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All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Automated ISS Flight Utilities

During my internship at NASA Johnson Space Center, I worked in the Space Radiation Analysis Group (SRAG), where I was tasked with a number of projects focused on the automation of tasks and activities related to the operation of the International Space Station (ISS). As I worked on a number of projects, I have written short sections below to give a description for each, followed by more general remarks on the internship experience. My first project is titled "General Exposure Representation EVADOSE", also known as "GEnEVADOSE". This project involved the design and development of a C++/ ROOT framework focused on radiation exposure for extravehicular activity (EVA) planning for the ISS. The utility helps mission managers plan EVAs by displaying information on the cumulative radiation doses that crew will receive during an EVA as a function of the egress time and duration of the activity. SRAG uses a utility called EVADOSE, employing a model of the space radiation environment in low Earth orbit to predict these doses, as while outside the ISS the astronauts will have less shielding from charged particles such as electrons and protons. However, EVADOSE output is cumbersome to work with, and prior to GEnEVADOSE, querying data and producing graphs of ISS trajectories and cumulative doses versus egress time required manual work in Microsoft Excel. GEnEVADOSE automates all this work, reading in EVADOSE output file(s) along with a plaintext file input by the user providing input parameters. GEnEVADOSE will output a text file containing all the necessary dosimetry for each proposed EVA egress time, for each specified EVADOSE file. It also plots cumulative dose versus egress time and the ISS trajectory, and displays all of this information in an auto-generated presentation made in LaTeX. New features have also been added, such as best-case scenarios (egress times corresponding to the least dose), interpolated curves for trajectories, and the ability to query any time in the EVADES output. As mentioned above, GEnEVADOSE makes extensive use of ROOT version 6, the data analysis framework developed at the European Organization for Nuclear Research (CERN), and the code is written to the C++11 standard (as are the other projects). My second project is the Automated Mission Reference Exposure Utility (AMREU).Unlike GEnEVADOSE, AMREU is a combination of three frameworks written in both Python and C++, also making use of ROOT (and PyROOT). Run as a combination of daily and weekly cron jobs, these macros query the SRAG database system to determine the active ISS missions, and query minute-by-minute radiation dose information from ISS-TEPC (Tissue Equivalent Proportional Counter), one of the radiation detectors onboard the ISS. Using this information, AMREU creates a corrected data set of daily radiation doses, addressing situations where TEPC may be offline or locked up by correcting doses for days with less than 95% live time (the total amount time the instrument acquires data) by averaging the past 7 days. As not all errors may be automatically detectable, AMREU also allows for manual corrections, checking an updated plaintext file each time it runs. With the corrected data, AMREU generates cumulative dose plots for each mission, and uses a Python script to generate a flight note file (.docx format) containing these plots, as well as information sections to be filled in and modified by the space weather environment officers with information specific to the week. AMREU is set up to run without requiring any user input, and it automatically archives old flight notes and information files for missions that are no longer active. My other projects involve cleaning up a large data set from the Charged Particle Directional Spectrometer (CPDS), joining together many different data sets in order to clean up information in SRAG SQL databases, and developing other automated utilities for displaying information on active solar regions, that may be used by the space weather environment officers to monitor solar activity. I consulted my mentor Dr. Ryan Rios and Dr. Kerry Lee for project requirements and added features, and ROOT developer Edmond Offermann for advice on using the ROOT library. I also received advice and feedback from Dr. Janet Barzilla of SRAG, who tested my code. Besides these inputs, I worked independently, writing all of the code by myself. The code for all these projects is documented throughout, and I have attempted to write it in a modular format. Assuming that ROOT is updated accordingly, these codes are also Y2038-compliant (and Y10K-compliant). This allows the code to be easily referenced, modified and possibly repurposed for non-ISS missions in the future, should the necessary inputs exist. These projects have taught me a lot about coding and software design - I have become a much more skilled C++ programmer and ROOT user, and I also learned to code in Python and PyROOT (and its advantages and disadvantages compared to C++/ ROOT). Furthermore, I have learned about space radiation and radiation modeling, topics that greatly interest me as I pursue a degree in physics. Working alongside experimental physicists like Dr. Rios, I have developed a greater understanding and appreciation for experimental science, something I have always leaned towards but to which I lacked significant exposure. My work in SRAG has also given me the invaluable opportunity to witness the work environment for physicists at NASA, and what a career in academia may look like at a government laboratory such as NASA Johnson Space Center. As I continue my studies and look forward to graduate school and a future career, this experience at NASA has given me a meaningful and enjoyable opportunity to put my skills to use and see what my future career path might hold.

