Fourier transform infrared (FTIR) spectroscopy is examined as a rapid alternative to wet chemistry methods for the detection of adulteration of freeze‐dried instant coffees. Spectra have been collected of pure coffees, and of samples adulterated with glucose, starch or chicory in the range 20–100 g kg−1. Two different FTIR sampling methods have been employed: diffuse reflectance, and attenuated total reflectance. Three different statistical treatments of the spectra were carried out. Firstly, the spectra were compressed by principal component analysis and a linear discriminant analysis performed. With this approach, a 98% successful classification rate was achieved. Secondly, a simultaneous partial least square regression was carried out for the content of three added carbohydrates (xylose, glucose and fructose) in order to assess the potential of FTIR spectroscopy for determining the carbohydrate profile of instant coffee. Lastly, the discrimination of pure from adulterated coffee was performed using an artificial neural network (ANN). A perfect rate of assignment was obtained. The generalization ability of the ANN was tested on an independent validation data set; again, 100% correct classifications were achieved.
|Number of pages||8|
|Journal||Journal of the Science of Food and Agriculture|
|Publication status||Published - Jul 1996|
- principal component analysis
- artificial neural networks