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Progress in Agricultural Engineering Sciences
Donald Bimpong
Lois Amponsah Adofowaa
Ama Agyeman
Abena Boakye
Ibok Nsa Oduro
Ellis William Otoo
, and
John-Lewis Zinia Zaukuu


Peanut butter and yoghurt are targeted for adulteration intended at consumer deception. This study aimed to fingerprint and detect peanut butter and yoghurt adulteration with cassava flour and starch using Near Infrared Spectroscopy (NIRS) in a quasi-experimental approach. Ingredients for laboratory sample preparation were obtained from the Kumasi Metropolis. Peanut butter was adulterated at 1, 3, 5, 10, 15, 20% w/w and yoghurt at 0.25, 0.5, 1, 3, 5, 10, 15, 20, 25, 45, 50% w/w. Selected concentrations mimicked practices on the market. Marketed products were randomly sampled from six markets in the Kumasi Metropolis to validate the study models. Samples were scanned with a hand-held NIRS in triplicates. Chemometric (Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Partial Least Square Regression (PLSR) models) statistical methods were employed to develop classification and prediction models. Peaks with spectral bands such as 1050 , 1200 and 1450 nm were observed for peanut butter and 990–1100 nm, 1100–1200 nm and 1300–1408 nm were observed for yoghurt in the NIR spectrum. Some yoghurt brands were suspected of containing cassava starch, while Peanut butter from the different markets differed based on classification models. Cassava flour and starch concentrations were quantitatively predicted by PLSR with an R2 CV of 0.98 and an error of 0.9 g/100 g (low error).

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