Characterization and classification of Romanian acacia honey based on its physicochemical parameters and chemometrics

• Published in: Scientific reports Vol. 10; no. 1; p. 20690
• Main Authors: Crăciun, Mihaela Emanuela, Pârvulescu, Oana Cristina, Donise, Andreea Cristina, Dobre, Tănase, Stanciu, Dumitru Radu
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 26-11-2020; Nature Publishing Group
• Subjects: 639/166; 639/638; Acacia - chemistry; Acidity; Acids - chemistry; Animals; Bees; Carbohydrates - chemistry; Carbon isotopes; Carbon Isotopes - chemistry; Classification; Discriminant Analysis; Food Contamination - analysis; Fructose - chemistry; Furaldehyde - analogs & derivatives; Furaldehyde - chemistry; Glucose - chemistry; Honey; Honey - analysis; Humanities and Social Sciences; Hydrogen-Ion Concentration; Isotopes; multidisciplinary; Physicochemical properties; Principal Component Analysis; Principal components analysis; Romania; Science; Science (multidisciplinary); Sucrose; Sucrose - chemistry; Sugar; Syrups; Romania
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-020-77685-9

Three groups of Romanian acacia honey, i.e., pure, directly adulterated (by mixing the pure honey with three sugar syrups), and indirectly adulterated (by feeding the bees with the same syrups), were characterized and discriminated based on their physicochemical parameters. Moisture, ash, 5-hydroxymethylfurfural (HMF), reducing sugars (fructose and glucose), and sucrose contents, free acidity, diastase activity, ratio between stable carbon isotopes of honey and its proteins (
δ
13
C
H
and
δ
13
C
P
) were evaluated. Adulteration led to a significant increase in sucrose content, HMF level, and Δ
δ
13
C
 = 
δ
13
C
H
‒
δ
13
C
P
as well a decrease in reducing sugar content and diastase activity. Principal component analysis (PCA) and linear discriminant analysis (LDA) were applied to experimental data in order to distinguish between pure and adulterated honey. The most relevant discriminative parameters were diastase activity, HMF, sucrose, and reducing sugar contents. Posterior classification probabilities and classification functions obtained by LDA revealed that 100% of honey samples were correctly assigned to their original group.