Quality Evaluation Of Products Research Articles

How Explainable Machine Learning Enhances Intelligence in Explaining Consumer Purchase Behavior: A Random Forest Model with Anchoring Effects

This study proposes a random forest model to address the limited explanation of consumer purchase behavior in search advertising, considering the influence of anchoring effects on rational consumer behavior. The model comprises two components: prediction and explanation. The prediction part employs various algorithms, including logistic regression (LR), adaptive boosting (ADA), extreme gradient boosting (XGB), multilayer perceptron (MLP), naive bayes (NB), and random forest (RF), for optimal prediction. The explanation part utilizes the SHAP explainable framework to identify significant indicators and reveal key factors influencing consumer purchase behavior and their relative importance. Our results show that (1) the explainable machine learning model based on the random forest algorithm performed optimally (F1 = 0.8586), making it suitable for analyzing and predicting consumer purchase behavior. (2) The dimension of product information is the most crucial attribute influencing consumer purchase behavior, with features such as sales level, display priority, granularity, and price significantly influencing consumer perceptions. These attributes can be considered by merchants to develop appropriate tactics for improving the user experience. (3) Consumers’ purchase intentions vary based on the presented anchor point. Specifically, high anchor information related to product quality ratings increases the likelihood of purchase, while price anchors prompted consumers to compare similar products and opt for the most economical option. Our findings provide guidance for optimizing marketing strategies and improving user experience while also contributing to a deeper understanding of the decision−making mechanisms and pathways in online consumer purchase behavior.

Synthesis of activated carbon monolith from lignocellulosic material: Evaluation of product quality

Synthesis of activated carbon monolith from lignocellulosic material: Evaluation of product quality

Pengembangan dan Pertambahan Nilai Pada Produk Purun Inovatif Berpeluang Lolos Kurasi Ekspor

Kampung Purun, Palam, Banjarbaru is well-known as the development of creative industries making purun woven products. The products are in the form of various bags, hats, mats and tissue boxes as well as many other various products. The resulting product has a variety of colors, but in the coloring process the craftsmen still use chemical dyes which are not environmentally friendly. Besides that, the product design is still not varied. This service aimed at innovating purun products produced by the villagers of Kampung Purun, especially the Galoeh Bandjar group by redesigning and innovating the dyes used, namely using natural dyes to boost the chances of purun products being able to pass the export curation. Natural dyes were produced from a combination of jengkol skin and sappan wood, with various formulations developed based on previous research results. The best formula used was 12 : 1 : 7 consisting of water : cup : jengkol skin. The jengkol skin used was waste from the Jaring culinary production process. Dyes were made by boiling the two ingredients. Furthermore, the production stages by designing, coloring, determining color composition and evaluating product quality were carried out at the Banjarbaru Government Packaging House. The resulting color was brownish red and ready to be applied to purun products. The results of the curation by the Packaging House stated that the innovative purun product was feasible to be marketed from a quality standpoint. The selling price of the product was set at Rp. 46,000, - with a production cost of Rp. 36,621, - per unit. This means that there is an additional value of IDR 10,379.

Exploring the quality markers of the production region of Ligusticum chuanxiong through antiplatelet aggregation bioactivity and multiple active components, and correlation analysis of the quality markers and geographical factors.

