Automated Vegetative Stage Phenotyping Analysis of Maize Plants using Visible Light Images
Extracting meaningful numerical phenotypes from plant images remains a substantial bottleneck in image based automated plant phenotyping. We classify approaches to the analysis of automated image based plant phenotyping into two broad categories, namely, holistic and component based. Holistic analyses consider the whole plant as a single object and measure its attributes, whereas component based phenotyping analyzes the individual parts of a plant, i.e. individual leaves and stems. Two new holistic phenotypes are introduced in this paper, i.e. bi angular convex hull area ratio and plant aspect ratio. Bi angular convex hull area ratio is defined as the ratio of the area of the convex hull of the plant when viewed from the side at a particular angle and the convex hull of the same plant when viewed at a rotation of 90* Changes in bi angular convex hull area ratio provide information about temporal change in phyllotaxy, i.e. the arrangement of leaves around a stem. Plant aspect ratio is defined as the ratio of the height of the bounding rectangle of the plant viewed from the side and the diameter of the minimum enclosing circle of the plant when viewed from directly above. Plant aspect ratio identifies potential differences in the canopy architecture which would be generated by different crop accessions in the field. Two componentbased phenotyping parameters are also computed: number of leaves, and the length of each leaf. The paper introduces a benchmark dataset called Panicoid Phenomap 1, which comprises images of 40 genotypes of panicoid grain crops *Corresponding author. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. DS FEW '16 August 14, 2016, San Francisco, CA, USA c (c) 2016 ACM. ISBN 123 4567 24 567/08/06. $15.00 DOI: 10.475/123 4 captured by visible light camera once daily for 26 days using the Lemnatec scanalyzer 3D high throughput plant phenotyping facility at the University of Nebraska Lincoln, USA, to facilitate vegetative stage temporal phenotyping analysis. Experiments are performed on Panicoid Phenomap 1 dataset to demonstrate the genetic regulation of variation in these phenotypes in maize.