Graduate Thesis Or Dissertation
 

Characterization and detection of potential adulterants in apple juice by pattern recognition methods

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/w95053129

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  • Fruit juice concentrates- hard pear, soft pear, fig, prune, raisin, white grape, and pineapple, and sweeteners-invert beet, invert cane, and high fructose corn syrup (HFCS) were characterized by sugar profiles, nonvolatile acid profiles, UV spectral profiles, and mineral content. These fruit juices and sweeteners were also used to adulterate commercial apple juice at levels of 40%, 20%, and 10%. Sugar and nonvolatile acid analyses were performed by HPLC and isotopic carbon analyses were applied to selected samples. Data analysis included the application of Pattern Recognition methods and Chi-square test. Analysis by Pattern Recognition was restricted to sugar profiles because of the availability of an extensive data base on sugar composition of authentic apple juice, the compositional data base for the other components being limited. The "potential adulterants" were clearly distinguished from the cluster of authentic apple juice. Apple juice samples adulterated at 40% were at the perimeter and also distinguishable from the cluster, while the samples adulterated at 20% and 10% were intermingled within the cluster. Pattern Recognition methods were also used for classification of the authentic apple juice data base obtained from Mattick and Moyer (1983). Apple samples were classified by variety and geographical origin. Sucrose, glucose/fructose ratio, and sorbitol were important variables in the separability of the samples. Pattern Recognition methods are effective in classification of authentic juices and show potential as a powerful technique in discriminating between adulterated and authentic apple juice.
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