Multi-Criteria Reverse Engineering for Food: Genesis and Ongoing Advances

Infant food users' perceptions of safety: A web-based analysis approach

This paper aims to explore consumer beliefs about health hazards in infant foods by analyzing data gathered from the web, focusing on forums for parents in the UK. After selecting a subset of posts and classifying them by topic, according to the food product discussed and the health hazard discussed, two types of analyses were performed. Pearson correlation of term-occurrences highlighted what hazard-product pairs are most prevalent. Ordinary Least Squares (OLS) regression performed on sentiment measures generated from the texts provided significant results indicating positive or negative sentiment, objective or subjective language, and confident or unconfident modality associated with different food products and health hazards. The results allow comparison between perceptions obtained in different countries in Europe and may lead to recommendations concerning information and communication priorities.

Integrating collective know-how for multicriteria decision support in agrifood chains-application to cheesemaking

Agrifood chain processes are based on a multitude of knowledge, know-how and experiences forged over time. This collective expertise must be shared to improve food quality. Here we test the hypothesis that it is possible to design and implement a comprehensive methodology to create a knowledge base integrating collective expertise, while also using it to recommend technical actions required to improve food quality. The method used to test this hypothesis consists firstly in listing the functional specifications that were defined in collaboration with several partners (technical centers, vocational training schools, producers) over the course of several projects carried out in recent years. Secondly, we propose an innovative core ontology that utilizes the international languages of the Semantic Web to effectively represent knowledge in the form of decision trees. These decision trees will depict potential causal relationships between situations of interest and provide recommendations for managing them through technological actions, as well as a collective assessment of the efficiency of those actions. We show how mind map files created using mind-mapping tools are automatically translated into an RDF knowledge base using the core ontological model. Thirdly, a model to aggregate individual assessments provided by technicians and associated with technical action recommendations is proposed and evaluated. Finally, a multicriteria decision-support system (MCDSS) using the knowledge base is presented. It consists of an explanatory view allowing navigation in a decision tree and an action view for multicriteria filtering and possible side effect identification. The different types of MCDSS-delivered answers to a query expressed in the action view are explained. The MCDSS graphical user interface is presented through a real-use case. Experimental assessments have been performed and confirm that tested hypothesis is relevant.

From Biorefinery to Food Product Design: Peach (Prunus persica) By-Products Deserve Attention

There is an increasing demand for functional foods to attend the consumers preference for products with health benefits. Peach (Prunus persica), from Rosaceae family, is a worldwide well-known fruit, and its processing generates large amounts of by-products, consisting of peel, stone (seed shell + seed), and pomace, which represent about 10% of the annual global production, an equivalent of 2.4 million tons. Some studies have already evaluated the bioactive compounds from peach by-products, although, the few available reviews do not consider peach by-products as valuable materials for product design methodology. Thereby, a novelty of this review is related to the use of these mostly unexplored by-products as alternative sources of valuable components, encouraging the circular bioeconomy approach by designing new food products. Besides, this review presents recent peach production data, compiles briefly the extraction methods for the recovery of lipids, proteins, phenolics, and fiber from peach by-products, and also shows in vivo study reports on anti-inflammatory, anti-obesity, and anti-cerebral ischemia activities associated with peach components and by-product. Therefore, different proposals to recover bioactive fractions from peach by-products are provided, for further studies on food-product design.

A Systematic Literature Review on Packaging Sustainability: Contents, Opportunities, and Guidelines

The relationship between packaging and sustainability has caused the evolution of literature towards the minimization of environmental damage. The task of packaging professionals is becoming more demanding, as they need to collect information from distinct topics to stay up to date. The aim of this research is to gather information on packaging in the sustainability context to provide a systemic view of the contents, to identify opportunities, and define guidelines for packaging design. A systematic literature review of 472 papers was performed. The first step was a bibliographic search using Pack *, Sustainab *, and eco * as keywords. Secondly, the content analysis revealed the emergence of nine categories grouped in four clusters. These categories and nineteen subthemes were considered research opportunities. Going beyond the coding units of the content analysis, we have used context units to propose (i) the gathering of technical procedures to support the design phases of sustainable packaging; and (ii) the proposition of a framework based on the life cycle stages and design phases. At last, we have provided insights and guidelines that can be useful for packaging professionals.

New Insights into Cheese Microstructure

Microscopy is often used to assist the development of cheese products, but manufacturers can benefit from a much broader application of these techniques to assess structure formation during processing and structural changes during storage. Microscopy can be used to benchmark processes, optimize process variables, and identify critical control points for process control. Microscopy can also assist the reverse engineering of desired product properties and help troubleshoot production problems to improve cheese quality. This approach can be extended using quantitative analysis, which enables further comparisons between structural features and functional measures used within industry, such as cheese meltability, shreddability, and stretchability, potentially allowing prediction and control of these properties. This review covers advances in the analysis of cheese microstructure, including new techniques, and outlines how these can be applied to understand and improve cheese manufacture.

Food Supply Chains as Cyber-Physical Systems: a Path for More Sustainable Personalized Nutrition

Current food system evolved in a great degree because of the development of processing and food engineering technologies: people learned to bake bread long before the advent of agriculture; salting and smoking supported nomad lifestyles; canning allowed for longer military marches; etc. Food processing technologies went through evolution and significant optimization and currently rely on minor fraction of energy comparing with initial prototypes. Emerging processing technologies (high-pressure, pulsed electric fields, ohmic heating, ultrasound) and novel food systems (cultured biomass, 3-D bioprinting, cyber-physical chains) try to challenge the existing chains by developing potentially more nutritious and sustainable food solutions. However, new food systems rely on low technology readiness levels and estimation of their potential future benefits or drawbacks is a complex task mostly due to the lack of integrated data. The research is aimed for the development of conceptual guidelines of food production system structuring as cyber-physical systems. The study indicates that cyber-physical nature of modern food is a key for the engineering of more nutritious and sustainable paths for novel food systems. Implementation of machine learning methods for the collection, integration, and analysis of data associated with biomass production and processing on different levels from molecular to global, leads to the precise analysis of food systems and estimation of upscaling benefits, as well as possible negative rebound effects associated with societal attitude. Moreover, such data-integrated assessment systems allow transparency of chains, integration of nutritional and environmental properties, and construction of personalized nutrition technologies.