Product Quality Research Articles

Autonomous Self-Propelled Napa Cabbage Harvester: Cutting, Attitude Control, and Loading Modules

This paper introduces an autonomous self-propelled Napa cabbage harvester, designed to significantly improve the efficiency and effectiveness of the traditionally labor-intensive harvesting process. The harvester integrates three key modules: a cutting, an attitude control, and a loading module. The cutting module is equipped with an attitude control module that ensures precise severance of the Napa cabbage stems, minimizing damage to the crop and maintaining product quality. The attitude control module employs a backstepping-based force control that continuously adjusts the cutting angle and height to ensure consistent cutting precision, even on uneven terrain, thereby optimizing the quality of the Napa cabbages. The loading module automates the collection and transfer of harvested Napa cabbages into storage, significantly reducing the physical burden on workers and improving operational efficiency. Field experiments demonstrated improvements, including a 42–66% reduction in task time compared to manual harvesting, as well as a 37% increase in cutting accuracy through the use of autonomous control. The proposed system presents a comprehensive solution for enhancing productivity, reducing labor demands, and maintaining high crop quality in Napa cabbage harvesting, offering a practical approach to modernizing agricultural practices.

Operational excellence in online food delivery service: the role of food biosafety measures

PurposeThis study explores how food biosafety measures (FBM), electronic service quality and product quality influence consumer satisfaction and loyalty in the online food delivery service (OFDS) sector. It also integrates the technology acceptance model (TAM) and the theory of planned behaviour (TPB) to form a robust framework for assessing consumer behaviours and providing insights for this sector.Design/methodology/approachData from 877 Colombian urban consumers were collected. The proposed theoretical model was tested using structural equation modelling (SEM) in the SEMinR package of the R program (an open-source programming language).FindingsThe results reveal that food biosafety measures and product quality are the most essential factors for OFDS consumers. Besides, food biosafety measures strongly affect product and e-service quality, which in turn significantly and directly impact consumer satisfaction and loyalty. This means that it is necessary to consider both visible actions strongly related to product quality and invisible actions that highlight the role of e-service quality in ensuring operational excellence.Practical implicationsTo maintain customer satisfaction and loyalty, OFDS managers should consider first working with restaurants that practice high food biosafety measures so that the order leaves the restaurant in good condition. However, OFDS should maintain these measures to ensure operational excellence from the order on the platform until delivery to the end consumer.Originality/valueThis innovative study demonstrates how FBMs directly affect perceptions of service, product quality, satisfaction and loyalty. This goes beyond traditional findings suggesting that food biosafety measures' influence is only indirect and mediated by satisfaction.

The impact of visionary leadership on product quality from the perspective of quality assurance managers in small and medium-sized companies: the mediating role of continual improvement

PurposeA review of relevant literature supported the need to examine the nature of the relationships (if any) between visionary leadership, continual improvement and product quality. This study examined the relationship between visionary leadership and product quality and investigated the mediating role of continual improvement in the relationship between visionary leadership and product quality.Design/methodology/approachVisionary leadership, continual improvement and product quality were measured through a questionnaire developed based on a theoretical framework derived from the literature and distributed to quality assurance managers in small and medium-sized companies in the engineering, electrical and information technology sectors in Jordan.FindingsThe results indicated that the levels of visionary leadership, continual improvement and product quality are good and more from the perspective of quality assurance managers in these companies. The results also indicated that there is a positive, statistically significant relationship between visionary leadership and continual improvement and between continual improvement and product quality. Moreover, the results indicated that the relationship between visionary leadership and product quality is partially mediated by continual improvement. This indicates that there is a direct, positive and statistically significant relationship between visionary leadership and product quality.Originality/valueTo the author’s knowledge, this is the first study that examined the relationship between visionary leadership, continual improvement and product quality and investigated the mediating role of continual improvement in the relationship between visionary leadership and product quality. This study concluded that visionary leadership is the driver of all improvement initiatives and activities, which in turn improve the final products. The study contributes to the literature by revealing that visionary leadership leads to continual improvement and thus product quality, supporting the sequential relationship between them. Accordingly, the study provides useful theoretical insights and practical implications.

