The Impact of Colour in Food: Functions and Measurement

When you walk into a supermarket, what’s the first thing you do? Before you smell the bread or tap the melons, you look. You scan the pyramids of apples, choosing the one that’s a deep, glossy red. You bypass the brownish bananas for the perfectly yellow ones. This instant, subconscious judgment is all based on one powerful property: colour. It’s the first language food speaks, telling us a rich story about its quality, flavour, and freshness before it ever reaches our lips. But colour is far more than just decoration; it’s a critical piece of data that drives consumer choice, ensures quality, and protects our safety.

The functions of colour in food 🔗

Colour serves as the most immediate indicator of food quality. It’s an essential part of our sensory evaluation, often setting our expectations for taste and smell. This visual assessment is so powerful that it can override our other senses, making a food seem to taste different based purely on its hue. In the food industry, this “language” is broken down into several key functions.

The first language of food: What colour tells us 🔗

At its most basic level, food colour acts as a maturity index. Think about a strawberry. A pale green or white berry tells us it’s unripe, hard, and sour. A deep, uniform red signals that it’s mature, juicy, and sweet. This transformation-the development of red anthocyanin pigments-is a direct visual cue for the peak of ripeness and flavour. The same is true for tomatoes, bananas, and countless other fruits and vegetables.

Colour also signals quality and potential spoilage. Fresh, high-quality beef is expected to be a bright “cherry-red.” This colour comes from a pigment called oxymyoglobin, which forms when the meat’s natural pigment, myoglobin, is exposed to oxygen. When that meat turns a dull brown (metmyoglobin), it signals to the consumer that it’s been exposed to air longer, even if it’s not yet spoiled. Conversely, a golden-brown crust on bread, a result of the Maillard reaction during baking, signals a complex, rich flavour, while a pale crust suggests it’s undercooked.

Eating with our eyes: Colour and consumer preferences 🔗

We have deeply ingrained psychological expectations for what our food “should” look like. Would you drink brown orange juice? Or eat blue mashed potatoes? Probably not. We associate bright orange with fresh, vitamin-C-rich orange juice. We expect butter to be a creamy yellow and salmon to be a healthy pink. When these expectations aren’t met, our brain sounds an alarm. Studies on consumer perception consistently show that visual cues, especially colour, are the primary factor in a person’s decision to purchase a food product. This is why food manufacturers work so hard to maintain a consistent colour. If a popular brand of ketchup suddenly came out a shade too brown or orange, consumers would likely reject it, perceiving it as “off” or “unnatural,” even if the recipe and taste were identical.

The business of colour: Grading and standardization 🔗

Because colour is so tied to perceived quality, it has become a cornerstone of industrial food grading. This moves colour from a subjective preference to an objective, measurable metric. Government and industry standards use colour to classify and price food products, ensuring consistency for both buyers and sellers.

Think of maple syrup, which is graded based on its light-transmittance (colour). A “Grade A Golden Colour and Delicate Taste” is light and pale, while “Grade A Dark Colour and Robust Taste” is much darker. Similarly, apples are graded (e.g., “U.S. Extra Fancy”) based, in part, on the percentage of their surface covered by a “good” red colour. This standardization is impossible without reliable tools to remove human guesswork, which is why we need to measure it.

Measuring colour in foods 🔗

“That looks red” is not a precise enough statement for a food scientist or a quality control manager. To maintain consistency for a product sold in millions of units, or to fairly grade a farmer’s harvest, that “red” needs a number. This process of quantifying colour is called colourimetry.

The entire science is based on how light interacts with a food object. When light hits an apple, the apple’s surface absorbs some wavelengths (like the blues and greens) and reflects others (the reds). Our eyes see that reflected red light. For a clear liquid like apple juice, light passes through it, and we measure the transmittance. For an opaque solid like an apple, we measure the reflectance.

How machines see colour: The basics of colourimetry 🔗

To turn a visual sensation into a useful number, scientists use a standardized model. The most common is the CIE L*a*b* colour space. It’s a bit like giving every colour a unique address with three coordinates:

• L* (Lightness): A scale from 0 (pure black) to 100 (pure white).
• a* (Red/Green axis): A negative value is green, and a positive value is red.
• b* (Yellow/Blue axis): A negative value is blue, and a positive value is yellow.

Using this system, a “ripe strawberry red” isn’t just “red”-it’s a precise address like L*=45, a*=55, b*=28. A food company can now program its machines to reject any strawberry that doesn’t fall within a very small range of that exact coordinate, ensuring perfect consistency.

The classic tools: From tintometers to spectrophotometers 🔗

How do we get those L*a*b* numbers? We use specialized instruments designed to “see” colour more accurately and objectively than the human eye.

