Effective population size ( N e ) is a pivotal evolutionary parameter with crucial implications in conservation practice and policy. Genetic methods to estimate N e have been preferred over demographic methods because they rely on genetic data rather than time-consuming ecological monitoring. Methods based on linkage disequilibrium, in particular, have become popular in conservation as they require a single sampling and provide estimates that refer to recent generations. A recently developed software based on linkage disequilibrium, GONE, looks particularly promising to estimate contemporary and recent-historical N e (up to 200 generations in the past). Genomic datasets from non-model species, especially plants, may present some constraints to the use of GONE, as linkage maps and reference genomes are seldom available, and SNPs genotyping is usually based on reduced-representation methods. In this study, we use empirical datasets from four plant species to explore the limitations of plant genomic datasets when estimating N e using the algorithm implemented in GONE, in addition to exploring some typical biological limitations that may affect N e estimation using the linkage disequilibrium method, such as the occurrence of population structure. We show how accuracy and precision of N e estimates potentially change with the following factors: occurrence of missing data, limited number of SNPs/individuals sampled, and lack of information about the location of SNPs on chromosomes, with the latter producing a significant bias, previously unexplored with empirical data.