Nobody can see with their eyes the sugar inside a strawberry or the dry matter in an avocado, but light can pick up on both. Every time light hits a piece of fruit, part of it is absorbed and part of it comes back. The pattern it leaves behind says a lot about what is going on inside. Reading that pattern is called spectroscopy.
The idea is centuries old. Scientists first used spectroscopy to find out what the sun and stars are made of, long before anyone pointed it at food. Agriculture followed much later, first to check the moisture in grain and later the sweetness (Brix) of fruit. Today, the same principle fits in our scanner that works anywhere in the supply chain.
In this blog, we explain what spectroscopy is, how it works, why near-infrared (NIR) light is such a good fit for fresh produce, and what it means for the quality control process.
Spectroscopy is the study of how light interacts with matter. Light is made up of many different wavelengths. When it hits an object, some wavelengths are absorbed and others are reflected or pass straight through. Which ones depends on the molecules inside that object.
Because every type of molecule absorbs light in its own way, the result works like a fingerprint. Plot how much light comes back at each wavelength and you get a spectrum: a curve that shows what the object is made of.
You already know a simple version of this. A ripe tomato looks red because it absorbs most visible light and reflects the red part back to your eyes. Spectroscopy works on the same principle, only far more precisely and across wavelengths our eyes cannot see.
Every spectroscopy system, from a large lab instrument to a compact scanner, follows the same four steps.
Light source. A light bulb or LEDs shine light with a known range of wavelengths onto an object.
Interaction. The light enters the object. Molecules absorb specific wavelengths, and the rest is reflected, scattered or transmitted.
Detection. A sensor called a spectrometer records how much light returns at each wavelength. That is the spectrum.
Interpretation. Software translates the spectrum into something useful, such as a sugar level or a dry matter percentage.
The first three steps happen in a fraction of a second. The fourth step is where most of the knowledge sits, and we come back to it below.
Spectroscopy is the overall technique of reading how light interacts with matter, and it can use many types of light, from ultraviolet to visible to infrared. NIR spectroscopy is one type of it, using near-infrared light. It is the type most used for assessing the internal quality of fresh produce. NIR sits just beyond red on the light spectrum, roughly between 780 and 2,500 nanometres, so it is invisible to the human eye.
NIR is a strong fit for fruit for three reasons:
It responds to the right molecules. NIR light is absorbed by chemical bonds that contain hydrogen, like those in water, sugars and oils. These are exactly the components behind quality parameters such as Brix and dry matter.
It goes beneath the skin. NIR light travels into the flesh, so the reading reflects what is inside the fruit, not only the surface.
It is gentle. NIR is low-energy light. Low amounts do not damage or change the fruit, so a scanned piece of fruit can go straight back into the box.
NIR light picks up on components like water, sugars and oils. With the right models in place, that translates into several internal quality parameters per produce, all assessed with one scanner. It also helps to flag internal defects, like stem-end rot in avocados.
| Produce | Internal parameters | Why it matters |
|---|---|---|
| Strawberry | Brix, shelf life prediction | Know how sweet a batch is and how long it will stay fresh. |
| Blueberry | Brix, firmness | Check taste and how well berries will hold up during long transport. |
| Avocado | Dry matter, ripeness index, stem-end rot | Confirm harvest maturity, track ripening and catch internal decay you cannot see from the outside. |
Good to know: spectroscopy covers internal quality. External quality, like visual defects, sizing and counting, is assessed with visual inspection using a camera. And shelf life prediction combines spectral data with other inputs, such as visual inspection and growing conditions. All of it comes together in one report.
Spectroscopy reads how light interacts with a material, and every molecule leaves its own fingerprint in the light that comes back. Near-infrared light is a particularly strong fit for fruit. It responds to water, sugars and oils, travels beneath the skin and does not damage the fruit. Compared to traditional destructive methods, that means you can check more fruit, faster, without losing any of it.
At OneThird, we use NIR spectroscopy and AI to help you assess the quality of strawberries, blueberries and avocados without destroying a single piece of fruit. The result is objective, instant data you can act on at every step of the quality control process.
Curious what NIR spectroscopy can reveal about your fruit? Get in touch, we'd love to show you.