Quality Assessment Of Products Research Articles

Participation and commercialization in producer cooperatives: Insights on the role of cooperative functioning and equity strategies

AbstractIn sub‐Saharan Africa, there are growing calls for policy reforms to revive the farmer cooperative movement. However, questions remain over whether farmer participation in agricultural cooperatives brings the desired innovation for markets and commercialization. This study uses a sample of 206 farmers from northern Uganda to examine what drives farmer participation and commercialization among members of groundnut producer cooperatives. Results from a two‐stage Heckman regression reveal that cooperative functioning in the form of hiring equipment to farmers, value addition, farmer training, and product quality assessment drives farmer participation in cooperative business. The study also shows that equity strategies, notably through subscription fees and farm‐inputs supply negatively impact commercialization among cooperative participant farmers. This study deepens the literature on cooperatives pinpointing the role of cooperative services in farmer participation and how stringent equity strategies reduce farmer commercialization among cooperative participants. We call for policy interventions that prioritize capacity building of producer cooperatives for improved functioning and better provision of services. This approach will enable these cooperatives to be effectively harnessed for market innovation.

Multi-Attribute Method (MAM) Analytical Workflow for Biotherapeutic Protein Characterization from Process Development to QC.

The multi-attribute method (MAM) has emerged significantly in recent years to support biotherapeutic protein characterization from process development to the QC environment. MAM is a liquid chromatography mass spectrometry (LC-MS) based peptide mapping approach, which combines the benefits from liquid chromatography coupled to high resolution accurate mass mass spectrometry (LC-HRAM MS), enabling direct assessment of protein sequence and product quality attributes with site specificity. These product quality attributes may impact efficacy, safety, stability, and process robustness. MAM is intended to replace conventional analytical approaches as it offers a more streamlined strategy for parallel monitoring of multiple attributes in a single analysis with high sensitivity and confidence, and ultimately supports more robust Quality by Design (QbD) approaches and faster decision cycles for biotherapeutic development. MAM consists of three main stages. The first stage is sample digestion, which typically entails proteolytic digestion of the protein. The second stage is reversed-phase chromatographic separation of the generated peptides and detection by HRAM MS in two phases. During MAM Phase I (discovery phase), data-dependent acquisition (DDA) MS/MS is performed to enable confident identification of peaks and development of a peptide workbook. During MAM Phase II (monitoring phase), full MS acquisition is only carried out for the monitoring of predefined product quality attributes (PQAs). The third stage is data processing, which entails analysis and reporting for each of the two phases including evaluation of sequence coverage, assessment of PQAs and peptide workbook creation during phase I, and targeted monitoring of predefined product attributes and new peak detection (NPD) during phase II. The latter is a comparative analysis that uses a base peak alignment algorithm to determine any non-monitored differences between the LC-MS chromatograms of a test sample and a reference standard. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: In-solution sample digestion Alternate Protocol: Automated sample digestion Basic Protocol 2: Reversed-phase chromatographic separation and detection by HRAM-MS (RPLC-HRAM MS) Basic Protocol 3: Data processing and reporting.

PENGARUH MEDIA PEMBELAJARAN E-ATLAS DENGAN MOTIVASI BELAJAR SISWA SMA

E-Atlas was assessed using an assessment instrument in the form of a product quality assessment questionnaire by 1 media expert, 1 material expert, and paired t-test of 15 class XI students at SMA. The results of the E-Atlas of So (Scleroderma aurantium) Morphological Character assessment by media experts obtained an average score of 83.75% with quality in the feasible category, material experts scored 89.6% with quality in the very feasible category, and the biology teacher's assessment get a value of 96.25% with quality in the very decent category. The results of the paired t-test were found to be Sig.(2-tailed) of 0.000 0.05, so it can be concluded that there is a significant difference between the results of data collection before and after being given E-Atlas media.

