Root lodging, the agronomic term for plant mechanical failure, causes yield loss in crops, including maize. Brace roots can provide structural support and assist in preventing root lodging. While the mechanics of brace roots (e.g., stiffness and strength) can play a role in their ability to prevent root lodging, there has been limited characterization of individual brace root mechanical properties. Methods to quantify root mechanics can thus be useful for characterizing maize mechanical traits and breeding new varieties with improved root anchorage and lodging resistance. Here, we describe a protocol for evaluating mechanical properties of maize brace roots. Specifically, we outline the steps necessary to perform three-point bend mechanical testing of maize brace roots using an Instron Universal Testing Stand. We describe root preparation, instrument setup, method establishment, testing, and data analysis. While we exemplify the protocol using maize brace roots, the approach can be adapted for assessing the mechanics of other plants or root types.

The mechanical properties of individual roots and entire root systems play key roles in essential root functions such as water and nutrient acquisition, defense against soil microorganisms, and plant anchorage. However, relatively few studies have quantified the mechanics (e.g., stiffness and strength) of individual and entire root systems, or explored the link between root mechanics and root functions. This limitation is likely due to a lack of standardized methods for quantifying root mechanical properties, and has created a gap in our understanding of how root mechanical traits contribute to root functions. To date, most of our knowledge comes from studies in maize, where mechanical failure (i.e., root lodging) has detrimental impacts on crop yield. Here, we review the importance of root mechanics for maize production and discuss methods used to measure individual and entire root system mechanics.

Cotton (Gossypium spp.) is the most important fiber crop for the textile industry globally. Abiotic stresses, including drought, have become prevalent in affecting cotton production worldwide. There is a shortage of studies on the use of biochar as a soil amendment in the semi-arid and arid Southwest and West U.S. Cotton Belt to alleviate drought stress. This study was conducted to examine the effects of biochar at four application rates (0, 6.25, 12.5, and 25.0 t ha−1) on cotton yield and yield components using six tetraploid cotton genotypes, including one Pima (G. barbadense L.) and five Upland cottons (G. hirsutum L.), under well-watered (WW) and drought stress (DS) conditions in an arid region of New Mexico, USA. The six cotton genotypes consistently showed that DS at the flowering stage significantly decreased boll number (BN), boll weight (BW), and lint percentage (LP), and thereby seed cotton weight (SCW) per plant and lint weight (LW) per plant. However, Pima DP 359 RF had the lowest reduction (23–33%) in BN, SCW, and LW due to drought, while DP 2020 B3XF was the most sensitive to drought, with a 45–48% reduction in the traits. Under DS conditions, biochar at the rate of 12.5 t ha−1 had the highest SCW and LW, and the lowest reduction in BN, BW, SCW, and LW due to drought, which was significantly different from the non-biochar control, and no genotype × biochar interaction was detected. However, biochar had no positive effects on cotton productivity under non-drought conditions. This study has demonstrated the positive effects of biochar on cotton yield and yield components in alleviating drought stress, laying the foundation for more follow-up studies toward its utility in cotton production in semi-arid and arid areas.

Integrating multi-omics data, including phenomic, genomic, and environmental inputs, offers a powerful approach for enhancing maize performance and predicting grain yield. In this study, crop health was quantified using temporal NGRDI (Normalized Green Red Difference Index) trajectories collected from 16 unoccupied (unmanned) aerial vehicle or system (UAV or UAS, drones and sensors) flights (from 19 to 117 d after planting) in maize trials conducted in Texas. Crop health indices (CHIs) were calculated through area under the curve (CHIAUC) and functional principal component analysis (CHIFPCA), capturing dynamic plant health responses throughout the growing season. Heritability estimates of NGRDI fluctuated between 0.3 and 0.7, averaging 0.51 ± 0.02, reflecting consistent genetic contributions to growth dynamics. CHIs derived from a favorable (irrigated) trial in Texas effectively separated high- and low-yielding hybrids across 41 environment-tester combinations, achieving significant differentiation in 27 (CHIAUC) and 28 (CHIFPCA1) environments. In comparison, only 21 environments were differentiated when using grain yield alone. Genomic mapping of temporal NGRDI revealed key quantitative trait loci (QTLs) linked to maize growth, containing candidate genes including br2, phyC1, wus1, mads69, cct1, rap2, miR172, and gl15, associated with canopy development, flowering regulation, and drought adaptation. Integrating multi-omics data into phenomic- and environment-informed genomic prediction models improved yield prediction accuracy by approximately 18.5%, particularly for untested genotypes in both tested and untested environments. These findings demonstrate that multi-omics integration provides a scalable framework for enhancing maize performance and advancing grain yield prediction across diverse agricultural systems.

