It is rare for scientific publications to focus objectives that were unachieved, or results that failed. This is unfortunate, as such studies can offer valuable insight to other researchers.
In this paper (USD $27 purchase required) the authors report a near-infrared (NIR) spectroscopy-based partial least squares regression (PLS) method for distinguishing and quantifying soluble coffee and soluble chicory percentages in a solid mixture. They also attempted a NIR-based PLS method to distinguish soluble Arabica coffee, soluble Robusta coffee and soluble chicory in one shot; however, they found that NIR with PLS is unable to differentiate soluble Robusta and soluble Arabica when these three components are in a mixture. They contrasted this with 1H NMR and 13C NMR spectroscopy, which could differentiate.
They conclude that their results show the limitations of NIR spectroscopy in combination with PLS to distinguish the type of soluble coffee (soluble Arabica and soluble Robusta) when mixed with soluble chicory.
Photo by Archer Allstars on Unsplash
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