Bio-impedance measurements for meat quality determination of pork loins under repeated freeze-thaw treatments

Evaluation of key quality traits in the cold chain is an important factor in ensuring meat safety. To meet the demands of consumers, development of non-destructive detection methods is essential for quality assessment of meat products. Electrical impedance spectroscopy (EIS) has emerged as one promising non-destructive technique in the food industry. In this study, EIS was developed to investigate the effects of freeze-thawing on quality parameters of porcine meat. Bioimpedance from 20 Hz to 200 kHz was collected from frozen-thawed meat, and the experimental impedance data were fitted to a Cole impedance model. The model fitting resulted in corresponding determination coefficient values of the resistance R and the reactance X, for needle electrodes (R2R=0.9683; R2X =0.9063) and plate electrodes (R2R=0.9442; R2X =0.8347). The Cole-impedance model well represented the collected bioimpedance datasets with standard deviations of 0.9611 Ω for needle electrodes and 0.9272 Ω for plate electrodes. Furthermore, there were significant differences in the Cole-impedance model parameters, which were attributed to the formation of ice crystals that implied cell membrane degeneration during freeze-thawing. Our results highlight the potential of bio-impedance measurements, gaining better insight on quality defects assessing in freeze-thawed meat.

The Development of Apple MRI Dataset for Internal Quality Analysis

Internal quality assessment of agricultural products is challenging for exporting premium quality of Agri products like apple fruits. In this, we have analyzed the internal quality of apple fruits by a non-destructive method. We have developed our own dataset of MR images of apples by subjecting 21 apples into MRI scanning for the development of robotics detection of internal defects in apples. This MRI scanning led into 196 MR images Comparative study was carried out on the basis of MRI images with respective external photographic images of apple fruits. The apples were grouped into four categories depending on external and internal defects. By this study, we can easily identify the percentage and area of the defect without affecting the physical appearance of the apple.

Development of Animation Video Learning Media Loaded Contextual on Reaction Material Redox Using Web Apps Animaker

Redox materials contain many abstract concepts. Therefore, an animated video is needed to illustrate abstract material to make it more concrete and easier to understand. This study aims to develop animated videos with contextual content on redox reaction materials using Web Apps Animaker and know the product's quality. The data collection procedure was carried out based on the 4 steps of 4D development model (define, design, develop, and disseminate). Data collection techniques used are interview, questionnaires, and product assessment. Product assessment is carried out by material experts, media experts, reviewers, and student responses. The data obtained were analyzed using qualitative and quantitative approaches. The results of product quality assessment by material experts got 92% in the very good category, media experts got 90% in the very good category, and reviewers got 95% in the very good category. Class X high school students responded positively to the product developed with a percentage of 94.5%. Based on the results of the assessment, the videos developed can be used as alternative media for student learning independently or in groups. The developed media can also help teachers to create more innovative learning

Comparing the potential of IR-spectroscopic techniques to gas chromatography coupled to ion mobility spectrometry for classifying virgin olive oil categories.

Virgin olive oil (OO) can be classified into three different categories: extra virgin, virgin and lampante. The official method for this classification, based on physicochemical analysis and sensory tasting, is considered useful and effective, although it is a costly and time-consuming process. The aim of this study was to assess the potential of some analytical techniques for classifying and predicting different OO categories to support official methods and to provide olive oil companies with a rapid tool to assess product quality. Thus, mid and near infrared spectroscopies (MIR and NIR) have been compared by using different instruments and with head-space gas chromatography coupled to an ion mobility spectrometer (HS-GC-IMS). High classification success rates in validation models were obtained using IR spectrometers (>70% and>80% in average for ternary and binary classifications, respectively), although HS-GC-IMS showed greater classification potential (>85% and>90%).

