Maize Genomics and Genetics 2025, Vol.16, No.1, 45-59 http://cropscipublisher.com/index.php/mgg 56 10 Concluding Remarks When it comes to corn breeding, the diversity of germplasm resources is a real treasure. Methods such as principal component analysis (PCA) and GT biplots have been of great help, allowing us to see the variation patterns of key traits such as grain weight and plant height. Interestingly, the differences between varieties in different regions are particularly obvious - temperate and tropical strains are like two different worlds, and SNP marker analysis makes this genetic difference clear. The local varieties in West Africa are also quite surprising. Although they look inconspicuous, they are rich in genetic variation. Of course, the most practical traits are nitrogen use efficiency, which is directly related to yield performance. But then again, with so many good genes discovered, the real challenge is how to use them in actual breeding. When it comes to corn breeding, it is not enough to just look at the phenotype, it must be combined with genotype analysis to be reliable. The data from the field is of course important, as it can show which traits are truly resistant to stress and have stable yields. But to be honest, sometimes the same variety performs very differently in different plots, and this requires genetic testing to find the cause. Now using technologies such as RNA-seq and SNP, we can discover a lot of interesting gene variants. Although the sequencing data looks dazzling, it does help us locate a lot of key QTLs. The most interesting thing is that using these genetic markers in the genomic selection model can accurately predict the performance of new varieties. Of course, no matter how beautiful the laboratory data is, it ultimately depends on how well it grows in the field. However, it is undeniable that the combination of these two aspects does improve breeding efficiency a lot. Corn breeding is easier said than done. Although the GEM project has enriched the gene pool of American corn, to be honest, many foreign germplasms have not been properly utilized. Look at the local varieties in China and southern Africa, the genetic variation is quite rich (Smith et al., 2021), but not many of them are actually used in breeding. The problem now is that we have to maintain yield and improve stress resistance, and existing materials alone are indeed a bit stretched. Of course, phenotypic analysis and genetic testing technology have made a lot of progress in recent years, which has greatly helped breeding work. However, if we want to continue to improve global corn varieties, we must work harder and integrate more diverse germplasm resources. After all, climate change is so severe, no one knows what new challenges we will encounter tomorrow. Acknowledgments We would like to thank CropSci Publisher continuous support throughout the development of this study. 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 Ababulgu D., Shimelis H., Laing M., and Amelework B., 2018, Phenotypic characterization of elite quality protein maize (QPM) inbred lines adapted to tropical-highlands and the association studies using SSR markers, Australian Journal of Crop Science, 12: 22-31. https://doi.org/10.21475/ajcs.18.12.01.pne567 Abdel-Ghani A., Kumar B., Reyes-Matamoros J., Gonzalez-Portilla P., Jansen C., Martin J., Lee M., and Lübberstedt T., 2012, Genotypic variation and relationships between seedling and adult plant traits in maize (Zeamays L.) inbred lines grown under contrasting nitrogen levels, Euphytica, 189: 123-133. https://doi.org/10.1007/s10681-012-0759-0 Al-Naggar A., Shafik M., and Musa, R., 2020, Genetic diversity based on morphological traits of 19 maize genotypes using principal component analysis and GT Biplot, Annual Research & Review in Biology, 35(2): 68-85. https://doi.org/10.9734/arrb/2020/v35i230191 Azrai M., Aqil M., Efendi R., Andayani N., Makkulawu A., Iriany R., Suarni, Yasin M., Suwardi, Zainuddin B., Salim, Sitaresmi T., Bahtiar, Paesal, and Suwarno W., 2023, A comparative study on single and multiple trait selections of equatorial grown maize hybrids, Frontiers in Sustainable Food Systems, 7: 1185102. https://doi.org/10.3389/fsufs.2023.1185102 Boer M., Wright D., Feng L., Podlich D., Luo L., Cooper M., and Van Eeuwijk F., 2007, A mixed-model quantitative trait loci (QTL) analysis for multiple-environment trial data using environmental covariables for QTL-by-environment interactions, with an example in maize, Genetics, 177: 1801-1813. https://doi.org/10.1534/genetics.107.071068
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