Offermann, Jan Tuzlic↗
DOE OSTI2026

L'Arlesienne de ROOT

Over many years, ROOT users have repeatedly stumbled over—and loudly rediscovered—the infamous 1 GB limit on individual I/O operations, a constraint that somehow survived long past the era when anyone thought a gigabyte was “a lot.” As experiments embraced ever-larger objects and collections, this limit became an increasingly unavoidable rite of passage. This contribution recounts the sustained, multi-year quest by ROOT I/O developers to finally retire this relic, navigating a maze of legacy APIs, memory-management assumptions, and integer boundaries that seemed determined to preserve the status quo. We describe how internal interfaces were carefully modernized to introduce fully 64-bit–capable code paths without breaking the mountains of existing user code that would definitely have noticed. With the limit now lifted, ROOT can finally handle multi-gigabyte objects in a single read or write operation, even when splitting them into an RNTuple is not an option (we’re looking at you, large RooWorkspaces and giant histograms), liberating users from yet another “fun” debugging adventure and clearing the way for the massive analyses of the HL-LHC and beyond.

Canal, Philippe G. [Fermilab] (ORCID:0000000277487↗
DOE OSTI2026

L'Arlesienne de ROOT

Over many years, ROOT users have repeatedly stumbled over—and loudly rediscovered—the infamous 1 GB limit on individual I/O operations, a constraint that somehow survived long past the era when anyone thought a gigabyte was “a lot.” As experiments embraced ever-larger objects and collections, this limit became an increasingly unavoidable rite of passage. This contribution recounts the sustained, multi-year quest by ROOT I/O developers to finally retire this relic, navigating a maze of legacy APIs, memory-management assumptions, and integer boundaries that seemed determined to preserve the status quo. We describe how internal interfaces were carefully modernized to introduce fully 64-bit–capable code paths without breaking the mountains of existing user code that would definitely have noticed. With the limit now lifted, ROOT can finally handle multi-gigabyte objects in a single read or write operation, even when splitting them into an RNTuple is not an option (we’re looking at you, large RooWorkspaces and giant histograms), liberating users from yet another “fun” debugging adventure and clearing the way for the massive analyses of the HL-LHC and beyond.

Canal, Philippe G. [Fermilab] (ORCID:0000000277487↗
DOE OSTI2020

Non-destructive spatial analysis of phosphatase activity and total protein distribution in the rhizosphere using a root blotting method

Phosphorus (P) is an essential macronutrient for plant growth, but bioavailable P in soils is often limited due to immobilization resulting from pH and geochemical interactions. Understanding the dynamics of P in soils and elucidating the mechanisms by which plants access P from their environment are critical to evaluating productivity, particularly in nutrient poor environments. Phosphorus from organic matter can act as a major source of P for organisms in soil systems. Phosphatases, enzymes that liberate inorganic P from organic sources, are produced by both plants and microbes and are considered one of the most active classes of enzymes in soil. In this work we developed a root blotting method to spatially image phosphatase activity in the rhizosphere. Proteins from the rhizosphere are transferred to a nitrocellulose membrane while retaining their enzymatic activity and two-dimensional spatial distribution. Subsequent application of a fluorogenic phosphatase indicator, DDAO phosphate, enables visualization of the distribution of phosphatase activity in the sample. The proteins can then be fixed to the membrane and treated with a SYPRO® Ruby gel stain, a fluorescent total protein stain, allowing for visualization of total protein distribution. Taken together, the images of phosphatase activity and total protein localization can be mapped back to the root architecture and provide insight into factors affecting the spatial distribution of enzymatic activity and protein accumulation in the rhizosphere. Notably, this method can be applied to plants growing in rhizoboxes containing soil or soilless growth mixtures (e.g., sand or various potting mixes) and, because of the non-destructive nature of this approach, be performed over time to track changes. We anticipate that this fluorescent indicator imaging technique on root blots can be used in diverse plant-microbe-soil systems to better understand the role of phosphatases in P acquisition and soil P cycling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Overcoming small minirhizotron datasets using transfer learning