Development of Google Sites Based Learning Media on Chemical Bonds with Multilevel Chemical Representation

Website-based online learning media are needed by students to make it easier to understand multilevel representations of chemistry during the COVID-19 pandemic. This study aims to develop learning media based on google sites on chemical bonding material containing multilevel chemical representations and determine product quality. This media development adapts the 4-D development model, consisting of four stages: define, design, development, and disseminate. Quality assessment was carried out by material experts, media experts, chemistry teachers, and students responded. The research instrument was a product quality assessment sheet and student response sheets. The results showed that the quality of the media developed based on the assessment by the media obtained an ideal percentage of 97.5% in the excellent category, material experts obtained an ideal percentage of 85% in the excellent category, and chemistry teachers obtained an ideal percentage of 97% in the excellent category. Learning media based on google sites on chemical bonding material containing multilevel chemical representations also responded positively with a percentage of 93.75%. It can be concluded that the developed media is suitable for use in the learning process to improve students' multi-representation abilities on chemical bonding material.

Smart manufacturing under limited and heterogeneous data: a sim-to-real transfer learning with convolutional variational autoencoder in thermoforming

ABSTRACT Data in advanced manufacturing are often sparse and collected from various sensory devices in a heterogeneous and multi-modal fashion. Thus, for such intricate input spaces, learning robust and reliable predictive models for product quality assessments entails implementing complex nonlinear models such as deep learning. However, these ‘data-greedy’ models require massive datasets for training, and they tend to exhibit poor generalization performance otherwise. To address the data paucity and the data heterogeneity in smart manufacturing applications, this paper introduces a sim-to-real transfer-learning framework. Specifically, using a unified wide-and-deep learning approach, the model pre-processes structured sensory data (wide) as well as high-dimensional thermal images (deep) separately, and then passes the respective concatenated features to a regressor for predicting product quality metrics. Convolutional variational autoencoder (ConvVAE) is utilized to learn concise representations of thermal images in an unsupervised fashion. ConvVAE is trained via a sim-to-real transfer learning approach, backed by theory-based heat transfer simulations. The proposed metamodeling framework was evaluated in an industrial thermoforming process case study. The results suggested that ConvVAE outperforms conventional dimensionality reduction methods despite limited data. A model explainability analysis was conducted and the resulting SHAP values demonstrated the agreement between the model’s predictions, theoretical expectations, and data correlation statistics.

Digital-twin deep dynamic camera position optimisation for the V-STARS photogrammetry system based on 3D reconstruction

ABSTRACT Photogrammetry systems are widely used in industrial manufacturing applications as an assistance measurement tool. Not only does it provide high-precision feedback for assembly process inspection and product quality assessment, but also it can improve the flexibility and robustness of manufacturing systems and production lines. However, with growing global competition and demands, companies are forced to enhance production efficiency, shorten production lifecycle and increase product variety by incorporating reconfigurable factory design that can meet challenging timeline and requirements. Although dynamic facility layout is widely investigated, the position selection for the photogrammetry system in dynamic manufacturing environment is usually overlooked. In this paper, dynamic layout of the V-STARS photogrammetry system is investigated and optimised in a digital-twin environment using deep reinforcement learning. The learning objectives are derived from the field of view (FoV) evaluation from point clouds 3D reconstruction, and collision detection from the digital twin simulated in Visual Components. The application feasibility of the proposed dynamic layout optimisation of the V-STARS photogrammetry system is verified with a real world industrial application.

Research on the Rheological Properties of Dough Based on Dry Flour Semi-Finished Products Using Rye Flour

The market formation of functional bakery products enriched with valuable non-traditional raw materials meets the principles of healthy nutrition and satisfies individual human needs. Dry flour semi-finished products are heterogeneous systems consisting of several components, which requires an analysis of its technological combination and mutual influence. The study aims at quality assessment of dry flour semi-finished products of various formulations using rye flour according to the “Simulator” protocol and through the “Profiler” system in automated mode on the “Mixolab Chopin” device. The water absorption capacity of the prototypes had a range of values from 52.0 to 59.7%, in the control – 57.3%. The researchers revealed rheological characteristics features of the dough obtained on the basis of different dry flour semi-finished product types due to the impact of protein-proteinase and carbohydrate-amylase complexes of individual components. The production of dough based on most of the considered dry flour semi-finished products requires less water than traditional dough based on wheat flour. The presented dry flour semi-finished products are mainly capable of forming a “stable” dough with good elasticity. The thesis presents mixolabograms together with the Mixolab Profiler function of a test sample based on a dry flour semi-finished product “Plain Rye Bread”. “Mixolab Chopin” is applicable to study the properties and quality control of dry flour semi-finished products using rye flour, additional and non-traditional raw materials. The shelf life of products based on the considered dry flour semi-finished products are at the level of shelf life of products based on wheat flour grade I.

