La Trobe

A new method for extracting individual plant bio-characteristics from high-resolution digital images

journal contribution
posted on 2025-11-07, 03:08 authored by Saba Rabab, Edmond Breen, Alem Gebremedhin, Fan Shi, Pieter Badenhorst, Yi-Ping Phoebe ChenYi-Ping Phoebe Chen, Hans Daetwyler
The extraction of automated plant phenomics from digital images has advanced in recent years. However, the accuracy of extracted phenomics, especially for individual plants in a field environment, requires improvement. In this paper, a new and efficient method of extracting individual plant areas and their mean normalized difference vegetation index from high-resolution digital images is proposed. The algorithm was applied on perennial ryegrass row field data multispectral images taken from the top view. First, the center points of individual plants from digital images were located to exclude plant positions without plants. Second, the accurate area of each plant was extracted using its center point and radius. Third, the accurate mean normalized difference vegetation index of each plant was extracted and adjusted for overlapping plants. The correlation between the extracted individual plant phenomics and fresh weight ranged between 0.63 and 0.75 across four time points. The methods proposed are applicable to other crops where individual plant phenotypes are of interest.<p></p>

Funding

The authors acknowledge financial support from Agriculture Victoria, Dairy Australia, and The Gardiner Foundation through the DairyBio initiative and La Trobe University.

History

Publication Date

2021-03-23

Journal

Remote Sensing

Volume

13

Issue

6

Article Number

1212

Pagination

18p.

Publisher

Multidisciplinary Digital Publishing Institute

ISSN

2072-4292

Rights Statement

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).