The increasing global demand for food necessitates ensuring authenticity and traceability, especially for products like honey, which is frequently adulterated. While botanical sources of honey have been extensively studied, entomological sources, crucial for determining honey quality and value, remain less explored. Different *Apis* species produce honey with varying nutritional value and economic worth. The lack of a simple, reliable method to distinguish honey from different *Apis* species hinders industry development and consumer protection. Existing methods, such as DNA-based approaches with species-specific primers or real-time PCR coupled with HRM analysis, face limitations in terms of cost, complexity, and the number of species identifiable simultaneously. PCR-RFLP, a cost-effective and accurate technique widely used in food authenticity identification, has not yet been applied comprehensively to honey entomological origin identification. This study aimed to develop a PCR-RFLP method to address this gap, using samples from six *Apis* species prevalent in China, and testing its robustness against various honey processing conditions.

Numerous methods exist for honey authentication, focusing primarily on botanical origins. DNA-based methods offer high specificity and stability for identifying entomological origins, with previous studies successfully employing species-specific primers targeting genes like tRNA-cox2, MRJP2, and ND2. However, these methods often have limitations: limited species identification within a single PCR reaction, difficulty designing primers for closely related species, and reliance on costly equipment (e.g., real-time PCR and HRM analysis). PCR-RFLP, a cost-effective and easy-to-perform technique, has proven effective in other food authenticity studies, overcoming the limitations of other molecular methods. Despite this, its application to identifying the entomological origin of honey from multiple closely related *Apis* species has been lacking.

The study utilized honey bee worker specimens and honey samples from six *Apis* species (*A. mellifera*, *A. cerana*, *A. laboriosa*, *A. dorsata*, *A. florea*, and *A. andreniformis*) collected from various regions in China. DNA extraction was performed using a commercially available silica-column extraction kit, following a pretreatment step for honey samples to remove interfering substances. A pair of universal primers (16S rRNA-F/16S rRNA-R) was designed to amplify a 470–479 bp fragment of the mitochondrial 16S rRNA gene. PCR amplification was performed, and the resulting products were sequenced and analyzed using BLAST to confirm species identity. Phylogenetic analysis was conducted to evaluate genetic distances between species. The amplified 16S rRNA gene fragment was then digested using the restriction enzyme *Asel*, and the resulting Restriction Fragment Length Polymorphism (RFLP) patterns were analyzed using gel electrophoresis to differentiate between species. The method's robustness was evaluated by testing it on *A. mellifera* honey samples subjected to various processing conditions, including heating, long-term storage, and crystallization, as well as on commercial honey samples.

High-quality DNA was successfully extracted from both honey bee tissues and honey samples. The designed primers effectively amplified the 16S rRNA gene fragment in all six *Apis* species and their corresponding honey samples. Sequence analysis confirmed the identity of each species, with high sequence similarity to published sequences in GenBank. Pairwise genetic distance analysis revealed significant genetic differences among the six species. The *Asel* restriction enzyme successfully generated species-specific RFLP patterns for all six honeybee species and their honeys, enabling differentiation based on fragment size. The method proved robust across various processing conditions—heat treatment (up to 100 °C for 1 hour), long-term storage (up to 8 years at -20 °C), and crystallization—maintaining consistent RFLP profiles comparable to raw honey. This indicates the method's effectiveness for authenticating honey irrespective of processing.

This study successfully developed a cost-effective and simple PCR-RFLP method for identifying the entomological origin of honey from six *Apis* species. The use of a single restriction enzyme (*Asel*) and a universal primer pair simplifies the procedure and makes it accessible even without sophisticated equipment. The method's robustness to various processing treatments is crucial for real-world applications. The ability to differentiate between closely related species adds significant value for honey authentication and traceability, particularly in regions where various *Apis* species coexist. The findings address the current lack of a standardized method for entomological honey certification. This method can be applied to market surveillance, consumer protection, and fair trade practices, ensuring sustainable development of the honey industry.

This study presents a novel, cost-effective PCR-RFLP method for honey authentication using the mitochondrial 16S rRNA gene and *Asel* restriction enzyme. This approach enables the simultaneous identification of six closely related *Apis* species in honey, regardless of processing. This method holds significant potential for establishing standardized guidelines for honey traceability and combatting honey fraud. Future research could explore the application of this method to a wider range of *Apis* subspecies and other honey bee genera, and further optimization of the method for higher throughput.

The study had a limited number of *A. andreniformis* honey samples due to the species' limited distribution and low honey production. While the method's robustness was tested on *A. mellifera* honey, further testing on other species is recommended to ensure broader applicability. The method relies on the presence of honey bee DNA in the honey samples; therefore, highly processed honey samples might yield less reliable results.