A variety-specific analysis of climate change effects on California winegrapes.

California contains a broad geography over which climate conditions can be suitable for cultivating multiple varieties of winegrapes. However, climate change is projected to make winegrape cultivation more challenging across many of California's winegrowing regions. In order to understand the potential effects of climate change on winegrapes, this study models variety-specific phenology for six winegrape varieties and quantifies the change in phenology and viticulturally-important agroclimate metrics over 12 of California's American Viticultural Areas (AVAs) by the mid-21st century. Results show more rapid development for winegrapes with earlier budburst, flowering, veraison, and maturation across all varieties and AVAs. Cabernet Sauvignon shows the greatest change in phenology timing, while Chardonnay shows the least change. Likewise, the West Sonoma Coast AVA shows the greatest average change in phenology timing across varieties and development stages and Lodi AVA shows the least. Projected changes in agroclimatic metrics include an additional month of potentially damaging heat days (above 35 °C) in some AVAs, and decreases in frost days. These results have implications for numerous factors related to viticultural production, including water resources management and crop yield and quality, and underscore the need for California winegrape growers to improve their resilience to climate change by adopting strategies such as increasing soil health and water use efficiency and selecting cultivars suited for future climate conditions. By conducting climate effects analyses at the variety-specific and AVA scale, important information is provided to the winegrowing industry at a resolution that can support decision-making towards resilience.

Grape cultivars adapted to hotter, drier growing regions exhibit greater photosynthesis under hot conditions despite less drought-resistant leaves.

BACKGROUND AND AIMS: Many agricultural areas are expected to face hotter, drier conditions from climate change. Understanding the mechanisms crops use to mitigate these stresses can guide breeding for more tolerant plant material. We tested relationships between traits, physiological function under hot conditions, and historical climate associations to evaluate these mechanisms for winegrapes. We expected a more negative leaf osmotic potential at full hydration (πo), which reduces leaf turgor loss during drought, and either a metabolically cheaper or more osmoprotectant leaf chemical composition, to allow cultivars associated with hot, dry regions to maintain greater gas exchange under hot growing conditions. METHODS: We measured πo, gas exchange, and leaf chemistry for 7 commercially important winegrape cultivars that vary widely in historical climate associations. Vines were grown under common garden field conditions in a hot wine-growing region (Davis, California) and measured over the hottest period of the growing season (July - September). KEY RESULTS: □o varied significantly between cultivars, and all cultivars significantly reduced □o (osmotically adjusted) over the study period, though osmotic adjustment did not vary across cultivars. πo was correlated with gas exchange and climate associations, but in the opposite directions than expected. Photosynthesis and πo were higher in the cultivars associated with hotter, less humid regions. Leaf chemical composition varied between cultivars, but was not related to climate associations. CONCLUSIONS: These findings suggest that leaf turgor maintenance is not a primary limitation on grapevine adaptation to hot or atmospherically dry growing conditions. Thus, selecting for a more negative πo or greater osmotic adjustment is not a promising strategy to develop more climate-resilient grape varieties, contrary to findings for other crops. Future work is needed to identify the mechanisms increasing photosynthesis in the cultivars associated with hot, dry regions.

Drought-induced fiber water release and xylem embolism susceptibility of intact balsam poplar saplings.

Balsam poplar (Populus balsamifera L.) is a widespread tree species in North America with significant ecological and economic value. However, little is known about the susceptibility of saplings to drought-induced embolism and its link to water release from surrounding xylem fibers. Questions remain regarding localized mechanisms that contribute to the survival of saplings in vivo of this species under drought. Using X-ray micro-computed tomography on intact saplings of genotypes Gillam-5 and Carnduff-9, we found that functional vessels are embedded in a matrix of water-filled fibers under well-watered conditions in both genotypes. However, water-depleted fibers started to appear under moderate drought stress while vessels remained water-filled in both genotypes. Drought-induced xylem embolism susceptibility was comparable between genotypes, and a greater frequency of smaller diameter vessels in GIL-5 did not increase embolism resistance in this genotype. Despite having smaller vessels and a total vessel number that was comparable to CAR-9, stomatal conductance was generally higher in GIL-5 compared to CAR-9. In conclusion, our in vivo data on intact saplings indicate that differences in embolism susceptibility are negligible between GIL-5 and CAR-9, and that fiber water release should be considered as a mechanism that contributes to the maintenance of vessel functional status in saplings of balsam poplar experiencing their first drought event.

