|MELANDRI, GIOVANNI - University Of Arizona|
|BROECKLING, COREY - Colorado State University|
|PAULI, DUKE - University Of Arizona|
Submitted to: Frontiers in Plant Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/30/2021
Publication Date: 10/22/2021
Citation: Melandri, G., Thorp, K.R., Broeckling, C., Thompson, A.L., Hinze, L.L., Pauli, D. 2021. Assessing drought and heat stress-induced changes in the cotton leaf metabolome and their relationship with hyperspectral reflectance. Frontiers in Plant Science. 12. Article 751868. https://doi.org/10.3389/fpls.2021.751868.
Interpretive Summary: The biochemical status of plant leaves can reveal their tolerance to heat and drought stresses, which can facilitate crop improvement for adaptation to climate change. Leaf reflectance sensing promises to rapidly estimate biochemical status in plant leaves; however, further research is necessary to develop methods for using sensing technology in plant breeding and crop improvement. In this study, hyperspectral sensing was uses to estimate hundreds of leaf metabolic states among 22 cotton varieties under drought stress in Arizona. Results indicated that the hyperspectral sensing methods were successful for estimating 34% of the evaluated biochemical states. The study will benefit scientists and researchers working in the area of high-throughput plant phenotyping, and improved crop cultivars from this effort will benefit society by developing productive crop cultivars that are resilient to anticipated climate changes.
Technical Abstract: The study of phenotypes that reveal mechanisms of adaptation to drought and heat stress is crucial for the development of climate resilient crops in the face of climate uncertainty. The leaf metabolome effectively summarizes stress-driven perturbations of the plant physiological status and represents an intermediate phenotype that bridges the plant genome and phenome. The objective of this study was to analyze the effect of water deficit and heat stress on the leaf metabolome of 22 genetically diverse accessions of upland cotton grown in the Arizona low desert over two consecutive years. Results revealed that membrane lipid remodeling was the main leaf mechanism of adaptation to drought. The magnitude of metabolic adaptations to drought, which had an impact on fiber traits, was found to be quantitatively and qualitatively associated with different stress severity levels during the two years of the field trial. Leaf-level hyperspectral reflectance data were also used to predict the leaf metabolite profiles of the cotton accessions. Multivariate statistical models using hyperspectral data accurately estimated (R2 > 0.7 in 34% of the metabolites) and predicted (Q2 > 0.5 in 15–25% of the metabolites) many leaf metabolites. Predicted values of metabolites could efficiently discriminate stressed and non-stressed samples and reveal which regions of the reflectance spectrum were the most informative for predictions. Combined together, these findings suggest that hyperspectral sensors can be used for the rapid, non-destructive estimation of leaf metabolites, which can summarize the plant physiological status.