Ligusticum chuanxiong Hort. (L. chuanxiong) is one of the most important herbs in traditional Chinese medicine. It is mainly produced in Sichuan Province, China. Dujiangyan City is considered the authentic production region (APR, superior-quality production region). However, there are differences in the geographical environments and cultivation conditions between the APR and non-APR, which may affect the accumulation of secondary metabolites, cause a difference in bioactivity, and eventually influence the quality of L. chuanxiong. Therefore, antiplatelet aggregation biopotency (AAB) in vitro of L. chuanxiong from different production regions was measured using a parallel-line assay based on the quantitative response method of the bioassay. The result of AAB indicated that the biopotency of L. chuanxiong from Dujiangyan city was stronger than that from other production areas, which scientifically validated Dujiangyan City as the APR of L. chuanxiong. The biopotency of L. chuanxiong from Shifang City was similar to that from Dujiangyan City, indicating that Shifang City could be considered a new APR. The quality markers of L. chuanxiong were analyzed through partial least squares-discrimination analysis based on AAB and 20 active ingredients. Six components were screened as quality markers, where Z-ligustilide, coniferyl ferulate, 3,5-O-dicaffeoylquinic acid were positively correlated with its quality, while cryptochlorogenic acid, butylidenephthalide, and neocnidilide were negatively correlated with it. Among the quality markers, they all exerted antiplatelet aggregation bioactivity, and the high content of Z-ligustilide was the quality feature in the APR. The correlations of the quality markers with the longitude, latitude, altitude were investigated through orthogonal partial least squares. The larger latitude, smaller longitude and higher altitude were beneficial for the accumulation of the quality markers. This may provide a reference for the suitable production regions and quality evaluation of L. chuanxiong.

Predicting the Physicochemical Properties of Molecules in Petroleum Based on Structural Increments

The structure-oriented lumping (SOL) method has been widely applied to molecular-level modeling and optimization in the refining industry. Calculating the physicochemical properties of products obtained by the SOL models can effectively guide the evaluation of product quality and optimization of the process. In this study, the SOL method was improved by extending the structural increments from 22 to 38 to describe the molecules in petroleum more accurately. According to the basic law that the properties and structures of molecules are inseparable, the structural increments with similar physical meanings were combined into a functional group to reduce the dimension to 11 characteristic parameters to describe the molecular structure, and a property prediction method that can be combined with the molecular-level refining models based on the optimized SOL method was constructed. In addition, the accuracy of the selection and definition of the 11 functional groups was verified by analyzing and discussing the effects of functional groups on the properties, which, in turn, ensured the accuracy of the property prediction models. Compared with other property prediction methods, this method can be combined with the SOL method to provide reliable predictions of the boiling point, critical temperature, critical volume, critical pressure, density, cetane number, motor octane number, and research octane number of molecules.

Model and experiment of shrinkage effect during hypobaric storage of Agaricus bisporus

AbstractThis study presents a comprehensive multiphase porous media model with thermo‐hydro‐mechanical (THM) bi‐directional coupling for hypobaric storage of porous food. Agaricus bisporus is used as a case study, and the proposed model is compared to the thermo‐hydro (TH) coupling model, which does not consider product shrinkage. The results indicate that the THM model is more sensitive to pressure changes, accurately simulates the development of the evaporation front, and considers the edge gradient effect. The model is validated through experiments and provides a deeper understanding of the mechanism of heat and mass transfer of porous food under low pressure. Increasing humidity reduces product shrinkage. The model's average relative errors for pressure, temperature, weight loss, and shrinkage are 3.64%, 0.06%, 6.07%, and 4.76%, respectively. This model can be used to optimize the hypobaric storage process and improve product quality.Practical applicationsIn this manuscript, a multiphase porous media model with THM bi‐directional coupling for the process of hypobaric storage was developed. Taking A. bisporus as an example, pressure, temperature, weight loss, and shrinkage were predicted. In addition, the effect of humidity on shrinkage of porous food during hypobaric storage has also been studied. In engineering practice, the model can be used to optimize the hypobaric storage process and evaluate product quality.

Rapid Sensing: Hand-Held and Portable FTIR Applications for On-Site Food Quality Control from Farm to Fork.