Anatomy of an agricultural antagonist: Feeding complex structure and function of three xylem sap-feeding insects illuminated with synchrotron-based 3D imaging.

Many insects feed on xylem or phloem sap of vascular plants. Although physical damage to the plant is minimal, the process of insect feeding can transmit lethal viruses and bacterial pathogens. Disparities between insect-mediated pathogen transmission efficiency have been identified among xylem sap-feeding insects; however, the mechanistic drivers of these trends are unclear. Identifying and understanding the structural factors and associated integrated functional components that may ultimately determine these disparities are critical for managing plant diseases. Here, we applied synchrotron-based X-ray microcomputed tomography to digitally reconstruct the morphology of three xylem sap-feeding insect vectors of plant pathogens: Graphocephala atropunctata (blue-green sharpshooter; Hemiptera, Cicadellidae) and Homalodisca vitripennis (glassy-winged sharpshooter; Hemiptera, Cicadellidae), and the spittlebug Philaenus spumarius (meadow spittlebug; Hemiptera, Aphrophoridae). The application of this technique revealed previously undescribed anatomical features of these organisms, such as key components of the salivary complex. The visualization of the 3D structure of the precibarial valve led to new insights into the mechanism of how this structure functions. Morphological disparities with functional implications between taxa were highlighted as well, including the morphology and volume of the cibarial dilator musculature responsible for extracting xylem sap, which has implications for force application capabilities. These morphological insights will be used to target analyses illuminating functional differences in feeding behavior.

A workflow for segmenting soil and plant X-ray computed tomography images with deep learning in Google's Colaboratory.

X-ray micro-computed tomography (X-ray µCT) has enabled the characterization of the properties and processes that take place in plants and soils at the micron scale. Despite the widespread use of this advanced technique, major limitations in both hardware and software limit the speed and accuracy of image processing and data analysis. Recent advances in machine learning, specifically the application of convolutional neural networks to image analysis, have enabled rapid and accurate segmentation of image data. Yet, challenges remain in applying convolutional neural networks to the analysis of environmentally and agriculturally relevant images. Specifically, there is a disconnect between the computer scientists and engineers, who build these AI/ML tools, and the potential end users in agricultural research, who may be unsure of how to apply these tools in their work. Additionally, the computing resources required for training and applying deep learning models are unique, more common to computer gaming systems or graphics design work, than to traditional computational systems. To navigate these challenges, we developed a modular workflow for applying convolutional neural networks to X-ray µCT images, using low-cost resources in Google's Colaboratory web application. Here we present the results of the workflow, illustrating how parameters can be optimized to achieve best results using example scans from walnut leaves, almond flower buds, and a soil aggregate. We expect that this framework will accelerate the adoption and use of emerging deep learning techniques within the plant and soil sciences.

Effects of meteorological and land surface modeling uncertainty on errors in winegrape ET calculated with SIMS.

Characterization of model errors is important when applying satellite-driven evapotranspiration (ET) models to water resource management problems. This study examines how uncertainty in meteorological forcing data and land surface modeling propagate through to errors in final ET data calculated using the Satellite Irrigation Management Support (SIMS) model, a computationally efficient ET model driven with satellite surface reflectance values. The model is applied to three instrumented winegrape vineyards over the 2017-2020 time period and the spatial and temporal variation in errors are analyzed. We illustrate how meteorological data inputs can introduce biases that vary in space and at seasonal timescales, but that can persist from year to year. We also observe that errors in SIMS estimates of land surface conductance can have a particularly strong dependence on time of year. Overall, meteorological inputs introduced RMSE of 0.33-0.65 mm/day (7-27%) across sites, while SIMS introduced RMSE of 0.55-0.83 mm/day (19-24%). The relative error contribution from meteorological inputs versus SIMS varied across sites; errors from SIMS were larger at one site, errors from meteorological inputs were larger at a second site, and the error contributions were of equal magnitude at the third site. The similar magnitude of error contributions is significant given that many satellite-driven ET models differ in their approaches to estimating land surface conductance, but often rely on similar or identical meteorological forcing data. The finding is particularly notable given that SIMS makes assumptions about the land surface (no soil evaporation or plant water stress) that do not always hold in practice. The results of this study show that improving SIMS by eliminating these assumptions would result in meteorological inputs dominating the error budget of the model on the whole. This finding underscores the need for further work on characterizing spatial uncertainty in the meteorological forcing of ET. Supplementary Information: The online version contains supplementary material available at 10.1007/s00271-022-00808-9.

