Deploying Fourier Coefficients to Unravel Soybean Canopy Diversity.
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.
Department of Mechanical Engineering, Iowa State University Ames, IA, USA.
Talukder Z
TZ
Jubery
Department of Agronomy, Iowa State University Ames, IA, USA.
Johnathon
J
Shook
Department of Agronomy, Iowa State University Ames, IA, USA.
Kyle
K
Parmley
Department of Agronomy, Iowa State University Ames, IA, USA.
Jiaoping
J
Zhang
Department of Mechanical Engineering, Iowa State University Ames, IA, USA.
Hsiang S
HS
Naik
Department of Agronomy, Iowa State University Ames, IA, USA.
Race
R
Higgins
Department of Mechanical Engineering, Iowa State University Ames, IA, USA.
Soumik
S
Sarkar
Department of Agronomy, Iowa State University Ames, IA, USA.
Arti
A
Singh
Department of Agronomy, Iowa State University Ames, IA, USA.
Asheesh K
AK
Singh
Department of Mechanical Engineering, Iowa State UniversityAmes, IA, USA; Department of Electrical and Computer Engineering, Iowa State UniversityAmes, IA, USA; Plant Sciences Institute, Iowa State UniversityAmes, IA, USA.
Baskar
B
Ganapathysubramanian
canopy outline; diversity panel; elliptic Fourier; image processing