Multivariate statistical visualisation and modelling of GC–MS data for sensory quality prediction of flavoured cider as influenced by storage time and temperature

It is important to cider producers to ensure the optimal quality of their products directly after production, and after extended shelf life. Quality assessments usually involve regular and continuous sensory evaluation conducted by trained panels. The competitive cider production environment necessitates extensive sensory analysis for new product launches, as part of quality control of existing products and during the production process. This could potentially lead to panel fatigue, less accuracy in sensory evaluation and delays in product launches. This paper describes the development of a partial least squares (PLS) model for the prediction of cider quality based on multivariate correlation of sensory and gas chromatography-mass spectroscopy (GC–MS) volatile compound profile data of a flavoured cider. Clear differences between cider samples of various batches and storage conditions could be visualised using principal component analysis (PCA). However, the developed PLS model was able to predict the commercial cider’s quality irrespective of differences in batch, storage temperature or storage time. The main compounds that are strongly associated with sensory quality and its decline during shelf-life storage were identified. This model is the first quality prediction model to be developed for South African flavoured cider which could be used to facilitate fast, consistent and accurate quality assessment in the high-pressure cider production and trade environment. Furthermore, since the model captures the sensory data obtained from a trained technical panel, it can be used to facilitate the calibration of sensory panels across production sites, reduce product development time and better optimise processes that impact sensory quality.

A Study on Consumer Behavior on Consumer Electronics and Home Appliances of Panasonic Products at Panasonic Brand Store, Naga Appliances, Bengaluru

Consumer Electronics and Home Appliances have become integral parts of contemporary living, shaping the way we interact with our surroundings and enhancing the quality of our daily lives. With the advent of smart technologies and sustainability concerns, the consumer electronics and home appliance market are witnessing dynamic shifts in consumer preferences, making it imperative to explore the underlying consumer behavior patterns. This paper delves into the intricate dynamics of consumer behavior within the distinct retail environment of the Panasonic Brand Store located at Naga Appliances in Bengaluru, seeking to unravel the myriad factors that shape consumers' choices, preferences, and purchasing decisions. Through an exploration of demographics, lifestyle choices, cultural influences, and technological trends, this research endeavors to provide valuable insights into how store visitors perceive the Panasonic brand, assess product quality, evaluate pricing, and consider after-sales services. It aims to assess the influence of demographic factors on purchase intentions, understand consumers' choices between Panasonic and other brands, analyze buying behavior across consumer segments, compare purchasing patterns with other brands, and evaluate consumer satisfaction within different socioeconomic groups.

Optimization and validation of analytical affinity chromatography for the in-process monitoring and quantification of peptides containing a C-tag

Antimicrobial peptides and proteins (AMPs) are promising alternatives to conventional antibiotics for the treatment of infections caused by multidrug-resistant bacteria. The production of recombinant AMPs is facilitated by platform technologies such as the C-tag, a sequence of four C-terminal amino acids that allows immunoaffinity capture and purification. However, the detection and quantification of such products throughout the manufacturing process is a significant challenge. We therefore used a design of experiments approach to optimize a novel high-throughput analytical immunoaffinity chromatography method for the accurate quantification of AMPs containing a C-tag, resulting in minimal analyte carryover (98.8 ± 0.1 % product elution). We then validated the method in accordance with International Conference on Harmonisation guideline Q2(R2). Validation confirmed that the method achieves high specificity, linearity, accuracy, and precision. We implemented in-process control and quantification throughout the manufacturing process, from cell lysis to the final purified product. We found that the lysate and acidic samples (pH < 2) can lead to deviations. However, following sample pretreatment, C-tag quantification reduced the error to ≤ 4 %, which is potentially superior to current non-specific quantification methods such as UV absorbance and colorimetry. Implementing this method for in-process control and quantification throughout the manufacturing process achieves the reliable assessment of product quantity and quality. This method also offers improvements over the product-specific enzyme-linked immunosorbent assay currently used for C-tagged products because it has a higher precision, accuracy and throughput, with a measurement time of 2.5 min per sample. Our analytical affinity chromatography method is therefore a valuable tool for the quantification of AMPs as part of a novel platform technology approach for C-tagged products.

