Los científicos utilizan pruebas de ADN para identificar las fuentes vegetales de la miel, detectar adulteraciones y revelar patógenos de las colmenas. Este método ayuda a distinguir la miel pura local de los productos importados o contaminados con jarabe. Los avances en secuenciación genética hacen que estas detecciones sean más precisas y accesibles.
Jay Evans, del Laboratorio de Abejas de Beltsville del USDA, explora cómo las huellas de ADN en la miel proporcionan información más allá de solo los orígenes vegetales. Estas trazas pueden identificar razas de abejas, patógenos, parásitos e incluso rastros de visitantes de colmenas o cosechadores. Combinado con pruebas químicas para pesticidas y aditivos, el análisis de ADN está fortaleciendo los esfuerzos contra el fraude en la miel. At the 2026 American Beekeeping Federation meeting, German beekeeper Bernhard Heuvel presented on detecting fraud using European scientific collaborations. His work highlights an ongoing arms race between fraudsters and investigators, where chemical methods are increasingly evaded, but DNA offers a more robust approach. Traditional pollen identification via microscopy has limitations, but DNA barcoding targets specific plant genes for precise sourcing. A 2025 UK study by Sophie Dodd and colleagues used this to detect corn and rice syrup adulteration at 1% levels in honey. Rice DNA, absent from UK flora, clearly indicated blending with foreign syrups. Shotgun DNA sequencing examines all genetic material in honey, overcoming biases in single-gene tests. A 2018 Italian study by Samuele Bovo and team confirmed labeled plant sources and identified bee pathogens like viruses and waxmoths. More recently, Priit Paluoja and colleagues analyzed nearly 400 Estonian honeys in 2025, verifying plant diversity for geographic tracing and detecting American foulbrood bacteria, especially in diseased colonies. The method showed no small hive beetle in Estonian samples but traces in US honeys, aiding monitoring of invasive pests. As sequencing costs drop and computational tools improve, these techniques promise better protection for authentic honey and deeper understanding of bee health.