Minirhizotron technology is widely used to study root growth and development. Yet, standard approaches for tracing roots in minirhiztron imagery is extremely tedious and time consuming. Machine learning approaches can help to automate this task. However, lack of enough annotated training data is a major limitation for the application of machine learning methods. Transfer learning is a useful technique to help with training when available datasets are limited. In this paper, we investigated the effect of pre-trained features from the massives-cale, irrelevant ImageNet dataset and a relatively moderate-scale, but relevant peanut root dataset on switchgrass root imagery segmentation applications. We compiled two minirhizotron image datasets to accomplish this study: one with 17,550 peanut root images and another with 28 switchgrass root images. Both datasets were paired with manually labeled ground truth masks. Deep neural networks based on the U-net architecture were used with different pre-trained features as initialization for automated, precise pixel-wise root segmentation in minirhizotron imagery. We observed that features pre-trained on a closely related but relatively moderate size dataset like our peanut dataset were more effective than features pre-trained on the large but unrelated ImageNet dataset. Here, we achieved high quality segmentation on peanut root dataset with 99.04% accuracy at the pixel-level and overcame errors in human-labeled ground truth masks. By applying transfer learning technique on limited switchgrass dataset with features pre-trained on peanut dataset, we obtained 99% segmentation accuracy in switchgrass imagery using only 21 images for training (fine tuning). Furthermore, the peanut pre-trained features can help the model converge faster and have much more stable performance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Breeding of microbiomes conferring salt tolerance to plants

Microbiome breeding through host-mediated selection is a technique to artificially select for microbiomes conferring beneficial properties to plants. Using a systematic selection protocol that maximises the heritability of microbiome effects, transmission fidelity, and microbiome stability through multiple selection cycles, we previously developed root-associated microbial communities conferring sodium and aluminium tolerance to Brachypodium distachyon, a model for cereal crops. Here, we explore the physiological mechanisms underlying our selected microbiomes’ effect on plant fitness and analyse how our selection protocol shaped the composition and structure of these microbiomes. We analysed the effects of our selected microbiomes on plant fitness and tissue-nutrient concentration, then used 16S rRNA amplicon sequencing to examine microbial community composition and co-occurrence network patterns. Our sodium-selected microbiomes reduced leaf sodium concentration by ~ 50%, whereas the aluminium-selected microbiomes had no effect on leaf-tissue nutrient concentration, suggesting different mechanisms underlying the microbiome-mediated stress tolerance. By testing the selected microbiomes in a cross-fostering experiment, we show that our artificially selected microbiomes attained (a) ecological robustness contributing to transplantability (i.e. inheritance) of microbiome-encoded effects between plants; and (b) network features identifying key bacteria promoting salt-stress tolerance. Combined, these findings elucidate critical mechanisms underlying host-mediated artificial selection as a framework to breed microbiomes with targeted benefits for plants under salt stresses, with significant implications for sustainable agriculture.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1984

Research study for effects of case flexibility on bearing loads and rotor stability

Methods to evaluate the effect of casing flexibility on rotor stability and component loads were developed. Recent Rocketdyne turbomachinery was surveyed to determine typical properties and frequencies versus running speed. A small generic rotor was run with a flexible case with parametric variations in casing properties for comparison with a rotor attached to rigid supports. A program for the IBM personal computer for interactive evaluation of rotors and casings is developed. The Root locus method is extended for use in rotor dynamics for symmetrical systems by transforming all motion and coupling into a single plane and using a 90 degree criterion when plotting loci.

