New mathematical model predicts fish freshness in real time
Every day, fish caught in oceans and seas around the world pass through a long journey before reaching supermarkets, restaurants, and home kitchens. Along the way, their freshness steadily declines, often in ways that are difficult to detect. Now imagine being able to measure how fresh a fish is at any point along this journey. Researchers at Hokkaido University have developed a mathematical model that can do exactly this. The latest development could help reduce food waste and improve seafood quality.
"As is well known, the freshness of fish and shellfish begins to deteriorate immediately after death, but these changes are difficult to track across complex distribution networks," says Naoto Tsubouchi, associate professor at Hokkaido University. "As a result, appropriate decisions cannot always be made accurately because the time-dependent changes related to freshness are not fully understood."
This uncertainty affects not only the safety and quality of fish, but also its economic value. Decisions about pricing, storage, and transport are often made without precise information, influencing logistics and inventory across retail seafood centers, fishmongers, supermarkets, conveyor-belt sushi restaurants, and convenience stores-often leading to inefficiencies and unnecessary waste.
The new study, published in the Journal of Food Engineering, introduces a mathematical model based on the well-known degradation pathway of the energy molecule adenosine triphosphate (ATP) in fish muscle after death. "When a fish dies, the ATP stored in its muscle tissue undergoes sequential decomposition, and we used this naturally-occurring process to create a predictive mathematical model," explains Tsubouchi.
By describing this biochemical process mathematically through what is known as the K-value, the model can estimate current freshness of a fish and predict how it will change over time. In addition to asking how fresh a fish is now, it also allows one to estimate how fresh it will be hours or days later.
More than 60 years ago, a freshness index based on the K-value was first proposed by researchers at Hokkaido University. Today, it is used globally as a scientific indicator of fish freshness. However, conventional methods for estimating the K-value require sampling fish tissue and analysing it in the laboratory, making the process time-consuming and destructive. The new model instead predicts K-value by modelling ATP degradation. It uses basic information like fish species, storage time, and temperature to offer a non-destructive and potentially real-time alternative.
Because the same biochemical pathway also determines fish taste, the new model can provide an insight into fish quality as well. Inosinic acid (IMP) is a compound produced during the ATP degradation pathway, which contributes to the desirable umami flavour. Other late-stage compounds in this pathway are associated with bitterness and off-odours. This means the model can estimate both, freshness and flavour.
The researchers tested the model across multiple fish species, including mackerel, and found that its predictions closely matched with measured freshness values in the laboratory. "This research shows that a single model structure can be applied across multiple fish species and that maintains predictive accuracy," Tsubouchi notes.
The researchers have patented related aspects of the technology in multiple countries and see future applications in sensor devices and automated freshness monitoring systems.
Seafood supply chains are expanding globally, with increasing exports and long-distance distribution. Here, the new model could support real-time monitoring systems that can estimate remaining shelf life, reduce waste, and improve decision-making across the industry.higami, co-author and head of the Laboratory of Physical Ethology at Hokkaido University.
Original article:
Yuji Shinohara et al., Predictive model for estimating fish freshness based on adenosine triphosphate degradation in marine fish: Application to Atka mackerel (Pleurogrammus azonus). Journal of Food Engineering. January 20, 2026. DOI: 10.1016/j.jfoodeng.2026.112987.
Funding:
This work was supported by the Consortium-based Robust Agricultural, Forestry and Fisheries Engineering Research Program, Hokkaido University International Collaborative Research and Education Center for Robust Agriculture, Forestry and Fisheries Engineering.
