Guidelines on reporting treatment conditions for emerging technologies in food processing.

In the last decades, different non-thermal and thermal technologies have been developed for food processing. However, in many cases, it is not clear which experimental parameters must be reported to guarantee the experiments' reproducibility and provide the food industry a straightforward way to scale-up these technologies. Since reproducibility is one of the most important science features, the current work aims to improve the reproducibility of studies on emerging technologies for food processing by providing guidelines on reporting treatment conditions of thermal and non-thermal technologies. Infrared heating, microwave heating, ohmic heating and radiofrequency heating are addressed as advanced thermal technologies and isostatic high pressure, ultra-high-pressure homogenization sterilization, high-pressure homogenization, microfluidization, irradiation, plasma technologies, power ultrasound, pressure change technology, pulsed electric fields, pulsed light and supercritical CO2 are approached as non-thermal technologies. Finally, growing points and perspectives are highlighted.

Integration of Digital Twin, Machine-Learning and Industry 4.0 Tools for Anomaly Detection: An Application to a Food Plant.

This work describes a structured solution that integrates digital twin models, machine-learning algorithms, and Industry 4.0 technologies (Internet of Things in particular) with the ultimate aim of detecting the presence of anomalies in the functioning of industrial systems. The proposed solution has been designed to be suitable for implementation in industrial plants not directly designed for Industry 4.0 applications. More precisely, this manuscript delineates an approach for implementing three machine-learning algorithms into a digital twin environment and then applying them to a real plant. This paper is based on two previous studies in which the digital twin environment was first developed for the industrial plant under investigation, and then used for monitoring selected plant parameters. Findings from the previous studies are exploited in this work and advanced by implementing and testing the machine-learning algorithms. The results show that two out of the three machine-learning algorithms are effective enough in predicting anomalies, thus suggesting their implementation for enhancing the safety of employees working at industrial plants.

Environmental benefits of pet food obtained as a result of the valorisation of meat fraction derived from packaged food waste.

The 2030 Agenda of the United Nations includes the objective of setting up sustainable production patterns by pursuing several Sustainable Development Goals. Among them, the "Responsible production and consumption" is a key topic in the food production and is strictly connected with the "Climate action"; the crucial point, however, is how to jointly act on all these aspects and apply them in practice. The waste yearly produced in the food chain represent both an ethical, economic and environmental issue. In particular, as far as the recovery of packaged food waste from retailers is concerned, the valorisation of the wasted meat is an extremely relevant issue. Pet food industries could be interested in valorising this waste fraction to replace meat coming from slaughters in their product recipes. This article evaluates the environmental impact of valorising meat fraction from packaged food waste to produce two different recipes of high quality pet food, called Natura and Pâté. A life cycle assessment of the current scenario (traditional pet food production and landfilling of packaged food waste) and of a new one (pet food production using meat fraction from packaged food waste) is carried out applying the ReCiPe 2016 method of impact assessment. Real data have been taken from retailers and pet food manufacturer. The production of pet food using the meat fraction from packaged food waste generates on average lower environmental impacts if compared to the traditional process, in terms of GWP (-56.40%), water consumption (-22.62%), land use (-87.50%) and fossil resource scarcity (-21.78%). Benefits are interesting even if considering the production of Pâté (-14.66%), for which the traditional production process makes use of some slaughter by-products. The proposed industrial process is demonstrated to be sustainable from an environmental point of view and appears to be in line with Sustainable Development Goals (SDGs) 2, 12 and 13.

Sustainability of food waste biorefinery: A review on valorisation pathways, techno-economic constraints, and environmental assessment.

The need to increase circularity of industrial systems to address limited resources availability and climate change has triggered the development of the food waste biorefinery concept. However, for the development of future sustainable industrial processes focused on the valorisation of food waste, critical aspects such as (i) the technical feasibility of the processes at industrial scale, (ii) the analysis of their techno-economic potential, including available quantities of waste, and (iii) a life cycle-based environmental assessment of benefits and burdens need to be considered. The goal of this review is to provide an overview of food waste valorisation pathways and to analyse to which extent these aspects have been considered in the literature. Although a plethora of food waste valorisation pathways exist, they are mainly developed at lab-scale. Further research is necessary to assess upscaled performance, feedstock security, and economic and environmental assessment of food waste valorisation processes.