Triticeae Genomics and Genetics, 2025, Vol.16, No.3, 130-137 http://cropscipublisher.com/index.php/tgg 135 comprehensive evaluation results. Like in the experiments in Russia, several varieties such as "Rushnik 2", "Bereginya" and "Novaya Era" performed quite well. They were not picky about the environment and the yield was stable. In Poland, the conditions were a bit more complex. Hybrid varieties such as KWS Vinetto and SU Performer demonstrated obvious advantages, with yields nearly 18% higher than those of population varieties (Safonova and Aniskov, 2023). Of course, recommendations cannot be copied directly. Ultimately, how to select still depends on the "field conditions" such as local soil, water and fertilizer, and management methods. Only when all these factors are matched can the variety truly perform at its best (Ghafoor et al., 2024; Sulek et al., 2024). 6.3 Application of multi-environment trial results in breeding and dissemination The purpose of completing the experiment is not to write a report, but more importantly, to apply it to breeding and promotion. Multi-environment trials (MET) have now become an indispensable part of rye breeding. If you don't do it, the varieties selected later might not adapt to the local environment. Nowadays, the breeding approach is also different from before. Relying solely on field observations is not enough; high-throughput phenotypic and even genomic data must also be incorporated. With the application of hyperspectral imaging techniques, the prediction of complex traits has become more accurate, and the breeding process can also be significantly accelerated (Galan et al., 2020). Methods such as genomic selection and marker-assisted selection are increasingly being used in combination with traditional methods to help breeders maintain a comprehensive balance of yield, quality and stress resistance (Hawliczek et al., 2023). Ultimately, the varieties truly pushed to farmers should not only be easy to grow and have high yields, but also be able to withstand external variables. 7 Conclusion and Outlook Over the past few years, environmental tests have indeed made it clearer for everyone whether rye can be stably produced under rain-fed conditions. The screening results of which varieties are more stable and better adapted to local conditions have also been gradually released. Indicators such as yield, quality and stability are now basically evaluated together, and genomic tools have also begun to be widely involved in the breeding process. It seems that there has been considerable progress. But things are not that simple. There are still many problems: the reporting standards are not uniform, the analysis methods are scattered here and there, and in addition, the practical operations such as how to recruit people and synchronize data in cross-regional trials are also not easy to handle. Some studies have pointed out that methods supported by highly certain evidence are actually in the minority. Many so-called comparative studies still lack reproducibility and design quality, which has reduced the promotional value of some research results. Where should I go next? Standardization is clearly inevitable. Statistical analysis must be rigorous and repeatability must also be improved. Especially when multi-environment data becomes complex, if issues such as cluster analysis and repeated measurements are not handled clearly, the credibility of the results becomes a question mark. One more point - the report must be transparent. What methods were used, where the data came from, and how the analysis was conducted cannot be kept under wraps. On the other hand, integrating new technologies such as genomic selection, high-throughput phenotyping, and modeling into the breeding process will also accelerate genetic improvement and enhance adaptability. But technology alone is not enough. To truly address the demands of regional breeding, it is still necessary to rely on a collaborative network, cross-location collaboration, and open data sharing. Only such large-scale cooperation can possibly cope with the challenges of complex environments. The connection between experiments and digital technology is actually already taking place. Remote sensing technology can monitor the growth conditions and environmental changes in the fields in real time. Big data methods can also help us understand those difficult G×E interactions, which ones are more compatible with each other, and speak with data. These new tools have indeed significantly enhanced the efficiency of experiments, data accuracy, and decision-making judgment, and are very helpful for more precise breeding and more targeted variety recommendations. Ultimately, it's not a matter of one replacing the other. Instead, it's about how to better
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