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These types of sensors are usually noninvasive in nature. Examples of product attributes that can be measured are color, the presence of surface defects, and chemical composition. Technological platforms include optical, acoustical, NMR, and electrical. Biomimetic devices such as electronic noses, which are already used for personalized medicine Fitzgerald et al. At the end of the sensing phase, an electronic reader allows signal processing so that results are displayed in a user-friendly manner.

Mobile diagnostics that use Internet-of-Things technologies to link sensor output to smartphones and cameras, and are even coupled with data entry on servers or the cloud, have been reported, particularly for detection of foodborne pathogens, food allergens, antibiotic residues, and shellfish toxins, in relevant sample matrices Rateni et al. Although handheld mobile readouts are still in development with significant need for improvement e. There are a number of practical impediments to successful, routine use of biosensor technologies in foods and environmental samples. Many different biosensors for detecting pathogens such as Salmonella in foods have been reported, but they vary widely in performance, particularly analytical sensitivity detection limit , frequently ranging from a low of one single cell to a high of millions Cinti et al.

While of lesser importance in clinical settings where samples come from ill individuals and pathogen concentrations are high, this is not the case for food, water, and environmental samples. These sample types may be infrequently contaminated and when the contaminant is present, concentrations are low. In addition, sample size should be large and testing done frequently in order to account for low contaminant prevalence. In addition, there is a pressing need to develop sample preparation methods and protocols that will efficiently concentrate and purify an analyte from the matrix prior to use in the sensing device Brehm-Stecher et al.

This includes validating sensor performance in relevant natural sample matrices i. Other factors related to conditions and ease of use, robustness, and cost are critical for success. The development of omics and sensor technologies will augment the capabilities to collect increasing amounts of data in the food processing, safety, and quality realms e. Ultimately, the value of data to the food supply chain is to provide more and better information on which to base system optimization and management decisions regarding food processing, safety, quality control e.

That means there must be an infrastructure to house massive amounts of records, and a means by which those records can be integrated and effectively used for decision-making purposes. Associated with these changes is the need to identify and understand the design and behaviors in emerging food supply chains.

In the area of food safety, there are a number of large, publicly accessible online databases used by the public health sector inventoried in Marvin et al. Examples are the National Outbreak Reporting System, the Genome Trakr Network whole-genome sequences of pathogens , and others used by industry, such as Combase data for quantitative microbiology and models predict growth and inactivation of microorganisms.

The availability of online searchable databases e. These and other databases have clear utility for different types of applications. However, that utility would be enhanced if data and databases were integrated with one another, particularly with less publicly accessible data such as industry process monitoring and product tracking systems e. There are some early examples see Box , but a much more concerted effort is needed toward data integration to. Hill et al. The model allowed this group to find associations between DNA sequence, location of the food animal across the production chain, and human illness.

With technologies that collect, transmit, store, and analyze data obtained from real-time sensors, along with a centralized system of databases with sampling and processing data, their approach holds promise and would theoretically allow the tracking and tracing of individual food units. Integrated data and data management systems can also be applied with the goal of improving resource efficiencies in the food system. A more integrated and holistic data management systems approach to thinking about minimizing product and food waste may focus on identifying food waste conversion methods for edible and nonedible purposes.

In such a distribution system, a seamless supply. Considerations of system design and science are discussed in Chapter 8. An example of an innovative exchange system developed to facilitate the diversion of surplus retail food products to distribution sites is the one recently developed with food banks. Efficiencies are gained through the development of networks and exchanges for distribution of surplus foods from retailers to food banks and distribution centers.

Integration of real-time data on available foods and existing needs provides a mechanism for redirecting food to help feed the hungry and reduce food waste Prendergast, Within the industry itself, goals for reducing food waste can be accomplished by setting standards for ordering, receiving, preparing, processing, packaging, serving, and tracking food production. One technology that has enormous potential to revolutionize the management and storage of data and to facilitate the integration of food distribution systems, among other applications, is blockchain see Chapter 7 on data science.

Blockchain also called open, distributed ledgers is a system in which a continuously growing list of decentralized and encrypted records blocks are linked so that it can be securely distributed across peer-to-peer networks. Blockchain allows for highly transparent and instantaneous transfer of product data associated with many attributes, including the safety and quality of food, as well as environmental stewardship, all arising from activities such as routine monitoring, inspection and audit, accreditation, and laboratory analyses.

The improvements from implementation of blockchain technology will also benefit consumers as they demand more detailed information about product sourcing, origin, processes, and production methods. Consumers and other buyers are able to access information on the product via smartphone applications and other data platforms. Although some applications that link purchases to specific retail outlets or consumers have benefits at the consumer level e. See Box for more concrete examples of the application of blockchain technology to the management of data on the food supply chain.

As companies are increasingly exploring the uses of blockchain technology in the agriculture and food arena, both challenges and solutions are arising. A recent report aimed at better understanding the implications and needs of the blockchain technology to stakeholders e. Specific stakeholder groups have identified cost and knowledge of the technology as main challenges IFIC Foundation, Food scientists apply engineering principles to design novel processing and packaging technologies that result in profound improvements to the quality, safety, acceptability, and shelf life of foods.

