. Addressing the issues of low efficiency and poor repeatability of manual counting, this paper proposes a carded cotton wadding mesh counting method based on an improved YOLOv11-seg. A spatial depth lossless convolutional SPD-Conv block is introduced into the backbone network, providing a complete prior knowledge of the underlying structure for deep networks and improving the model's noise resistance and removal capabilities against dense pseudo-defects. To address the mask boundary breakage and instance adhesion defects caused by rigid nearest neighbor interpolation during the feature pyramid decoding stage, a lightweight dynamic up sampling operator, DySample, is introduced. A content-aware point sampling strategy based on global static range constraints is adopted to improve the smoothness and closure of mask edges. Ablation and cross-sectional comparison experiments on the carded cotton wadding mesh dataset demonstrate that the proposed improved architecture achieves engineering-optimal solutions across multiple evaluation metrics. The parameter count is only 4.85M, the model mask mAP50 reaches 98.4%, an improvement of 0.3% compared to the original model, and the precision reaches 99.3%, an improvement of 0.2%. By introducing statistical linear regression analysis, the results showed that the coefficient of determination (R²) between the predicted and actual values of the improved model reached 0.983, and the root mean square error (RMSE) decreased to 4.47, demonstrating significant statistical consistency with the results of manual testing (P<0.05). This study provides strong technical support and important guidance for the industrial testing of carded cotton wadding quality.

As a critical fundamental material for the textile industry, the development trend of patented technologies for new fiber materials directly reflects the sector’s innovation orientation and industrial competitiveness. Based on the HimmPat patent database, this paper analyzes patent data from four perspectives: application trend, geographical distribution, technical composition, and innovation hotspots. The results show that global patent applications in the field of new fiber materials generally grew from 2007 to 2025. Especially over the past decade, the average annual number of applications has remained steadily above 2000, with invention patents accounting for 84.67% of the total. China accounted for 52.4% of global applications, making it the core region for new fiber material patents worldwide. Among these, high-performance fiber patents accounted for the highest proportion, reaching 41.84%. Chinese universities rank high in patent applications but still lag behind internationally renowned textile enterprises.

The curriculum ideological and political construction of fashion design and craft major in secondary vocational schools has long been confronted with three predicaments: the excavation of ideological and political elements stays at the superficial level, the curriculum system is fragmented, and there exists institutional deficiency in key teaching elements. Supported by Tyler's Curriculum Theory, competency-based education theory and collaborative education theory, this paper puts forward the construction framework of "Three Chains and Four Integrations" for curriculum ideological and political education. Taking Garment Sewing Technology course as the practical carrier for empirical verification, it finds that students have achieved positive qualitative changes in professional identity, process standardization and cultural belonging. The framework effectively eliminates the institutional barriers between professional education and ideological and political education, and provides a systematic path reference for cultivating talents with both morality and skills in secondary vocational fashion majors.

In response to common problems in textile industrial clusters, such as weak testing capabilities, lack of quality control, and difficulties in breaking through key technical bottlenecks, the Dezhou Fiber Inspection Institute has developed and validated a normalized service model of "inspection agency+industrial cluster". The core of this model is a "point (laboratory)-line (industrial chain)-surface (industry ecosystem)" three-level empowerment system, whose effective operation is driven by breakthroughs in key inspection technologies. This paper takes the rapid grading technology for cotton stickiness as a breakthrough point, illustrating how technical problem-solving provides feasibility support for model innovation, and how the model platform, in turn, facilitates iterative optimization of the technology. Practice shows that this model has reduced equipment adhesion rates by 60% in pilot enterprises, increased production efficiency by 25%, lowered costs by 30%, and cumulatively reduced costs and increased efficiency by over ten million yuan for the regional industry. The collaborative framework proposed in this paper provides a replicable technical pathway and theoretical reference for grassroots fiber inspection institutes to serve high-quality industrial development.

