Does hyperspectral always matter? A critical assessment of near infrared versus hyperspectral near infrared in the study of heterogeneous samples

Abstract

Near Infrared spectroscopy (NIR), in combination with Chemometrics, has been used for many years in diverse scenarios, mostly focused on the classification and quantitation of properties in food, pharmaceutical preparations, artwork material, etc. This success has been possible due to their desirable properties: fast, reliable (under certain conditions), non-destructive, easy to implement from a hardware perspective, and able to create robust and transferable multivariate models.

For some years now, another modality has been gaining the attention of NIR users, especially in the Food sector. That is the plausibility of using NIR in the hyperspectral (HSI) domain. This adds to the previously mentioned abilities, the benefit of scanning the whole surface of samples, acquiring much richer spatial information and, therefore, assuring the quality of the final product more accurately by including parameters that depend on the surface distribution of certain components. This is especially relevant in heterogeneous samples. While this statement is generally true, there are certain situations where this oversampling feature is not strictly needed, and the problem can be easily solved with a classical NIR spectrophotometer. Besides, NIR-hyperspectral imaging (NIR-HSI), despite the abovementioned advantages, has several drawbacks that must be highlighted as well, like their measuring speed, instability, or price.

This manuscript will demonstrate that for certain situations, tuning the focal distance of a NIR spectrophotometer is a more feasible, reliable, and inexpensive strategy to collect all the needed information of samples with a certain degree of heterogeneity.