ReviewFrontiers in plant science2026
Deciphering plant stress resilience in different millet crops: from multi-omics discoveries to predictive breeding for climate-resilient crop enhancement.
Review in Frontiers in plant science, 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
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Global climatic and abiotic stresses severely affect agricultural production, while millets are stress-tolerant and nutritious cereal crops adapted to diverse environments. Although single-omics technologies, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, ionomics, and phenomics, have substantially advanced our understanding of individual components of plant stress responses, each approach captures only one molecular layer and therefore cannot fully resolve the interconnected regulatory networks that govern complex stress adaption. The challenge now is to bring together these widely varied molecular data to make them biologically meaningful and to be able to predict genotype-phenotype relationships under varying field conditions. This review critically covers recent developments in multi-omics technologies that have been used to uncover abiotic stress tolerance mechanisms, and how they can be complementary to identify stress-responsive genes, regulatory pathways, stress markers, and adaptive metabolic processes. Additionally, the review covers recent developments in AI and ML integration with multi-omics data, predictive modeling, and precision breeding to enhance the identification of better genotypes and breeding decisions. Finally, future prospects for the integration of multi-omics, AI analytics, digital phenotyping and breeding pipelines for next-generation cultivars of millets for future climate change are outlined, which will enable the improvement of current cultivars with higher resilience, yield and nutritional value, while simultaneously supporting sustainable agriculture.
Indexed as
Identifiers
What OpenQuestion holds
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.