Root system stiffness is a measurement associated with root lodging resistance in maize. This measurement combines contributions of root architecture, individual root-level mechanics, and root-soil interactions. In this study, we deconvolve the contribution of each of these factors to root system stiffness. Collectively, larger above- and below-ground root systems and stiffer individual brace roots contribute to a higher root system stiffness. When considering all traits in predictive models, the below-ground root architecture drives the prediction of root system stiffness categories. These below-ground traits describe the size and distribution of the root system. Analysis of a roothairless3 mutant revealed a reduction in root system stiffness primarily driven by a reduction in root size, with limited evidence for a contribution from root hairs. Together these results link root system stiffness to the size and distribution of the below-ground root system and highlight the importance of this measurement for both root lodging resistance and root phenotyping. ### Competing Interest Statement Erin E Sparks and Jonathan W Reneau are co-founders of Izbe Innovations, LLC, which may benefit from the commercialization of the SMURF device described in this manuscript. U.S. National Science Foundation, https://ror.org/021nxhr62, 2040346 United States Department of Agriculture, 2022-67012-36840

OBJECTIVES: The genomes to fields (G2F) 2024 Maize Genotype by Environment (GxE) Prediction Competition challenged participants to develop and submit their best performing models to predict grain yield for the 2024 maize GxE project field trials, using G2F data collected from 2014 to 2023 and other publicly available data. DATA DESCRIPTION: The G2F Maize GxE Project is a collaborative effort, with all generated data made publicly available. The resource presented here includes the training and test datasets used for the G2F 2024 Maize GxE Prediction Competition. Specifically, data collected from 2014 to 2023 served as the training set to predict grain yield in the 2024 test set. The dataset comprises phenotypic, genotypic, soil, weather, and environmental covariate data, along with metadata describing environments (year-location combinations). It has been curated and lightly filtered for quality control and to ensure consistent naming across years. Competitors also had access to readme files that describe the structure and content of the datasets.

Abstract Nitrogen is an essential nutrient for the growth and development of plants, aiding many physiological and biological functions. Due to the high demand for the nutrient, it is common for agricultural production systems to fertilize crop fields with large quantities of nitrogen. However, excessive fertilization can be harmful economically and environmentally. Understanding the mechanism by which plants take up nitrogen from their environment is critical to optimize plant growth and agricultural productions. Over the past several decades, researchers have used a variety of methods to quantify nitrogen uptake, including using nitrogen isotopes, measuring uptake through depletion of a solution over time, using compartmented chambers or agarose blocks to target specific root regions, and more recent small‐scale approaches such as nanoscale secondary ion mass spectrometry (nanoSIMS), microdialysis, and biomarkers. Several of these studies have been conducted in maize due to its high nitrogen demand and significance in global food and feed production; however, these techniques can be applied to any plant system. This review will examine the application of these methods, highlighting their advantages and limitations. By exploring existing methods, we aim to provide insights into advancing nitrogen uptake studies, ultimately supporting sustainable nitrogen management and improving crop production efficiency.

Future agricultural systems must become more resilient as the impacts of climate change increase. One expected outcome of climate change is an increase in severe thunderstorms with high velocity straight line winds, with deleterious impacts on crops. We collected in-season standability data from short-stature maize (Zea mays L.) hybrids derived from both conventional breeding and biotechnology approaches and tall comparators from 444 site-years on standability between 2019 and 2021. This large dataset provides us with an overview of the frequency of crop damage from storms, as well as a comparison of short-stature and tall hybrid performance when exposed to damaging winds. Looking at data across locations and germplasm, 10.6% of tall hybrid plots sustained some level of wind damage, while 3.8% of short-stature hybrid plots sustained damage, a 64% reduction. Root lodging observations comprise the largest standability dataset, with 39 site-years. Stalk lodging and greensnap were less common, with 9 and 8 site-years, respectively. Yield data from 41 locations with plant damage show a range of yield loss from 28 to 75 kg ha-1 per unit of plant damage, depending on the type of damage, with an average loss of 34 kg ha-1 per unit of total plant damage. Reduced root lodging in short-stature hybrids can be partially explained by a reduction in height combined with a reduction in the stiffness of the root system. The reduction of plant damage for short-stature maize hybrids will provide risk mitigation for growers under more variable climate conditions in the future.