Elevated endoplasmic reticulum pH is associated with high growth and bisAb aggregation in CHO cells.

Chinese hamster ovary (CHO) bioprocesses, the dominant platform for therapeutic protein production, are increasingly used to produce complex multispecific proteins. Product quantity and quality are affected by intracellular conditions, but these are challenging to measure and often overlooked during process optimization studies. pH is known to impact quality attributes like protein aggregation across upstream and downstream processes, yet the effects of intracellular pH on cell culture performance are largely unknown. Recently, advances in protein biosensors have enabled investigations of intracellular environments with high spatiotemporal resolution. In this study, we integrated a fluorescent pH-sensitive biosensor into a bispecifc (bisAb)-producing cell line to investigate changes in endoplasmic reticulum pH (pHER). We then investigated how changes in lactate metabolism impacted pHER, cellular redox, and product quality in fed-batch and perfusion bioreactors. Our data show pHER rapidly increased during exponential growth to a maximum of pH 7.7, followed by a sharp drop in the stationary phase in all perfusion and fed-batch conditions. pHER decline in the stationary phase was driven by an apparent loss of cellular pH regulation that occurred despite differences in redox profiles. Finally, we found protein aggregate levels correlated most closely with pHER which provides new insights into product aggregate formation in CHO processes. An improved understanding of the intracellular changes impacting bioprocesses can ultimately help guide media optimizations, improve bioprocess control strategies, or provide new targets for cell engineering.

The Influence of Product Quality and Service Quality on Customer Loyalty Through Customer Satisfaction

Product quality an important role in the marketing strategy that can be implemented by Informa by providing the best products for its consumers to provide trust, satisfaction and a positive experience so that consumers make product purchases in the future. The purpose of this study was to determine the greatest influence of customer loyalty. This type of research is quantitative with a purposive sampling technique distributed through a questionnaire to 190 male and female respondents of Informa product customers aged 17-50 years who have made a purchase at least 1 time in the last 1 year and domiciled in Jakarta. Primary data analysis was carried out using the SEM Smart PLS method. The results of this study indicate that product quality and service quality have an effect on customer satisfaction. Furthermore, product quality and service quality have a direct effect on customer loyalty, but satisfaction does not affect customer loyalty. Customer satisfaction is not proven to be a mediation between product quality and service quality on customer loyalty. This study contributes to Informa in maintaining and increasing customer loyalty, which can be seen from several factors formed from each consumer complaint optimally and measurably. For further research, the researcher suggests expanding the research area and looking for objects in other fields.

Cross-border supply chain coordination of low-carbon agricultural products under the risk of supply uncertainty.

The purpose of this paper is to discuss how cross-border e-commerce enterprises can promote the sustainable development of the supply chain by optimizing the risk of supply disruption and product quality control mechanism of the cross-border supply chain of low-carbon agricultural products in the face of the problem of uneven quality and inventory shortage that prevails in the supply chain of low-carbon agricultural products under the framework of low-carbon economy. Methods: A two-level supply chain model consisting of a risk-averse cross-border e-commerce enterprise and two risk-neutral overseas suppliers is constructed to compare the optimal strategies and their coordination effects under the centralized and decentralized decision-making modes, and to deeply analyze the supply chain's operation mechanism. Further, the quality cost factor is introduced and an option contract model is designed to quantitatively analyze the impact of different decision-making scenarios and parameter changes on the overall supply chain performance. The results of the study show that under the coordination of option contract, the profit of cross-border e-commerce companies tends to decrease as the risk of supply disruption increases, while the profit of suppliers rises accordingly. Meanwhile, improving the quality of agricultural products can significantly improve the overall profitability of the supply chain. The cost-sharing mechanism is positively related to the profit of cross-border e-commerce companies, but negatively affects the profit of suppliers. In addition, the adjustment of the option price is directly associated with the increase of the specific supplier's profit and the decrease of the cross-border e-commerce enterprise's profit. Conclusion: By constructing and analyzing the option contract model considering the risk of supply disruption, this study effectively reveals the key influencing factors and their interactions in the cross-border supply chain of low-carbon agricultural products, and provides cross-border e-commerce enterprises with specific strategies to achieve coordination of the supply chain contract, improve product quality, and mitigate the risk of supply disruption, and then promote the sustainable development of the supply chain of low-carbon agricultural products.