A classic instrument still used for many transparent liquids (like oils, beers, and syrups) is the Lovibond Tintometer. This is a form of disc colourimetry. It works a bit like an eye exam. An operator views the food sample through an eyepiece and, on the other side of their view, sees a set of standardized red, yellow, and blue glass discs. The operator manually slides and combines these calibrated discs until the colour in the eyepiece perfectly matches the food sample. The result isn’t an L*a*b* value, but a “Lovibond unit” (e.g., 6.0 Red, 20.0 Yellow) that serves as a quality standard.

The modern, objective workhorse, however, is the spectrophotometer (or its close cousin, the colorimeter). This technique is often called reflectance spectrophotometry. A spectrophotometer shines a precisely controlled, full-spectrum light onto the food sample. Advanced sensors then measure exactly how much light is reflected back at every single wavelength across the visible spectrum. It doesn’t just “see” red; it sees a data spike at the 650-700 nanometer wavelengths. A computer inside the device then instantly calculates the precise L*a*b* coordinates. This is the gold standard in food science for quality control, research, and development.

Qualitative and quantitative analysis 🔗

So far, we’ve discussed measuring the natural colours of food, or the colours created through processing like baking. But what about colours that are added to food? Think of brilliantly coloured candies, sports drinks, and cereals. These often use synthetic colours (like FD&C Red 40 or Yellow 5) that are approved for use by regulatory bodies. For these foods, analysis serves two purposes: identifying *what* colour is present (qualitative) and *how much* is present (quantitative).

Finding the colour: Qualitative analysis 🔗

The “what is this?” question is crucial. A food manufacturer might need to verify that a “natural blue” additive is truly from spirulina and not an undeclared synthetic dye. Or, a regulatory lab might be testing a product to ensure it only contains approved colourants.

The classic technique for this is chromatography. The principle is simple, like a race. You take a small sample of the unknown dye and place it on a “starting line” on a special medium (like a strip of paper or a coated glass plate, known as Thin-Layer Chromatography or TLC). You then dip the edge of that medium into a solvent. As the solvent moves up the medium, it carries the dyes with it. But, based on their chemical structure, different dyes travel at different speeds. The “race” separates the components. By running known standard dyes (like Red 40) in other “lanes” on the same plate, you can identify the unknown dye by seeing if it “ran” the exact same distance (known as the Retention Factor, Rf) as one of the standards.

Measuring the amount: Quantitative analysis 🔗

Once you know *what* dye is present, you must find out *how much* is present. This is a critical food safety issue. Regulatory agencies like the U.S. Food and Drug Administration (FDA) set strict limits on the maximum concentration allowed for each synthetic colour. Using too much is illegal and can pose health risks.

To quantify the dye, scientists again turn to the spectrophotometer, but this time they use it to measure absorbance in a liquid. The guiding principle is the Beer-Lambert Law, which states that the more concentrated a coloured solution is, the more light it will absorb. The process is straightforward: 1. First, the colour (e.g., Blue 1 from a sports drink) is extracted and isolated. 2. It’s dissolved in a clear solvent and placed in the spectrophotometer. 3. The machine is set to shine a light at the *exact* wavelength that Blue 1 absorbs most (its *lambda max*). 4. The machine measures how much light *doesn’t* make it through the sample, giving an Absorbance value. 5. This value is then compared to a calibration curve (made from samples of known concentrations) to determine the exact concentration, such as “15 mg per liter.”

Why this matters: Colour, safety, and consumer trust 🔗

From a simple visual choice in the grocery aisle to a complex chemical analysis in a lab, colour is woven into the very fabric of our food system. Analyzing colour ensures consistency for manufacturers, helps grade products fairly, and, most importantly, protects consumers. Advanced laboratory methods like High-Performance Liquid Chromatography (HPLC) allow for highly accurate and fast analysis of multiple dyes at once. This complex science ensures that whether a colour is natural or synthetic, the food you eat is safe, consistent, and exactly what you expect it to be.

What do you think? Think about the last time you chose one food item over another (like a fruit, a piece of meat, or a baked good) purely based on its appearance. What did that colour “tell” you? And now that you know about the strict analysis of synthetic colours, does it change how you feel about seeing “artificial colours” on an ingredient label?

References

1. https://www.sciencedirect.com/science/article/pii/S096399691500350X
2. https://www.hunterlab.com/blog/applications-solutions/measuring-color-in-the-food-industry/
3. https://foodscience.psu.edu/research/labs/food-chemistry-and-analysis/instrumentation/color-measurement
4. https://www.fda.gov/food/food-additives-petitions/color-additives-food
5. https://www.agilent.com/cs/library/applications/5991-3069EN.pdf