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High throughput phenotyping of cross-sectional morphology to assess stalk lodging resistance

Authors
  • Oduntan, Yusuf A.1
  • Stubbs, Christopher J.2
  • Robertson, Daniel J.1
  • 1 University of Idaho, Moscow, ID, 83844, USA , Moscow (United States)
  • 2 Fairleigh Dickinson University, Teaneck, NJ, 07666, USA , Teaneck (United States)
Type
Published Article
Journal
Plant Methods
Publisher
Springer (Biomed Central Ltd.)
Publication Date
Jan 04, 2022
Volume
18
Issue
1
Identifiers
DOI: 10.1186/s13007-021-00833-3
Source
Springer Nature
Keywords
Disciplines
  • Methodology
License
Green

Abstract

BackgroundStalk lodging (mechanical failure of plant stems during windstorms) leads to global yield losses in cereal crops estimated to range from 5% to 25% annually. The cross-sectional morphology of plant stalks is a key determinant of stalk lodging resistance. However, previously developed techniques for quantifying cross-sectional morphology of plant stalks are relatively low-throughput, expensive and often require specialized equipment and expertise. There is need for a simple and cost-effective technique to quantify plant traits related to stalk lodging resistance in a high-throughput manner.ResultsA new phenotyping methodology was developed and applied to a range of plant samples including, maize (Zea mays), sorghum (Sorghum bicolor), wheat (Triticum aestivum), poison hemlock (Conium maculatum), and Arabidopsis (Arabis thaliana). The major diameter, minor diameter, rind thickness and number of vascular bundles were quantified for each of these plant types. Linear correlation analyses demonstrated strong agreement between the newly developed method and more time-consuming manual techniques (R2 > 0.9). In addition, the new method was used to generate several specimen-specific finite element models of plant stalks. All the models compiled without issue and were successfully imported into finite element software for analysis. All the models demonstrated reasonable and stable solutions when subjected to realistic applied loads.ConclusionsA rapid, low-cost, and user-friendly phenotyping methodology was developed to quantify two-dimensional plant cross-sections. The methodology offers reduced sample preparation time and cost as compared to previously developed techniques. The new methodology employs a stereoscope and a semi-automated image processing algorithm. The algorithm can be used to produce specimen-specific, dimensionally accurate computational models (including finite element models) of plant stalks.

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