PhenoPhyte: a flexible affordable method to quantify 2D phenotypes from imagery

Jason M Green,Chi-Ren Shyu,Jaturon Harnsomburana,Peter Balint-Kurti,Heidi Appel,Jia-Fu Chang,Erin Macneal Rehrig

doi:10.1186/1746-4811-8-45

Abstract

BackgroundAccurate characterization of complex plant phenotypes is critical to assigning biological functions to genes through forward or reverse genetics. It can also be vital in determining the effect of a treatment, genotype, or environmental condition on plant growth or susceptibility to insects or pathogens. Although techniques for characterizing complex phenotypes have been developed, most are not cost effective or are too imprecise or subjective to reliably differentiate subtler differences in complex traits like growth, color change, or disease resistance.ResultsWe designed an inexpensive imaging protocol that facilitates automatic quantification of two-dimensional visual phenotypes using computer vision and image processing algorithms applied to standard digital images. The protocol allows for non-destructive imaging of plants in the laboratory and field and can be used in suboptimal imaging conditions due to automated color and scale normalization. We designed the web-based tool PhenoPhyte for processing images adhering to this protocol and demonstrate its ability to measure a variety of two-dimensional traits (such as growth, leaf area, and herbivory) using images from several species (Arabidopsis thaliana and Brassica rapa). We then provide a more complicated example for measuring disease resistance of Zea mays to Southern Leaf Blight.ConclusionsPhenoPhyte is a new cost-effective web-application for semi-automated quantification of two-dimensional traits from digital imagery using an easy imaging protocol. This tool’s usefulness is demonstrated for a variety of traits in multiple species. We show that digital phenotyping can reduce human subjectivity in trait quantification, thereby increasing accuracy and improving precision, which are crucial for differentiating and quantifying subtle phenotypic variation and understanding gene function and/or treatment effects.

Highlights

Accurate characterization of complex plant phenotypes is critical to assigning biological functions to genes through forward or reverse genetics
Forward or traditional genetics is based on the identification of genetic variation associated with observable changes in phenotypic traits like growth rate, morphology, or coloring followed by the identification and characterization of the gene associated with the variation
Pathogenesis or herbivory can be evaluated using scales based on infection or leaf damage levels assessed visually [2,3,4], which can introduce error into the measurements, especially if multiple people are scoring or if a presentation of the phenotype does not fit into one of the predefined categories

Summary

Introduction

Accurate characterization of complex plant phenotypes is critical to assigning biological functions to genes through forward or reverse genetics. It can be vital in determining the effect of a treatment, genotype, or environmental condition on plant growth or susceptibility to insects or pathogens. While identifying yes/no phenotypes is relatively simple, it can be considerably more difficult to assess phenotypic variation that is measured on a continuous scale (i.e. quantitative variation). In these cases, phenotype quantification is often performed using rubrics. One can subsample tissue over time for analysis of pathogens or herbivory; this can introduce an additional wounding treatment, which could render the plant unsuitable for measurements taken at a later time

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Conclusion