ReviewMolecular breeding : new strategies in plant improvement2025
Text mining reveals the increasing importance of genomic approaches in crop research and breeding.
Review in Molecular breeding : new strategies in plant improvement, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed.
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.