Simulation of Automatically Annotated Visible and Multi-/Hyperspectral Images Using the Helios 3D Plant and Radiative Transfer Modeling Framework.

Deep learning and multimodal remote and proximal sensing are widely used for analyzing plant and crop traits, but many of these deep learning models are supervised and necessitate reference datasets with image annotations. Acquiring these datasets often demands experiments that are both labor-intensive and time-consuming. Furthermore, extracting traits from remote sensing data beyond simple geometric features remains a challenge. To address these challenges, we proposed a radiative transfer modeling framework based on the Helios 3-dimensional (3D) plant modeling software designed for plant remote and proximal sensing image simulation. The framework has the capability to simulate RGB, multi-/hyperspectral, thermal, and depth cameras, and produce associated plant images with fully resolved reference labels such as plant physical traits, leaf chemical concentrations, and leaf physiological traits. Helios offers a simulated environment that enables generation of 3D geometric models of plants and soil with random variation, and specification or simulation of their properties and function. This approach differs from traditional computer graphics rendering by explicitly modeling radiation transfer physics, which provides a critical link to underlying plant biophysical processes. Results indicate that the framework is capable of generating high-quality, labeled synthetic plant images under given lighting scenarios, which can lessen or remove the need for manually collected and annotated data. Two example applications are presented that demonstrate the feasibility of using the model to enable unsupervised learning by training deep learning models exclusively with simulated images and performing prediction tasks using real images.

Practical Considerations and Limitations of Using Leaf and Canopy Temperature Measurements as a Stomatal Conductance Proxy: Sensitivity across Environmental Conditions, Scale, and Sample Size.

Stomatal conductance (gs) is a crucial component of plant physiology, as it links plant productivity and water loss through transpiration. Estimating gs indirectly through leaf temperature (Tl) measurement is common for reducing the high labor cost associated with direct gs measurement. However, the relationship between observed Tl and gs can be notably affected by local environmental conditions, canopy structure, measurement scale, sample size, and gs itself. To better understand and quantify the variation in the relationship between Tl measurements to gs, this study analyzed the sensitivity of Tl to gs using a high-resolution three-dimensional model that resolves interactions between microclimate and canopy structure. The model was used to simulate the sensitivity of Tl to gs across different environmental conditions, aggregation scales (point measurement, infrared thermometer, and thermographic image), and sample sizes. Results showed that leaf-level sensitivity of Tl to gs was highest under conditions of high net radiation flux, high vapor pressure deficit, and low boundary layer conductance. The study findings also highlighted the trade-off between measurement scale and sample size to maximize sensitivity. Smaller scale measurements (e.g., thermocouple) provided maximal sensitivity because they allow for exclusion of shaded leaves and the ground, which have low sensitivity. However, large sample sizes (up to 50 to 75) may be needed to differentiate genotypes. Larger-scale measurements (e.g., thermal camera) reduced sample size requirements but include low-sensitivity elements in the measurement. This work provides a means of estimating leaf-level sensitivity and offers quantitative guidance for balancing scale and sample size issues.

Quantifying water-use efficiency in plant canopies with varying leaf angle and density distribution.

BACKGROUND AND AIMS: Variation in architectural traits related to the spatial and angular distribution of leaf area can have considerable impacts on canopy-scale fluxes contributing to water-use efficiency (WUE). These architectural traits are frequent targets for crop improvement and for improving the understanding and predictions of net ecosystem carbon and water fluxes. METHODS: A three-dimensional, leaf-resolving model along with a range of virtually generated hypothetical canopies were used to quantify interactions between canopy structure and WUE by examining its response to variation of leaf inclination independent of leaf azimuth, canopy heterogeneity, vegetation density and physiological parameters. KEY RESULTS: Overall, increasing leaf area index (LAI), increasing the daily-averaged fraction of leaf area projected in the sun direction (Gavg) via the leaf inclination or azimuth distribution and increasing homogeneity had a similar effect on canopy-scale daily fluxes contributing to WUE. Increasing any of these parameters tended to increase daily light interception, increase daily net photosynthesis at low LAI and decrease it at high LAI, increase daily transpiration and decrease WUE. Isolated spherical crowns could decrease photosynthesis by ~60 % but increase daily WUE ≤130 % relative to a homogeneous canopy with equivalent leaf area density. There was no observed optimum in daily canopy WUE as LAI, leaf angle distribution or heterogeneity was varied. However, when the canopy was dense, a more vertical leaf angle distribution could increase both photosynthesis and WUE simultaneously. CONCLUSIONS: Variation in leaf angle and density distributions can have a substantial impact on canopy-level carbon and water fluxes, with potential trade-offs between the two. These traits might therefore be viable target traits for increasing or maintaining crop productivity while using less water, and for improvement of simplified models. Increasing canopy density or decreasing canopy heterogeneity increases the impact of leaf angle on WUE and its dependent processes.