Plants grown in spaceflight exhibit differences in physiology and morphology compared to those grown on Earth. While changes in gravity are a major environmental change, other space-related stressors make it difficult to identify the microgravity-specific responses. These knowledge gaps can be filled by ground-based microgravity simulators that randomize the perceived gravity vector, but these approaches have primarily been limited to smaller plants and seedlings. This study reports a set of meter-scale 2D clinostats that support the growth of plants beyond the seedling stage. Tomato plants were grown in five sequential trials under upright rotating control and clinorotated “simulated microgravity” conditions. We found that simulated microgravity impacted plant growth in each trial, but the response varied by trial. Analysis of environmental co-variates across trials revealed that temperature significantly contributed to variation in plant growth. Further, our results show that moderate heat stress can promote plant growth under simulated microgravity. Thus, this work demonstrates the potential of meter-scale clinostats to uncover interactions between the environmental and simulated microgravity, which alter plant growth.

Understanding genotype-by-environment (G × E) interactions that underlie phenotypic variation, when observed for complex traits in multi-environment trials, is important for biological discovery and for crop improvement. The regression-on-the-mean model is an approach to observe G × E trends for complex traits across a gradient of environmental inputs. Biologically relevant environmental index values can be utilized to quantify phenotypic plasticity of individuals by correlating environmental means and environmental parameters within specific time windows. By accounting for trait stability, improvements can be made in genome-wide association studies and genomic prediction models involving data with high volumes of environments, genotypes, and their interaction effects. Here, field data collected through the national hybrid maize (Zea mays L.) Genomes-to-Fields project was analyzed. Reaction norm parameters were obtained from photothermal ratio (PTR) indices for hybrid grain yield (GY) using three separate tester populations across 29 diverse environments. The PTR time windows most correlated with the average GY were discovered to differ by tester but were confounded by region. Using 100,000 single-nucleotide polymorphisms (SNPs), we discovered 96 quantitative trait loci (QTLs) significantly associated with GY and six QTLs significantly associated with GY stability. The modified, regression-on-the-mean genomic prediction model using PTR-estimated reaction norm parameters of each hybrid worked nearly as well as a traditional, additive genomic prediction model using the G × E interaction terms but took 192× less time. The PTR genomic prediction model predicted untested environment performance (0.57-0.71) better than untested hybrid performance (0.26-0.37). This study suggests improved potential for multi-environment genomic predictions by incorporating environmental measures to dissect the complexities of differential performance of genotypes across environments.

Plant mechanical failure, known as lodging, has detrimental impacts on the quality and quantity of maize yields. Failure can occur at stalks (stalk lodging) or at roots (root lodging). While previous research has focused on proxy measures for stalk stiffness, stalk strength, and root strength, there is a need to quantify the root system stiffness, which quantifies the force-displacement relationship. Here, we report a tool to quantify the root system stiffness of maize hybrids grown in different conditions. The results show that maize hybrids with a higher root system stiffness have a greater susceptibility to root lodging. This result is consistent with expected mechanical behavior, since higher root system stiffness values mean that the plant reaches the failure strength at lower displacements compared with a plant with lower root system stiffness. Collectively, this study describes the first tool to measure root system stiffness and enables a comprehensive understanding of the integrated plant mechanics and lodging.

