Quality Control Of Products Research Articles

Optimized near infrared reflectance model based on preprocessing selection strategy for rapid analysis of 2-acetyl-1-pyrroline content in rice flour

The chemical compound 2-acetyl-1-pyrroline (2-AP) is a major contributor to the fragrance of rice. This report presents the first efforts towards determining the quantities of 2-AP in rice by grating-based visible–near-infrared reflectance spectroscopy using a diverse set of rice varieties. Calibration models generated by preprocessing treatments using Design of Experiment (DoE) and ‘one-variable-at-atime’ (OVAT) methods were compared and optimized. A modified partial least squares model with “2, 3, 1, 1”/SNV and 174 variables yielded a coefficient of determination for calibration values of 0.978. The results showed that a DoE-based preprocessing selection could efficiently and accurately optimize 2-AP calibration models, with advantages over OVAT. The findings of this study provide high-throughput screening technology for high-precision fragrance quality breeding, monitoring and control in the rice industry. The method demonstrated here also has potential for application in many other disciplines, including identification of plant fragrances and quality control of cereal products.

A dataset of NDVI for the vegetation growing season in Central Asia with a resolution of 250 m (2001–2020) and 30 m (2020)

Central Asia is the largest arid and semi-arid region in the Northern Hemisphere, and its ecological environment is extremely fragile and susceptible to the effects of global climate change. Maintaining the stability of the region's ecosystem is crucial to global economic and social development due to its unique geographic location. Vegetation serves as a significant indicator of the ecological environment, and the spatial and temporal distribution pattern, as well as the change trend of vegetation, are important indicators in evaluating the ecological status of the region. The Normalized Difference Vegetation Index (NDVI) is a commonly used remote sensing index to study vegetation, which characterizes the spatio-temporal changes of vegetation. This dataset utilized MODIS13Q1 to generate long-term time series growing season mean NDVI data with a spatial resolution of 250m in Central Asia from 2001 to 2020. To obtain the 2020 growing season mean NDVI data with a higher spatial resolution of 30m, the Cubist algorithm based on rule segmentation regression was utilized to fuse the Landsat data and MODIS data. Meanwhile, this dataset carried out quality control of data products from three aspects: data source quality control, model training optimization, and model independent verification to ensure the accuracy and reliability of data. The generation of this dataset provides powerful data support for the analysis of vegetation dynamic change and spatial pattern in Central Asia.

AI-based R&D for frozen and thawed meat: Research progress and future prospects.

Frozen and thawed meat plays an important role in stabilizing the meat supply chain and extending the shelf life of meat. However, traditional methods of research and development (R&D) struggle to meet rising demands for quality, nutritional value, innovation, safety, production efficiency, and sustainability. Frozen and thawed meat faces specific challenges, including quality degradation during thawing. Artificial intelligence (AI) has emerged as a promising solution to tackle these challenges in R&D of frozen and thawed meat. AI's capabilities in perception, judgment, and execution demonstrate significant potential in problem-solving and task execution. This review outlines the architecture of applying AI technology to the R&D of frozen and thawed meat, aiming to make AI better implement and deliver solutions. In comparison to traditional R&D methods, the current research progress and promising application prospects of AI in this field are comprehensively summarized, focusing on its role in addressing key challenges such as rapid optimization of thawing process. AI has already demonstrated success in areas such as product development, production optimization, risk management, and quality control for frozen and thawed meat. In the future, AI-based R&D for frozen and thawed meat will also play an important role in promoting personalization, intelligent production, and sustainable development. However, challenges remain, including the need for high-quality data, complex implementation, volatile processes, and environmental considerations. To realize the full potential of AI that can be integrated into R&D of frozen and thawed meat, further research is needed to develop more robust and reliable AI solutions, such as general AI, explainable AI, and green AI.

