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<p>The release of the rice reference genome marked the beginning of a genomic era for crops. Over the past decades, the improvements in genome sequencing and assembly techniques, coupled with the continuous decrease in cost, had revolutionized crop research and breeding. In this review, by text mining the literatures published from 2000 to 2024, we summarize the traits, tissues, and methods prioritized by crop scientists during this period. These analyses reveal profound influence of genomic approaches across all the stages of crop research and breeding, and propose a 4D roadmap of crop research, which are decoding, discovery, design and delivery, representing four steps from crop genome sequencing (decoding) to breeding (delivery). The results also highlight a strong bias of crops and traits in the current studies. Finally, a dramatic increase in the frequency of keywords related to artificial intelligence (AI) indicate wider and deeper AI applications in crop science, forecasting the imminent AI era for crops.</p>

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Text mining reveals the increasing importance of genomic approaches in crop research and breeding

  • 期刊论文

  • 发表日期：

    2025年10月10日

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  • Zhiyi Ye,
  • Jinjin Lu,
  • Yuchen Sun,
  • Tanrui Zou,
  • Sixing Li,
  • Bo Song

摘要

The release of the rice reference genome marked the beginning of a genomic era for crops. Over the past decades, the improvements in genome sequencing and assembly techniques, coupled with the continuous decrease in cost, had revolutionized crop research and breeding. In this review, by text mining the literatures published from 2000 to 2024, we summarize the traits, tissues, and methods prioritized by crop scientists during this period. These analyses reveal profound influence of genomic approaches across all the stages of crop research and breeding, and propose a 4D roadmap of crop research, which are decoding, discovery, design and delivery, representing four steps from crop genome sequencing (decoding) to breeding (delivery). The results also highlight a strong bias of crops and traits in the current studies. Finally, a dramatic increase in the frequency of keywords related to artificial intelligence (AI) indicate wider and deeper AI applications in crop science, forecasting the imminent AI era for crops.