Being the first plant to have its genome sequenced, Arabidopsis thaliana (Arabidopsis) is a well-established genetic model plant system. Studies on Arabidopsis have provided major insights into the physiological and biochemical nature of plants. Methods that allow us to study organisms' metabolism computationally include using genome-scale metabolic models (GEMs). Despite its popularity, no GEM currently maps the metabolic activity in the roots of Arabidopsis, which is the organ that faces and responds to stress conditions in the soil. We have developed a comprehensive metabolic model of the Arabidopsis root system - AraRoot. The final model includes 2,682 reactions, 2,748 metabolites, and 1,310 genes. Analyzing the metabolic pathways in this model identified 158 possible bottleneck genes that impact biomass production, most of which were found to be related to phosphorous-containing- and energy-related pathways. Further insights into tissue-specific metabolic reprogramming conclude that the cortex layer in the roots is likely responsible for root growth under prolonged exposure to high salt conditions. At the same time, the endodermis and epidermis are responsible for producing metabolites responsible for increased cell wall biosynthesis. The epidermis was found to have a very poor ability to regulate its metabolism during exposure to high salt concentrations. Overall, AraRoot is the first metabolic model that comprehensively captures the biomass formation and stress responses of the tissues in the Arabidopsis root system.

Gravity is a pervasive cue that directs the growth and development of living systems on Earth and in space environments. However, little is understood about how gravity shapes living systems. This study reports a set of large-scale 2D clinostats that support the growth of plants beyond the seedling stage. Using these clinostats, five replicate experiments containing two tomato cultivars were grown under upright control and simulated microgravity conditions. We showed a variable response to simulated microgravity that was impacted by replicate experiment, but not cultivar. This variable response showed an increase in shoot and root traits under simulated microgravity in some replicate experiments and a reduction in shoot and root traits under simulated microgravity in other replicate experiments. We additionally report a cultivar-specific change in stem vascular anatomy in response to simulated microgravity, which was not impacted by replicate experiment. This work demonstrates the potential to promote plant growth under simulated microgravity and reports a novel modulation of vascular anatomy in response to simulated microgravity. ### Competing Interest Statement The authors have declared no competing interest. * ANOVA : analysis of variance dap : days after planting FOL : Fusarium oxysporum f. sp. Lycopersici H7996 : Hawaii7996 ISS : International Space Station MM : MoneyMaker PCA : Principal Component Analysis PC : Principal Component PDB : potato dextrose broth RPM : revolutions per minute TBA : tert-butyl alcohol National Aeronautics and Space Administration, 19099981

Stalk mechanical properties impact plant stability and interactions with pathogenic microorganisms. The evaluation of stalk mechanics has focused primarily on the end-of-season outcomes and defined differences among inbred and hybrid maize genotypes. However, there is a gap in understanding how these different end-of-season outcomes are achieved. This study measured stalk flexural stiffness in maize inbred genotypes across multiple environments and in maize commercial hybrid genotypes under different disease states. Under all conditions, stalk flexural stiffness followed a biphasic trajectory, characterized by a linear increase phase and a sustained phase. Within a genotype, the environment or disease state altered the rate of increase in the linear phase but did not impact the timing of transition to the sustained phase. Whereas between genotypes, the timing of transition between phases varied. Destructive 3-point bend tests of inbred stalks showed that the trajectory of stalk mechanics is defined by the bending modulus, not the geometry. Together, these results define a biphasic trajectory of maize stalk mechanics that can be modulated by internal and external factors. This work provides a foundation for breeding programs to make informed decisions when selecting for optimized stalk mechanical trajectories, which are necessary for enhancing resilience to environmental stresses.

Toxic metal contamination in the environment is pervasive and of significant concern due to its high abundance in agricultural lands across the globe. Future engineering of plants tolerant to toxic metals requires a detailed understanding of plant responses to these toxins, which are currently poorly understood. We discovered that, among four toxic metals, lead (Pb) targets conserved cellular and developmental processes in evolutionary diverse plant systems - the model plant Arabidopsis thaliana and crop plant Zea mays . This study shows that Pb increases the phytohormone auxin, which in turn inhibits cell cycle progression to inhibit root growth and alters root gravitropic responses. Both root growth and gravitropic responses are critical for soil exploration, which is required for plants to live and thrive in harsh environments. ### Competing Interest Statement The authors have declared no competing interest. Natural Sciences and Engineering Research Council of Canada, RGPIN-2025-04277