Development of powtoon web apps assisted colloid system material animation video to increase students' interest in learning

Colloidal material is theoretical and abstract, making it less attractive to students studying it. This study aims to develop an animated video for colloidal system material using the Powtoon web app and test its quality. This research method is Research and Development (R&amp;D) using the ADDIE development model. Product assessment is carried out using product quality assessment sheets and student responses. Data analysis techniques use qualitative and quantitative analysis techniques described in descriptive form. The results of the evaluation of animated videos by material experts obtained an ideal percentage of 98.1% in the very good category, media experts 90% in the very good category, reviewers 94.8% in the very good variety, and students responded positively with a percentage of 93.4%. Based on the assessment results, it was concluded that the animated video developed could be used as an alternative learning medium in colloidal system material to increase students' interest in learning.

Development of E-Worksheet Based on STEAM-PjBL in Reaction Rate Material to Improve Creative Thinking Skills High School Student

The lack of creative thinking skills causes students to be less optimal in facing challenges in the era of the industrial revolution 4.0. Therefore, efforts are needed to improve students' creative thinking skills through the learning process in the classroom. This study aims to develop and determine the quality of E-Worksheet loaded with STEAM-PjBL on reaction rate material to improve students' creative thinking skills. Research conducted using 4D models (Define, Design, Development, and Disseminate). The instrument used is in the form of product quality assessment sheets and student responses. The results of the E-Worksheet assessment based on the assessment of material experts, media experts, reviewers, and student responses received an ideal percentage of 93%, 97%, 90%, and 93% in the excellent category. Based on the assessment results, the developed E-Worksheet can be used as an alternative learning medium to improve students' creative thinking skills. Keywords: STEAM-PjBL, Development Worksheet, Creative Thinking

XRF analysis searching for fingerprint elemental profile in south-eastern Sicily tomatoes

The implementation of analytical techniques able to certify food quality and origin in a fast and non-destructive way is becoming a widespread need in the agri-food sector. Among the physical non-destructive techniques, X-ray fluorescence (XRF) spectrometry is often used to analyze the elemental composition of biological samples. In this study, X-ray fluorescence (XRF) elemental profiles were measured on tomato samples belonging to different geographical areas in Sicily (Italy). The purpose of this investigation was aiming to establish a protocol for in-situ measurement and analysis able to provide quality assessment and traceability of PGI agri-food products, specifically sustaining health safety and self qualifying bio-chemical signature. In detail, sampling was performed in one of the most tomato productive area of south-eastern Sicily (Pachino district), characterised by a relative higher amount of Organic Carbon and Cation Exchange Capacity, and compared with samples from other growing areas of Sicily, falling in Ragusa province and Mt. Etna region. Experimental data were analyzed in the framework of multivariate analysis by using principal component analysis and further validated by discriminant analysis. The results show the presence of specific elemental signatures associated to several characterizing elements. This methodology establishes the possibility to disentangle a clear fingerprint pattern associated to the geographical origin of an agri-food product.