Soft-sensor model development for CHO growth/production, intracellular metabolite, and glycan predictions.

Efficaciously assessing product quality remains time- and resource-intensive. Online Process Analytical Technologies (PATs), encompassing real-time monitoring tools and soft-sensor models, are indispensable for understanding process effects and real-time product quality. This research study evaluated three modeling approaches for predicting CHO cell growth and production, metabolites (extracellular, nucleotide sugar donors (NSD) and glycan profiles): Mechanistic based on first principle Michaelis-Menten kinetics (MMK), data-driven orthogonal partial least square (OPLS) and neural network machine learning (NN). Our experimental design involved galactose-fed batch cultures. MMK excelled in predicting growth and production, demonstrating its reliability in these aspects and reducing the data burden by requiring fewer inputs. However, it was less precise in simulating glycan profiles and intracellular metabolite trends. In contrast, NN and OPLS performed better for predicting precise glycan compositions but displayed shortcomings in accurately predicting growth and production. We utilized time in the training set to address NN and OPLS extrapolation challenges. OPLS and NN models demanded more extensive inputs with similar intracellular metabolite trend prediction. However, there was a significant reduction in time required to develop these two models. The guidance presented here can provide valuable insight into rapid development and application of soft-sensor models with PATs for ipurposes. Therefore, we examined three model typesmproving real-time product CHO therapeutic product quality. Coupled with emerging -omics technologies, NN and OPLS will benefit from massive data availability, and we foresee more robust prediction models that can be advantageous to kinetic or partial-kinetic (hybrid) models.

Escherichia coli as a sentinel in the assessment of antimicrobial resistance in the tilapia production chain: from production environment to the final product

IntroductionThe intensification of tilapia production has increased animal density in tanks, leading to more frequent exposure to pathogenic agents and compromising the quality of fish products. Antimicrobial resistance is a global concern that affects human treatment, and sentinel microorganisms like Escherichia coli are crucial for monitoring production chains, especially in aquaculture, where research is still limited. The aim of this study was to identify the presence of E. coli and investigate its antimicrobial resistance profiles throughout the entire tilapia production chain.MethodsA total of 240 samples were collected from various points in the production process: carcasses before scaling (Ca), scaling wastewater (Sw), filleting wastewater (Fw), fillet washing wastewater (Tw), fillet handling surfaces (Su), and pre-packaged fillets (Pf). The samples were collected during 10 visits, each corresponding to animals from different farms. E. coli isolates were identified using MacConkey agar and biochemical tests. Phenotypic resistance profiles were determined using nine classes of antimicrobials. Extended- spectrum b-lactamase (ESBL) production was identified with ceftazidime and cefotaxime and confirmed by a double-disc synergy test. Isolates were classified as sensitive or resistant based on the inhibition zone. Multidrug-resistant (MDR) was defined as resistance to at least one agent in three or more antimicrobial categories, while extensively drug-resistant (XDR) was defined as resistance to at least one agent in all but two or fewer categories.ResultsOverall, 50.8% of the samples (122/240) tested positive for E. coli, with 403 isolates identified. Of these, 33% (133/403) were resistant to at least two antimicrobials, and 20% (48/240) of the samples had MDR isolates, with the highest frequency found at the filleting point (Fw), which also had the only XDR profile. Resistance was most commonly observed against amoxicillin (35.73%), tetracycline (30.77%), and ciprofloxacin (26.30%).DiscussionThese findings emphasize the importance of E. coli as an indicator of antimicrobial resistance throughout tilapia processing and highlight the need for good production practices and qualified technical support to mitigate risks to public health, animal health, and the environment.