Maize root lodging causes yield and grain quality reduction. We hypothesized that conservation tillage (CST) could increase root lodging resistance compared to conventional tillage (CVT) by facilitating root development. In this study, we compared maize root pushing resistance (RPR), a proxy for root lodging, in paired CST and CVT fields at 14 field sites and evaluated the relationship between RPR, soil physical properties and the maize plant traits. We found CST significantly increase maize RPR by 33.0 % in CVT system. Soil bulk density (BD), penetration resistance (PR) and shear strength (SS) of the topsoil (0-20 cm) was also significantly higher in CST. Brace root traits, including diameter (BRD), whorl number (BRWN) and angle (BRA), and stalk width were significantly increased following CST relative to CVT. Correlation analysis showed the variation in RPR can be attributed to maize stalk width and brace root phenotypes. A positive correlation was also found between soil strength and brace root traits. These findings indicate that improved soil properties are key factors for stimulating maize brace root development, and increasing maize root lodging resistance in CST fields. These results shed new light on the optimizing tillage practice to minimize maize root lodging.

Plants have a remarkable ability to generate organs with a different identity to the parent organ, called ‘trans-organogenesis’. An example of trans-organogenesis is the formation of roots from stems (a type of adventitious root), which is the first type of root that arose during plant evolution. Despite being ancestral, stem-borne roots are often contextualised through lateral root research, implying that lateral roots precede adventitious roots. In this review we challenge that idea, highlight what is known about stem-borne root development across the plant kingdom, the remarkable diversity in form and function, and the many remaining evolutionary questions. Exploring stem-borne root evolutionary development can enhance our understanding of developmental decision making and the processes by which cells acquire their fates.

Under all environments, roots are important for plant anchorage and acquiring water and nutrients. However, there is a knowledge gap regarding how root architecture contributes to stress tolerance in a changing climate. Two closely related plant species, maize and sorghum, have distinct root system architectures and different levels of stress tolerance, making comparative analysis between these two species an ideal approach to resolve this knowledge gap. However, current research has focused on shared aspects of the root system that are advantageous under abiotic stress conditions rather than on differences. Here we summarize the current state of knowledge comparing the root system architecture relative to plant performance under water deficit, salt stress, and low phosphorus in maize and sorghum. Under water deficit, steeper root angles and deeper root systems are proposed to be advantageous for both species. In saline soils, a reduction in root length and root number has been described as advantageous, but this work is limited. Under low phosphorus, root systems that are shallow and wider are beneficial for topsoil foraging. Future work investigating the differences between these species will be critical for understanding the role of root system architecture in optimizing plant production for a changing global climate.

Graft compatibility is the capacity of two plants to form cohesive vascular connections. Tomato and pepper are incompatible graft partners; however, the underlying cause of graft rejection between these two species remains unknown. We diagnosed graft incompatibility between tomato and diverse pepper varieties based on weakened biophysical stability, decreased growth, and persistent cell death using viability stains. Transcriptomic analysis of the junction was performed using RNA-sequencing, and molecular signatures for incompatible graft response were characterized based on meta-transcriptomic comparisons with other biotic processes. We show that tomato is broadly incompatible with diverse pepper cultivars. These incompatible graft partners activate prolonged transcriptional changes that are highly enriched for defense processes. Amongst these processes was broad nucleotide-binding and leucine-rich repeat receptors (NLR) upregulation and genetic signatures indicative of an immune response. Using transcriptomic datasets for a variety of biotic stress treatments, we identified a significant overlap in the genetic profile of incompatible grafting and plant parasitism. In addition, we found over 1000 genes that are uniquely upregulated in incompatible grafts. Based on NLR overactivity, DNA damage, and prolonged cell death we hypothesize that tomato and pepper graft incompatibility is characterized by an immune response that triggers cell death which interferes with junction formation.

Maize brace roots develop from aboveground stem nodes in both upright and vertically displaced stalks. The cues that trigger brace root development after displacement are unknown. Possibilities include disturbance of the belowground roots, gravity, moisture, physical interaction, or node anatomical changes. We show that brace root formation occurs at all growth stages, with more nodes producing brace roots when plants are displaced at later growth stages. This occurs with the underground roots intact, without moisture accumulation and without physical interaction. We propose that the formation of brace roots after vertical stalk displacement is most likely due to gravity or anatomical changes at the node.