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Related Concept Videos

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Related Experiment Video

Updated: Jan 7, 2026

Author Spotlight: Unraveling Plant Responses to Abiotic Stresses Using the PlantScreen Robotic Platform
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Methodological Advances in Transcriptomics and Metabolomics for Assessing Crop Stress Resilience.

Sanja Ćavar Zeljković1,2, Faisal Saeed3, Dunja Šamec4

  • 1Czech Agrifood Research Center, Olomouc, Czech Republic.

Physiologia Plantarum
|December 30, 2025
PubMed
Summary
This summary is machine-generated.

Advancements in transcriptomics and metabolomics offer powerful tools to understand how crops respond to climate change. These integrative omics approaches accelerate the development of climate-resilient crops for global food security.

Keywords:
crop resiliencedata integrationmachine learningmetabolomicstranscriptomics

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Area of Science:

  • Agricultural Science
  • Plant Biology
  • Genomics

Background:

  • Climate change threatens agriculture, biodiversity, and food security.
  • Developing crops with enhanced abiotic stress resilience is crucial.
  • Transcriptomics and metabolomics provide molecular and biochemical insights into plant stress responses.

Purpose of the Study:

  • To review methodological advancements in transcriptomics and metabolomics for assessing crop stress resilience.
  • To highlight the synergistic potential of these omics approaches.
  • To discuss challenges and emerging solutions for cross-omics data integration.

Main Methods:

  • Review of recent innovations in high-throughput sequencing, long-read transcriptomics, and mass spectrometry.
  • Examination of integrative omics approaches.
  • Discussion of computational and standardization challenges in data integration.

Main Results:

  • Transcriptomics and metabolomics offer high-resolution insights into plant stress responses.
  • Synergistic use of these methods enhances understanding of plant resilience.
  • Emerging solutions like spatial omics and AI-assisted analytics address integration challenges.

Conclusions:

  • Integrative omics approaches, including AI-assisted analytics, are vital for developing climate-resilient crops.
  • These methods accelerate breeding programs and support climate-smart agriculture.
  • Enhanced crop resilience is key to ensuring global food security.