A New Method for Extracting Individual Plant Bio-Characteristics from High-Resolution Digital Images

Abstract

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.

Plant phenotyping relevance

個体植物の画像から面積とNDVIを自動抽出する手法を開発し、収量関連形質との相関で評価しており、表現型取得法が研究の中心である。

Code and data availability

The paper's perennial ryegrass UAV multispectral images and extracted plant area/NDVI phenotypes are not publicly deposited; the Data Availability Statement restricts them to on-request access. The only online supplement contains extra comparison figures, not datasets or code, and no author code URL is given.

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