Application of fluorescence spectroscopy as a field method in the determination of varietal differences parsley (Petroselinum crispum) accessions after harvesting

The aim of this study is to establish the application of fluorescence spectroscopy as a field method for determining post-harvest varietal differences in parsley accessions (Petroselinum crispum). The proposed method includes studies of leaves from four standard varieties of parsley by means of fluorescence spectroscopy. Due to varietal differences of a given genotype, they will be compared in terms of determining the spectral distribution. Specimens were grown under uncontrolled field conditions. This will allow the approach to be practiced non-invasively in the quality control of parsley production in undefined premises and outdoors.The experimental studies were carried out locally on the farm. The spectral installation for generating emission fluorescence spectra is mobile. A system engineering approach based on the classical principles of modern optoelectronics was applied in its setup (optical setup). The results can be used to optimize the time for the analysis of the varietal difference of parsley genotypes after harvest, under uncontrolled conditions. The stability of the breeding variety and its common blacks with an established variety of the same species can be observed by monitoring the intensity of the signal. This will support the process of determining the belonging of a specific accession to a given variety (even for samples of unknown origin, when it is necessary to qualify the result of samples in a short time.

Pharmacy Compounding Regulation in the German Pharmaceutical Market. Part 2. Organisational Features (Review)

INTRODUCTION. The Russian Federation has decided to restore the system of compounding pharmacies as an element of the critical national healthcare infrastructure and pharmaceutical supply chain. To improve Russian regulatory practices, develop novel advanced approaches to pharmacy compounding and quality control, and implement these approaches, it is necessary to study relevant good compounding practices applied in healthcare systems of other countries.AIM. The study aimed to analyse the German experience in the organisation and regulation of pharmaceutical compounding to suggest recommendations for the development and implementation of Russian guidelines on good compounding and dispensing practices.DISCUSSION. This work continues a comprehensive study that delves into the current provisions of German legislation governing the system of good compounding practices. This article examines the differences between approaches to compounding by medical and pharmaceutical specialists. According to the findings, compounding by medical specialists is guided by the “free practice of medicine” principle and is subject to minimal regulatory oversight. All pharmacy organisations operate as compounding pharmacies, thereby enhancing the physical accessibility of compounded medicinal products to the population. The authors highlight the features of a process-based quality assurance system encompassing production process controls and quality control methods for compounded medicinal products. Additionally, the authors discuss the applicability of rapid test methods to compounding. In accordance with the German concept of good pharmacy practices, a compounding pharmacy may use the available validation, qualification, and verification tools in the pharmaceutical development of compounded medicinal products and may outsource its internal quality control function. Using the concept of risk ranking, compounding pharmacies may design their own sampling programmes. The article describes approaches to and requirements for organising the evaluation of compounding prescriptions. In Germany, compounding pharmacies may independently assign shelf lives to the compounded medicinal products they produce.CONCLUSIONS. Some German solutions are of considerable practical importance and are applicable to the development and implementation of Russian guidelines on good compounding and dispensing practices. In particular, pharmacy organisations may outsource the quality control of their compounded medicinal products. Additionally, pharmacies can conduct the full-scale pharmaceutical development of compounding technologies and quality control methods (including rapid test methods) using the validation, qualification, and verification tools available to drug manufacturers. Moreover, pharmacy organisations may independently assign shelf lives to the compounded medicinal products they produce. Finally, pharmacy organisations may design their individual sampling programmes.

Fuzzy averaging level control for tight product quality control

AbstractThis work develops a fuzzy averaging level controller (ALC) to mitigate flow variability while avoiding high and low level alarm limit breaches. Comparison with proportional (P) and proportional integral (PI) level controllers and their non‐linear variants demonstrates the fuzzy controller to be highly effective in mitigating flow transients for low and moderate size flow disturbances. The performance is comparable for large disturbances. Application of the developed fuzzy ALC to a ternary benzene‐toluene‐xylene direct split separation scheme as well as the separation section of a conventional cumene process demonstrates significantly superior product quality control due to flow transient variability mitigation. The product quality control variability is reduced by up to 1.5 times. The developed fuzzy ALC is therefore suitable for plant‐wide control applications.

