Near InfraRed spectroscopy or NIR has been in use in the food and agricultural industries since the late 1970s. Offering significant benefits over “wet chemistry”, NIR instruments have become very widely adopted worldwide.  Among the key benefits of an NIR are:

  • Speed – an NIR instrument delivers results in only seconds rather than hours
  • Lower cost –multiple parameters can be measured in a single sample. In addition, much less manpower is required, no chemicals are used an as NIR spectroscopy is non-destructive, tests can be repeated on the same sample.
  • Easier to use – It only takes a few minutes to learn how to operate an NIR instrument, and analysis can be performed confidently by plant personnel and temporary workers.
  • Data-logging with network / cloud access. With Perten Results Plus with NetPlus software, readings and results are available from the network, along with notes and trend analysis.
  • Improvements in efficiency and quality, along with manpower savings and loss reduction often mean that you see a Return on Investment inside of a year for NIR instruments.

How NIR works

NIR instruments use infrared light to analyze materials.  An analogy helps explain how it works: Humans investigate and evaluate objects we see, by looking at their colours. In the painting below we can see that the apple and pears are different colours. To paint these colours, the artist used two different chemical pigments – and just by observing their colours, we can identify them as being different from each other.

For food, quality parameters such as moisture, fat, protein, sugar, starch etc which we want to determine have their unique infrared colours. We cannot see this as we cannot see infrared light, but the NIR instrument can, and it can recognize and determine the relative levels / percentages of these components in the material it analyzes.

To explain how an NIR instrument can see the difference between 10% moisture and 10.5% moisture we again use an analogy. Look at the three glasses of coffee below. Which of them contains the coffee with the weakest milk flavour?

 

We can easily tell from the colour that the coffee to the left has the most intense coffee pigment. We know from experience that more intense coffee colour corresponds to a stronger taste and less milk.

In exactly the same manner, an NIR instrument looks at the intensity of the infrared colours of moisture and the other compounds we want to determine, and judges their concentration based on the intensity of their infrared colours.

To convert this to scientific terminology, the infrared colours of compounds come from the fact that certain molecular bonds absorb specific wavelengths of infrared light. The higher the concentration of a compound, the more infrared light is absorbed and the less is reflected to the NIR instrument. The NIR instrument measures the proportion of light which is reflected by the material which is then analyzed.

Just as we have trained ourselves to recognize weak and strong teas just by looking at their colour intensity, the NIR instrument needs to be “taught” how to see the difference between different concentrations.

We’ve learned to recognize the strength of tea by tasting different teas, and matching their colour intensity to their flavour. In other words we have “calibrated” our eyes to predict what our tongue will taste.

To calibrate the NIR we need to show it a number of samples that we also analyze by the reference wet chemistry method. We then extract the infrared data from the NIR instrument and combine it with the corresponding reference analysis data. A statistical software is used to determine the relationship between the infrared data and the reference analysis data. The result is a mathematical equation, unique to the product and parameter it was calculated for.

This equation is often called a calibration model, or just a calibration. To use the calibration in an NIR instrument, it is stored as a file and imported to the memory of the instrument. Whenever an unknown sample is then analyzed, the calibration we stored in the instrument is used to calculate the analysis result, based on the infrared absorption of the unknown sample.

What can NIR measure?

Not all compounds absorb infrared light, and it is only those that do which can be measured by NIR. Water does, and so do organic compounds such as protein, fat, starch, sugar and many others.

These compounds can be measured by NIR, as long as they are present at a level which is not too low. In many cases the limit for measurement by NIR is around 0.1% but there are a number of examples of applications where lower concentrations are measured.

Minerals and most inorganic compounds do not absorb infrared light and hence cannot be determined by NIR. Physical properties such as density or texture cannot absorb infrared light either.

NIR Accuracy

Since an NIR calibration is created based on a reference method, it can only ever be as accurate as the reference it was created from. In other words – it will inherit the variability of that reference method.  A rule of thumb is that NIR has an accuracy of around 1.5 times the variability of the reference method.

i.e: if you are measuring meat with 20% protein, the laboratory reference method may offer an accuracy of ± 0.5% (result will be between 19.5% and 20.5%).  In this instance the NIR will be accurate to ± 0.75% (result will be between 19.25% and 20.75%)

Here it is important to recognize that all analytical methods do have an inherent variability. Some methods have a very low variability, whereas others have a higher one. More manual methods generally have a higher variability than highly automated ones. The variability also varies from lab to lab, and while it is very useful to refer to published studies on the variability of a certain analytical method, we need to remember that the variability of a particular lab can be lower or higher than published numbers.

It is also very important that we recognize the difference between two commonly used terms: accuracy and precision (or repeatability). Precision is the ability to repeat the same result several times, whereas accuracy is the ability to reach the correct results.

For an illustration of this we use the example of dart. In the dartboard to the left in the image below we see that all three darts are in the middle. They are all in the same place, which means precision was high. They are also on the middle where we actually wanted them to be, so accuracy is also high.

In the dartboard in the middle the three darts are all in the same place, so repeatability is very high. However they are not where we aimed at, so accuracy is poor. This means that it is possible to have very good repeatability, but still poor accuracy.

The last example, the dartboard to the right, shows a case with both poor repeatability and poor accuracy. The darts are not in the middle of the board accuracy is poor, and they are spread out, so precision is also poor.

What this means is that to determine the accuracy of a method used in a particular lab, we cannot rely on repeatability studies since they only study precision. The best way to study accuracy is to participate in proficiency tests and compare results with those of other labs. It is also possible to analyze a set of samples at a second lab and calculate the standard deviation between the two labs.

An NIR application specialist who has experience from the analyses you want to perform can tell you what accuracy is normal for your particular application.

 

An NIR instrument is a very strong tool for the QA / QC specialist because the ease of operation, speed, repeatability and absence of any chemicals means not only that more tests can be made, but also that tests can be quickly repeated after reformulation, or if results are other than expected.  There is no weighing or cooking required which makes the tests more convenient & reliable.  In addition – the multiple parameters returned from a single test greatly improves efficiency.

 

This article was extracted from Perten / Perkin Elmer article “An Introduction to Near InfraRed Spectroscopy”  23 June 2020.