Fenwick, J. R.↗
NASA NTRS1994

A season of heat, water vapor, total hydrocarbon, and ozone fluxes at a subarctic fen

High-latitude environments are thought to play several critical roles in the global balance of radiatively active trace gases. Adequate documentation of the source and sink strengths for trace gases requires long time series of detailed measurements, including heat and moisture budgets. A fen near Schefferville, Quebec, was instrumented during the summer of 1990 for the measurement of the surface energy, radiation, and moisture balances as well as for eddy correlation estimates of ozone and methane flux. Despite the limited fetch at this site, analysis of the tower flux 'footprint' indicates that at least 80% of the flux observed originates from sources within the fen. Sensible heat fluxes averaged 25% of the daytime net radiation at the site, while the latent heat flux, determined from the energy balance, was 63%; the Bowen ratio varied from 0.2 to 0.8 from day to day, without a seasonal trend to the variation. The competing effects of rooted macrophyte development (with concomitant effects on roughness and transpiration) and the normal shift in synoptic pattern around day 200 to warm, dry conditions results in a lack of net seasonal effect on the energy partitioning. Over the period from days 170 to 230, the evaporation (167 mm) was double the rainfall, while the decline in water level was 107 mm, leaving a net runoff of 0.44 mm/d. The total hydrocarbon flux was 75-120 mg m(exp -2)/d, following a diurnal pattern similar to heat or moisture flux, while the daytime ozone flux was about -1.11 x 10(exp 11) molecules cm(exp -2)/s. A period near the end of the experiment, during week 30, produced the strongest total hydrocarbon flux, associated with warmer deep (1 m) soil temperatures, lower fen water levels, and the late summer shift in wind direction at that time. An early summer 'flush' of total hydrocarbon was not observed.

Moore, Kathleen E.↗
NASA NTRS2001

Using mini-rockwool blocks as growing media for limited-cluster tomato production

Rockwool is an excellent growing medium for the hydroponic production of tomato; however, the standard size rockwool blocks [4 x 4 x 2.5 inches (10 x 10 x 6.3 cm) or 3 x 3 x 2.5 inches (7.5 x 7.5 x 6.3 cm)] are expensive. The following experiments were conducted with less expensive minirock wool blocks (MRBs), on rayon polyester material (RPM) as a bench top liner, to reduce the production cost of tomatoes (Lycopersicon esculentum) grown in a limited-cluster, ebb and flood hydroponic cultivation system. Fruit yield for single-cluster plants growing in MRBs [2 x 2 x 1.6 inches (5 x 5 x 4 cm) and 1.6 x 1.6 x 1.6 inches (4 x 4 x 4 cm)] was not significantly different from plants grown in larger sized blocks (3 x 3 x 2.5 inches). When the bench top was lined with RPM, roots penetrated the RPM, and an extensive root mat developed between the RPM and the bench top. The fruit yield from plants on RPM was significantly increased compared to plants without RPM due to increases in fruit size and fruit number. RPM also significantly reduced the incidence of blossom-end rot. In a second experiment, single- and double-cluster plants were grown on RPM. Fruit yield for double-cluster plants was 40% greater than for single-cluster plants due to an increase in fruit number, although the fruit were smaller in size. As in the first experiment, fruit yield for all plants grown in MRBs was not significantly different from plants grown in the larger sized blocks. MRBs and a RPM bench liner are an effective combination in the production of limited-cluster hydroponic tomatoes.