Control of the parameters of thermosetting binders directly during the molding of products made of polymer composite materials

For aviation binders at the moment there is no necessary methodological base on the basis of which it is possible to control the conditions of their curing by viscosity, reaction rate and glass transition temperature in real time. The paper presents a method of control of thermosetting binder parameters directly during the molding process. The epoxy binder VSE-59 was studied. A mathematical model of the relationship between the frequency maximum parameter of the imaginary component of the electrical impedance and the degree of curing is given, the results of dielectric analysis are compared with laboratory methods (differential scanning calorimetry and rheometry). It is shown that the convergence of the values of the degree of conversion is high. Rheological and dielectric analyses revealed a direct correlation between electrical and rheological properties in the range of injection temperatures. Equations were determined and coefficients were experimentally selected to describe the correlation between viscosity and glass transition temperature and dielectric parameters, which provides the possibility of their control in real time. The obtained results can be used to create a hardware and software base, which makes it possible to control the state of the binder at each moment of the process of forming products from polymer composite materials, as well as to carry out optimization to eliminate the emergence of conditions of uneven polymerization. Realization of the detailed control of the binder state in different parts of the product will allow to carry out verification of calculations, to predict and avoid the occurrence of warping and, accordingly, to increase the quality of composite products.

Improvement of the safety of artisanal Spanish fermented sausages: Spotlight on the role of bacteriocinogenic Lactiplantibacillus paraplantarum against a Companilactobacillus alimentarius histaminogenic strain

Biogenic amines (BA) in fermented sausages result from amino acid decarboxylation by microbial activity, either from technological or spoilage bacteria. Certain lactic acid bacteria typically found in fermented sausages are characterised for their ability to produce BA, especially histamine and tyramine. On the other hand, the bacteriocinogenic strain Lactiplantibacillus paraplantarum BPF2, isolated from a Spanish spontaneously dry-fermented sausages, has been characterized by good technological properties, production of leucocin K with antimicrobial activity against Listeria monocytogenes and ability to reduce the accumulation of BA in the final products. The antagonistic activity of leucocin K bacteriocin was tested in vitro against Companilactobacillus alimentarius SE14 (histamine producer), Enterococcus faecalis EF37 (tyramine producer), and L. monocytogenes Scott A. The inhibition of Comp. alimentarius SE14 by Lpl. paraplantarum BPF2 was assessed in traditional Spanish fermented sausages obtained in pilot plant, and chemico-physical parameters, microbial counts, and BA accumulation were monitored during fermentation and ripening. Leucocin K produced by Lpl. paraplantarum BPF2 was active in vitro against Comp. alimentarius SE14 and L. monocytogenes but was ineffective against E. faecalis EF37. The inoculation of the strain BPF2 as starter culture did not affect the expected chemico-physical (pH and colour) and microbial characteristics of the dry-fermented sausages. On the other hand, this strain was effective to significantly reduce the accumulation of histamine produced by the strain SE14, as well as putrescine and cadaverine. These findings demonstrated the relevant role of bacteriocin-producing strains as bio-protective starter cultures in improving the safety and quality of fermented meat products.

