Additive manufacturing (AM) has gained significant attention due to its ability to drive technological development as a sustainable, flexible, and customizable manufacturing scheme. Among the various AM techniques, direct ink writing (DIW) has emerged as the most versatile 3D printing technique for the broadest range of materials. DIW allows printing of practically any material, as long as the precursor ink can be engineered to demonstrate appropriate rheological behavior. This technique acts as a unique pathway to introduce design freedom, multifunctionality, and stability simultaneously into its printed structures. Here, a comprehensive review of DIW of complex 3D structures from various materials, including polymers, ceramics, glass, cement, graphene, metals, and their combinations through multimaterial printing is presented. The review begins with an overview of the fundamentals of ink rheology, followed by an in‐depth discussion of the various methods to tailor the ink for DIW of different classes of materials. Then, the diverse applications of DIW ranging from electronics to food to biomedical industries are discussed. Finally, the current challenges and limitations of this technique are highlighted, followed by its prospects as a guideline toward possible futuristic innovations.

Direct Ink Writing: A 3D Printing Technology for Diverse Materials

Deep learning has been proved to be an advanced technology for big data analysis with a large number of successful cases in image processing, speech recognition, object detection, and so on. Recently, it has also been introduced in food science and engineering. To our knowledge, this review is the first in the food domain. In this paper, we provided a brief introduction of deep learning and detailedly described the structure of some popular architectures of deep neural networks and the approaches for training a model. We surveyed dozens of articles that used deep learning as the data analysis tool to solve the problems and challenges in food domain, including food recognition, calories estimation, quality detection of fruits, vegetables, meat and aquatic products, food supply chain, and food contamination. The specific problems, the datasets, the preprocessing methods, the networks and frameworks used, the performance achieved, and the comparison with other popular solutions of each research were investigated. We also analyzed the potential of deep learning to be used as an advanced data mining tool in food sensory and consume researches. The result of our survey indicates that deep learning outperforms other methods such as manual feature extractors, conventional machine learning algorithms, and deep learning as a promising tool in food quality and safety inspection. The encouraging results in classification and regression problems achieved by deep learning will attract more research efforts to apply deep learning into the field of food in the future.

https://onlinelibrary.wiley.com/doi/epdf/10.1111/1541-4337.12492

Application of Deep Learning in Food: A Review.

Background: Food 3 D printing is an emerging food processing technology. Due to the advantages of functionalization, customization, personalized nutrition design, simplified supply chain an...

3D printing of food: pretreatment and post-treatment of materials

Background 4D printing technology has attracted extensive attention in academic and industrial circles since 2013 although commercialization still requires additional research and development. 4D food printing is an extension of 3D printing, which permits customization of new food products. Compared with aerospace, automobile, robotics, biomedicine and materials etc, there are few reviews on 4D food printing. Scope and approach This review shows recent advances in 4D printing technology applied to foods. To adapt current 4D printing technology to foods it is necessary to improve the extrusion printer and develop the necessary software. Aspects of recombination of different food materials and reasons of alterations in color, shape, flavor and nutrition via 4D food printing are discussed critically. The key to the success of 4D food printing and diverse solutions to the corresponding problems are outlined and analyzed. Future prospects for 4D food printing technology are discussed along with research and development needs. Key findings and conclusions At present, 4D food printing experiment is mainly based on soy protein isolate, starch and hydrogels and is realized through material properties, internal structural design and spatial arrangement of recombined food materials. The stimulation factors responsible for causing alteration of 3D printed products include pH, water absorption, microwave and temperature, resulting in deformation, modification of color, flavor and nutritional value. It is noteworthy that 4D food printing is still at research stage. There are opportunities for enhancement in the link between internal structure and stimulation, design of the printer, printing software, printing materials as well as evaluation of the properties of the printed foods.

4D printing: Recent advances and proposals in the food sector

Computer Vision Technology for Food Quality Evaluation

Additive manufacturing of food is a method of creating three-dimensional edible products layer-by-layer. While food printers have been in use since 2007, commercial cooking appliances to simultaneously cook and print food layers do not yet exist. A key challenge has been the spatially controlled delivery of cooking energy. Here, we explore precision laser cooking which offers precise temporal and spatial control over heat delivery and the ability to cook, broil, cut and otherwise transform food products via customized software-driven patterns, including through packaging. Using chicken as a model food, we combine the cooking capabilities of a blue laser (λ = 445 nm), a near-infrared (NIR) laser (λ = 980 nm), and a mid-infrared (MIR) laser (λ = 10.6 μm) to broil printed chicken and find that IR light browns more efficiently than blue light, NIR light can brown and cook foods through packaging, laser-cooked foods experience about 50% less cooking loss than foods broiled in an oven, and calculate the cooking resolution of a laser to be ~1 mm. Infusing software into the cooking process will enable more creative food design, allow individuals to more precisely customize their meals, disintermediate food supply chains, streamline at-home food production, and generate horizontal markets for this burgeoning industry.

/pdf/precision-cooking-for-printed-foods-via-multiwavelength-4i3ig4cooi.pdf

Precision cooking for printed foods via multiwavelength lasers.

To date, analog methods of cooking such as by grills, cooktops, stoves and microwaves have remained the world's predominant cooking modalities. With the continual evolution of digital technologies, however, laser cooking and 3D food printing may present nutritious, convenient and cost-effective cooking opportunities. Food printing is an application of additive manufacturing that utilizes user-generated models to construct 3D shapes from edible food inks and laser cooking uses high-energy targeted light for high-resolution tailored heating. Using software to combine and cook ingredients allows a chef to more easily control the nutrient content of a meal, which could lead to healthier and more customized meals. With more emphasis on food safety following COVID-19, food prepared with less human handling may lower the risk of foodborne illness and disease transmission. Digital cooking technologies allow an end consumer to take more control of the macro and micro nutrients that they consume on a per meal basis and due to the rapid growth and potential benefits of 3D technology advancements, a 3D printer may become a staple home and industrial cooking device. 

/pdf/the-future-of-software-controlled-cooking-dw4c6vyq.pdf

The future of software-controlled cooking

Selective laser broiling of Atlantic salmon.

Characterization of dough baked via blue laser

We study the application of laser-heating technology to browning dough, due to its potential for high-resolution spatial and surface color control. An important component of this process is the identification of how laser parameters affect browning and baking and whether desirable results can be achieved. In this study, we analyze the performance of a carbon dioxide (CO2) mid-infrared laser (operating at 10.6 μm wavelength) during the browning of dough. Dough samples—consisting of flour and water—were exposed to the infrared laser at different laser power, beam diameter, and sample exposure time. At a laser energy flux of 0.32 MW m−2 (beam diameter of 5.7 mm) and sample exposure time of 180 s we observe a maximum thermal penetration of 0.77 mm and satisfactory dough browning. These results suggest that a CO2 laser is ideal for browning thin goods as well as for food layered manufacture. Industrial relevance A CO2 laser that operates at a wavelength of 10.6 μm (IR) was used as an alternative method for browning dough. The high-power flux of the laser and the high energy absorption of food at this wavelength allow for rapid surface browning; however, the high absorption limits thermal penetration depth. Nevertheless, accuracy of the laser beam enables high resolution spatial and thermal control of the non-enzymatic browning process. This high precision cooking makes laser-browning particularly ideal for food layered manufacture (FLM), a food processing technique that has gained increased attention in recent years. Using FLM, one can adjust the printed layer height to match cooking penetration depth. As a digital manufacturing technology, laser-browning could also enable manufacture of highly complex and customized food geometries and textures.

Characterization of CO2 laser browning of dough

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