Non-NASA Center↗
NASA NTRS2007

Systems Modeling to Implement Integrated System Health Management Capability

ISHM capability includes: detection of anomalies, diagnosis of causes of anomalies, prediction of future anomalies, and user interfaces that enable integrated awareness (past, present, and future) by users. This is achieved by focused management of data, information and knowledge (DIaK) that will likely be distributed across networks. Management of DIaK implies storage, sharing (timely availability), maintaining, evolving, and processing. Processing of DIaK encapsulates strategies, methodologies, algorithms, etc. focused on achieving high ISHM Functional Capability Level (FCL). High FCL means a high degree of success in detecting anomalies, diagnosing causes, predicting future anomalies, and enabling health integrated awareness by the user. A model that enables ISHM capability, and hence, DIaK management, is denominated the ISHM Model of the System (IMS). We describe aspects of the IMS that focus on processing of DIaK. Strategies, methodologies, and algorithms require proper context. We describe an approach to define and use contexts, implementation in an object-oriented software environment (G2), and validation using actual test data from a methane thruster test program at NASA SSC. Context is linked to existence of relationships among elements of a system. For example, the context to use a strategy to detect leak is to identify closed subsystems (e.g. bounded by closed valves and by tanks) that include pressure sensors, and check if the pressure is changing. We call these subsystems Pressurizable Subsystems. If pressure changes are detected, then all members of the closed subsystem become suspect of leakage. In this case, the context is defined by identifying a subsystem that is suitable for applying a strategy. Contexts are defined in many ways. Often, a context is defined by relationships of function (e.g. liquid flow, maintaining pressure, etc.), form (e.g. part of the same component, connected to other components, etc.), or space (e.g. physically close, touching the same common element, etc.). The context might be defined dynamically (if conditions for the context appear and disappear dynamically) or statically. Although this approach is akin to case-based reasoning, we are implementing it using a software environment that embodies tools to define and manage relationships (of any nature) among objects in a very intuitive manner. Context for higher level inferences (that use detected anomalies or events), primarily for diagnosis and prognosis, are related to causal relationships. This is useful to develop root-cause analysis trees showing an event linked to its possible causes and effects. The innovation pertaining to RCA trees encompasses use of previously defined subsystems as well as individual elements in the tree. This approach allows more powerful implementations of RCA capability in object-oriented environments. For example, if a pressurizable subsystem is leaking, its root-cause representation within an RCA tree will show that the cause is that all elements of that subsystem are suspect of leak. Such a tree would apply to all instances of leak-events detected and all elements in all pressurizable subsystems in the system. Example subsystems in our environment to build IMS include: Pressurizable Subsystem, Fluid-Fill Subsystem, Flow-Thru-Valve Subsystem, and Fluid Supply Subsystem. The software environment for IMS is designed to potentially allow definition of any relationship suitable to create a context to achieve ISHM capability.

Figueroa, Jorge F.↗
NASA NTRS2008

Experiments Advance Gardening at Home and in Space

Aeroponics, the process of growing plants suspended in air without soil or media, provides clean, efficient, and rapid food production. Crops can be planted and harvested year-round without interruption, and without contamination from soil, pesticides, and residue. Aeroponic systems also reduce water usage by 98 percent, fertilizer usage by 60 percent, and eliminate pesticide usage altogether. Plants grown in aeroponic systems have been shown to absorb more minerals and vitamins, making the plants healthier and potentially more nutritious. The suspended system also has other advantages. Since the growing environment can be kept clean and sterile, the chances of spreading plant diseases and infections commonly found in soil and other growing media are greatly reduced. Also, seedlings do not stretch or wilt while their roots are forming, and once the roots are developed, the plants can be easily moved into any type of growing media without the risk of transplant shock. Lastly, plants tend to grow faster in a regulated aeroponic environment, and the subsequent ease of transplant to a natural medium means a higher annual crop yield. For example, tomatoes are traditionally started in pots and transplanted to the ground at least 28 days later; growers using an aeroponic system can transplant them just 10 days after starting the plants in the growing chamber. This accelerated cycle produces six tomato crops per year, rather than the traditional one to two crop cycles. These benefits, along with the great reduction in weight by eliminating soil and much of the water required for plant growth, illustrate why this technique has found such enthusiastic support from NASA. Successful long-term missions into deep space will require crews to grow some of their own food during flight. Aeroponic crops are also a potential source of fresh oxygen and clean drinking water, and every ounce of food produced and water conserved aboard a spacecraft reduces payload weight, decreasing launch costs and freeing room for other cargo.

