The Orchidaceae family represents the largest and most diverse group of flowering plants or angiosperms. This family has garnered significant attention due to its aesthetic appeal, as well as its economic and ecological importance. Globally, the Orchidaceae family encompasses approximately 600-800 genera and 25,000-35,000 species. In India, the family includes 158 genera and 1,331 species. The allure and exotic beauty of orchids, combined with their high productivity, extended shelf life, optimal blooming seasons, ease of packaging and transportation, and substantial international market value, have led to frequent smuggling and illegal trade, both offline and online. Effective and accurate identification of smuggled orchid species is crucial for combating this illegal trade. The review highlights both traditional taxonomical approaches, which rely on morphological traits like floral structures, leaf morphology, and root characteristics and advanced molecular methods such as DNA barcoding, ISSR, RAPD, and SCAR markers. DNA barcoding, which employs specific DNA sequences (e.g., ITS, rbcL, and matK), enhances the accuracy of identification, particularly for species that are illegally trafficked at juvenile or sterile stages. The review also addresses the importance of precise species identification in conservation and law enforcement, which is essential for preventing illicit trade and observing international regulations such as CITES. Technical barriers in molecular methods, voids in genetic databases, and ethical concerns regarding plant conservation are examined. This review discusses the possibility of incorporating machine learning and deep learning approaches as well as the use of eDNA(Environmental DNA) for orchid identification purposes. The manuscript concludes by suggesting that additional research be conducted on portable identification technologies, AI integration, and multi-locus barcodes in order to enhance the identification of species and conservation activities, to promote sustainable conservation and prevent illegal trade. Additionally, the article explores future perspectives on the application of emerging identification techniques in this field.
