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A two-stage approach for the spatio-temporal analysis of high-throughput phenotyping data
Diana M Pérez-Valencia1,2, María Xosé Rodríguez-Álvarez3,4,5, Martin P Boer6
1BCAM-Basque Center for Applied Mathematics, Mazarredo 14, 48009, Bilbao, Spain. dperez@bcamath.org.
Scientific Reports
|February 25, 2022
Summary
This study introduces a novel two-stage statistical method for analyzing high-throughput plant phenotyping (HTP) data. The approach effectively models plant growth trajectories, aiding in genotype selection for plant breeding programs.
Area of Science:
- Agricultural Science
- Plant Biology
- Statistical Genetics
Background:
- High-throughput phenotyping (HTP) platforms generate extensive longitudinal data for plant genotypes.
- Analyzing HTP data is challenging due to complex spatio-temporal noise and the need to estimate genetic signals.
- Accurate statistical methods are crucial for extracting meaningful biological insights from HTP datasets.
Purpose of the Study:
- To develop and validate a robust statistical framework for analyzing longitudinal HTP data.
- To address the challenges of spatio-temporal noise in HTP data analysis.
- To facilitate genotype selection in plant breeding by extracting key growth phenotypes.
Main Methods:
- A two-stage statistical approach for HTP data analysis.
- Stage 1: Correction for design features and spatial trends per time point.
- Stage 2: Hierarchical three-level P-spline growth curve modeling (plants nested in genotypes, genotypes in populations) applied to spatially corrected data.
Main Results:
- The proposed method effectively corrects for spatio-temporal variations in HTP data.
- The hierarchical P-spline model successfully captures shared longitudinal features across plants and genotypes.
- Extracted phenotypes, including growth rates derived from growth curves and their derivatives, are useful for genotype selection.
Conclusions:
- The developed two-stage approach provides a powerful tool for analyzing complex longitudinal HTP data.
- This methodology enhances the ability to identify superior genotypes in plant breeding through precise growth characterization.
- The approach is validated using real-world HTP data from diverse phenotyping platforms.