Source record↗
NASA NTRS2010

Internal Acoustics of a Pintle Valve with Supercritical Helium Flow

Large amplitude flow unsteadiness is a common phenomenon within the high flow rate ducts and valves associated with propulsion systems. Boundary layer noise, shear layers and vortex shedding are a few of the many sources of flow oscillations. The presence of lightly damped acoustic modes can organize and amplify these sources of flow perturbation, causing undesirable loading of internal parts. The present study investigates the self-induced acoustic environment within a pintle valve subject to high Reynolds Number flow of helium gas. Experiments were conducted to measure the internal pressure oscillations of the Ares I Launch Abort System (LAS) Attitude Control Motor (ACM) valve. The AGM consists of a solid propellant gas generator with eight pintle valves attached to the aft end. The pintle valve is designed to deliver variable upstream conditions to an attache( converging diverging nozzle. In order to investigate the full range of operating conditions 28 separate tests were conducted with varying pintle position and upstream pressure. Helium gas was utilized in order to closely mimic the speed of sound of the gas generator exhaust, minimizing required scaling during data analysis. The recordec pressure measurements were interrogated to multiple ends. The development of root mean square (RMS) value! versus Reynolds Number and Pintle position are important to creating bounding unsteady load curves for valve internal parts. Spectral analysis was also performed, helping to identify power spectral densities (PSD) of acoustic natural frequencies and boundary layer noise. An interesting and unexpected result was the identification of an acoustic mode within the valve which does not respond until the valve was over 60% open. Further, the response amplitude around this mode can be as large or larger than those associated with lower frequency modes.

Fishbach, Sean R.↗
NASA NTRS1980

Analysis techniques for multivariate root loci

Analysis and techniques are developed for the multivariable root locus and the multivariable optimal root locus. The generalized eigenvalue problem is used to compute angles and sensitivities for both types of loci, and an algorithm is presented that determines the asymptotic properties of the optimal root locus.

Thompson, P. M.↗
DOE OSTI2021

The UPR regulator IRE1 promotes balanced organ development by restricting TOR-dependent control of cellular differentiation in Arabidopsis

Proteostasis of the endoplasmic reticulum (ER) is controlled by sophisticated signaling pathways that are collectively called the unfolded protein response (UPR) and are initiated by specialized ER membrane-associated sensors. The evidence that complete loss-of-function mutations of the most conserved of the UPR sensors, inositol-requiring enzyme 1 (IRE1), dysregulates tissue growth and development in metazoans and plants raises the fundamental question as to how IRE1 is connected to organismal growth. To address this question, we interrogated the Arabidopsis primary root, an established model for organ development, using the tractable Arabidopsis IRE1 mutant ire1a ire1b, which has marked root development defects in the absence of exogenous stress. We demonstrate that IRE1 is required to reach maximum rates of cell elongation and root growth. We also established that in the actively growing ire1a ire1b mutant root tips the Target of Rapamycin (TOR) kinase, a widely conserved pro-growth regulator, is hyperactive, and that, unlike cell proliferation, the rate of cell differentiation is enhanced in ire1a ire1b in a TOR-dependent manner. By functionally connecting two essential growth regulators, these results underpin a novel and critical role of IRE1 in organ development and indicate that, as cells exit an undifferentiated state, IRE1 is required to monitor TOR activity to balance cell expansion and maturation during organ biogenesis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

GWAS identifies candidate genes controlling adventitious rooting in Populus trichocarpa

Adventitious rooting (AR) is critical to the propagation, breeding, and genetic engineering of trees. The capacity for plants to undergo this process is highly heritable and of a polygenic nature; however, the basis of its genetic variation is largely uncharacterized. To identify genetic regulators of AR, we performed a genome-wide association study (GWAS) using 1148 genotypes of Populus trichocarpa. GWASs are often limited by the abilities of researchers to collect precise phenotype data on a high-throughput scale; to help overcome this limitation, we developed a computer vision system to measure an array of traits related to adventitious root development in poplar, including temporal measures of lateral and basal root length and area. GWAS was performed using multiple methods and significance thresholds to handle non-normal phenotype statistics and to gain statistical power. These analyses yielded a total of 277 unique associations, suggesting that genes that control rooting include regulators of hormone signaling, cell division and structure, reactive oxygen species signaling, and other processes with known roles in root development. Numerous genes with uncharacterized functions and/or cryptic roles were also identified. These candidates provide targets for functional analysis, including physiological and epistatic analyses, to better characterize the complex polygenic regulation of AR.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