Depending on the technology e. Some of these technologies may be particularly well suited for certain foods or venues, especially those in which large capital outlay for food processing is not possible or economically feasible. Advances in materials science and nanotechnology, as applied to production of packaging materials, holds great promise for advancing quality and safety of food products.

For example, nanocomposite materials i. The materials that have smart properties are those able to control their interfacial properties. These largely consist of self-cleaning, self-cooling, and self-heating technologies, already designed for the health care sector, that are now being applied to food systems.

In some ways, this technology relates back to the biosensors discussed above in Opportunity 2. The output of intelligent packaging can be expressed in the form of data e. All of these provide information that can then be included as a basis for decision-making and management systems. While monitoring food quality and freshness with indicators is routine in the food industry sector, intelligent packaging technologies are extremely well suited for detecting metabolites occurring as a consequence of food spoilage, and thus may.

From the consumer perspective, communicative packaging has emerged as a potential tool to address concerns about product quality, safety, and the consumer demand for specific product information as they make purchasing decisions. Although alternative food processing and packaging technologies have the potential to deliver better quality, nutrition, safety, and acceptability to food products, some questions related to the need to decrease the energetic footprint e. Likewise, acceptability of these. Relative to nanomaterials, consideration of potential unintended consequences of their use is critical.

Safety concerns focus on the potential interactions between nanomaterials and the food matrix, particularly potential toxicity to consumers and environmental impacts. Because these materials are very recent in their introduction to the market, there are relatively few data available to systematically assess health or environmental risks, and legislators err on the side of caution when it comes to regulatory decision making. Similarly, consumer acceptance of new technologies may be an issue and depend ultimately on the degree of trust consumers place on the products themselves Roosen et al.

Identifying factors that determine consumer acceptance and choices over product attributes and qualities is essential information to determining the success in producing foods that will be purchased and consumed e. Traditionally, consumers respond to market prices and other monetary signals in their product selection. However, there is increased evidence that financial incentives such as taxes and subsidies applied to products , social factors, and context of food choices, as well as other behavioral motivators or nudges can encourage or discourage food-related behavior.

Ignoring the need to better understand and anticipate consumer food behaviors, drivers, and trade-offs may limit consumer acceptance of new products, technologies, and market innovations. This applies to the need for effective food labeling approaches as well as basic communication about scientific and technological advances. A National Academies of Sciences, Engineering, and Medicine report NASEM, highlights the need to understand the optimal communication approaches for use under different circumstances,.

Scientific advancements in technologies related to food processing and product design, packaging, and handling may be limited by existing regulations, such as food law and product identity standards. A few examples are provided here. Many of the emerging food processing technologies i. It may not be prudent from food safety and liability standpoints to use these processes commercially until such validations are conducted and reviewed. The inclusion of nanotechnology-based products e. There is also the possibility that sensor devices or novel packaging materials may be prohibited based on current food adulteration regulations.

The replacement of pathogen culture methods with whole-genome sequencing is being questioned because historically, proof of product adulteration in recall or outbreak situations relies on having a pure culture of the implicated organism, not simply evidence of the presence of its DNA. The practical use of technologies intended to collect data at a faster rate may be hindered if they have negative effects on other aspects of the process that fall under regulatory scrutiny, such as adhering to maximum line speeds in meat processing plants.

Integrated and blockchain data systems offer the opportunity to digitize record keeping, some of which may be relevant for regulatory purposes e. However, relevant agencies may not yet be able to accommodate transfer of information using their current data management systems. A relatively large share of investment in innovation and technologies for foods is done through the private sector where private returns to investment dictate technology choice with less emphasis placed on the public benefit.

Furthermore, some basic research requires significant investment in underlying infrastructure. As an example, system-wide innovation and data networks often require large, upfront expenditures to develop and support data infrastructures. However, interoperability of systems and data networks between the various participants in the supply chain is required to effectively monitor and maintain the safety and integrity of the food system, and to support efforts to integrate sustainability opportunities.

With funding predominantly from private sources, the allocation of resources to research and research infrastructure may not address the highest-priority public needs. Several of the scientific advances discussed above will provide more improved instrumentation and allow for collection of more sophisticated data. Training will be necessary to ensure that the existing and emerging workforce has the scientific skills to use these instruments, analyze the data, and make appropriate decisions that capitalize on the value of these new technologies.

Ultimately, consumer practices and food choice will determine the ability of product and process development to successfully improve product safety, quality, and design. Advances in behavioral sciences and effective communication about science, technology, risk, and decision-making communication are required to underpin successful adoption in the market. Emerging technologies e. Solving the fundamental and applied scientific problems necessary to use these technologies more widely will require multidisciplinary collaboration and funding mechanisms.

Research efforts need to be transdisciplinary, involving not only food scientists but also those in other disciplines ranging from data and computer science, engineering, synthetic biology, and the social sciences, and many more. The committee identified the following high-priority research areas:. Alahi, M. Detection methodologies for pathogens and toxins: A review.

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Muth, W. Nganje, T. Stinson, and H. Mills, A. A solvent-based intelligence ink for oxygen. Analyst 2 : Mlalila, N. Kadam, H. Swai, and A. Transformation of food packaging from passive to innovative via nanotechnology: Concepts and critiques. Journal of Food Science and Technology 53 9 Xueni Chen, Stephen C. Dreskin Application of phage peptide display technology for the study of food allergen epitopes Mol.

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