## 3 Discussion  
Breeding for improved faba bean quality is primarily driven by the food industry's demand to increase protein content and reduce off-flavours in plant-based products. This study aimed to investigate the natural variation present in the faba bean germplasm for these traits and dissect their genetic architecture via a GWAS. Phenotyping chemical traits is typically costly, labour-intensive, and time-consuming. We successfully used NIRS to predict protein, oil, fatty acids, and tannins, achieving high cross-validation correlations (r\({}_{\rm cv}\) > 0.72) among the predicted and actual lab values. However, as cross-validation results may overestimate predictive performance, further validation on external samples or under different condition is necessary. Notably, this is the first successful NIRS-based prediction of C18:2, C18:3, and individual tannins in this crop. Further research should focus on predicting phenolic acids, flavonoids, and lipid-derived products. Poor predictions for these compounds in our study are likely due to their low concentrations below the NIRS detection threshold [36]. The CGN population exhibited substantial phenotypic diversity, as indicated by the high coefficients of variation (CV%). This diversity was expected due to the inclusion of three botanical groups (_Vicia faba minor_, _major_, and _equina_) from 43 countries and the low genetic relatedness between CGN accessions [37]. We identified accessions with C18:1 content up to 27% and protein content up to 35% (phenotypic values). These values are among the highest reported in the literature [29; 38; 39]. Thus, these accessions are promising breeding candidates, as high C18:1 and protein are key targets. Some genotypes also showed low levels of phenolic acids, tannins, flavonoids, and lipid-derived products. Overall, tannins were higher than flavonoids, which exceeded phenolic acids. This pattern was previously observed [25; 40; 41]. The lower abundance of phenolic acids is likely due to their rapid metabolism. This study is the first to report the presence of 1-linoleoyl glycerol and 2-hydroxyoleic acid in faba bean. These are compounds that were previously linked to bitterness in peas [42]. The heritability (\(h^{2}\)) values suggest that genetic gain can be achieved faster for traits such as oil, fatty acids, and tannins, with \(h^{2}\) > 0.6 in both years. Protein content had high \(h^{2}\) in 2022 (0.7) but moderate \(h^{2}\) (0.45) in 2022, likely due to the better field conditions. For phenolic acids, flavonoids, lipid-derived products, and convicine, \(h^{2}\) values ranged from moderate to low (0.07 < \(h^{2}\) < 0.49). For these compounds, separating genetic signals from  
Figure 6: Manhattan plots for tannins based on the GWAS performed in 2021. The black dashed line represents the LOD threshold set at 4.5, while the red dashed lines represent the Bonferroni-corrected threshold. Significant signals on chromosome 2 spanned positions 671,378,841 bp to 953,872,991 bp. The x-axis labels “chr1L” and “chr1S” indicate the official division of the very large chromosome 1, as defined by the faba bean genome consortium. residual noise is challenging due to the lower replication, so the \(h^{2}\) estimates mainly reflect the few genotypes with field replicates. The year of cultivation significantly affected all chemical traits. In 2022, higher protein content was likely due to better field conditions and nitrogen availability, while higher levels of phenolic acids, flavonoids, and tannins in 2021 were likely driven by biotic and abiotic stress pressure [43; 44]. Previous research has shown that cultivation location or year affects volatile compounds [45], oil [46], total phenolics and tannins [47], and protein [46], all of which also exhibited genotype-by-environment (GxE) interactions. Different genotypes respond differently to environmental changes--a behaviour known as GxE.