Molecular Soil Biology 2025, Vol.16, No.2, 91-102 http://bioscipublisher.com/index.php/msb 98 a large scale. Some countries treat gene-edited crops the same as genetically modified crops, with strict approval, resulting in a slow pace of new varieties being brought to market. In order to implement these results, the policy level needs to make a distinction, clarify which ones belong to traditional genetic modification and which ones are editing breeding, and reduce social concerns. In addition, detection methods, field testing methods and seed management systems must be established to ensure the stability and safety of these varieties (Fiaz et al., 2021; Hu et al., 2022). 7.2 Combination with sustainable agriculture Improving NUE cannot rely solely on genetic modification, but also requires reasonable planting management measures, such as precision fertilization, use of slow-release fertilizers, and adjustment of fertilization locations (Hu et al., 2022; Wang et al., 2022). In practice, combining efficient nitrogen utilization varieties with these technologies can further reduce the use of chemical fertilizers while maintaining yields (Wang et al., 2022; Jyoti et al., 2024). Breeding varieties with strong root systems and combining them with organic fertilizers can increase the release rate of nitrogen in the soil, allowing crops to grow normally in low-nitrogen environments (Ajmera et al., 2022; Wang et al., 2022). In the future, it is necessary to strengthen the coordination of breeding and agronomic technology, develop local cultivation models for different climate and soil conditions, and achieve the goal of high yields with less fertilizer (Wang et al., 2022; Jyoti et al., 2024). This type of low-nitrogen and high-efficiency variety is very suitable for organic agriculture or ecological planting methods. Combining traditional methods such as green manure, intercropping, and organic fertilizers with varieties with strong nitrogen absorption capacity can not only improve the overall nitrogen utilization efficiency of the system, but also reduce pollution and greenhouse gas emissions (Ajmera et al., 2022; Jyoti et al., 2024). Next, we should focus on promoting this low-input, high-efficiency green planting system to promote sustainable agricultural development (Wang et al., 2022; Jyoti et al., 2024). 7.3 Application of digital technology and AI in rice breeding Current remote sensing, drones, and digital phenotyping platforms are developing rapidly, which can efficiently record the growth of rice, such as plant growth, leaf color, root status, etc. (Ajmera et al., 2022; Salama et al., 2024). These devices can quickly collect a large amount of information and can be used repeatedly in different locations and at different times, without being restricted by weather and labor, which improves the accuracy and efficiency of phenotypic analysis. In the future, these technologies will become important tools for low-nitrogen rice breeding. Big data and artificial intelligence also play an important role in analyzing these data. Combining genetic data, phenotypic data, soil environment, field management and other information, AI algorithms can be used to screen genotypes with good performance and predict the yield performance of new varieties under various nitrogen levels. Machine learning models can also help breeders optimize breeding routes, such as how to combine genes, in which areas to test, and how to arrange field trials. Acknowledgments We sincerely thank the two anonymous reviewers for their valuable opinions and suggestions. 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 Ajmera I., Henry A., Radanielson A., Klein S., Ianevski A., Bennett M., Band L., and Lynch J., 2022, Integrated root phenotypes for improved rice performance under low nitrogen availability, Plant, Cell & Environment, 45: 805-822. https://doi.org/10.1111/pce.14284
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