Improving the spatiotemporal resolution of remotely sensed ET information for water management through Landsat, Sentinel-2, ECOSTRESS and VIIRS data fusion.

Robust information on consumptive water use (evapotranspiration, ET) derived from remote sensing can significantly benefit water decision-making in agriculture, informing irrigation schedules and water management plans over extended regions. To be of optimal utility for operational usage, these remote sensing ET data should be generated at the sub-field spatial resolution and daily-to-weekly timesteps commensurate with the scales of water management activities. However, current methods for field-scale ET retrieval based on thermal infrared (TIR) imaging, a valuable diagnostic of canopy stress and surface moisture status, are limited by the temporal revisit of available medium-resolution (100 m or finer) thermal satellite sensors. This study investigates the efficacy of a data fusion method for combining information from multiple medium-resolution sensors toward generating high spatiotemporal resolution ET products for water management. TIR data from Landsat and ECOSTRESS (both at ~ 100-m native resolution), and VIIRS (375-m native) are sharpened to a common 30-m grid using surface reflectance data from the Harmonized Landsat-Sentinel dataset. Periodic 30-m ET retrievals from these combined thermal data sources are fused with daily retrievals from unsharpened VIIRS to generate daily, 30-m ET image timeseries. The accuracy of this mapping method is tested over several irrigated cropping systems in the Central Valley of California in comparison with flux tower observations, including measurements over irrigated vineyards collected in the GRAPEX campaign. Results demonstrate the operational value added by the augmented TIR sensor suite compared to Landsat alone, in terms of capturing daily ET variability and reduced latency for real-time applications. The method also provides means for incorporating new sources of imaging from future planned thermal missions, further improving our ability to map rapid changes in crop water use at field scales.

Application of a remote-sensing three-source energy balance model to improve evapotranspiration partitioning in vineyards.

Improved accuracy of evapotranspiration (ET) estimation, including its partitioning between transpiration (T) and surface evaporation (E), is key to monitor agricultural water use in vineyards, especially to enhance water use efficiency in semi-arid regions such as California, USA. Remote-sensing methods have shown great utility in retrieving ET from surface energy balance models based on thermal infrared data. Notably, the two-source energy balance (TSEB) has been widely and robustly applied in numerous landscapes, including vineyards. However, vineyards add an additional complexity where the landscape is essentially made up of two distinct zones: the grapevine and the interrow, which is often seasonally covered by an herbaceous cover crop. Therefore, it becomes more complex to disentangle the various contributions of the different vegetation elements to total ET, especially through TSEB, which assumes a single vegetation source over a soil layer. As such, a remote-sensing-based three-source energy balance (3SEB) model, which essentially adds a vegetation source to TSEB, was applied in an experimental vineyard located in California's Central Valley to investigate whether it improves the depiction of the grapevine-interrow system. The model was applied in four different blocks in 2019 and 2020, where each block had an eddy-covariance (EC) tower collecting continuous flux, radiometric, and meteorological measurements. 3SEB's latent and sensible heat flux retrievals were accurate with an overall RMSD ~ 50 W/m2 compared to EC measurements. 3SEB improved upon TSEB simulations, with the largest differences being concentrated in the spring season, when there is greater mixing between grapevine foliage and the cover crop. Additionally, 3SEB's modeled ET partitioning (T/ET) compared well against an EC T/ET retrieval method, being only slightly underestimated. Overall, these promising results indicate 3SEB can be of great utility to vineyard irrigation management, especially to improve T/ET estimations and to quantify the contribution of the cover crop to ET. Improved knowledge of T/ET can enhance grapevine water stress detection to support irrigation and water resource management. Supplementary Information: The online version contains supplementary material available at 10.1007/s00271-022-00787-x.

Structural and functional leaf diversity lead to variability in photosynthetic capacity across a range of Juglans regia genotypes.