PCB plug-in solder joint defect detection method based on coordinated attention-guided information fusion

Printed Circuit Boards (PCBs) are the foundational component of electronic devices, and the detection of PCB defects is essential for ensuring the quality control of electronic products. Aiming at the problem that the existing PCB plug-in solder defect detection algorithms cannot meet the requirements of high precision, low false alarm rate, and high speed at the same time, this paper proposes a method based on spatial convolution pooling and information fusion. Firstly, on the basis of YOLOv3, an attention-guided pyramid structure is used to fuse context information, and multiple convolutions of different size are used to explore richer high-level semantic information; Secondly, a coordinated attention network structure is introduced to calibrate the fused pyramidal feature information, highlighting the important feature channels, and reducing the adverse impact of redundant parameters generated by feature fusion; Finally, the ASPP (Atrous Spatial Pyramid Pooling) structure is implemented in the original Darknet53 backbone feature extraction network to acquire multi-scale feature information of the detection targets. With these improvements, the average detection accuracy of the enhanced network has been elevated from 94.45 to 96.43%. This experiments shows that the improved network is more suitable for PCB plug-in solder defect detection applications.

Analisis Pengendalian Kualitas Menggunakan Statistical Process Control untuk Mengurangi Produk Cacat pada Mebel UD Sadewo Jagat di Ngawi

UD Sadewo Jagat is a company engaged in furniture production, this company provides sales of finished, semi-finished products and maintenance for various types of teak wood furniture. Finished products include tables, chairs, shelves and various other types of displays. However, in this study, we only analyzed defective products for wooden box table products because the production process of wooden box table products because the production process of wooden box tables experienced problems, namely the number of defects exceending 5% of the company’s standard provisions. The aim of this research is to analyze product quality control techniques using the Statistical Process Control method in reducing defective products, and to find out what factors cause defects in products produced by UD Sadewo Jagat. This research uses the Statistical Process Control (SPC) method, which is one of the analytical methods used to analyze the causes of defects that occur, both in terms of product quality and in terms of the quality of the production process. Quality control analysis is carried out using. The results of the check sheet analysis show an average of 9,6% product defects per month. From the results of the Pareto diagram, it can be seen that the highest level of defects is crack defects, with a total of 80 units or 44,94% of total product defects in 2023. Meanwhile, the results of the control chart that has been made can be seen that quality control is uncontrolled and not according to standards. From the results of the fishbone diagram, it is concluced that the factors causing product defects are human factors, materials, environment, and methods.

Implementation Of Quality Control In The Crab Production Process

The purpose of this study is to determine the steps in PT. Manage Mina Laut's production process and to put quality control measures in place for the procedure. Qualitative research is the name given to this type of study. Three techniques were employed to acquire the data: observation, interviews, and documentation. One kind of data analysis used in this study is the interactive model. The results of research indicate that PT. Manage Mina Laut takes crab from fishermen who harvest it while it is still fresh and of very good quality. The company then processes these raw materials effectively to produce high quality goods. PT. Manage Mina Laut consistently upholds the quality of the goods they produce. Before the product is sent to the customer, quality control goes through several verification stages in the production process, starting with the selection of fresh and high quality raw materials (off-line quality control). (on-line quality control). PT. Kelola Mina Laut has carried out production processes and quality control in accordance with relevant protocols.

Determination of Single Sampling Attribute Plans Based Upon Dodge Roaming Model with Application

Bayesian sampling plans for production inspection involve using a sampling method to assess the features of the plan, under the assumption that defect rates fluctuate randomly among different production batches. This results in a likelihood distribution that can be established through experience and the quality information at hand. In this study, the parameters of a single Bayesian sampling plan were determined using the Beta-Binomial distribution, and were subsequently contrasted with parameters from other single sampling plans. Based on research findings, (Ala corporation for soft drinks) oversees the control of product quality. Since the variable fluctuates randomly between manufacturing batches, 120 batches were selected to calculate the defect rate by analyzing batch size and number of defective items. Applying Bayesian and decision-making models can lead to the development of a single sampling inspection procedure that closely approximates the actual quality level. When the decision-making model was used, the researchers discovered that the sample size was smaller and led to lower inspection costs compared to other inspection plans.

Applications of Capillary Electrophoresis for the Detection of Adulterants in Dietary Supplements.