Today, one of the world's biggest problems is the assurance of food integrity from farm to fork. Economically motivated food adulteration and food authenticity problems are increasing daily with considerable health and economic effects. Early detection and prevention of food integrity-related problems could be provided by the application of effective on-site food analysis technologies. FTIR spectroscopy coupled with chemometrics can be used for the rapid quality control of a wide variety of food products with fast, high-throughput, accurate and nondestructive analysis advantages. In particular, hand-held and portable FTIR instruments have the potential to surveil food quality and food safety in various critical segments of the food supply chain. In this review, we explore the abilities of hand-held and portable FTIR spectrometers combined with multivariate statistics to conduct a quality evaluation of various food products in terms of food adulteration and authenticity issues. An examination of the literature showed that comparable results were obtained based on detection limits, correlation coefficient (R2) values, standard error values and discrimination power by using both portable/hand-held FTIR spectrometers and benchtop FTIR spectrometers. In conclusion, this review highlights the potential usefulness of portable and hand-held FTIR spectrometers combined with chemometrics for maintaining the food quality through the presentation of various applications that may shed light for on-site food control at any point of the food supply chain.

Optimal Grading Scales for Enhancing Product Evaluation by Infomediaries

Infomediaries, such as movie critics, play a crucial role in evaluating product quality and providing valuable information to potential consumers. Their use of discrete grades, such as thumbs-up and thumbs-down, helps consumers make informed purchasing decisions. In this study, we aim to investigate how the grading process can be improved, addressing research questions such as determining quality cutoffs for each grade, identifying the optimal number of grades to use, exploring grading strategies for goals beyond informativeness (e.g., maximizing reviewer's traffic), and designing grading systems that encourage producers to enhance product quality. Through the use of an analytical model, we demonstrate that the optimal grade cutoffs are contingent upon the distributions of product quality and consumer taste. Additionally, we find that the resulting grading scale may exhibit unequal intervals. Surprisingly, our findings indicate that as few as five grades can approach optimality in terms of consumer welfare. Furthermore, we reveal that grading should be made more challenging when producers have the ability to invest in quality improvement. These insights shed light on the design of grading scales for reporting quality, offering practical guidance to infomediaries and industry stakeholders. By understanding the interplay between product quality, consumer preferences, and grading strategies, we can enhance the effectiveness and relevance of grading systems, ultimately empowering consumers to make more informed decisions.
 
 Received: 12 January 2023 / Accepted: 16 March 2023 / Published: 20 March 2023

Hygienic Milk Production, Milk Marketing And Milk Quality Evaluation in Urban and Peri-Urban of Sululta District, Ethiopia.

The study was conducted in Sululta district, Oromia special Zone Surrounding Finfinnee, with the objective of assessing hygienic milk production, marketing system and milk quality evaluation. Raw milk marketing channels producers to Collectors (80%), producers to processors (19%) and producers to consumers (1%), with  the average milk price (25) Ethiopia Birr/L during the study was conducted. The overall mean of fat 2.968±0.27%, protein 2.71±0.149%, specific gravity 1.0161±0.0007, Sold-non-fat 5.91±.396, temperature 23.8±.97℃, added water 23.11± 5.049%, freezing points -0.4027±0.0364℃, titratable acidity 0.151±0.009 and pH 6.293±0.077 and there was significant (P≤0.05) difference while milk temperature was not significant (P≤0.05) difference between the two study areas. The overall mean of total bacterial count 7.80±0.25log10cfu/ml, Coliforms 5.71±0.24 log10cfu/ml, Somatic cell 1.10±0.414 log10cfu/ml and yeast and mold 4.13±0.168 log10cfu/ml, there was significant (P≤0.05) difference milk microbial quality between the two study areas. High bacterial load of milk due to contamination from fecal or other contaminating agents from poor pre-harvesting and post harvesting of milk handling, insufficient udder preparation, use of poor quality and un-boiled water for cleaning utensil. The chemical composition and microbial quality of milk not fulfilling milk quality standards, except titratable acidity and somatic cell count, might be due to milk adulteration, cream separation and neglected hygienic milk production practices etc. Appropriate intervention of concerned technical supportive stakeholders would be essential to overcome prevailing poor hygienic milk production, milk marketing and milk quality problem in general.

Correlation between Water Characteristics and Gel Strength in the Gel Formation of Golden Pompano Surimi Induced by Dense Phase Carbon Dioxide.

