Identifying stock is key to sustainable fisheries management and conservation. Using traditional morphometrics (TMR) and image-based truss network analysis (ITNA), we evaluated the stock structure of the endangered queen loach, Botia dario. The study was carried out in the following five stocks in Bangladesh’s northern rivers: the Atrai, Dhorala, Danu, Jamuna, and Padma. The inventory regarding stock structure was investigated using a total of nine traditional morphometrics, 11 ratios, and 23 truss measurements for each individual. To generate 23 ITNA, 12 landmarks were used. To assess variations among the stocks, a principal component analysis (PCA), factor analysis (FA), canonical variate analysis (CVA), and cluster analysis (CA) were performed. Six principal components explained 91.50% of the variation in TMR, while seven principal components explained 73.425% of the variation in ITNA. CVA, using traditional methods and ratios were correctly classified as 65.0%, 42.0%, 64.2%, 89.3%, and 77.5% for Danu, Padma, Jamuna, Dhorala, and Atrai River stocks, respectively, based on original grouped classes. CVA using ITNA was correctly classified as 90.0%, 80.0%, 77.4%, 94.6%, and 98.6% for Danu, Padma, Jamuna, Dhorala, and Atrai River stocks, respectively, based on original grouped classes. CVA analysis based on TMR and ITNA showed that cannonical variates (CV1 to CV3) are related to the whole-body shape. Both TMR and ITNA formed two clusters. In the first cluster, the Jamuna and Atrai River stocks combinedly formed a separate stock based on (TMR). In ITNA, the Dhorala and Atrai River formed as separate stocks from the other four stocks. According to this study, combining TMR and ITNA analysis aids in the differentiation of various B. dario stocks. The stock separation of this species was supposed to be geographic disconnection, waterway nature, and temperature variations. The B. dario stocks are heavily exploited and the species is an ideal nominee for species variation to boost the aquaculture yield. Within-stock distinctions were revealed in this study, necessitating the identification of gene pools and molecular studies to achieve a deeper understanding of the stocks. Through a more scientific approach, this stock structure study may aid in the development of conservation programs for this endangered species.