Evaluation of Clayey Raw Materials and Ceramic Masses from Ceramic Building Material Companies Located in Northeastern Brazil

The challenge of improving the quality of ceramic products is faced worldwide, especially in areas where artisanal production is common and the need for in-depth knowledge about raw materials, together with inefficient production processes, limits the advancement of the ceramic industry. Scientifically, detailed investigation of ceramic masses’ physical, chemical and mechanical properties can provide essential insights to optimize production, contribute to developing more advanced and sustainable techniques, and increase competitiveness. This study evaluated raw clay materials and ceramic masses obtained from northeastern Brazilian, focusing on their chemical composition, mineralogical phases, thermal behavior, and particle size distribution. Rectangular samples (80 mm × 20 mm × 7 mm) prepared using uniaxial pressing (25 MPa by 30 s) were fired at different temperatures (950 and 1050 °C) and linear shrinkage, flexural strength, water absorption, and apparent porosity measurements were taken. The results showed that the companies still need to improve the production process to meet the minimum strength requirement of 1.5 MPa according to the Brazilian standard NBR 15270.

A comprehensive framework to evaluate the financial impacts of genetic improvement on wood products from planted forests

Increasing the productivity of planted forests may efficiently provide an important part of the world’s growing demand for wood while protecting natural forests. In this study, we developed an integrated modelling framework to evaluate the financial impacts of improving productivity of planted forests by tree breeding. Using this framework, we compared three genetic improvement scenarios of white spruce plantations, a key reforestation species in North America, and evaluated the differences in the derived wood product assortments in terms of quantity, quality, and revenues. Favouring the production of wood volume appears as the best way to enhance financial gains from white spruce plantations in the current market. The scenario that focused on increasing tree height produced a greater volume of wood products and larger lumber pieces, which resulted in the greatest revenues. In comparison, favouring wood stiffness over volume led to poorer results, as the increased product quality was not sufficient to surpass the financial gain associated with greater wood volumes. While we successfully provided an evaluation of the product assortments derived from genetically improved plantations, the proposed framework would benefit from more data input to help maximize financial gains from a range of tree breeding strategies.

Effects of Ultrasound on Reactive Crystallization and Particle Properties of an Aromatic Amine in Batch and Continuous modes

Ultrasound has shown its benefits in the manufacturing processes of many pharmaceuticals and fine chemicals. This study focused on the reactive crystallization system of an aromatic amine and explored the potential uses of ultrasound in both batch and continuous modes. In batch experiments, we studied the effects of different sonication conditions including power, duration, and starting point on final particle properties. Under ultrasound, the crystal form and crystal morphology remained well maintained. The results of particle size and size distribution suggested that ultrasound reduced the mean sizes by improving the nucleation process and breaking up large particles. Additionally, the presence of ultrasound in continuous experiments was capable of inducing nucleation and the crystal products collected had a suitable distribution. Integrating ultrasound into the beginning of the continuous crystallization process can be an alternative to the seeding technique. The increasing sonication power did not reduce the induction time substantially. This indicated that a rational sonication condition should balance the overall process efficiency and energy consumption. The findings from batch and continuous experiments indicate that ultrasound could intensify industrial crystallization of the aromatic amine. Incorporating energy-efficient ultrasound with the continuous process will potentially lead to increased production efficiency and a well-controlled product quality.

A Programmable Handheld Extrusion-Based Bioprinting Platform for In Situ Skin Wounds Dressing: Balance Mobility and Customizability.

Bioprinting technology plays a crucial role for constructing tissue substitutes. However, the mismatched scaffold shapes and the poor treatment timeliness limit its clinical translational application. In situ printing technology that prints bioregenerants directly inside patient's body can meet the needs of specific tissue repair. This study develops a smartphone controlled handheld bioprinter for in situ skin wounds dressing. The mini bioprinter can be handheld and placed on any printing surface to create strips, complex patterns, and 3D structures, and can be equipped with microchannel needles to expand functionality. The size of the strips as well as the printing path can be programmed and controlled by the smartphone to ensure the precision of the printed product quality. Furthermore, the device not only allows for smooth switching between different bioinks for printing heterogeneous structure, but also allows for fast and uniform coverage of large wound surfaces. When dealing with complex wounds in vitro & vivo, the printer can effectively fill and precisely close wounds, promoting wound healing. The programmable handheld bioprinter can balance mobility and customizability in the management of skin wounds and is expected to realize its potential for emergency medical treatment in condition-constrained scenarios, such as battlefields or disaster areas.

