Triticeae Genomics and Genetics, 2025, Vol.16, No.6, 245-253 http://cropscipublisher.com/index.php/tgg 247 between the output result and the manual scoring by experts is not significant, but it saves a lot of manpower. It is precisely for this reason that the acquisition of phenotypic data can finally be more standardized and consistent. Figure 1 Fusarium head blight resistance in Xinong 511 and Aikang 58 (Adopted from Yang et al., 2025) 3.3 Multi-timepoint, multi-trait dynamic monitoring and data standardization Fusarium head blight does not end as soon as it appears. It will continue to develop throughout the entire growth period. Therefore, data at a single time point is inevitably one-sided. The advantage of the new generation phenotypic platform lies in its ability to monitor multiple traits in real time and continuously, including various detailed reactions during the disease development process. Although data collection has become easier, standardization processing is still necessary in the later stage to ensure that data from different batches and locations match. This step still cannot be ignored. Especially when it comes to linking phenotypic results with GWAS, the accuracy of data integration becomes even more important (Yang et al., 2020; Leiva-Sandoval, 2023). Judging from the current trend, these technologies are gradually shortening the path between genotype screening and resistance breeding. 4 Overview of Genome-Wide Association Study (GWAS) Methods 4.1 Principles and application processes of GWAS in plants To identify the genes behind complex traits like fusarium head blight resistance, GWAS has become a mainstream tool. This type of analysis usually focuses on SNPS (Single nucleotide polymorphisms), but in fact, the entire process is more complicated than imagined. From the very beginning of designing the experiment, to obtaining phenotypic and genotypic data, and then to the later statistical analysis, no step can be taken lightly. For plant research, the appeal of GWAS lies in its ability to identify the connections between traits and genetic variations in natural populations, thereby helping to identify potential breeding candidate genes (Uffelmann et al., 2021). However, the reliability of the result depends on whether each link is solid, especially the rigor of the statistical part and the consistency of the data.
RkJQdWJsaXNoZXIy MjQ4ODYzNA==