Efficiently recording and processing data from arbuscular mycorrhizal colonization assays using AMScorer and AMReader

Area of Science:

• Plant biology
• Mycology
• Agricultural science

Background:

• Arbuscular mycorrhizal (AM) fungi form mutualistic symbioses with land plants, enhancing nutrient uptake and stress resistance.
• Increasing interest in AM fungi stems from their potential to reduce fertilizer use and improve crop resilience.
• Accurate quantification of AM colonization is crucial for research but current methods are time-consuming.

Purpose of the Study:

• To develop streamlined tools for recording and processing AM fungal colonization data.
• To accelerate research on AM symbioses and support researchers with limited resources.
• To facilitate data storage and sharing for AM colonization assays.

Main Methods:

• Development of AMScorer, an Excel spreadsheet for rapid data recording during microscopy.
• Implementation of AMReader, an R package for visualization and statistical analysis of AMScorer data.
• Validation of tools requiring minimal Excel and R proficiency.

Main Results:

• AMScorer reduced data collection time by over 50% compared to traditional paper-based methods.
• AMReader provides user-friendly visualization and statistical analysis capabilities.
• The combined tools simplify and accelerate the entire process of AM colonization assessment.

Conclusions:

• AMScorer and AMReader significantly improve the efficiency of quantifying AM fungal colonization.
• These tools lower barriers to research in plant-fungal symbiosis, aiding resource-limited labs.
• The developed software facilitates data management and promotes collaborative research in the field.