One-Step Regeneration of Hairy Roots to Induce High Tanshinone Plants in Salvia miltiorrhiza

Salvia miltiorrhiza is a traditional Chinese medicinal plant of Labiatae, which has been widely utilized to treat a variety of cardiovascular and cerebrovascular diseases. However, due to the long growth cycle, low content of active ingredients, and serious quality deterioration of S. miltiorrhiza , the use of biotechnology to improve S. miltiorrhiza to meet the growing demand for clinical applications has become a research hotspot. In this study, a novel one-step hairy root regeneration method was developed, which could rapidly obtain hairy roots and regenerated plants with high tanshinone content. By optimizing the parameters of Agrobacterium rhizogenes transformation in S. miltiorrhiza , it was finally established that the explants were infected in Ar.qual (OD 600 = 0.6) for 10 min, co-cultured for 3 days, and then screened on the screening medium containing 7.5 mg/l hygromycin, the maximum transformation frequency can reach 73.85%. GFP and PCR detection yielded a total of 9 positive transgenic hairy root lines and 11 positive transgenic regenerated plants. SmGGPPS1 was successfully overexpressed in positive transgenic regenerated plants, according to the results of qRT-PCR. The content of tanshinone IIA and cryptotanshinone were dramatically enhanced in transgenic regenerated plants and hairy roots by Ultra Performance Liquid Chromatography analysis. Based on the Agrobacterium-mediated transformation of S. miltiorrhiza , this study developed a new method for regenerating plants with transgenic hairy roots. This method provides a foundation for the breeding of S. miltiorrhiza and the sustainable development of medicinal plant resources, as well as provides a useful reference for the application of other species.

Su, Yuekai↗
DOE OSTI2026

Data for Soil Oxygen Dynamics: A Key Mediator of Tile Drainage Impacts on Coupled Hydrological, Biogeochemical, and Crop Systems

Tile drainage removes excess water and is an essential, widely adopted management practice to enhance crop productivity in the US Midwest and throughout the world. Tile drainage has been shown to significantly change hydrological and biogeochemical cycles by lowering the water table and reducing the residence time of soil water, although examining the complex interactions and feedbacks in an integrated hydrology–biogeochemistry–crop system remains elusive. Oxygen dynamics are critical to unraveling these interactions and have been ignored or oversimplified in existing models. Understanding these impacts is essential, particularly so because tile drainage has been highlighted as an adaptation under projected wetter springs and drier summers in the changing climate in the US Midwest. We used the ecosys model that uniquely incorporates first-principle soil oxygen dynamics and crop oxygen uptake mechanisms to quantify the impacts of tile drainage on hydrological and biogeochemical cycles and crop growth in corn–soybean rotation fields. The model was validated with data from a multi-treatment, multi-year experiment in Washington, IA. The relative root mean square error (rRMSE) for the corn and soybean yield in validation is 5.66 % and 12.57 %, respectively. The Pearson coefficient (r) of the monthly tile flow during the growing season is 0.78. Plant oxygen stress turns out as an emergent property of the equilibrium between the soil oxygen supply and biological demand. The impact of tile drainage on the system is achieved through a series of coupled feedback mechanisms. The model results show that tile drainage reduces the soil water content and enhances soil oxygenation. It additionally increases the subsurface discharge and elevates inorganic nitrogen leaching, with seasonal variations influenced by climate and crop phenology. The improved aerobic condition alleviates crop oxygen stress during wet springs, thereby promoting crop root growth during the early growth stage. The development of greater root density, in turn, mitigates water stress during dry summers, leading to an overall increase in the crop yield by ∼6 %. These functions indicate the potential of tile drainage in bolstering crop resilience to climate change and the use of this modeling tool for large-scale assessments of tile drainage. The model reveals the underlying causal mechanisms that drive the agroecosystem response to drainage on the coupled hydrology, biogeochemistry, and crop system dynamics.

Modeling↗