Is it time to abandon the flow cytometry in estimations of genome size when the K<i>-</i>mer analysis is available? The case of <i>Engelhardia</i> species

Genome size represents a fundamental genomic trait with profound implications across evolutionary biology, ecology, and genomics. Flow cytometry (FCM) has served as the gold standard for estimating genome size for decades, while the advent of next-generation sequencing has popularized K<italic>-</italic>mer analysis as an increasingly viable alternative. This technological development prompts a critical reassessment of FCM, a method that is revered yet often questioned. To evaluate their relative accuracy and applicability in non-model plants, we conducted a comparative evaluation of both methods in five ecologically significant but genomically understudied <italic>Engelhardia</italic> species as a test case. Our results revealed that FCM yielded genome sizes with consistent estimates of 800–870 Mb, while K-mer analysis produced broader estimates (720–1,130 Mb) with additional genomic insights into their heterozygosity and repeat content. K-mer analysis provides simultaneous structural information as well as indicating genomic size; however, it also presents three notable limitations: (1) it is sensitive to repetitive elements and sequencing biases; (2) it requires a sustained period of analytical processing to complete the related workflow; and (3) it has variable precision with broad estimations of genomic size despite the higher theoretical resolution. Contrary to the prevailing technological thinking, our findings challenge the assumption that K-mer methods universally supersede FCM. The continued utility of FCM is evidenced by its operational simplicity, cost-effectiveness and reliability for preliminary assessments. We argue that methodological selection should be guided by research objectives rather than technological novelty. For nonmodel plants particularly, FCM remains an indispensable tool rather than competing with sequencing-based approaches. The future of estimating genome size lies not in the exclusive adoption of either method, but in their strategic integration depending on the required precision, the available resources, and the desired genomic insights.