NIR is the commonly used term for Near InfraRed spectroscopy, a technique widely used for quantitative determination of the major constituents in most types of dairy and meat products.
Two commonly heard terms in connection with NIR are ‘reflectance’ and ‘transmission’. Let’s take a look at what they are about and what they are used for, starting with the overall principle of NIR analysis.
NIR analysis works in the following way:
- Near Infrared light is directed onto a sample
- The light is modified according to the composition of the sample and this modified light is detected
- The spectral modifications are converted to information regarding the composition of the sample
- These conversion algorithms are called ”calibrations”
Transmission and reflectance
Infrared light can be passed through a sample and collected on the other side to determine what fraction is absorbed by the sample (transmission). Alternatively, light can be reflected from the sample and the absorption properties can be extracted from the reflected light (reflectance).
An infrared spectrum can be obtained by passing infrared light through a sample (transmission) or the light can be reflected from the sample (reflectance).
Which should I use?
NIR reflectance and transmittance methods can be chosen according to the analysis job, for example, transmittance is good for measuring cheese or meat to obtain a representative measurement throughout the sample. For homogenous samples such as milk powder, reflectance is better, also because reflectance systems often cover a larger wavelength range relevant to minor or more specific components.
The choice is important because it can affect the time you spend on your everyday analytical operations, particularly if you have to test inhomogeneous samples such as meat. Here, transmittance is preferable because its ability to penetrate the sample and acquire representative data helps to reduce the sample homogenization time required. With a reflectance approach, a more thorough homogenization step will be required.
Calibration considerations for reflectance and transmission
The type of calibration available for your NIR instrument will also mean a lot for your operations. For instance, staying with our meat example discussed above, a calibration method called ANN is relevant.
ANN stands for artificial neural network and it is a particularly powerful calibration method for handling inhomogeneous food samples with many variables involved, for example in the meat and cheese products that transmittance is good at measuring.
Learn more in this related video blog post: Artificial neural network calibrations.