Anomaly detection in smart manufacturing: An Adaptive Adversarial Transformer-based model

In Industry 5.0, smart manufacturing brings additional intricacies and novel data processing challenges. Given the evolving nature of manufacturing processes and the inherent complexity of data, including noise and missing entries, achieving accurate anomaly detection becomes even more intricate. Conventional methods often miss nuanced anomalies, especially when dealing with high-dimensional, multivariate, non-stationary data. These data types are typical of smart manufacturing environments. Hence, many recent approaches have embraced deep learning to confront these challenges, making use of diverse attention mechanisms to acquire data representations. However, in manufacturing, where the dynamics of time series data change over time, methods relying solely on pointwise or pairwise representations often fall short. Thus, ensuring product quality and operational integrity calls for even more advanced methodologies. The deficiency lies in the capability of state-of-the-art models to effectively capture abnormal patterns while considering both local and global contextual information. This challenge is compounded by the rarity of anomalies, making it exceedingly challenging to establish substantial associations between individual abnormal points and the entire time series. To tackle these challenges, we introduce the “Adaptive Adversarial Transformer” as a novel deep learning technique that combines Transformer architecture with an anomaly attention mechanism and Adversarial Learning. Our Model effectively captures intricate temporal patterns, distinguishes normal and anomalous behaviors, and dynamically adjusts thresholds to align with the evolving dynamics of time-series data. Empirical validation on four benchmark datasets and three real-world manufacturing datasets demonstrates our model’s effectiveness compared to the state-of-the-art, as evidenced by the F1-Score.

Microencapsulation Efficiency of Carboxymethylcellulose, Gelatin, Maltodextrin, and Acacia for Aroma Preservation in Jasmine Instant Tea.

Enhancing the sensory appeal of jasmine instant tea, particularly its aroma, poses a significant challenge due to the loss of volatile organic compounds during conventional processing. This study introduces a novel approach to address this issue through the application of microencapsulation techniques, aimed at preserving these key aromatic elements. Our investigation focused on the encapsulating agents gelatin, acacia gum, carboxymethylcellulose (CMC), and maltodextrin, chosen for their compatibility with the volatile organic compounds of tea. A statistical analysis was conducted on the analytical results through comprehensive analytical techniques like Principal Component Analysis (PCA), Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA), and Variable Importance in Projection (VIP) analysis for microcapsule characterization. The statistical analysis revealed gelatin to be a particularly effective encapsulating medium, preserving an aroma profile more akin to fresh tea. The statistical analysis confirmed the reliability of these findings, highlighting the potential of microencapsulation in refining the quality of jasmine instant tea products. The results of this research suggest that microencapsulation could be instrumental in improving the sensory quality and shelf life of instant tea products, offering new opportunities for product enhancement in the beverage industry.

An integrated prototyping tool to enhance interdisciplinary communication in smart product design

The increasing integration of smart products into society is noteworthy in the field of Prospective Ergonomics (PE), as they herald the emergence of novel products featuring yet-to-be-discovered interaction modalities. Literature highlights a lack of front-end prototyping approaches that transcend disciplinary skills and aid communication across diverse design fields, highly relevant in early-stage smart product development. This paper introduces an integrated, low-fidelity prototyping tool to enhance interdisciplinary communication and understanding of future products’ interactive and environmental qualities. A survey provides preliminary validation of the integrated tool’s format and content. Findings endorse the tool’s structure and flexibility in supporting understanding and communication of interactive and environmental qualities of smart product concepts across a range of design disciplines. As such we advance the discourse on PE by envisioning a low-fidelity prototyping tool to create intermediary objects supporting design efforts towards future products and their new and emerging interaction modalities.

