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Increased signal-to-noise ratios within experimental field trials by regressing spatially distributed soil properties as principal components

Authors :
Jeffrey C Berry
Mingsheng Qi
Balasaheb V Sonawane
Amy Sheflin
Asaph Cousins
Jessica Prenni
Daniel P Schachtman
Peng Liu
Rebecca S Bart
Source :
eLife, Vol 11 (2022)
Publication Year :
2022
Publisher :
eLife Sciences Publications Ltd, 2022.

Abstract

Environmental variability poses a major challenge to any field study. Researchers attempt to mitigate this challenge through replication. Thus, the ability to detect experimental signals is determined by the degree of replication and the amount of environmental variation, noise, within the experimental system. A major source of noise in field studies comes from the natural heterogeneity of soil properties which create microtreatments throughout the field. In addition, the variation within different soil properties is often nonrandomly distributed across a field. We explore this challenge through a sorghum field trial dataset with accompanying plant, microbiome, and soil property data. Diverse sorghum genotypes and two watering regimes were applied in a split-plot design. We describe a process of identifying, estimating, and controlling for the effects of spatially distributed soil properties on plant traits and microbial communities using minimal degrees of freedom. Importantly, this process provides a method with which sources of environmental variation in field data can be identified and adjusted, improving our ability to resolve effects of interest and to quantify subtle phenotypes.

Details

Language :
English
ISSN :
2050084X
Volume :
11
Database :
Directory of Open Access Journals
Journal :
eLife
Publication Type :
Academic Journal
Accession number :
edsdoj.94caaf32400148299b662b392dcd3dc8
Document Type :
article
Full Text :
https://doi.org/10.7554/eLife.70056