Abstract:
This study aims to apply handheld infrared spectral technique to develop a
predictive model for the identification of adulterants and rapid estimation of the
quality of coffee products. For the classification of coffee varieties, the novel
potable NIR spectrometer combined with multivariant qualitative algorithms gave
98.8%, 99.72% and 99.22% identification for raw, roasted and roasted powdered
coffee, respectively. Also, in the classification of Africa coffee types, it gave
99.76%, 99.78% and 99.88% identification for raw, roasted and roasted powdered
coffee, respectively. Qualitatively, FD-LDA performed better with 97.78% and
100% in both calibration and prediction sets in the determination of coffee husk in
roasted coffee powder. Quantitatively, in the detection of coffee adulteration, SPAPLS
model had the best results with R=0.9711 and 0.9897 in both calibration and
prediction sets respectively. The novel handheld spectroscopy could be employed
for the discrimination of coffee varieties and African robusta coffee in three forms
(raw, roasted and powder) and quantification of coffee husk in coffee. With 10%
occurrence frequencies, two fungi, Aspergillus niger and flavus were found in
commercially sold powder coffee in some of the major markets in Ghana with
acrylamide levels below the benchmark threshold (400ug/kg) set by the European
Commission. The proximate analysis conducted on the commercially sold coffee
powder revealed high moisture and ash attributed to a substantial amount of
impurities in the coffee samples. Furthermore, minerals namely nitrogen,
phosphorus, potassium and magnesium were found in the coffee powders.