In recent years, the consumption of dietary supplements, particularly those incorporating plant-based ingredients, has increased greatly, driven by the perception of their natural origins and purported minimal health risks. However, one significant safety concern revolves around the adulteration of dietary supplements, wherein unscrupulous manufacturers may illegally incorporate pharmaceutical substances or their analogs into these products to achieve increased efficiency and bolster sales. This review assesses the role of capillary electrophoresis (CE) in ensuring the quality control of dietary supplement products over the past two decades. This study provides an overview of various applications of CE in analyzing dietary supplements, outlining the typical attributes of natural product analysis using CE. These analyses demonstrate the broad versatility of CE, exemplified by its diverse applications and detection modes. Moreover, the review highlights the growing prominence of CE as a separation technique in quality control, by comparison with more conventional methods like high-performance liquid chromatography (HPLC). Through this exploration, the review elucidates the pivotal role of CE in upholding the integrity and safety of dietary supplements, in connection with a landscape of evolving regulatory challenges and consumer demands.

Development of HPTLC method for simultaneous determination of quercetin and kaempferol in leaf extract of Hibiscus mutabilis

The aim of this study was to develop and validate a densitometric High-Performance Thin-Layer Chromatography (HPTLC) method for the simultaneous quantification of quercetin (Q) and kaempferol (K) in Hibiscus mutabilis leaf extracts. The analyses were performed on silica gel 60 F254 plates using a mobile phase composed of toluene, formic acid, and ethyl acetate (6:0.4:4, v/v/v). Detection was carried out at a wavelength of 272 nm using a deuterium and tungsten light source. The method exhibited excellent linearity over the concentration range of 100–600 ng/spot for quercetin and 500–3000 ng/spot for kaempferol, with determination coefficients (r2) of 0.9989 and 0.9973, respectively. The method showed no interferences from the plant matrix. The relative standard deviation (RSD) values for intra- and inter-day precision were less than 2% for both flavonoids. Recovery rates ranged from 97.69% to 99.20% for quercetin and from 89.91% to 95.87% for kaempferol. The limits of detection (LOD) were 190.23 ng/spot for quercetin and 187.23 ng/spot for kaempferol, while the limits of quantification (LOQ) were 570.10 ng/spot for quercetin and 566.12 ng/spot for kaempferol. This validated HPTLC method is reliable, precise, and accurate, making it suitable for the quality control of Hibiscus mutabilis leaf extracts. The study’s findings can be broadly applied to the quality control of herbal products, pharmacological research, and the development of nutraceuticals. The method’s ability to provide rapid and accurate quantification makes it an invaluable tool for researchers across various disciplines.

Consequences of Outsourcing Strategies on Employee Quality of Work Life, Attitudes and Performance in Nepalese Commercial Banks

This study examines the consequences of outsourcing strategies on employee quality of work life, attitudes and performance in Nepalese commercial banks. The dependent variable is organizational performance. The selected independent variables are employee satisfaction, employee commitment, cost-efficiency, quality control, training and development and leadership behaviour. The primary source of data is used to assess the opinions of the respondents regarding employee satisfaction, employee commitment, cost-efficiency, quality control, training and development and leadership behaviour. The study is based on primary data of commercial banks with 120 respondents. To achieve the purpose of the study, structured questionnaire is prepared. The regression models are estimated to test the significance and importance of consequences of outsourcing strategies on employee quality of work life, attitudes and performance in Nepalese commercial banks. The result shows that employee satisfaction is positively correlated to organizational performance. It indicates that higher the employee satisfaction, higher would be the organizational performance. Likewise, the result shows that employee commitment is positively correlated with organizational performance. It indicates that higher the employee commitment, higher would be the organizational performance. The result also reveals that cost-efficiency is positively correlated with organizational performance. It indicates that increase in cost-efficiency leads to increase in organizational performance. Similarly, training and development is positively correlated with organizational performance. It indicates that providing proper training and development to employees leads to increase in organizational performance. Likewise, quality control is positively correlated to organizational performance. It indicates that better the quality control of products, higher would be the organizational performance.

Determination of Bioactive Compounds in Buriti Oil by Prediction Models Through Mid-infrared Spectroscopy

