Interactive Hybrid Rice Breeding with Parametric Dual Projection
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arXiv
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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866918093943472128 |
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| author | Chen, Changjian Wang, Pengcheng Lyu, Fei Tang, Zhuo Yang, Li Wang, Long Cai, Yong Yu, Feng Li, Kenli |
| author_facet | Chen, Changjian Wang, Pengcheng Lyu, Fei Tang, Zhuo Yang, Li Wang, Long Cai, Yong Yu, Feng Li, Kenli |
| contents | Hybrid rice breeding crossbreeds different rice lines and cultivates the resulting hybrids in fields to select those with desirable agronomic traits, such as higher yields. Recently, genomic selection has emerged as an efficient way for hybrid rice breeding. It predicts the traits of hybrids based on their genes, which helps exclude many undesired hybrids, largely reducing the workload of field cultivation. However, due to the limited accuracy of genomic prediction models, breeders still need to combine their experience with the models to identify regulatory genes that control traits and select hybrids, which remains a time-consuming process. To ease this process, in this paper, we proposed a visual analysis method to facilitate interactive hybrid rice breeding. Regulatory gene identification and hybrid selection naturally ensemble a dual-analysis task. Therefore, we developed a parametric dual projection method with theoretical guarantees to facilitate interactive dual analysis. Based on this dual projection method, we further developed a gene visualization and a hybrid visualization to verify the identified regulatory genes and hybrids. The effectiveness of our method is demonstrated through the quantitative evaluation of the parametric dual projection method, identified regulatory genes and desired hybrids in the case study, and positive feedback from breeders. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_11848 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Interactive Hybrid Rice Breeding with Parametric Dual Projection Chen, Changjian Wang, Pengcheng Lyu, Fei Tang, Zhuo Yang, Li Wang, Long Cai, Yong Yu, Feng Li, Kenli Human-Computer Interaction Artificial Intelligence Quantitative Methods Hybrid rice breeding crossbreeds different rice lines and cultivates the resulting hybrids in fields to select those with desirable agronomic traits, such as higher yields. Recently, genomic selection has emerged as an efficient way for hybrid rice breeding. It predicts the traits of hybrids based on their genes, which helps exclude many undesired hybrids, largely reducing the workload of field cultivation. However, due to the limited accuracy of genomic prediction models, breeders still need to combine their experience with the models to identify regulatory genes that control traits and select hybrids, which remains a time-consuming process. To ease this process, in this paper, we proposed a visual analysis method to facilitate interactive hybrid rice breeding. Regulatory gene identification and hybrid selection naturally ensemble a dual-analysis task. Therefore, we developed a parametric dual projection method with theoretical guarantees to facilitate interactive dual analysis. Based on this dual projection method, we further developed a gene visualization and a hybrid visualization to verify the identified regulatory genes and hybrids. The effectiveness of our method is demonstrated through the quantitative evaluation of the parametric dual projection method, identified regulatory genes and desired hybrids in the case study, and positive feedback from breeders. |
| title | Interactive Hybrid Rice Breeding with Parametric Dual Projection |
| topic | Human-Computer Interaction Artificial Intelligence Quantitative Methods |
| url | https://arxiv.org/abs/2507.11848 |