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Background Digitalizing food using 3-Dimensional (3D) printing is an incipient sector that has a great potential of producing customized food with complex geometries, tailored texture and nutritional content. Yet, its application is still limited and the process utility is under the investigation of many researchers. Scope and approach The main objective of this review was to analyze and compare published articles pertaining 3D food printing to ensure how to reach compatibility between the huge varieties of food ingredients and their corresponding best printing parameters. Different from previously published reviews in the same journal by Lipton et al. (2015) and Liu et al. (2017), this review focuses in depth on optimizing extrusion based food printing which supports the widest array of food and maintains numerous shapes and textures. The benefits and limitations of 3D food printing were critically reviewed from a different perspective while providing ample mechanisms to overcome those barriers. Key findings and conclusions Four main obstacles hamper the printing process: ordinance and guidelines, food shelf life, ingredients restrictions and post processing. Unity and integrity between material properties and process parameters is the key for a best end product. For each group, specific criteria should be monitored: rheological, textural, physiochemical and sensorial properties of the material its self in accordance with the process parameters of nozzle diameter, nozzle height, printing speeds and temperature of printing. It is hoped that this paper will unlock further research on investigating a wider range of food printing ingredients and their influence on customer acceptability. [ABSTRACT FROM AUTHOR]

Background Agri-food is one of the most important sectors of the industry in Europe and potentially a major contributor to the global warming. Sustainability issues in this context pose a huge challenge for several reasons: the variety of considered scales, the number of disciplines involved, the uncertainties, the out-of-equilibrium states, the complex quantitative and qualitative factors, the normative issues and the availability of data. Although important insight and breakthroughs have been attained in different scientific domains, an overarching and integrated analysis of these complex problems have yet to be realized. Scope and Approach This context creates huge opportunities for research in interaction with mathematical programming, integrative models and decision-support tools. The paper propose a computational viewpoint including questions of holistic approach, multiscale reconstruction and optimization. Some directions are discussed. Key Findings and Conclusions Several research questions based on a mathematical programming framework are emerging: how can such a framework manage uncertainty, cope with complex qualitative and quantitative information essential for social and environmental considerations, encompass diverse scales in space and time, cope with a multivariable dynamic environment and with scarcity of data. Moreover, how can it deal with different perspectives, types of models, research goals and data produced by conceptually disjoint scientific disciplines, ranging from physics and physiology to sociology and ethics? Building models is essential, but highly difficult; it will need a strong iterative interaction combining computational intensive methods, formal reasoning and the experts of the different fields. Some future research directions are proposed, involving all those dimensions: mathematical resilience, human-machine interactive learning and optimization techniques. [ABSTRACT FROM AUTHOR]