Advance industrial monitoring of physio-chemical processes using novel integrated machine learning approach

With the rapid transition of Industry 4.0 to 5.0, modern industrial physio-chemical processes are characterized by two critical challenges: process safety and the quality of the final product. Traditional industrial monitoring methods have low reliability in accuracy and robustness, and they are inefficiently providing satisfactory results. This paper introduces a novel integration technique that employs machine learning (ML) to tackle the challenges associated with real industrial monitoring in physical and industrial processes. The proposed framework integrates distributed canonical correlation analysis - R-vine copula (DCCA-RVC), global local preserving projection (GLPP), and 2-Dimensional Deng information entropy (2-DDE). The framework's ability and productivity are assessed utilizing existing approaches such as wavelet-PCA, MRSAE, and DALSTM-AE and the new proposed novel integrated machine learning-based (DCCA-RVC) approach as benchmarks for model performance. The proposed novel approach has been validated by testing it on the ethanol-water system distillation column (DC) and Tennessee Eastman Process (TEP), utilizing it as actual industrial benchmarks. The results demonstrate that the novel integration ML-technique (DCCA-RVC) T22 – GLP monitoring graphs for the fault class type 1 in the distillation column showed a (FAR) of 0 %, a (FDR) of 100 %, a precision of 100 %, F1-score of 100 % and an accuracy of 100 %. However, for the TEP process failure event 13, the (FAR) was 0 %, the (FDR) was 99 %, the accuracy was 100 %, the F1-score was 99.5 %, and the accuracy was 99.5 %.

MỘT SỐ VẤN ĐỀ LÍ LUẬN TRONG ĐÀO TẠO THẠC SĨ QUẢN LÍ GIÁO DỤC ĐÁP ỨNG YÊU CẦU PHÁT TRIỂN NGUỒN NHÂN LỰC CHẤT LƯỢNG CAO, TRÌNH ĐỘ CAO

In recent years, the training of the master's program in educational management in our country has developed strongly, making an important contribution to improving the quality of educational management staff. However, the training courses today still face various limitations and inadequacies that affect the quality of training. Using the theoretical research method, the article has pointed out several characteristics in the training of master's in educational management to meet the requirements of developing high-quality and highly qualified human resources in our country today such as characteristics of students; High requirements for quality, ethics, and capacity of training products; The continuous, systematic and intensive nature of the training process; complexity in designing and implementing training programs to meet the needs of students, and so on. Research results are an important scientific basis for building several specific criteria in training master's in management. Educational principles need to meet the requirements of developing high-quality and highly qualified human resources.

The benefits of the dairy value chain to inclusive sustainable development in European highlands: a systems thinking approach

This research investigates the benefits of the dairy value chain beyond food provision, and its contribution to inclusive sustainable development (ISDH) in European highlands. Transdisciplinary teams interviewed and analysed 11 cases related to the dairy value chain sourced from three highland regions in Europe: Alps (Austria, France, Italy), Massif Central (France), Pyrenees (Spain). Actors interviewed were farmers, cooperatives, retailers and associations. A systems thinking approach was applied to develop a conceptual map (Causal Loop Diagram, CLD) describing the contribution of the dairy value chain to ISDH, through the interpretation of the viewpoints of interviewed actors. For each case, the factors contributing to ISDH were identified, then clustered within related topics. Topics from all the cases were used to develop a CLD, and subsystems and leverage points identified. Six interconnected subsystems were identified: local resources, environment, dairy production, collaboration, supply chain and socio-economic. Four leverage points were also identified: public subsidies, feed autonomy, certification of product, and added value. In conclusion, the dairy value chain provides the following benefits aligned with the dimensions of ISDH: landscape maintenance and ecosystem services, quality of dairy products and added value, inclusive governance for actors, reduction of environmental impact, and local development. This model delivers a decision-making tool for the actors involved in the dairy value chain, to prioritise strategic interventions.