ArticleFood science & nutrition2026
Detection of Adulterants in Apple Juice Concentrate by Physicochemical Properties, Organic Acids Profile, Minerals, and Multivariate Classification Strategies.
Article in Food science & nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
From a food safety perspective, with a focus on natural fruit juices and concentrates, various types of adulteration, such as substitution with cheaper sweeteners, are increasingly recognized. In the present work, pure apple juice concentrate was adulterated with fructose syrup, glucose syrup, and date concentrate. Physicochemical properties (acidity, reducing sugars, formalin index, Brix, and total sugar), organic acid profiles (lactic acid, ascorbic acid, fumaric acid, and malic acid), and minerals (magnesium, iron, zinc, copper, sodium, and potassium) of pure and adulterated apple juice concentrate were evaluated and used to detect adulteration. For this purpose, after reducing the number of parameters determined by principal component analysis (PCA) and identifying the principal components (PCs) using linear and quadratic discriminant analyses (LDA and QDA), 15 parameters (including 4 organic acid factors, 5 physicochemical factors, and 6 mineral elements) were applied to classify the adulteration and authenticity of apple juice concentrate. Based on the results, the first four PCs that showed eigenvalues greater than 1 accounted for 84.5% of the total variance of the data set. The best classification (100%) was obtained using the values of three mineral elements, including sodium, potassium, and copper. Also, two physicochemical parameters, pH and total sugar, as well as the amounts of two organic acids, malic acid and ascorbic acid, were identified as the best parameters for classifying the type and concentration of adulterations in apple concentrate, respectively. The obtained results illustrated supreme discrimination for the type and concentration of the adulterants with a zero 2Log (likelihood) factor and 100% correct classification, which can be used for reliable detection of adulteration in apple concentrate.
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