Buriti oil is a vegetable oil extracted from the pulp and seeds of buriti (Mauritia flexuosa L.), a palm commonly found in the Amazon region, and is used both in popular medicine and in the cosmetic and food industries. This work aimed to develop a faster and more accessible procedure to quantify the content of carotenoids, polyphenols, and total flavonoids in buriti oils, where predictive models emphasize figures of merit. The study was carried out with 50 buriti oil samples from the state of Pará, Brazil, which were sampled by combining attenuated total reflection (ATR) spectroscopy with mid-infrared Fourier transform (FT-MIR) together with partial least squares regression (PLSR). The confidence and validation matrix were obtained from ultraviolet–visible spectroscopy. The PLSR model regarding the total carotenoid content presented values ​​between 335.33 and 1557.05 μg/g was validated by the concentration demonstration coefficient (R2cal) equal to 0.9556, prediction demonstration coefficient (R2pred) equal to 0.85642, bias = 5.68.10−13, performance deviation ratio value (RDP) of 2.0135, and range error rate (RER) equal to 4.3747. Concentrations of phenolic compounds were predicted between 96.2964 and 121.857 GAE/100 g, where the model presented R2cal = 0.9762, R2pred = 0.8198, bias = 3.38.10−10, RDP = 5.9028, and RER = 5.7578. The flavonoid prediction model contains concentrations between 86.844 and 133.852 mg EC/100 g that circulate R2cal = 0.9445, R2pred = 0.8536, bias = 6.98.10−8, RDP = 6.7085, and RER = 6.7085. Buriti oil showed high levels of b-carotene. Prediction models are overwhelming and can be used for screening and quality control of natural products.

Capability Indices for Digitized Industries: A Review and Outlook of Machine Learning Applications for Predictive Process Control

Leveraging machine learning applications for predictive process control signifies a decisive advancement in manufacturing quality management, transitioning from traditional descriptive to predictive capability indices. This review highlights the growing importance of predictive process control, essential for quality assurance and the dynamic adaptability of production lines, which is paramount in satisfying stringent quality standards and evolving consumer demands. The investigation into the integration of comprehensive sensor networks and sophisticated algorithmic analytics enriches continuous improvement strategies, markedly enhancing the accuracy and efficiency of production quality monitoring and control mechanisms. By moving beyond the limits of statistical process control to predictive methods enabled by machine learning algorithms, the study presents a transformative leap in manufacturing processes. The presented findings illustrate the critical role of predictive algorithms in navigating the complexities of process variability, thereby ensuring consistent adherence to established quality specifications. This approach not only facilitates immediate and accurate product quality categorization, increasing overall operational efficiency, but also equips manufacturers to swiftly respond to the variable nature of manufacturing requirements. Furthermore, this research delves into the multifaceted impacts of predictive process control on the manufacturing ecosystem. The ability to predict process quality decrease before it occurs, the optimization of resource allocation, and the anticipation of production bottlenecks before they impact output are among the notable benefits of this technological evolution. These developments to predictive process control is instrumental in propelling the manufacturing industry toward a more agile, sustainable, and customer-centric future. This shift not only complements the industry’s drive toward comprehensive digitization but also promises significant strides in achieving superior process improvements and maintaining a competitive edge on the global market.

Revealing novel insights into the enhancement of quality in black tea processing through microbial intervention

Black tea is highly favored by consumers worldwide, with enzymatic reactions being recognized as a pivotal factor influencing tea quality. The role of microorganisms in shaping the composition of black tea has emerged as a focus of research due to their involvement in enzyme catalysis and metabolic processes. In this study, full-length amplicon sequencing combined with qPCR more accurately reflected microbial profile, and Pantoea, Pseudomonas, Paucibacter, and Cladosporium were identified as the main microbial genera. Moreover, by comprehensively analyzing color, aroma, and taste components over time in black tea samples, correlations were established between the dominant genus and various quality factors. Notably, peroxidase activity levels, total soluble sugar content, and tea pigments concentration exhibited significant associations with the dominant genus. Consequently, this microbiological perspective facilitated the exploration of driving factors for improving black tea quality while establishing a theoretical foundation for quality control in industrial production.

Application of Steady-State and Time-Resolved Fluorescence Spectroscopy in Identification of Bee Products

In this study, steady-state and time-resolved fluorescence spectroscopy techniques have been applied to determine fluorescence characteristics and fluorescence decay kinetics parameters (fluorescence lifetimes and their amplitudes) of available on the Polish market bee products, including several nectar honeys, royal jelly, bee bread in honey and in liquid artificial honey. The fluorescence properties of the tested bee products arise from the presence of a unique composition of aromatic amino acids, vitamins, phenolic compounds and Maillard reaction products. In the 300–550 nm region of the emission spectra (excited at 280 nm), each of the tested bee products exhibited (showed) a specific and distinctive vibronic structure, which was not observed in the spectrum of artificial honey. Quantitative and qualitative composition as well as specific interactions between fluorescent constituents determine the specific fluorescence characteristics of a given bee product providing a unique fingerprint that can be used in the identification of bee products of different botanical origin. Combination of stationary and time-resolved fluorescence techniques seems to be a promising approach in the identification, authentication and quality control of bee products to verify their health-beneficial properties.