Similar to other cropping systems, few walnut cultivars are used as scion in commercial production. Germplasm collections can be used to diversify cultivar options and hold potential for improving crop productivity, disease resistance and stress tolerance. In this study, we explored the anatomical and biochemical bases of photosynthetic capacity and response to water stress in 11 Juglans regia accessions in the U.S. department of agriculture, agricultural research service (USDA-ARS) National Clonal Germplasm. Net assimilation rate (An ) differed significantly among accessions and was greater in lower latitudes coincident with higher stomatal and mesophyll conductances, leaf thickness, mesophyll porosity, gas-phase diffusion, leaf nitrogen and lower leaf mass and stomatal density. High CO2 -saturated assimilation rates led to increases in An under diffusional and biochemical limitations. Greater An was found in lower-latitude accessions native to climates with more frost-free days, greater precipitation seasonality and lower temperature seasonality. As expected, water stress consistently impaired photosynthesis with the highest % reductions in lower-latitude accessions (A3, A5 and A9), which had the highest An under well-watered conditions. However, An for A3 and A5 remained among the highest under dehydration. J. regia accessions, which have leaf structural traits and biochemistry that enhance photosynthesis, could be used as commercial scions or breeding parents to enhance productivity.

Desiccation of the leaf mesophyll and its implications for CO2 diffusion and light processing.

Leaves balance CO2 and radiative absorption while maintaining water transport to maximise photosynthesis. Related species with contrasting leaf anatomy can provide insights into inherent and stress-induced links between structure and function for commonly measured leaf traits for important crops. We used two walnut species with contrasting mesophyll anatomy to evaluate these integrated exchange processes under non-stressed and drought conditions using a combination of light microscopy, X-ray microCT, gas exchange, hydraulic conductance, and chlorophyll distribution profiles through leaves. Juglans regia had thicker palisade mesophyll, higher fluorescence in the palisade, and greater low-mesophyll porosity that were associated with greater gas-phase diffusion (gIAS ), stomatal and mesophyll (gm ) conductances and carboxylation capacity. More and highly-packed mesophyll cells and bundle sheath extensions (BSEs) in Juglans microcarpa led to higher fluorescence in the spongy and in proximity to the BSEs. Both species exhibited drought-induced reductions in mesophyll cell volume, yet the associated increases in porosity and gIAS were obscured by declines in biochemical activity that decreased gm . Inherent differences in leaf anatomy between the species were linked to differences in gas exchange, light absorption and photosynthetic capacity, and drought-induced changes in leaf structure impacted performance via imposing species-specific limitations to light absorption, gas exchange and hydraulics.

Ecologically driven selection of nonstructural carbohydrate storage in oak trees.

Leaf habit is a major axis of plant diversity that has consequences for carbon balance since the leaf is the primary site of photosynthesis. Nonstructural carbohydrates (NSCs) produced by photosynthesis can be allocated to storage and serve as a resiliency mechanism to future abiotic and biotic stress. However, how leaf habit affects NSC storage in an evolutionary context has not been shown. Using a comparative physiological framework and an analysis of evolutionary model fitting, we examined if variation in NSC storage is explained by leaf habit. We measured sugar and starch concentrations in 51 oak species (Quercus spp.) growing in a common garden and representing multiple evolutions of three different leaf habits (deciduous, brevideciduous and evergreen). The best fitting evolutionary models indicated that deciduous oak species are evolving towards higher NSC concentrations than their brevideciduous and evergreen relatives. Notably, this was observed for starch (the primary storage molecule) in the stem (a long-term C storage organ). Overall, our work provides insight into the evolutionary drivers of NSC storage and suggests that a deciduous strategy may confer an advantage against stress associated with a changing world. Future work should examine additional clades to further corroborate this idea.

Inherent and Stress-Induced Responses of Fine Root Morphology and Anatomy in Commercial Grapevine Rootstocks with Contrasting Drought Resistance.