The relationship between the gel quality of golden pompano surimi treated with dense phase carbon dioxide (DPCD) and changes in water characteristics was evaluated. Low-field nuclear magnetic resonance (LF-NMR) and nuclear magnetic resonance imaging were used to monitor changes in the water status of surimi gel under different treatment conditions. Whiteness, water-holding capacity and gel strength were used as the quality indicators of the surimi gel. The results showed that DPCD treatment could significantly increase the whiteness of surimi and the strength of the gel, while the water-holding capacity decreased significantly. LF-NMR analysis showed that, as the DPCD treatment intensity increased, the relaxation component T22 shifted to the right, T23 shifted to the left, the proportion of A22 decreased significantly (p < 0.05) and the proportion of A23 increased significantly (p < 0.05). A correlation analysis of water characteristics and gel strength showed that the water-holding capacity of surimi induced by DPCD was strongly positively correlated with gel strength, while A22 and T23 were strongly negatively correlated with gel strength. This study provides helpful insights into the quality control of DPCD in surimi processing and also provides an approach for the quality evaluation and detection of surimi products.

A Systematic Literature Review of the Relationship between Consumer Ethnocentrism and Product Evaluation

Globalization has added new dimensions to consumers’ decision-making. Consumer Ethnocentrism is among the critical variables affecting consumers’ decisions to purchase foreign products. Consumer Ethnocentrism research has gained momentum in the last few decades, and a copious amount of literature is available on this subject. This article presents an overview of Consumer Ethnocentrism literature and a compressive review of research work on the relationship between “Consumer Ethnocentrism” and “Product Evaluation” with critical insights from previous literature findings. There is a fractured opinion on the subject of whether Consumer Ethnocentrism leads to a lower quality evaluation of foreign products or whether consumer preference for the domestic product is purely out of a feeling that it is unfair to buy a foreign product. We also provided future research directions using TMC (Theory, Methodology, and Context) framework in line with earlier studies.

Analysis on Key Points of Safety and Effectiveness Evaluation of Wearable Rehabilitation Walking Aid Robot

To analyze the key points of evaluation on the safety and effectiveness of wearable rehabilitation walking aid robot, then improve its quality control ability. Combined with the functional and structural characteristics of the wearable rehabilitation walking aid robot, the key points of quality evaluation were analyzed from the aspects of electrical safety and main performance. Some reasonable suggestions were put forward for the design and development of the robot. The key points of safety and effectiveness evaluation of wearable rehabilitation aid walking robot focused on battery, protection device, operation parameters, static load strength, network security, environmental adaptability and other aspects. By analyzing the key points of safety and effectiveness evaluation of wearable rehabilitation walking aid robot, certain ideas are provided for the design and development of such products, and reference is provided for the improvement of product quality evaluation system.

Nutritional quality evaluation of complementary baby food products in Korea according to food composition

Nutritional quality evaluation of complementary baby food products in Korea according to food composition

System of indicators and the classifier of methods for quality control and evaluation of agricultural products in the structure of multidimensional inter-industry production cooperation

The article deals with the main issues of product quality management and control in multidimensional inter-industry production cooperation. Regulatory requirements and industry methods for assessing the quality of agricultural raw materials and finished industrial products on the example of leather and foot-wear industry are analyzed. The article presents the structural and logical scheme of the integrated classifier of methods for comprehensive quality assessment of objects and processes in multidimensional organizational structure of interindustry production cooperation. The conditions of digital transformation of agro-industrial complex aiming at improving the quality of leather footwear production on the basis of information-organizational inter-branch interaction between industrial and agricultural enterprises are formed int he article.

Development of a smart spectral analysis method for the determination of mulberry (Morus alba var. nigra L.) juice quality parameters using FT-IR spectroscopy.

