Maize Genomics and Genetics 2025, Vol.16, No.6, 284-293 http://cropscipublisher.com/index.php/mgg 292 establish the genetic basis of these biomarkers. The practical application of metabolomic markers in breeding programs becomes evident through particular examples which link scientific laboratory results to agricultural development. The future development of spatiotemporal metabolomics together with multi-omics integration and computational modeling will enhance metabolomics to become the core foundation of systems biology. The execution of these methods according to plan will speed up the development of salt-resistant maize varieties which will protect sustainable farming practices and global food security because salinization has emerged as a major issue. Acknowledgments We are grateful to Dr. W. Jin for his assistance with the serious reading and helpful discussions during the course of this work. Conflict of Interest Disclosure The authors affirm that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. References Brar M., De Souza A., Ghai A., Ferreira J., Sandhu D., and Sekhon R., 2025, Untargeted metabolomics reveals key metabolites and genes underlying salinity tolerance mechanisms in maize, bioRxiv, 647850: 1-29. https://doi.org/10.1101/2025.04.08.647850 Cambiaghi A., Ferrario M., and Masseroli M., 2016, Analysis of metabolomic data: tools, current strategies and future challenges for omics data integration, Briefings in Bioinformatics, 18(3): 498-510. https://doi.org/10.1093/bib/bbw031 Cao Y., Zhou X., Song H., Zhang M., and Jiang C., 2023, Advances in deciphering salt tolerance mechanism in maize, The Crop Journal, 11(4): 1001-1010. https://doi.org/10.1016/j.cj.2022.12.004 Chong J., Soufan O., Li C., Caraus I., Li S., Bourque G., Wishart D.S., and Xia J., 2018, MetaboAnalyst 4.0: towards more transparent and integrative metabolomics analysis, Nucleic Acids Research, 46(W1): W486-W494. https://doi.org/10.1093/nar/gky310 He X., Zhu J., Gong X., Zhang D., Li Y., Zhang X., Zhao X., and Zhou C., 2025, Advances in deciphering the mechanisms of salt tolerance in maize, Plant Signaling and Behavior, 20(1): 2479513. https://doi.org/10.1080/15592324.2025.2479513 Hou Y., Zeng W., Ao C., and Huang J., 2024, Integrative analysis of the transcriptome and metabolome reveals Bacillus atrophaeus WZYH01-mediated salt stress mechanism in maize (Zeamays L.), Journal of Biotechnology, 383: 39-54. https://doi.org/10.1016/j.jbiotec.2024.02.004 Ji M., Xu S., Xiao C., Xu J., Zhu Y., Cai R., and Bo C., 2025, Maize leaves salt-responsive genes revealed by comparative transcriptome of salt-tolerant and salt-sensitive cultivars during the seedling stage, PeerJ, 13: e19268. https://doi.org/10.7717/peerj.19268 Khan R., Gao F., Khan K., Shah M., Ahmad H., Fan Z., and Zhou X., 2024, Evaluation of maize varieties via multivariate analysis: Roles of ionome, antioxidants, and autophagy in salt tolerance, Plant Physiology, 196(1): 195-209. https://doi.org/10.1093/plphys/kiae335 Li P., Yang X., Wang H., Pan T., Yang J., Wang Y., Xu Y., Yang Z., and Xu C., 2021, Metabolic responses to combined water deficit and salt stress in maize primary roots, Journal of Integrative Agriculture, 20(1): 109-119. https://doi.org/10.1016/S2095-3119(20)63242-7 Liang X., Liu S., Wang T., Li F., Cheng J., Lai J., Qin F., Li Z., Wang X., and Jiang C., 2021, Metabolomics-driven gene mining and genetic improvement of tolerance to salt-induced osmotic stress in maize, New Phytologist, 230(3): 1732-1747. https://doi.org/10.1111/nph.17323 Luo M., Zhao Y., Wang Y., Shi Z., Zhang P., Zhang Y., Song W., and Zhao J., 2018, Comparative proteomics of contrasting maize genotypes provides insights into salt-stress tolerance mechanisms, Journal of Proteome Research, 17(1): 141-153. https://doi.org/10.1021/acs.jproteome.7b00455 Pang Z., Lu Y., Zhou G., Hui F., Xu L., Viau C., Spigelman A., MacDonald P., Wishart D.S., Li S., and Xia J., 2024, MetaboAnalyst 6.0: towards a unified platform for metabolomics data processing, analysis and interpretation, Nucleic Acids Research, 52(W1): W398-W406. https://doi.org/10.1093/nar/gkae253 Ren S., Bai T., Zhao Y., Ci J., Ren X., Zang Z., Xiong R., Song X., Yang W., and Yang W., 2025, Molecular mechanisms underlying salt tolerance in maize: A combined transcriptome and metabolome analysis, Plants, 14(13): 2031. https://doi.org/10.3390/plants14132031 Shoukat A., Saqib Z., Akhtar J., Aslam Z., Pitann B., Hossain M., and Mühling K., 2024, Zinc and silicon nano-fertilizers influence ionomic and metabolite profiles in maize to overcome salt stress, Plants, 13(9): 124. https://doi.org/10.3390/plants13091224
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