Response of Cyclopia subternata to drought stress – assessment of leaf composition, proteomics and product quality

Honeybush tea is made from the fynbos plant Cyclopia subternata, which is unique to South Africa. Cultivation takes place in its natural environment, which has a Mediterranean climate with dry summers and wet winters. During the summer, the plant is vulnerable to drought, an abiotic stress factor that is likely to affect its development and yield. This study investigated the effect of drought stress for a short duration on the leaf, as well as the quality of the herbal tea. Protein expression in the leaf was measured to gain insight into possible mechanisms used by the plant to cope with drought stress conditions. Fifteen-month-old C. subternata plants were subjected to three water treatments (control, moderately-stressed (MS), and severely-stressed (SS)) for ten days. Leaves were sampled at regular intervals throughout the treatment period to determine their relative water content (RWC). Leaves were also sampled on the 11th day for untargeted and targeted chemical composition and protein expression analyses. The remaining leaves and stems were processed to obtain the herbal tea. Descriptive sensory analysis of the herbal tea was performed to determine whether drought stress affected product quality. RWC was substantially higher (p < 0.05) in the control plants (100%) than in the MS and SS treated plants (83–90% and 47%, respectively). Untargeted analysis revealed that drought stress considerably altered leaf chemical composition. According to targeted analysis, the proline content of SS treated plants increased more than 40-fold when compared to the control, however, the treatments had no effect on the total carbohydrate and major phenolic compound content of the leaves, nor on the sensory quality of the herbal tea. Differences in the expression of 27 proteins, 24 of which were identified using proteomic analysis, were observed. During drought stress, 17 of these proteins increased, whereas seven decreased. Thirteen of the 24 identified proteins produced statistically significant results based on their Byonic scores. The findings laid the foundation for future research into the functions of drought response genes in Cyclopia species, as well as helping with the identification of stress-tolerant honeybush genotypes.

Alleviative effects of mannosylerythritol lipid-A on the deterioration of internal structure and quality in frozen dough and corresponding steamed bread

The effects of mannosylerythritol lipid-A (MEL-A) on the quality of frozen dough and corresponding steamed bread were investigated. The results revealed that the rheological properties of frozen dough were improved with the increment of MEL-A (0%-2.0%). Adding 1.5% and 2% MEL-A significantly reduced the moisture migration and enhanced the water-holding capacity of the frozen dough. Microstructure observation demonstrated that high levels of MEL-A enabled more starch granules to be embedded in the dough network. A series of product quality assessments illustrated that frozen dough steamed bread containing 2.0% of MEL-A had the largest specific volume (2.981 mL/g), the highest springiness (77.47%), more uniform and porous crumb structure. Moreover, MEL-A exhibited a positive effect on steamed bread's flavor profile, which was explored for the first time in this study. Hence, these results suggested that MEL-A has promising applications as a novel dough improver in the food industry.

A Review on Acoustics of Wood as a Tool for Quality Assessment

Acoustics is a field with significant application in wood science and technology for the classification and grading, through non-destructive tests, of a large variety of products from standing trees to building structural elements and musical instruments. In this review article the following aspects are treated: (1) The theoretical background related to acoustical characterization of wood as an orthotropic material. We refer to the wave propagation in anisotropic media, to the wood anatomic structure and propagation phenomena, to the velocity of ultrasonic waves and the elastic constants of an orthotropic solid. The acoustic methods for the determination of the elastic constants of wood range from the low frequency domain to the ultrasonic domain using direct contact techniques or ultrasonic spectroscopy. (2) The acoustic and ultrasonic methods for quality assessment of trees, logs, lumber and structural timber products. Scattering-based techniques and ultrasonic tomography are used for quality assessment of standing trees and green logs. The methods are based on scanning stress waves using dry-point-contact ultrasound or air-coupled ultrasound and are discussed for quality assessment of structural composite timber products and for delamination detection in wood-based composite boards. (3) The high-power ultrasound as a field with important potential for industrial applications such as wood drying and other applications. (4) The methods for the characterization of acoustical properties of the wood species used for musical instrument manufacturing, wood anisotropy, the quality of wood for musical instruments and the factors of influence related to the environmental conditions, the natural aging of wood and the effects of long-term loading by static or dynamic regimes on wood properties. Today, the acoustics of wood is a branch of wood science with huge applications in industry.