Under the backdrop of China's "dual carbon" goal and the global trend of green transformation in the textile trade, the Xinjiang textile industry, as a regional pillar industry, faces multiple pressures for green transition regarding energy structure, technological level, industrial chain support, and environmental governance. Based on the current development status and resource endowments of the Xinjiang textile industry, this paper analyzes the core advantages and practical bottlenecks of the industry's green transition in the context of carbon peaking. From the dimensions of low-carbon energy substitution, green process upgrading, circular system construction, intensive park development, and policy-standard empowerment, it systematically proposes implementation paths for green transition tailored to conditions. The aim is to drive the industry's shift from high-energy-intensive extensive growth to low-carbon, efficient, and intensive development, enhance its international green competitiveness, and realize carbon peaking goals in Xinjiang's industrial sector and the high-quality development of the textile industry.

This study develops a quality optimization framework based on uncertainty evaluation for chemical analytical instruments. A combined bottom-up and top-down approach was used to identify and quantify uncertainty sources in LC-MS/MS and ICP-MS. Monte Carlo simulation was applied to complex models, and a contribution analysis method was established. Results show that sample pretreatment, standard solution preparation, and instrument repeatability are key contributors. Targeted optimization reduced combined relative standard uncertainty by 25%~45%, providing a systematic approach for quality improvement.

By constructing a compensation model based on the ideal gas state equation and multi-parameter nonlinear correspondence, combining hardware optimization approaches such as PTFE heated sampling probes, membrane dehumidifiers, and PID closed-loop control, and processing high-frequency noise and long-term drift in signals with the Kalman filter and least squares dynamic zero-point tracking algorithm, this paper meticulously investigates various factors affecting environmental monitoring gases and corresponding improvement measures, thereby providing important technical support and theoretical reference for achieving a high-precision, low-maintenance online intelligent gas metrology system.

Amid the high-quality development of the manufacturing industry and the continuous updating of global quality standards, to better perform metrological inspection and testing in the process of product quality control, this paper first discusses the critical role of metrological inspection and testing in quality management throughout the entire product life cycle. It then analyzes the existing problems. Finally, improvement ideas in four aspects are proposed, transforming metrological inspection and testing from a reactive "post-inspection gatekeeping" model into a "preventive control" model, thereby substantially enhancing the authenticity of quality information, the efficiency of inspection work, and the speed of handling unexpected problems.

By systematically reviewing the basic situation of the development of China’s cotton planting industry, this paper, on this basis, deeply analyzes the core driving mechanisms of the dynamic evolution of cotton planting cost-benefit from four dimensions: changes in production factor prices, fluctuations in cotton market prices, the promotion of mechanized production technology, and agricultural support policy adjustments. In response to existing problems, countermeasures and suggestions are proposed, such as promoting large-scale and standardized planting, accelerating full-process mechanization coverage, improving the price and subsidy regulatory mechanism, and strengthening technology-enabled industrial upgrading. This provides theoretical reference and practical guidance for promoting cost reduction and efficiency improvement in China’s cotton industry and achieving high-quality development.

Leveraging new-generation information technologies such as microservice architecture and cloud computing, this paper is dedicated to building a standardized, integrated, intelligent, and domestically controlled information management platform for the inspection and testing of special equipment. It defines the overall construction objectives and core principles, designs a layered technical architecture, integrates all business processes, and breaks down data silos across multiple parties. Through safeguard measures such as unifying data standards, strengthening top-level planning, improving operation and maintenance mechanisms, and increasing investment in funding and talent, it achieves online management of the entire business process, life-cycle traceability of equipment, and intelligent early warning of safety risks. This addresses the pain points of traditional management, enhances inspection and testing efficiency and safety control levels, and fortifies the protective barrier for the safe operation of special equipment.