Recently, the application of Fourier transform infrared (FT-IR) spectroscopy as a noninvasive technique combined with chemometric methods has been widely noted for quality evaluation of agricultural products. Mulberry (Morus alba var. nigra L.) is a native fruit of Iran and there is limited information about its quality characteristics. The present study aims at assessing a nondestructive optical method for determining the internal quality of mulberry juice. To do so, first, FT-IR spectra were acquired in the spectral range 1000-8333 nm. Then, the principal component analysis (PCA) was used to extract the principal components (PCs) which were given as inputs to three predictive models (support vector regression (SVR), partial least square (PLS), and artificial neural network (ANN)) to predict the internal parameters of the mulberry juice. The performance of predictive models showed that SVR got better results for the prediction of ascorbic acid (R 2= .84, RMSE=0.29), acidity (R 2= .71, RMSE=0.0004), phenol (R 2= .35, RMSE=0.19), total anthocyanin (R 2= .93, RMSE=5.85), and browning (R 2= .89, RMSE=0.062) compared to PLS and ANN. However, the ANN predicted the parameters TSS (R 2= .98, RMSE=0.003) and pH (R 2= .99, RMSE=0.0009) better than the other two models. The results indicated that a good prediction performance was obtained using the FT-IR technique along with SVR and this method could be easily adapted to detect the quality parameters of mulberry juice.

Determination of the quality of tea from different picking periods: An adaptive pooling attention mechanism coupled with an electronic nose

An efficient nondestructive testing method is important to inspect the quality of agricultural products. The material content of tea differs across different picking periods, leading to variation in the quality. Traditional methods for evaluating the quality of tea are relatively complex, in-efficient, and generally destructive. This prompted our work, which led to the development of nondestructive testing technology comprising an electronic nose (e-nose) combined with an effective data analysis method, to determine the quality of tea from different picking periods. First, the e-nose system was used to acquire information about the volatile components of tea from different picking periods. Second, an adaptive pooling attention mechanism (APAM) is proposed based on the data characteristics of the e-nose system. By adapting the attention to the essential information that affects the classification performance, the feature-learning ability of the gas information is enhanced. Finally, the proposed APAM was combined with a classic convolutional neural network (CNN) to identify the gas information of tea picked during different picking periods. The method was evaluated in comparison with other gas recognition methods to prove its effectiveness. The results show that APAM can effectively realize the adaptive attention to the deep gas information. The MobileNetV1 +APAM has accuracy of 97.62%, precision of 97.57%, recall of 97.71%, and F1-score of 97.64%, confirming the capability of the method to successfully distinguish among the gas information of tea gathered in different picking periods. In summary, integrating APAM with a classic CNN combined with e-nose technology offers an effective nondestructive testing method for agricultural production and tea quality evaluation.

Development of a Portable Near-Infrared Spectroscopy Tool for Detecting Freshness of Commercial Packaged Pork.

Real-time monitoring of meat quality requires fast, accurate, low-cost, and non-destructive analytical methods that can be used throughout the entire production chain, including the packaged product. The aim of this work was to evaluate the potential of a portable near-infrared (NIR) spectroscopy tool for the on-site detection of freshness of pork loin fillets in modified atmosphere packaging (MAP) stored on display counters. Pork loin slices were sealed in MAP trays under two proportions of O2/CO2/N2: High-Ox-MAP (30/40/30) and Low-Ox-MAP (5/20/75). Changes in pH, color, thiobarbituric acid reactive substances (TBARS), Warner−Bratzler shear force (WBSF), and microbiology (total viable counts, Enteriobacteriaceae, and lactic acid bacteria) were monitored over 15 days post-mortem at 4 °C. VIS-NIR spectra were collected from pork fillets before (through the film cover) and after opening the trays (directly on the meat surface) with a portable LABSPEC 5000 NIR system in diffuse reflectance mode (350−2500 nm). Quantitative NIR models by partial least squares regression (PLSR) showed a promising prediction ability for meat color (L*, a*, C*, and h*) and microbiological variables (R2VAL > 0.72 and RPDVAL > 2). In addition, qualitative models using PLS discriminant analysis obtained good accuracy (over 90%) for classifying pork samples as fresh (acceptable for consumption) or spoiled (not acceptable) based on their microbiological counts. VIS-NIR spectroscopy allows rapid evaluation of product quality and shelf life and could be used for on-site control of pork quality.