Some grapevine rootstocks perform better than others during and after drought events, yet it is not clear how inherent and stress-induced differences in root morphology and anatomy along the length of fine roots are involved in these responses. Using a variety of growing conditions and plant materials, we observed significant differences in root diameter, specific root length (SRL) and root diameter distribution between two commonly used commercial grapevine rootstocks: Richter 110 (110R; drought resistant) and Millardet et de Grasset 101-14 (101-14Mgt; drought sensitive). The 110R consistently showed greater root diameters with smaller SRL and proportion of root length comprised of fine lateral roots. The 110R also exhibited significantly greater distance from tip to nearest lateral, longer white root length, and larger proportion of root length that is white under drought stress. Mapping of fine root cortical lacunae showed similar patterns between the rootstocks; mechanical failure of cortical cells was common in the maturation zone, limited near the root tip, and increased with drought stress for both genotypes; however, lacuna formed under wetter soil conditions in 110R. Results suggest that drought resistance in grapevine rootstocks is associated with thick, limitedly branched roots with a larger proportion of white-functional roots that tend to form lacuna under more mild water deficit, all of which likely favor continued resource acquisition at depth.

Maximum CO2 diffusion inside leaves is limited by the scaling of cell size and genome size.

Maintaining high rates of photosynthesis in leaves requires efficient movement of CO2 from the atmosphere to the mesophyll cells inside the leaf where CO2 is converted into sugar. CO2 diffusion inside the leaf depends directly on the structure of the mesophyll cells and their surrounding airspace, which have been difficult to characterize because of their inherently three-dimensional organization. Yet faster CO2 diffusion inside the leaf was probably critical in elevating rates of photosynthesis that occurred among angiosperm lineages. Here we characterize the three-dimensional surface area of the leaf mesophyll across vascular plants. We show that genome size determines the sizes and packing densities of cells in all leaf tissues and that smaller cells enable more mesophyll surface area to be packed into the leaf volume, facilitating higher CO2 diffusion. Measurements and modelling revealed that the spongy mesophyll layer better facilitates gaseous phase diffusion while the palisade mesophyll layer better facilitates liquid-phase diffusion. Our results demonstrate that genome downsizing among the angiosperms was critical to restructuring the entire pathway of CO2 diffusion into and through the leaf, maintaining high rates of CO2 supply to the leaf mesophyll despite declining atmospheric CO2 levels during the Cretaceous.

Xylem network connectivity and embolism spread in grapevine(Vitis vinifera L.).

Xylem networks are vulnerable to the formation and spread of gas embolisms that reduce water transport. Embolisms spread through interconduit pits, but the three-dimensional (3D) complexity and scale of xylem networks means that the functional implications of intervessel connections are not well understood. Here, xylem networks of grapevine (Vitis vinifera L.) were reconstructed from 3D high-resolution X-ray micro-computed tomography (microCT) images. Xylem network performance was then modeled to simulate loss of hydraulic conductivity under increasingly negative xylem sap pressure simulating drought stress conditions. We also considered the sensitivity of xylem network performance to changes in key network parameters. We found that the mean pit area per intervessel connection was constant across 10 networks from three, 1.5-m stem segments, but short (0.5 cm) segments fail to capture complete network connectivity. Simulations showed that network organization imparted additional resistance to embolism spread beyond the air-seeding threshold of pit membranes. Xylem network vulnerability to embolism spread was most sensitive to variation in the number and location of vessels that were initially embolized and pit membrane vulnerability. Our results show that xylem network organization can increase stem resistance to embolism spread by 40% (0.66 MPa) and challenge the notion that a single embolism can spread rapidly throughout an entire xylem network.

Modification of a gas exchange system to measure active and passive chlorophyll fluorescence simultaneously under field conditions.

Solar-induced fluorescence (SIF) is a promising tool to estimate photosynthesis across scales; however, there has been limited research done at the leaf level to investigate the relationship between SIF and photosynthesis. To help bridge this gap, a LI-COR LI-6800 gas exchange instrument was modified with a visible-near-infrared (VIS-NIR) spectrometer to measure active and passive fluorescence simultaneously. The system was adapted by drilling a hole into the bottom plate of the leaf chamber and inserting a fibre-optic to measure passive steady-state fluorescence (F t , λ , analogous to SIF) from the abaxial surface of a leaf. This new modification can concurrently measure gas exchange, passive fluorescence and active fluorescence over the same leaf area and will allow researchers to measure leaf-level F t , λ in the field to validate tower-based and satellite measurements. To test the modified instrument, measurements were performed on leaves of well-watered and water-stressed walnut plants at three light levels and a constant air temperature. Measurements on these same plants were also conducted using a similarly modified Walz GFS-3000 gas exchange instrument to compare results. We found a positive linear correlation between F t , λ measurements from the modified LI-6800 and GFS-3000 instruments. We also report a positive linear relationship between F t , λ and normalized steady-state chlorophyll fluorescence (F t /F o ) from the pulse-amplitude modulation (PAM) fluorometer of the LI-6800 system. Accordingly, this modification will inform the link between spectrally resolved F t , λ and gas exchange-leading to improved interpretation of how remotely sensed SIF tracks changes in the light reactions of photosynthesis.

