What Is EPL?
The Easy Phenotyping Lab (EPL) is a movement dedicated to simplifying and democratizing crop phenotyping for researchers worldwide. As a non-profit scientific initiative—just getting under way—EPL develops simple, novel, and reliable solutions for the widespread phenotyping challenges researchers in crop and plant sciences face globally. Building on the founder’s published high-throughput phenotyping (HTP) research, EPL also shares its own software tools, code snippets, computational models, and novel measurement approaches designed to make plant and crop phenotyping accessible to any lab, anywhere.
Initiated by: Abbas Haghshenas (Independent Researcher in Crop Production, Shiraz, Iran)
Contact: haqueshenas@gmail.com
With thanks to Prof. Yahya Emam (Shiraz University, Iran) for his invaluable support and collaboration.
Why We’re Here?
- Empower Research Worldwide: Offer our easy-to-use and reliable phenotyping tools and methods to research labs globally, ensuring that simplicity and accessibility drive scientific discovery.
- Bridge Innovation and Adoption: Invite phenotyping experts to adapt and share their latest solutions in formats that are readily available, affordable, and user-friendly for non-specialist researchers. By aligning diverse innovations with EPL’s principles, we aim to close the gap between the multitude of annual technical advances and their practical uptake.
- This approach addresses the current imbalance between the rapid pace of phenotyping tool development and its limited global utilization due to technical complexity and resource barriers.
Core Principles
- Reliability: Rigorous, tested code and scientifically sound methodologies.
- Simplicity: Clear examples, minimal dependencies, and step-by-step guides.
- Availability: All code hosted openly on GitHub under permissive licenses.
- Affordability: No proprietary software required—just open-source tools or nearly free options.
- Reproducibility: Sample data and parameter files included so outputs can be cross-checked.
- Community: Any researcher, anywhere, is welcome to use, test, and improve these tools.
Explore Our Tools
Canopy-CCGR
Canopy CCGR is a user-friendly tool that pioneers the quantitative definition of image-based phenology alongside traditional methods. This RGB-based, reproducible Code Ocean capsule is helpful for evaluating the effects of environmental variations—such as ripening trend, irrigation regimes, soil moisture, cold or pest stress—and of genotype on crop canopies.
Run on Code Ocean →
Canopy-GSM
Explore 2D crop canopy images with GSM: Efficiently quantify shading patterns using RGB triplets. Generate a versatile graph for canopy identification, sunlight exposure classification, and valuable quantitative output. Dive into modern phenotyping with this user-friendly image mining tool.
Run on Code Ocean → View on GitHub →
Visual-Grain-Analyzer
Visual Grain Analyzer (VGA) is a user-friendly ImageJ macro, which has utilized ImageJ/or Fiji facilities to provide a simple tool for grain analysis, seed technology, and phenomics studies.
View on GitHub →
Optical-Leaf-Area
Optical Leaf Area (OLA) is a user-friendly ImageJ macro, which has utilized ImageJ/or Fiji facilities to provide a simple tool for leaf area measurement.
View on GitHub →
Volumetric-Leaf-Area
A novel destructive phenotyping method that replaces labor-intensive leaf unfolding and scanning with a simple leaf-pile volumetry approach. By measuring the volume of an entire leaf pile via a basic suspension technique, VLA delivers precise and accurate total leaf-area estimates—streamlining workflows and removing the tedium of conventional methods.
Read the paper →
Easy-Quadrat
Easy Quadrat is nothing but the same quadrat traditionally used in agronomy and crop science. Now, it has been brought into the field of modern phenotyping, for cropping and sampling; not from the plants themselves but rather from the images of plants.
View on GitHub →
Acoustic-Volumeter
An open source, DIY, microphone free acoustic volumetry platform for rapid, precise volumetric measurements—designed for global phenotyping applications.
View on GitHub →Scientific Datasets
The Easy-Phenotyping Lab (EPL) is committed to open science. We share datasets that underpin our research to support reproducibility and foster further innovation.
Images of Wheat Grains
Platform: Figshare
This image archive includes 180 images taken from ~72,000 harvested grains of wheat cultivars grown under varied irrigation conditions. Used in:
Haghshenas, A., Emam, Y., & Jafarizadeh, S. (2022). Wheat grain width: a clue for re-exploring visual indicators of grain weight. Plant Methods, 18(1), 58. https://doi.org/10.1186/s13007-022-00891-1
View Dataset on Figshare →
Diverse Canopy of Wheat Cultivar Mixtures
Platform: Zenodo
Includes 1676 nadir images captured from 90 wheat plots across two growing seasons with different irrigation treatments. Useful for phenotyping, phenology, and water stress research.
View Dataset on Zenodo →Key Eco-Physiological Findings by EPL
Grain width is the core phenotypic contributor to wheat grain weight.
Found using Visual-Grain-Analyzer (VGA).
Read more →An independent, image-based quantitative phenology model—pioneering in its parallel application to conventional qualitative approaches—was introduced.
Developed and validated with Canopy-CCGR.
Read more →A new definition of canopy: each green canopy can be represented quantitatively using two image-derived exponential equations—based on green-gradient-normalized red and blue trends—that together form the GSM curve (Green-Gradient-Based Canopy Segmentation). Shading patterns are then categorized by the local slopes of those trends, and also their curvature can predict and characterize environmental and genetic variation.
Developed using Canopy-GSM.
Read more →An accidental observation revealed that soil red-color intensity in RGB images taken at wheat booting can predict final relative grain yield.
Discovered with Canopy-CCGR.
Read more →Leaf-pile volumetry offers a rapid, simple, and highly accurate alternative to laborious destructive leaf-area methods—regardless of sample size—and suggests that leaf volume may better characterize canopy light interactions than area.
Demonstrated with the Volumetric Leaf Area (VLA) method.
Read more →Citation
If you use Easy-Phenotyping Lab (EPL) tools, please cite us:
Haghshenas, A. (2025). Easy-Phenotyping Lab (EPL) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.15296178