Ultrasensitive electrochemical sensing for simultaneous rapid detection of zearalenone and ochratoxin A in feedstuffs and foodstuffs

Mycotoxins are causing persistent worries regarding food safety worldwide due to their ability to elicit a wide range of harmful effects in both animals and humans. Approaches that can identify a single mycotoxin are not sufficient for addressing the needs of quality control of agricultural products since they are often co-contaminated by multiple mycotoxins. This paper presents the development of an electrochemical sensor that is free of biomolecules and is capable of simultaneously detecting zearalenone (ZEN) and ochratoxin A (OTA) through the incorporation of nickel oxide (NiO) with carboxylated carbon nanotubes (MWCNT(–COOH)).This is the first time that NiO–MWCNT(–COOH) based electrochemical sensor has achieved the simultaneous potential-resolved selective detection of ZEN and OTA. Under optimized conditions, good linear responses were observed in the range of 0.01–10.24 μg mL−1 for ZEN and 0.04–10.24 μg mL−1 for OTA with low detection limit of 6 and 15 ng mL−1, respectively. The proposed electrochemical sensor demonstrated good selectivity, reusability, reproducibility, and shelf-life for the sensitive detection of both mycotoxins. Moreover, the sensor was made utilizing screen-printing technology to demonstrate its potential for commercialization and practical application. Our biomolecule-free electrochemical sensor was successful in evaluating these mycotoxins in actual samples of corn flour and wheat flour, proving its promising application in monitoring ZEN and OTA co-contamination in agricultural products.

An Exploratory Study on the Rapid Detection of Volatile Organic Compounds in Gardenia Fruit Using the Heracles NEO Ultra-Fast Gas Phase Electronic Nose.

Gardenia fruit is a popular functional food and raw material for natural pigments. It comes from a wide range of sources, and different products sharing the same name are very common. Volatile organic compounds (VOCs) are important factors that affect the flavor and quality of gardenia fruit. This study used the Heracles NEO ultra-fast gas phase electronic nose with advanced odor analysis performance and high sensitivity to analyze six batches of gardenia fruit from different sources. This study analyzed the VOCs to find a way to quickly identify gardenia fruit. The results show that this method can accurately distinguish the odor characteristics of various gardenia fruit samples. The VOCs in gardenia fruit are mainly organic acid esters, ketones, and aldehyde compounds. By combining principal component analysis (PCA) and discriminant factor analysis (DFA), this study found that the hexanal content varied the most in different gardenia fruit samples. The VOCs allowed for the fruit samples to be grouped into two main categories. One fruit sample was quite different from the fruits of other origins. The results provide theoretical support for feasibility of rapid identification and quality control of gardenia fruit and related products in the future.

Pemetaan Moluska Komoditas Ekspor dan Impor Melalui Balai Besar KIPM Jakarta I

Indonesia has high biodiversity and it has the opportunity to expand as fisheries business in the international commodity market. The research aims to analyze the diversity of mollusk species, map the distribution, and analyze the sustainability of these commodities in the Indonesian export and import markets. The research conducted at the Jakarta I Fish Quarantine Center for Quality Control and Safety of Fishery Products (BBKIPM) on January to February 2023. The data used comes from data available at BBKIPM Jakarta 1 on 2021 to 2022 periods. The method used is descriptive quantitative analysis. The results showed that mollusk commodities traded in exports were more diverse than imported mollusks. The most commodity classes are pelecypod (35 species), gastropods (12 species) and cephalopods (12 species). The total number of exported mollusk commodities (4,823,969.879 kg) is higher than imports (7,281.04 kg) on 2021 to 2022 periods. Mollusk exports from Indonesia spread to 44 countries on 2021 to 2022 periods. Meanwhile, mollusk imports to Indonesia only came from 2 countries (2021) and either from 1 country (2022).