Differences in grapevine rootstock sensitivity and recovery from drought are linked to fine root cortical lacunae and root tip function.

Structural changes during severe drought stress greatly modify the hydraulic properties of fine roots. Yet, the physiological basis behind the restoration of fine root water uptake capacity during water recovery remains unknown. Using neutron radiography (NR), X-ray micro-computed tomography (micro-CT), fluorescence microscopy, and fine root hydraulic conductivity measurements (Lpr ), we examined how drought-induced changes in anatomy and hydraulic properties of contrasting grapevine rootstocks are coupled with fine root growth dynamics during drought and return of soil moisture. Lacunae formation in drought-stressed fine roots was associated with a significant decrease in fine root Lpr for both rootstocks. However, lacunae formation occurred under milder stress in the drought-resistant rootstock, 110R. Suberin was deposited at an earlier developmental stage in fine roots of 101-14Mgt (i.e. drought susceptible), probably limiting cortical lacunae formation during mild stress. During recovery, we found that only 110R fine roots showed rapid re-establishment of elongation and water uptake capacity and we found that soil water status surrounding root tips differed between rootstocks as imaged with NR. These data suggest that drought resistance in grapevine rootstocks is associated with rapid re-establishment of growth and Lpr near the root tip upon re-watering by limiting competing sites along the root cylinder.

Evapotranspiration partitioning assessment using a machine-learning-based leaf area index and the two-source energy balance model with sUAV information.

Accurate quantification of the partitioning of evapotranspiration (ET) into transpiration and evaporation fluxes is necessary to understanding ecosystem interactions among carbon, water, and energy flux components. ET partitioning can also support the description of atmosphere and land interactions and provide unique insights into vegetation water status. Previous studies have identified leaf area index (LAI) estimation as a key descriptor of biomass conditions needed for the estimation of transpiration and evaporation. LAI estimation in clumped vegetation systems, such as vineyards and orchards, has proven challenging and is strongly related to crop phenological status and canopy management. In this study, a feature extraction model based on previous research was built to generate a total of 202 preliminary variables at a 3.6-by-3.6-meter-grid scale based on submeter-resolution information from a small Unmanned Aerial Vehicle (sUAV) in four commercial vineyards across California. Using these variables, a machine learning model called eXtreme Gradient Boosting (XGBoost) was successfully built for LAI estimation. The XGBoost built-in function requires only six variables relating to vegetation indices and temperature to produce high-accuracy LAI estimation for the vineyard. Using the six-variable XGBoost-based LAI map, two versions of the Two-Source Energy Balance (TSEB) model, TSEB-PT and TSEB-2T were used for energy balance and ET partitioning. Comparing these results with the Eddy-Covariance (EC) tower data, showed that TSEB-PT outperforms TSEB-2T on the estimation of sensible heat flux (within 13% relative error) and surface heat flux (within 34% relative error), while TSEB-2T outperforms TSEB-PT on the estimation of net radiation (within 14% relative error) and latent heat flux (within 2% relative error). For the mature vineyard (north block), TSEB-2T performs better than TSEB-PT in partitioning the canopy latent heat flux with 6.8% relative error and soil latent heat flux with 21.7% relative error; however, for the younger vineyard (south block), TSEB-PT performs better than TSEB-2T in partitioning the canopy latent heat flux with 11.7% relative error and soil latent heat flux with 39.3% relative error.

