The fourth industrial revolution in the food industry—part II: Emerging food trends

Hassoun, Abdo; Bekhit, Alaa El‐Din A.; Jambrak, Anet Režek; Regenstein, Joe M.; Chémat, Farid; Morton, James D.; Guðjónsdóttir, María; Carpena, María; Prieto, Miguel A.; Varela, Paula; Arshad, Rai Naveed; Aadil, Rana Muhammad; Bhat, Zuhaib F.; Ueland, Øydis

doi:10.1080/10408398.2022.2106472

Cited by 72 publications

(34 citation statements)

References 251 publications

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“…3 | BRIEF OVERVIEW OF INDUSTRY 4.0 FOR CM Industry 4.0 comprises a variety of novel enabling technologies and their features such as AI, block chain (BC), DSA, IoT, ML and few more as detailed in Table 1 (Hassoun, Bekhit, et al, 2022). Industry 4.0 can have a direct impact on CM manufacturing and supply chain by integrating human efforts with intelligent machines for the rapidly developing global CM industry.…”

Section: Methodology Of Literature Reviewmentioning

confidence: 99%

Industry 4.0 technologies for cultivated meat manufacturing

Kamalapuram,

Choudhury

2024

Food Bioengineering

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Industry 4.0 integrates the physical, digital, and biological realms by applying digital automation in systems, processes, and manufacturing facilities. Industry 4.0 is actively shaping the development of intelligent food processing industries in cultivated meat (CM) sector. This integration plays a crucial role in accelerating progress within the global CM sector, facilitating the achievement of its objectives related to food sustainability, security, human health, environmental concerns, and hygiene. Incorporating Industry 4.0 into CM manufacturing systems empowers upstream and downstream production processes to become more intelligent and capable of self‐optimisation. However, enabling rapid adoption of Industry 4.0 by emerging startups and small to medium‐sized enterprises in the CM industry necessitates a thorough understanding of prerequisites and evaluation of technological and biological limitations. Challenges include the substantial initial costs associated with establishing Industry 4.0 infrastructure, robust cybersecurity measures to ensure effective risk management, and acquiring skilled professionals proficient in both operational and maintenance roles. Integrating Industry 4.0 with the evolving CM sector presents an exciting opportunity to foster business‐to‐business investments across various domains, including local markets, export opportunities, and the broader global consumer ecosystem.

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Section: Methodology Of Literature Reviewmentioning

confidence: 99%

Industry 4.0 technologies for cultivated meat manufacturing

Kamalapuram,

Choudhury

2024

Food Bioengineering

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“…The I4.0 approach depends on building a system that integrates everything effortlessly and conveniently. Every service and instrument is in constant contact, leading to a high level of synchronization (Hassoun et al., 2022d). In this system, high interconnection and intercommunication between physical resources and innovative technologies facilitate making the correct decision (Gajek et al., 2022; Hughes et al., 2022).…”

Section: An Overview Of I40 Technologiesmentioning

confidence: 99%

“…As consumers become more concerned about food quality and safety, the industry needs to thoroughly analyze the intrinsic and extrinsic factors that influence consumer acceptability to provide customized products (Bouchard et al, 2021;Prinyawiwatkul, 2023;Prinyawiwatkul & Chompreeda, 2017). It is anticipated that quality control and industrial operations will change significantly due to high-volume, multi-source real-time data with processing, forecasting, and tracking capabilities, encouraging the egg industry's continuous improvement (Hassoun et al, 2022b(Hassoun et al, , 2022d. For example, using multiple quality parameters for eggs from different housing systems, big data analysis could help identify any undesirable batch, and sort eggs based on freshness, fertility, gender, fabrication, and origin (Astill et al, 2020;Chen et al, 2019;Joshi et al, 2022).…”

Section: Big Data Analytics and Cloud Computingmentioning

confidence: 99%

Non‐destructive optical sensing technologies for advancing the egg industry toward Industry 4.0: A review

