Hemp (Cannabis sativa L.), an ancient crop, is a significant source of high-quality fiber that primarily caters to the textile industry worldwide. Fiber content is a crucial quantitative trait for evaluating fiber yield in hemp. Understanding the genetic mechanisms involved in hemp breeding is essential for improving yield. In this study, we developed 660 F1 plants from a cross between Jindao-15 (high fiber content fiber-use variety) and Fire No.1 (low fiber content fiber-use variety), and thirty plants each with high and low fiber content were selected from 305 monoecious plants of this population according to 5%-10% of population size for quantitative traits. The DNA from these plants was extracted to establish two bulk DNA pools and then subjected to the restriction digestion by the enzymes RsaI and HaeIII to obtain 314-364 bp digestion fragments and subjected to sequencing using specific length amplified fragment sequencing (SLAF-seq). Finally, we successfully developed 368,404 SLAF tags, which led to the detection of 25,133 high-quality SNPs. Combing with the resequencing results of parents, the SNPs of mixed pools were then subjected to the SNP-Index correlation algorithm, which revealed four candidate regions related to fiber content traits on Chromosome 1, with a length of 8.68 Mb and containing 389 annotated genes. The annotation information and the comparison results identified 15 genes that were highly likely to modulate the fiber content of hemp. Further, qPCR validation identified six genes (LOC115705530, LOC115705875, LOC115704794, LOC115705371, LOC115705688 and LOC115707511) that were highly positively correlated with influencing the hemp fiber content. These genes were involved in the transcription regulation, auxin and water transportion, one carbon and sugar metabolism. And non-synnoumous mutation SNPs which may play vital role in influencing the fiber content were detected in LOC115705875, LOC115704794, LOC115705688 and LOC115707511. Thus, our study highlights the importance of the combined use of SLAF-Seq and Bulked Segregant analysis (BSA) to locate genes related to hemp fiber content rapidly. Hence, our study provides novel mechanistic inputs for the fast identification of genes related to important agronomic traits of hemp and other crops catering to the textile industry.