**Author details**

*Innovation in the Food Sector Through the Valorization of Food and Agro-Food By-Products*

detects previously established chemical signatures of seafood freshness, quality, and species ID. This device integrates several types of spectroscopic data through its fusion-AI algorithm into simple, human readable reports. The handheld scanner will enable spot-checks of quality, species ID, and freshness all along the supply chain. Integration with a mobile device and app can couple the QAT output to blockchain-enabled, cloud-based, supply chain management platforms for tracking product quality, freshness, and species ID from harvest to market. When integrated with a digital platform using blockchain and dynamic pricing technology, these tools will support the modernization of the global fishing and seafood processing industries, supply chains and retail outlets, as well as provide accurate information to consumers about the sustainability, freshness, and quality of their seafood purchases. Specially designed apps can also integrate smallholder producers in developing economies into the broader, emerging digital supply chain platforms in

By providing trusted product and pricing data at any node of the supply chain, QAT fundamentally changes the business models of seafood processors, wholesalers and retailers, making it practical to (a) identify mislabeled product, and (b) dynamically price perishable seafood at multiple purchase decision points – beyond traditional final-discounting by retailers. The quantitative underlying data provides high confidence and additional visibility and trust in the freshness of such a highly perishable good, and makes intelligent pricing based on quality/freshness practical

With this capability, QAT will spur innovation in the execution of seafood supply chains by providing accountability at each node for maintaining quality. This will drive improvements in purchase decision making, traceability, authentication, and inventory planning. Retailers can use dynamic pricing in both their purchase and final sale decision making. Given the high proportion of seafood sales attributable to the largest retailers in both developed and developing markets, retailers can have significant economic incentive to adopt such technologies, and the power to

Technologies like SafetySpect QAT will have four major impacts on the global seafood industry: (1) Reduce waste by tracking fish freshness, thus enabling vastly improved freshness-based dynamic pricing tools at multiple supply chain nodes; (2) Increased visibility and trusted information; (3) Increased value of seafood across markets and positive impact on public health by providing assurance of quality, species, and freshness; (4) Positive impact on a number of sustainability goals including better management of at-risk wild fisheries, combatting illegal poaching of fish and wild animal species, improving food security, and providing better economic engagement and access for marginalized smallholder producers to broader digital supply chain systems and platforms, reducing resource consumption

Food waste is a global problem caused in large part by food spoilage that has gone undetected. This problem exacerbates world hunger issues and affects consumers by causing them to pay too high a price for food products whose shelf lives have been improperly or inadequately estimated. Several technologies have been applied to improve the detection of food spoilage and provide better valorization of food products at all points along the food supply chain, but many of these methods are either unreliable or damage the samples being evaluated. Spectroscopic techniques, on the other hand, offer a reliable and non-invasive means of detecting and

at all nodes along the supply chain before final retail sale.

encourage its adoption by upstream suppliers.

and combatting climate change.

**5. Conclusion**

**108**

these markets.

John Chauvin1 , Ray Duran1 , Stanley Ng1 , Thomas Burke2 , Kenneth Barton3 , Nicholas MacKinnon4 , Kouhyar Tavakolian1 , Alireza Akhbardeh4 and Fartash Vasefi3 \*


\*Address all correspondence to: fvasefi@safetyspect.com

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