Modern manufacturing is accelerating towards intelligence, precision, and digitalization. As the core of quality assurance, metrological inspection and testing technology is continuously making innovative breakthroughs in the intelligent, online, high-precision, and visualized directions. The deep integration of artificial intelligence promotes automation of the entire metrological inspection and testing process and a closed-loop early warning system; digital inline technology realizes synchronization of production and inspection, addressing the pain point of data lag; quantum metrology breaks through accuracy limits to meet the traceability requirements at the micro- and nano-scale for high-end manufacturing; and machine vision technology significantly improves the efficiency and consistency of appearance inspection. Despite remarkable innovation achievements, it still faces problems such as a shortage of specialized technologies in segmented fields, an imperfect metrological traceability system, lagging industry standards, and a lack of interdisciplinary talents.

With a focus on the metrological inspection of the net content of prepackaged goods, this paper proposes that by improving the dynamic updating mechanism of standards, promoting the standardized adaptation of inspection equipment and processes, building a diversified and interdisciplinary talent training system, and increasing infrastructure investment, a synergistic upgrade of the standard system and intelligent technology can be achieved, thereby further strengthening the effectiveness of metrological supervision and ensuring the accuracy and reliability of the net content of prepackaged goods.

In view of the problems of delayed risk identification and simplistic response measures in the supervision of the fiber products circulation process, this paper constructs a full-chain regulatory mechanism of "risk factor identification-quantitative rating-graded early warning-differentiated response." By analyzing data from national fiber product supervisory random inspections and consumer complaint information over the past three years, the study identifies core risk factors across six dimensions, including labeling, safety performance, and physical performance. A three-dimensional quantitative criterion based on risk severity, occurrence frequency, and detectability is established, and the analytic hierarchy process is used to determine the weights of each dimension. A risk priority number calculation model is subsequently constructed, providing an actionable practical pathway for primary market regulation authorities to optimize resource allocation and enhance regulatory effectiveness.

This paper discusses in detail the key testing points and precautions for determining formaldehyde emission from wood-based panels and their products using the climate chamber method from three aspects: specimen pretreatment, interference of background formaldehyde concentration in the climate chamber, and sealing requirements for specimen edge sealing during preparation. It aims to provide a reference for quality inspection institutions and enterprise quality control departments to accurately understand and master the application of the new version of GB 18580—2025, so as to improve the testing capability and level of determining formaldehyde emission from wood-based panels and their products using the climate chamber method, and to ensure the consistency and accuracy of inspection and testing data and results.

Some domestic fiber enterprises suffer from shortcomings such as insufficient awareness of data assets, prominent data fragmentation, an incomplete value assessment system, and an absence of data governance mechanisms, severely hindering the transformation of accounting data from a traditional accounting tool into a new type of production factor. In response, enterprises need to establish a new mindset of data as an asset, build a unified data middle platform to break down data silos, construct a dynamic value assessment system with an emphasis on elevating the weight of core indicators such as energy consumption and costs, and improve a comprehensive support system covering organization, institution, and technology. This will effectively leverage the core value of accounting data in cost control, business analysis and forecasting, and strategic upgrading, continuously empowering fiber enterprises to achieve high-quality and sustainable development.

With the rapid development of the digital economy and intelligent manufacturing technology, the transformation toward informatization and intelligence has become an inevitable trend in the reform and upgrading of the special equipment inspection and testing industry. Against this backdrop, this paper first elucidates the core connotation of information management, analyzes the significance of information management in the inspection and testing of special equipment, and then puts forward practical development suggestions, including formulating unified industry construction standards, promoting regionally coordinated and balanced development, expanding the application of advanced intelligent technologies, and strengthening talent introduction and incentive efforts, so as to provide a reference for the high-quality development of the special equipment industry and the improvement of public safety governance.

As market regulation reforms continue to advance, primary market regulation serves as the “last mile” in maintaining the order of the market economy, and the soundness of its quality governance system directly affects the optimization of the business environment, the protection of people’s livelihood rights and interests, and the realization of fair market competition. By analyzing the current status of quality governance in primary market regulation, this paper examines the fundamental structure and characteristics of the system, and proposes targeted and actionable optimization strategies from four key aspects: operational standards, resource assurance, digital transformation, and collaborative governance. It is hoped that this can provide a theoretical reference and a practical pathway for enhancing the effectiveness of primary market regulation and constructing a high-standard market system.