Honey quality and authenticity analysis represent a current concern for the food industry due to increasing fraud cases detected worldwide regarding botanical origin and adulteration. The main adulterants used in honey are cheap industrial sugars or syrups, molasses, and pollen, among others. Lately, adulteration with C3 plants syrups is replacing the ones obtained from C4 plants due to their difficult detection with official methods. This fact, together with the decreased global production of honey due to environmental imbalances, aggravates the practices of adulteration and falsification of its botanical origin. This fraud, which extends to other hive products, besides being dishonest and unfair to consumers, represents a significant economic loss for producers who do not engage in these fraudulent practices. Thus, producers and consumers require novel powerful analytical techniques capable of detecting these frauds with accuracy, precision, and fast, cheap, and non-destructive instrumentation for their implementation in the food industry. In this sense, spectroscopic techniques represent the best choice to meet this challenge, concretely Nuclear Magnetic Resonance (NMR), Infrared (IR), and Raman spectroscopies, combined with chemometric tools. Moreover, Hyperspectral Imaging (HSI) has emerged as the most promising approach in combination with artificial intelligence (AI).
Non-destructive Analytical Technologies for the Analysis of Honey and Related Bee-Based Products
Ciulu, Marco;
2025-01-01
Abstract
Honey quality and authenticity analysis represent a current concern for the food industry due to increasing fraud cases detected worldwide regarding botanical origin and adulteration. The main adulterants used in honey are cheap industrial sugars or syrups, molasses, and pollen, among others. Lately, adulteration with C3 plants syrups is replacing the ones obtained from C4 plants due to their difficult detection with official methods. This fact, together with the decreased global production of honey due to environmental imbalances, aggravates the practices of adulteration and falsification of its botanical origin. This fraud, which extends to other hive products, besides being dishonest and unfair to consumers, represents a significant economic loss for producers who do not engage in these fraudulent practices. Thus, producers and consumers require novel powerful analytical techniques capable of detecting these frauds with accuracy, precision, and fast, cheap, and non-destructive instrumentation for their implementation in the food industry. In this sense, spectroscopic techniques represent the best choice to meet this challenge, concretely Nuclear Magnetic Resonance (NMR), Infrared (IR), and Raman spectroscopies, combined with chemometric tools. Moreover, Hyperspectral Imaging (HSI) has emerged as the most promising approach in combination with artificial intelligence (AI).
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
