Dynamics of Maize Vegetative Growth and Drought Adaptability Using Image-Based Phenotyping Under Controlled Conditions.

Miroslav Zorić,Ana Nikolić,Dragana Ignjatović-Micić,Dejan Dodig,Jelena Vančetović,Astrid Junker,Thomas Altmann,Sofija Božinović,Nenad Delić,Kathleen Weigelt-Fischer

doi:10.3389/fpls.2021.652116

Abstract

Changes in climate are likely to have a negative impact on water availability and soil fertility in many maize-growing agricultural areas. The development of high-throughput phenotyping platforms provides a new prospect for dissecting the dynamic complex plant traits such as abiotic stress tolerance into simple components. The growth phenotypes of 20 maize (Zea mays L.) inbred lines were monitored in a non-invasive way under control, nitrogen, and water limitation as well as under combined nitrogen and water stress using an automated phenotyping system in greenhouse conditions. Thirteen biomass-related and morphophysiological traits were extracted from RGB images acquired at 33 time points covering developmental stages from leaf count 5 at the first imaging date to leaf count 10–13 at the final harvest. For these traits, genetic differences were identified and dynamic developmental trends during different maize growth stages were analyzed. The difference between control and water stress was detectable 3–10 days after the beginning of stress depending on the genotype, while the effect of limited nitrogen supply only induced subtle phenotypic effects. Phenotypic traits showed different response dynamics as well as multiple and changing interaction patterns with stress progression. The estimated biovolume, leaf area index, and color ratios were found to be stress-responsive at different stages of drought stress progression and thereby represent valuable reference indicators in the selection of drought-adaptive genotypes. Furthermore, genotypes could be grouped according to two typical growth dynamic patterns in water stress treatments by c-means clustering analysis. Inbred lines with high drought adaptability across time and development were identified and could serve as a basis for designing novel genotypes with desired, stage-specific growth phenotypes under water stress through pyramiding. Drought recovery potential may play an equal role as drought tolerance in plant drought adaptation.

Highlights

Crop research today is more important than ever as scientists confront global threats from climate changes and diseases which may affect food security and livelihoods of smallholder farmers around the world
To analyze the degree of variation during the different time points, estimated biovolume (EBv) from data collected on 20 inbred lines (ILs) was plotted against the coefficient of variation (CV, %)
The Bayesian information criterion (BIC) value was used to find the best matrix among each model considered, so that the lower its value, the better the adjustment of the model in question

Summary

Introduction

Crop research today is more important than ever as scientists confront global threats from climate changes and diseases which may affect food security and livelihoods of smallholder farmers around the world. Maize is one of the most important crops globally, and more than half of the increased food demand for cereal plants will come from maize (Yan et al, 2011). Average temperatures and water availability are predicted to become an increasing problem under future climate conditions (IPCC, 2014), which will influence soil organic matter (Brevik, 2013). Automated plant phenotyping contributes to the identification of a genetic variation to increase genetic gain within a breeding program (Araus et al, 2018). It is shown that a considerably high percentage of the total variation in grain yield under drought conditions could be predicted by vegetative phenotypic data generated in water-limited controlled environments (Chapuis et al, 2012; Zhang et al, 2017)

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