Kinetic factors of physiology and the dynamic light environment influence the economic landscape of short-term hydraulic risk.

Optimality-based models of stomatal conductance unify biophysical and evolutionary constraints and can improve predictions of land-atmosphere carbon and water exchange. Recent models incorporate hydraulic constraints by penalizing excessive stomatal opening in relation to hydraulic damage caused by low water potentials. We used simulation models to test whether penalties based solely on vulnerability curves adequately represent the optimality hypothesis, given that they exclude the effects of kinetic factors on stomatal behavior and integrated carbon balance. To quantify the effects of nonsteady-state phenomena on the landscape of short-term hydraulic risk, we simulated diurnal dynamics of leaf physiology for 10 000 patches of leaf in a canopy and used a ray-tracing model, Helios, to simulate realistic variation in sunfleck dynamics. Our simulations demonstrated that kinetic parameters of leaf physiology and sunfleck properties influence the economic landscape of short-term hydraulic risk, as characterized by the effect of stomatal strategy (gauged by the water potential causing a 50% hydraulic penalty) on both aggregated carbon gain and the aggregated carbon cost of short-term hydraulic risk. Hydraulic penalties in optimization models should be generalized to allow their parameters to account for kinetic factors, in addition to parameters of hydraulic vulnerability.

Catching Spores: Linking Epidemiology, Pathogen Biology, and Physics to Ground-Based Airborne Inoculum Monitoring.

Monitoring airborne inoculum is gaining interest as a potential means of giving growers an earlier warning of disease risk in a management unit or region. This information is sought by growers to aid in adapting to changes in the management tools at their disposal and the market-driven need to reduce the use of fungicides and cost of production. To effectively use inoculum monitoring as a decision aid, there is an increasing need to understand the physics of particle transport in managed and natural plant canopies to effectively deploy and use near-ground aerial inoculum data. This understanding, combined with the nuances of pathogen-specific biology and disease epidemiology, can serve as a guide to designing improved monitoring approaches. The complexity of any pathosystem and local environment are such that there is not a generalized approach to near-ground air sampler placement, but there is a conceptual framework to arrive at a "semi-optimal" solution based on available resources. This review is intended as a brief synopsis of the linkages among pathogen biology, disease epidemiology, and the physics of the aerial dispersion of pathogen inoculum and what to consider when deciding where to locate ground-based air samplers. We leverage prior work in developing airborne monitoring tools for hops, grapes, spinach, and turf, and research into the fluid mechanics governing particle transport in sparse canopies and urban and forest environments. We present simulation studies to demonstrate how particles move in the complex environments of agricultural fields and to illustrate the limited sampling area of common air samplers.

Helios: A Scalable 3D Plant and Environmental Biophysical Modeling Framework.

This article presents an overview of Helios, a new three-dimensional (3D) plant and environmental modeling framework. Helios is a model coupling framework designed to provide maximum flexibility in integrating and running arbitrary 3D environmental system models. Users interact with Helios through a well-documented open-source C++ API. Version 1.0 comes with model plug-ins for radiation transport, the surface energy balance, stomatal conductance, photosynthesis, solar position, and procedural tree generation. Additional plug-ins are also available for visualizing model geometry and data and for processing and integrating LiDAR scanning data. Many of the plug-ins perform calculations on the graphics processing unit, which allows for efficient simulation of very large domains with high detail. An example modeling study is presented in which leaf-level heterogeneity in water usage and photosynthesis of an orchard is examined to understand how this leaf-scale variability contributes to whole-tree and -canopy fluxes.

The accuracy of the compressible Reynolds equation for predicting the local pressure in gas-lubricated textured parallel slider bearings.

