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Deploying Fourier Coefficients to Unravel Soybean Canopy Diversity
Frontiers in Plant Science
  • Talukder Jubery, Iowa State University
  • Johnathon Shook, Iowa State University
  • Kyle Parmley, Iowa State University
  • Jiaoping Zhang, Iowa State University
  • Hsiang S. Naik, Iowa State University
  • Race Higgins, Iowa State University
  • Soumik Sarkar, Iowa State University
  • Arti Singh, Iowa State University
  • Asheesh K. Singh, Iowa State University
  • Baskar Ganapathysubramanian, Iowa State University
Document Type
Article
Publication Version
Published Version
Publication Date
1-1-2016
DOI
10.3389/fpls.2016.02066
Abstract
Soybean canopy outline is an important trait used to understand light interception ability, canopy closure rates, row spacing response, which in turn affects crop growth and yield, and directly impacts weed species germination and emergence. In this manuscript, we utilize a methodology that constructs geometric measures of the soybean canopy outline from digital images of canopies, allowing visualization of the genetic diversity as well as a rigorous quantification of shape parameters. Our choice of data analysis approach is partially dictated by the need to efficiently store and analyze large datasets, especially in the context of planned high-throughput phenotyping experiments to capture time evolution of canopy outline which will produce very large datasets. Using the Elliptical Fourier Transformation (EFT) and Fourier Descriptors (EFD), canopy outlines of 446 soybean plant introduction (PI) lines from 25 different countries exhibiting a wide variety of maturity, seed weight, and stem termination were investigated in a field experiment planted as a randomized complete block design with up to four replications. Canopy outlines were extracted from digital images, and subsequently chain coded, and expanded into a shape spectrum by obtaining the Fourier coefficients/descriptors. These coefficients successfully reconstruct the canopy outline, and were used to measure traditional morphometric traits. Highest phenotypic diversity was observed for roundness, while solidity showed the lowest diversity across all countries. Some PI lines had extraordinary shape diversity in solidity. For interpretation and visualization of the complexity in shape, Principal Component Analysis (PCA) was performed on the EFD. PI lines were grouped in terms of origins, maturity index, seed weight, and stem termination index. No significant pattern or similarity was observed among the groups; although interestingly when genetic marker data was used for the PCA, patterns similar to canopy outline traits was observed for origins, and maturity indexes. These results indicate the usefulness of EFT method for reconstruction and study of canopy morphometric traits, and provides opportunities for data reduction of large images for ease in future use.
Comments

This article is published as Jubery, Talukder Z., Johnathon Shook, Kyle Parmley, Jiaoping Zhang, Hsiang S. Naik, Race Higgins, Soumik Sarkar, Arti Singh, Asheesh K. Singh, and Baskar Ganapathysubramanian. "Deploying Fourier coefficients to unravel soybean canopy diversity." Frontiers in Plant Science 7 (2016). DOI:10.3389/fpls.2016.02066. Posted with permission.

Creative Commons License
Creative Commons Attribution 4.0
Copyright Owner
Jubery, Shook, Parmley, Zhang, Naik, Higgins, Sarkar, Singh, Singh and Ganapathysubramanian.
Language
en
File Format
application/pdf
Citation Information
Talukder Jubery, Johnathon Shook, Kyle Parmley, Jiaoping Zhang, et al.. "Deploying Fourier Coefficients to Unravel Soybean Canopy Diversity" Frontiers in Plant Science Vol. 7 (2016) p. 2066
Available at: http://works.bepress.com/baskar-ganapathysubramanian/12/