Nitrous oxide (N20) is a greenhouse gas that is three hundred times more potent than carbon dioxide.The majority of N20 emissions worldwide are the result of excess soil nitrogen being metabolized by microbes.It has been hypothesized that crops with better nitrogen uptake efficiency and more roots will reduce excess soil nitrogen therefore reducing N20 emissions.To test this hypothesis, a pilot study was performed in 2021 in collaboration with Iowa State University in which root growth dynamics were captured using RootTracker technology in four commercial maize hybrids.This preliminary study showed a correlation between increased root growth and reduced N20 emissions.Further, we find genetic differences in root growth that is consistent across reps, suggesting that i) cultivar choice impacts N2O emissions and ii) that it is possible to breed for root system architecture to limit N2O emissions.It was also observed that the hybrid with the fastest rate of root growth (lowest N20 emissions) did not reach the greatest soil depth, suggesting early root establishment could be pivotal to more efficient nitrogen uptake.These preliminary results suggest there are differences in root growth by variety that could be exploited to reduce agricultural N20 emissions at scale.

Optimizing root system architecture offers a promising approach to developing stress tolerant cultivars in the face of climate change, as root systems are critical for water and nutrient uptake as well as mechanical stability. However, breeding for optimal root system architecture has been hindered by the difficulty in measuring root growth in the field. Here, we describe a technology, the RootTracker (RT), which employs capacitance touch sensors to monitor in-field root growth over time. Configured in a cylindrical shutter-like fashion around a planted seed, 264 electrodes are individually charged multiple times over the course of an experiment. Signature changes in the measured capacitance and resistance readings indicate when a root has touched or grown close to an electrode. Using the RootTracker, we have measured root system dynamics of commercial maize hybrids growing in both typical Midwest field conditions and under different irrigation regimes. We observed rapid responses of root growth to water deficits and found evidence for a “priming response” in which an early water deficit causes more and deeper roots to grow at later time periods. There was genotypic variation among hybrid maize lines in their root growth in response to drought, indicating a potential to breed for root systems adapted for different environments.

Background: Traditional rice (Oryza sativa) varieties are valuable resources for the improvement of drought resistance. qDTY(3.2) is a drought-yield quantitative trait locus that was identified in a population derived from the traditional variety Moroberekan and the drought-susceptible variety Swarna. In this study, our aim was to characterize the physiological mechanisms associated with qDTY(3.2). Our approach was to phenotype fifteen BC2F3:4 lines for shoot and root drought resistance-related traits as compared to Swarna in the field under well-watered and drought stress conditions. Four BC2F3:4 lines contrasting for yield under drought were selected for detailed characterization of shoot morphology, water use related traits, flowering time and root system architecture in the field as well as in controlled environments (lysimeters in a greenhouse, and gel imaging platform in a growth chamber). Results: Across five field experiments, grain yield correlated significantly with root growth along the soil profile, flowering time, and canopy temperature under drought conditions. The four selected BC2F3:4 lines showed earlier flowering time, reduced distribution of root growth to shallow soil layers which resulted in lower water uptake (between 0 and 30 cm) and drought-induced increased distribution of root growth to deep soil layers (between 30 and 60 cm) as compared to Swarna in the field. Root system architecture phenotypes were confirmed in whole root systems in lysimeters, and corresponded to higher numbers of root tips in a gel imaging platform, highlighting the potential stability of some root traits across different growth stages and systems. Conclusions: We conclude that earlier flowering time, reduced shallow root growth, and drought-induced increased deep root growth are associated with the presence of qDTY(3.2) since these phenotypes were consistently observed in the selected QTL lines with full introgression of qDTY(3.2). We hypothesize that the qDTY(3.2) associated RSA phenotypes led to better use of water and metabolic resources which, combined with earlier flowering time, improved yield under drought.

Root system architecture (RSA) impacts plant fitness and crop yield by facilitating efficient nutrient and water uptake from the soil. A better understanding of the effects of soil on RSA could improve crop productivity by matching roots to their soil environment. We used x-ray computed tomography to perform a detailed three-dimensional quantification of changes in rice (Oryza sativa) RSA in response to the physical properties of a granular substrate. We characterized the RSA of eight rice cultivars in five different growth substrates and determined that RSA is the result of interactions between genotype and growth environment. We identified cultivar-specific changes in RSA in response to changing growth substrate texture. The cultivar Azucena exhibited low RSA plasticity in all growth substrates, whereas cultivar Bala root depth was a function of soil hardness. Our imaging techniques provide a framework to study RSA in different growth environments, the results of which can be used to improve root traits with agronomic potential.

Root system architecture (RSA) plays a major role in plant fitness, crop performance, and grain yield yet only recently has this role been appreciated. RSA describes the spatial arrangement of root tissue within the soil and is therefore crucial to nutrient and water uptake. Recent studies have identified many of the genetic and environmental factors influencing root growth that contribute to RSA. Some of the identified genes have the potential to limit crop loss caused by environmental extremes and are currently being used to confer drought tolerance. It is hypothesized that manipulating these and other genes that influence RSA will be pivotal for future crop advancements worldwide.

Plant development and survival is centered on complex regulatory networks composed of genes, proteins, hormone pathways, metabolites and signaling pathways. The recent advancements in whole genome biology have furthered our understanding of the interactions between these networks. As a result, numerous cell type-specific transcriptome profiles have been generated that have elucidated complex gene regulatory networks occurring at the cellular level, many of which were masked during whole-organ analysis. Modern technologies have also allowed researchers to generate multiple whole-organ metabolite profiles; however, only a limited number have been generated at the level of individual cells. Recent advancements in the isolation of individual cell populations have made cell type-specific metabolite profiles possible, enabling the enhanced detection and quantification of metabolites that were formerly unavailable when considering the whole organ. The comparison of metabolite and transcriptome profiles from the same cells has been a valuable resource to generate predictions regarding specific metabolite activity and function. In this review, we focus on recent studies that demonstrate the value of cell type-specific transcriptional profiles and their comparison with profiles generated from whole organs. Advancements in the isolation of single-cell populations will be highlighted, and the potential application towards generating detailed metabolic profiles will be discussed.