ReviewFundamental research2026
Research progress of omics technologies in forage breeding.
Review in Fundamental research, 2026. 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
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0 citing papers in PubMed.
No citing paper in PubMed yet.
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Forages are essential to global agriculture and ecosystems, with the development of high-yield, high-quality varieties as a cornerstone of efficient agricultural practices. However, traditional genetic breeding methods, characterized by lengthy cycles and limited efficiency, fall short of meeting the demands of modern agriculture. In recent years, the rapid advancements in omics technologies, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics, have significantly transformed forage research. These tools have deepened our understanding of the biological mechanisms underlying forage growth and development, aided in identifying essential genes and metabolic pathways, and accelerated the improvement of forage varieties. This review summarizes the applications and recent advances of various omics approaches in major forage species, including alfalfa (
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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.