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Updated: Mar 12, 2026

Monitoring Plant Hormones During Stress Responses
Published on: June 15, 2009
Hormonal profiling: Development of a simple method to extract and quantify phytohormones in complex matrices by
Carolina Delatorre1, Ana Rodríguez1, Lucía Rodríguez2
1Área de Fisiología Vegetal. Departamento de Biología de Organismos y Sistemas, Universidad de Oviedo, Catedrático Rodrigo Uría, 33006 Oviedo, Spain.
This study presents a new, fast method for extracting and quantifying 20 plant growth regulators (PGRs). The developed technique is robust and suitable for complex plant matrices, aiding in plant status analysis.
Area of Science:
- Plant Science
- Analytical Chemistry
Background:
- Plant growth regulators (PGRs) are crucial for plant development and physiological processes.
- Studying diverse PGRs is vital for understanding plant status due to complex interactions (cross-talk).
- Existing analytical methods often exclude certain PGRs or are limited to simple matrices.
Purpose of the Study:
- To develop a simple, fast, and robust method for extracting and quantifying a wide range of PGRs.
- To overcome limitations of existing methods in terms of compound coverage and matrix complexity.
- To provide a reliable tool for analyzing plant status through comprehensive PGR profiling.
Main Methods:
- Development of a novel extraction protocol for plant samples.
- Optimization of Ultra-High-Performance Liquid Chromatography coupled with tandem Mass Spectrometry (UHPLC-MS/MS).
- Validation of the method for the simultaneous quantification of 20 different PGRs in complex matrices.
Main Results:
- Successfully developed and optimized a simple, fast, and robust analytical method.
- The method enables the extraction and quantification of 20 diverse plant growth regulators.
- The UHPLC-MS/MS technique proved effective for complex plant matrices.
Conclusions:
- The presented method offers a significant advancement for PGR analysis.
- It allows for a more comprehensive understanding of plant physiology and status.
- This robust technique is applicable to complex plant matrices, enhancing research capabilities.
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