DNA methylation, a key component of epigenetic regulation, is essential for preserving normal cellular functions, supporting plant growth, and facilitating development and responses to stress. Whole genome bisulfite sequencing (WGBS) is the definitive method for studying DNA methylation and is extensively used in functional genomics research across both animal and plant species. While various analysis tools have been created for WGBS, a thorough evaluation of their performance in analyzing plant data remains lacking. This study provides a comprehensive assessment of six widely used alignment methods (Abismal, Bismark-his2, BSSeeker2-bwt2-local, BSSeeker2-bwt2-e2e, Bismark-bwt2-e2e, and BSMAP) across four DNA methylation analysis tools. The evaluation encompassed aspects such as runtime efficiency, memory resource utilization, alignment quality, and identification of methylation sites by analyzing DNA methylation data from three major crops: Arabidopsis thaliana, Oryza sativa, and Glycine max. The results indicated that although BSMAP required larger memory requirements, it exhibited higher efficiency in terms of running speed, particularly when dealing with large-scale genomic data. Furthermore, BSMAP showed excellent performance in alignment quality and identification of methylated sites, ensuring the reliability and precision of the results. The study highlights the importance of researchers carefully selecting alignment tools and considering factors like available computational resources, specific research needs, and the balance between processing speed and memory usage. This work offers valuable analytical guidance for scientists engaged in DNA methylation studies plants, contributing to improved research efficiency and result reliability. 1 t holds significant scientific importance for a deeper analysis of DNA methylation in plant biology.