Easy Leaf Area: Automated digital image analysis for rapid and accurate measurement of leaf area

By H. M. Easlon, A. Bloom. Applications in Plant Sciences, 2014

518 citations recorded by the source corpus.

Premise of the study: Measurement of leaf areas from digital photographs has traditionally required significant user input unless backgrounds are carefully masked. Easy Leaf Area was developed to batch process hundreds of Arabidopsis rosette images in minutes, removing background artifacts and saving results to a spreadsheet-ready CSV file. Methods and Results: Easy Leaf Area uses the color ratios of each pixel to distinguish leaves and calibration areas from their background and compares leaf pixel counts to a red calibration area to eliminate the need for camera distance calculations or manual ruler scale measurement that other software methods typically require. Leaf areas estimated by this software from images taken with a camera phone were more accurate than ImageJ estimates from flatbed scanner images. Conclusions: Easy Leaf Area provides an easy-to-use method for rapid measurement of leaf area and nondestructive estimation of canopy area from digital images.

Subfields: Ecology, Global and Planetary Change, Plant Science

View Paper: https://www.semanticscholar.org/paper/90fb95bf5a89b66541b8d47cd28db4c8b7097321

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In Ecology

In Global and Planetary Change

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Citations in the corpus

An interactive tool for semi-automated leaf annotation (2015, background): “plant) [10, 32], or under predefined experimental conditions (e.”
Extracting leaf area index using viewing geometry effects—A new perspective on high-resolution unmanned aerial system photography (2018, methodology): “2 % if correcting for distortion, as was done in this study (Easlon and Bloom, 2014).”