The validity of the compressible Reynolds equation to predict the local pressure in a gas-lubricated, textured parallel slider bearing is investigated. The local bearing pressure is numerically simulated using the Reynolds equation and the Navier-Stokes equations for different texture geometries and operating conditions. The respective results are compared and the simplifying assumptions inherent in the application of the Reynolds equation are quantitatively evaluated. The deviation between the local bearing pressure obtained with the Reynolds equation and the Navier-Stokes equations increases with increasing texture aspect ratio, because a significant cross-film pressure gradient and a large velocity gradient in the sliding direction develop in the lubricant film. Inertia is found to be negligible throughout this study.

Design, synthesis, and biological evaluation of aryloxyethyl thiocyanate derivatives against Trypanosoma cruzi.

As a continuation of our project aimed at the search for new and safe chemotherapeutic and chemoprophylactic agents against American trypanosomiasis (Chagas' disease), several drugs structurally related to 4-phenoxyphenoxyethyl thiocyanate (4) were designed, synthesized, and evaluated as antiproliferative agents against the parasite responsible for this disease, the hemoflagellated protozoan Trypanosoma cruzi. This thiocyanate derivative was previously shown to be an effective and potent agent against T. cruzi proliferation. Several drugs possessing thiocyanate groups proved to be effective growth inhibitors of T. cruzi growth. Among the designed compounds, it is important to point out the extremely potent activity shown by 11, 23, 38, 53, 90, 99, and 117 against the epimastigote forms of the parasite. All of them exhibited IC(50) values in the low micromolar range, and these values were comparable with those presented by our lead drug 4 and ketokonazole, a well-known antiparasitic agent. The activity displayed by the nitrogen-containing derivative 90 was very promising with IC(50) values of 3.3 microM. Several other thiocyanate derivatives also proved to be very potent inhibitors of the multiplication of T. cruzi epimastigotes, such as compounds 28, 33, 43, 48, 56, 61, 66, 71, 76, and 124. Compound 43 resulted in being a promising drug because it was also very effective against amastigotes, the clinically more relevant form of the parasite. This compound was 3-fold more potent than 4, while 11 showed nearly the same activity as our lead drug against intracellular T. cruzi. It was very surprising that the experimental juvenoid 124, although fairly devoid of activity against epimastigotes, was very effective against intracellular amastigotes growing in myoblasts. The rest of the designed compounds showed a broad degree of inhibitory action, from moderately active drugs to drugs almost devoid of antiparasitic activity. Compound 43 is an interesting example of an effective antichagasic agent that presents excellent prospectives not only as a lead drug but also to be used for further in vivo studies.

Magic-angle spinning (31)P NMR spectroscopy of condensed phosphates in parasitic protozoa: visualizing the invisible.

We report the results of a solid-state (31)P nuclear magnetic resonance (NMR) spectroscopic investigation of the acidocalcisome organelles from Trypanosoma brucei (bloodstream form), Trypanosoma cruzi and Leishmania major (insect forms). The spectra are characterized by a broad envelope of spinning sidebands having isotropic chemical shifts at approximately 0, -7 and -21 ppm. These resonances are assigned to orthophosphate, terminal (alpha) phosphates of polyphosphates and bridging (beta) phosphates of polyphosphates, respectively. The average polyphosphate chain length is approximately 3.3 phosphates. Similar results were obtained with whole L. major promastigotes. (31)P NMR spectra of living L. major promastigotes recorded under conventional solution NMR conditions had spectral intensities reduced with respect to solution-state NMR spectra of acid extracts, consistent with the invisibility of the solid-state phosphates. These results show that all three parasites contain large stores of condensed phosphates which can be visualized by using magic-angle spinning NMR techniques.

Radical cure of experimental cutaneous leishmaniasis by the bisphosphonate pamidronate.

The effects in vivo of the bisphosphonate drug pamidronate, used in bone resorption therapy, were investigated in an experimental model of cutaneous leishmaniasis. Pamidronate at an intraperitoneal dose of 10 mg/kg/day for 5 days effects a radical cure of cutaneous leishmaniasis in Balb/c mice, as evidenced by long-term disappearance of lesions; disappearance of amastigotes in lesion sites, as determined by histopathological analysis and cultivation of material obtained from lesions; and polymerase chain reaction analysis of necropsy material, using probes specific for kinetoplast DNA. Pamidronate is, therefore, a new lead compound for the synthesis of drugs effective against cutaneous leishmaniasis.