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In this work, the authors aim to present a compact low-cost and portable spectral imaging system for general purposes. The developed system provides information that can be used for a fast in situ identification and classification of samples based on the analysis of captured images. The connectivity of the instrument allows a deeper analysis of the images in an external computer.

The wavelength selection of the system is carried out by light multiplexing through a light-emitting diode panel where eight wavelengths covering the spectrum from ultraviolet (UV) to near-infrared region (NIR) have been included. The image sensor used is a red green blue – infrared (RGB-IR) micro-camera controlled by a Raspberry Pi board where a basic image processing algorithm has been programmed. It allows the visualization in an integrated display of the reflectance and the histogram of the images at each wavelength, including UV and NIRs.

The prototype has been tested by analyzing several samples in a variety of applications such as detection of damaged, over-ripe and sprayed fruit, classification of different type of plastic materials and determination of properties of water.

The designed system presents some advantages as being non-expensive and portable in comparison to other multispectral imaging systems. The low-cost and size of the camera module connected to the Raspberry Pi provides a compact instrument for general purposes.

Food manufacturing supply chain systems are the most relevant wheels of the world economy since they provide essential products supporting daily life. Nevertheless, various supply inefficiencies have been reported to compromise food safety in different regions. Sustainable supplier management and digitalization practices have become cornerstone activities in addressing these shortcomings. Therefore, this paper proposes an integrated method for sustainability management in digital manufacturing supply chain systems (DMSCS) from the food industry.

The Intuitionistic Fuzzy Analytic Hierarchy Process (IF-AHP) was used to weigh the criteria and subcriteria under uncertainty. Second, the Intuitionistic Fuzzy Decision-Making Trial and Evaluation Laboratory (IF-DEMATEL) was applied to determine the main DMSCS sustainability drivers whilst incorporating the expert's hesitancy. Finally, the Combined Compromise Solution (CoCoSo) was implemented to pinpoint the weaknesses hindering DMSCS sustainability. A case study from the pork supply chain was presented to validate this method.

The most important criterion for DMSCS sustainability management is “location” while “manufacturing capacity” is the most significant dispatcher.

This paper presents a novel approach integrating IF-AHP, IF-DEMATEL, and CoCoSo methods for sustainability management of DMSCS pillaring the food industry.

The purpose of this paper is to characterize consumers of traditional foods, taking as case study fresh cheeses produced in a village, in Central Mexico.

Semi-structured interviews were applied to a sample of 150 consumers, selected by non-probabilistic convenience sampling. A factorial analysis by principal component analysis was performed to the data, followed by a cluster analysis.

Four factors were obtained, named: artisanship, health and well-being, liking, and satisfaction with the purchase. Three consumer groups were identified: practical, in the process of valorization, and with liking and tradition. The socioeconomic characteristics of consumers do not have a relationship in the classification of groups. It is concluded that the consumption of fresh cheeses is due to a number of social and cultural attributes, and in lesser proportion, to economic aspects.

At present, as part of life in a dynamic society, people have the power of choice in the food they consume, a process that involves cultural, social, economic, political, and ideological aspects, established by the consumers themselves, or by a determined social group to which they belong. This has not been researched in Mexico. Being an emerging economy immersed in a rapid process of globalization, studies like this contribute in similar countries of Latin America and other places to find ways to valorize local foods and products that play important roles in the development of rural communities.

This study aims to explore how the attitudes, motivations and practices of informal entrepreneurs, who choose service exclusion, prevent them from recognizing and taking advantage of transformative opportunities and embracing change.

The authors conducted a two-year study to explore five types of informal entrepreneurs (musicians, street vendors, artists, owners of informal smoke shops and street food vendors). The authors used semi-structured interviews and applied thematic analysis (ATA) of popular music and narratives to shed light on their attitudes, motivations and practices.

The study shows how potential service participants freely exclude themselves from services and transformative service initiatives, preventing them from realizing opportunities and embracing change that can improve their well-being. The study also demonstrates that to serve human needs fairly, service designers need to recognize that some actors require more attention and resources than others to achieve their potential.

The study challenges the notion that any population experiencing vulnerability wants help and chooses to participate in transformative service initiatives. Service participants can, in fact, exclude themselves from services and transformative service initiatives by free will, demonstrating that service exclusion is a multidirectional phenomenon, not unidirectional. Additionally, the paper analyzes narratives gathered from aesthetic expressions, using principles of ATA, introducing music thematic analysis as a research approach.