Why multiple indicators are needed

The shelf life of roasted-ground coffee shouldn't be treated as a number detached from the product and storage conditions. Quality can change simultaneously in sensory perception, volatile compounds, oxygen state, water activity, and physical properties. A single indicator only sees one slice of the process. So a reliable shelf-life design should start by identifying which quality needs protecting and what evidence can demonstrate that state.

The role of sensory evaluation

Sensory evaluation has a special role because the endpoint of shelf life ultimately relates to product acceptability. Cardelli and Labuza used consumer-acceptance evaluation along with oxygen, water-activity, and temperature data to model the decline of roasted-ground coffee. The research showed changes in oxygen, water activity, and temperature can significantly change the rate of decline. This illustrates that sensory data can serve as an endpoint indicator, while other data helps explain the mechanism behind that endpoint.

Chemical and physical indicators

The chemical and physical indicator group can include oxygen, water activity, temperature, volatile compounds, and oxidation-related indicators. However, not every product needs all of them. For a specific product, you need to choose variables capable of changing under real conditions and relating to the quality that needs protecting. Chemical data usually helps detect or explain change, while sensory data helps confirm whether that change matters to the drinker.

Assembling it into a system

An evaluation design can split indicators into three layers. The first layer is outcome indicators, such as sensory acceptance. The second layer is explanatory indicators like volatile compounds or oxidation signs. The third layer is driving conditions like temperature, oxygen, and water activity. Sampling over time within such a design helps reveal not just “when the product spoils” but also “which condition changes the rate of change.”

Evidence from shelf-life research

Recent research continues to show roast level and storage temperature can jointly affect volatile-compound profile and shelf life. A 2025 study on Thai Arabica, for example, tracked multiple roast levels and storage temperatures while measuring moisture, color, peroxide value, volatile compounds, and shelf life. The specific results only apply within that test's conditions, but they illustrate the value of combining several indicators into one dataset instead of relying on a single number.

The most important limit is not directly turning one experimental curve into a common shelf life for every coffee. Packaging, mass, roast level, whole bean or ground form, temperature, and opening conditions can all change the kinetics. So shelf life should be presented as the result of a specific system. Using multiple indicators doesn't make the problem simpler, but it makes the conclusion more trustworthy because it's grounded in more than one signal.

Indicators also need to be classified by role to avoid collecting too much data without knowing how to use it. One indicator can be chosen as the endpoint criterion, one used to explain mechanism, and one used to confirm storage conditions. If all are treated as equal criteria, it becomes very hard to determine when the product truly exceeds an acceptable limit. Defining each indicator's role in advance is what turns a data collection exercise into a usable evaluation system.

Sensory data should be collected under standardized conditions with clear criteria. If the same sample is evaluated by different people without a consistent scale, sensory variation can mask storage-related change. When combining with chemical data, sample codes and time points need to be kept consistent. This helps determine whether a chemical indicator can predict a sensory change or is just a coincidental number.

An indicator group should also have a plan for when signals disagree. For example, volatile compounds change but sensory perception stays within the acceptable zone. In that case, you shouldn't automatically declare the product past its shelf life; you need to check which indicator the endpoint criterion is actually defined by. Conversely, if sensory quality declines before a chemical indicator changes clearly, sensory perception may be the decisive variable, and the chemical indicator should be reconsidered as merely supplementary.

A shelf-life model should therefore be seen as a model of a specific system. When packaging, roast level, or temperature changes, the curve can change. A good design must allow updating the model as new data arrives, rather than treating one equation as a fixed truth. This is also why raw data, test conditions, and acceptance criteria all need to be stored.

Choosing multiple indicators also doesn't mean measuring everything at every time point. A sensible design can use sensory measurement at key milestones, while some chemical indicators are tracked more densely if they're easy to measure and capable of giving early warning. This kind of layering helps reduce cost while still retaining the information needed to determine the endpoint. What matters is that each indicator's role is defined in advance.

References

• Cardelli & Labuza (2001), LWT 34, 273–278, DOI 10.1006/fstl.2000.0732.
• Anese, Manzocco & Nicoli (2006), J. Agric. Food Chem. 54, 5571–5576, DOI 10.1021/jf060204k.
• Błaszkiewicz et al. (2023), Scientific Reports 13, 6447, DOI 10.1038/s41598-023-33609-x.
• Impact of roasting and storage conditions on the shelf stability of Thai Arabica coffee (2025), Journal of Agriculture and Food Research 22, 102060, DOI 10.1016/j.jafr.2025.102060.