Evaluation of cosmetic creams containing Black cumin (Nigella sativa)-Lemon balm (Melissa officinalis L.)-Aloe vera (Aloe barbadensis miller) essences by modeling with Box Behnken method in Design Expert

In this investigation regarding medicinal and aromatic plants, an experimental study was conducted on the effectiveness of black cumin, lemon balm and Aloe vera essences in cosmetic creams, which were selected for their beneficial biological activities such as anti-inflammatory, moisturizing etc. In line with this study stability test, which was important in the quality evaluation of cosmetic products, was carried out. Cream samples containing different concentrations of black cumin and lemon balm essences were kept at under 3 different temperature conditions as 0 °C, 25 °C and 40 °C and the necessary values were recorded. In this direction, the effects of the temperature on the physical and chemical properties of the cosmetic creams were assessed. Homogenization and colors as physical properties and pH value of the herbal cream samples were examined. It was observed that the pH value, which was an important parameter for skin care products, was 6.5 under the optimum experimental condition and it was an acceptable value for skin creams according to the literature. In the second part of the experimental study, the effect of the essence obtained from the Aloe vera plant on the samples was tested with the optimum condition selected from 17 different experimental sets by using the Design Expert optimization application. In addition, from the production of cosmetic products; it was necessary to pay attention to the environmental conditions stipulated in storage, transportation, and sales points. As a result of the tests, it was seen that the medicinal and aromatic plants used could be evaluated in the field of cosmetics and successful results could be obtained.

Re-circulating indoor vertical farm: Technicalities of an automated duckweed biomass production system and protein feed product quality evaluation

Duckweeds are fast-growing and nutritious plants, which are gaining increased attention in different fields of application. Especially for animal nutrition, alternative protein sources are needed to substitute soybean meal. The current bottleneck is the standardized production of biomass, which yields stable quantities of a defined product quality. To solve this problem, an indoor vertical farm (IVF) for duckweed biomass production was developed. It consists of nine vertically stacked basins with a total production area of 25.5 m2. The nutrient solution, a modified N-medium, re-circulated within the IVF with a maximum flow rate of 10 L min−1. Nutrients were automatically added based on electrical conductivity. In contrast, ammonium was continuously supplied. A water temperature of 23 °C and a light intensity of 105 μmol m−2 s−1 with a photoperiod of 12:12 h were applied. During a 40-day production phase, a total of 35.6 kg of fresh duckweed biomass (equals 2.1 kg of dried product) was harvested from the IVF. On average, 0.9 kg day−1 of fresh biomass was produced. The dried product contained 32% crude protein (CP) and high levels of proteinogenic amino acids (e.g. lysine: 5.42 g, threonine: 3.85 g and leucine: 7.59 g/100 g CP). Biomass of this quality could be used as a protein feed alternative to soybean meal. The described IVF represents a modular model system for duckweed biomass production in a controlled environment and further innovations and upscaling processes.

Reliability optimization of flexible test system based on pyro-mechanical device products production driven

The quality evaluation of aerospace pyro-mechanical device products(PDPs) is very important to the safety of aerospace engineering. Aerospace PDPs are small-lot batch, multiple batches and one-off products which rely on the analysis of ignition test with limited samples. To accommodate multiple batches and small-lot batch of aerospace PDPs, the flexible test system(FTS) switches between different batches of products by the selection of instruments and channels. The conventional test mode is driven by the completion time of batch products, which usually leads to frequent switching of instruments and channels and affects the reliability of test system. Therefore, the FTS is configured according to the completion of production missions within a certain time period in the future. This paper considers the FTS of aerospace PDPs as a phased mission system, and designs the corresponding dynamic Bayesian network(DBN) model. A test of one batch is taken as a phase of phased mission system. In order to improve efficiency and optimize reliability of the aerospace PDPs FTS, the receding horizon optimization problem is constructed. Numerical experiments show that the FTS with phased mission model can optimize the test sequence during the test process, which improves efficiency and reliability of test system.