Ahmed,

Hossainy,

Khaliduzzaman

et al. 2023

Comp Rev Food Sci Food Safe

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The egg is considered one of the best sources of dietary protein, and has an important role in human growth and development. With the increase in the world's population, per capita egg consumption is also increasing. Ground‐breaking technological developments have led to numerous inventions like the Internet of Things (IoT), various optical sensors, robotics, artificial intelligence (AI), big data, and cloud computing, transforming the conventional industry into a smart and sustainable egg industry, also known as Egg Industry 4.0 (EI 4.0). The EI 4.0 concept has the potential to improve automation, enhance biosecurity, promote the safeguarding of animal welfare, increase intelligent grading and quality inspection, and increase efficiency. For a sustainable Industry 4.0 transformation, it is important to analyze available technologies, the latest research, existing limitations, and prospects. This review examines the existing non‐destructive optical sensing technologies for the egg industry. It provides information and insights on the different components of EI 4.0, including emerging EI 4.0 technologies for egg production, quality inspection, and grading. Furthermore, drawbacks of current EI 4.0 technologies, potential workarounds, and future trends were critically analyzed. This review can help policymakers, industrialists, and academicians to better understand the integration of non‐destructive technologies and automation. This integration has the potential to increase productivity, improve quality control, and optimize resource management toward sustainable development of the egg industry.

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“…Due to the availability of data and resources, the current contribution of analytics to achieving development goals varies by region, but the use of the presented methods is a common factor (Orhan & Guajardo, 2022). Emerging food trends, such as fortified and functional foods, additive manufacturing technologies, cultured meat, precision fermentation, and personalized food, will rely on massive amounts of information from and to the consumer that is not currently available (Hassoun et al, 2022).…”

Section: Future Trendsmentioning

confidence: 99%

A primer on predictive techniques for food and bioresources transformation processes

Sicard

Barbe²,

Boutrou

et al. 2023

J Food Process Engineering

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To meet current societal demand for more sustainable transformation processes and bioresources, these processes must be optimized and new ones developed. The evolution of various systems (raw material, food, or process attributes) can be predicted to optimize the uses of biomass for better quality, safety, economic benefit, and sustainability. Predictive modeling can guide the necessary changes and influence industrials, governmental policies and consumers decision-making. However, achieving good predictive capability requires reflection on the models and model validation, which can be difficult. This review aims to help scientists begin to predict by presenting the techniques currently used in predictive science for food and related bioproducts. First, a guideline helps readers initiate a prediction process along with final tips and a warning about the risks involved, with a particular focus on the crucial validation step. Three broad categories of techniques are then presented: empirical, mechanistic, and artificial intelligence (or "data-driven"). For each category, the advantages and limitations of current techniques for prediction are explained in light of their current domains of applications, illustrated with literature studies and a detailed example. Thus this article provides engineering researchers information about predictive modeling which is a recent relevant development in optimization of both food and nonfood bioresources processes. Practical applicationsPredictive modeling is a recent development of much relevance in the optimization of both food and nonfood bioresources processes. The goal of this article is to guide those in research or industry who would like to start predicting. Therefore, the article is intended as a primer on prediction concepts and predictive techniques for food and non-food bioresources processing. Three categories of techniques commonly used in these fields are illustrated by various examples of current applications and a more detailed example helps to understand the implementation process. An increased ability of the global scientific body to predict the outcome of various decisions, often linked or sequential, will open new avenues for designing food products with circularity in mind: maintaining value and not creating waste in the process.

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The fourth industrial revolution in the food industry—part II: Emerging food trends

Cited by 72 publications

References 251 publications

Industry 4.0 technologies for cultivated meat manufacturing

Industry 4.0 technologies for cultivated meat manufacturing

Non‐destructive optical sensing technologies for advancing the egg industry toward Industry 4.0: A review

A primer on predictive techniques for food and bioresources transformation processes

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