Development of High Performance Computing Tools for Estimation of High-Resolution Surface Energy Balance Products Using sUAS Information.

sUAS (small-Unmanned Aircraft System) and advanced surface energy balance models allow detailed assessment and monitoring (at plant scale) of different (agricultural, urban, and natural) environments. Significant progress has been made in the understanding and modeling of atmosphere-plant-soil interactions and numerical quantification of the internal processes at plant scale. Similarly, progress has been made in ground truth information comparison and validation models. An example of this progress is the application of sUAS information using the Two-Source Surface Energy Balance (TSEB) model in commercial vineyards by the Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment - GRAPEX Project in California. With advances in frequent sUAS data collection for larger areas, sUAS information processing becomes computationally expensive on local computers. Additionally, fragmentation of different models and tools necessary to process the data and validate the results is a limiting factor. For example, in the referred GRAPEX project, commercial software (ArcGIS and MS Excel) and Python and Matlab code are needed to complete the analysis. There is a need to assess and integrate research conducted with sUAS and surface energy balance models in a sharing platform to be easily migrated to high performance computing (HPC) resources. This research, sponsored by the National Science Foundation FAIR Cyber Training Fellowships, is integrating disparate software and code under a unified language (Python). The Python code for estimating the surface energy fluxes using TSEB2T model as well as the EC footprint analysis code for ground truth information comparison were hosted in myGeoHub site https://mygeohub.org/ to be reproducible and replicable.

Xylella fastidiosa causes transcriptional shifts that precede tylose formation and starch depletion in xylem.

Pierce's disease (PD) in grapevine (Vitis vinifera) is caused by the bacterial pathogen Xylella fastidiosa. X. fastidiosa is limited to the xylem tissue and following infection induces extensive plant-derived xylem blockages, primarily in the form of tyloses. Tylose-mediated vessel occlusions are a hallmark of PD, particularly in susceptible V. vinifera. We temporally monitored tylose development over the course of the disease to link symptom severity to the level of tylose occlusion and the presence/absence of the bacterial pathogen at fine-scale resolution. The majority of vessels containing tyloses were devoid of bacterial cells, indicating that direct, localized perception of X. fastidiosa was not a primary cause of tylose formation. In addition, we used X-ray computed microtomography and machine-learning to determine that X. fastidiosa induces significant starch depletion in xylem ray parenchyma cells. This suggests that a signalling mechanism emanating from the vessels colonized by bacteria enables a systemic response to X. fastidiosa infection. To understand the transcriptional changes underlying these phenotypes, we integrated global transcriptomics into the phenotypes we tracked over the disease spectrum. Differential gene expression analysis revealed that considerable transcriptomic reprogramming occurred during early PD before symptom appearance. Specifically, we determined that many genes associated with tylose formation (ethylene signalling and cell wall biogenesis) and drought stress were up-regulated during both Phase I and Phase II of PD. On the contrary, several genes related to photosynthesis and carbon fixation were down-regulated during both phases. These responses correlate with significant starch depletion observed in ray cells and tylose synthesis in vessels.

Coordinated decline of leaf hydraulic and stomatal conductances under drought is not linked to leaf xylem embolism for different grapevine cultivars.

Drought decreases water transport capacity of leaves and limits gas exchange, which involves reduced leaf leaf hydraulic conductance (Kleaf) in both the xylem and outside-xylem pathways. Some literature suggests that grapevines are hyper-susceptible to drought-induced xylem embolism. We combined Kleaf and gas exchange measurements, micro-computed tomography of intact leaves, and spatially explicit modeling of the outside-xylem pathways to evaluate the role of vein embolism and Kleaf in the responses of two different grapevine cultivars to drought. Cabernet Sauvignon and Chardonnay exhibited similar vulnerabilities of Kleaf and gs to dehydration, decreasing substantially prior to leaf xylem embolism. Kleaf and gs decreased by 80% for both cultivars by Ψ leaf approximately -0.7 MPa and -1.2 MPa, respectively, while leaf xylem embolism initiated around Ψ leaf = -1.25 MPa in the midribs and little to no embolism was detected in minor veins even under severe dehydration for both cultivars. Modeling results indicated that reduced membrane permeability associated with a Casparian-like band in the leaf vein bundle sheath would explain declines in Kleaf of both cultivars. We conclude that during moderate water stress, changes in the outside-xylem pathways, rather than xylem embolism, are responsible for reduced Kleaf and gs. Understanding this mechanism could help to ensure adequate carbon capture and crop performance under drought.