Detection of Xylella fastidiosa in almond orchards by synergic use of an epidemic spread model and remotely sensed plant traits.

The early detection of Xylella fastidiosa (Xf) infections is critical to the management of this dangerous plan pathogen across the world. Recent studies with remote sensing (RS) sensors at different scales have shown that Xf-infected olive trees have distinct spectral features in the visible and infrared regions (VNIR). However, further work is needed to integrate remote sensing in the management of plant disease epidemics. Here, we research how the spectral changes picked up by different sets of RS plant traits (i.e., pigments, structural or leaf protein content), can help capture the spatial dynamics of Xf spread. We coupled a spatial spread model with the probability of Xf-infection predicted by a RS-driven support vector machine (RS-SVM) model. Furthermore, we analyzed which RS plant traits contribute most to the output of the prediction models. For that, in almond orchards affected by Xf (n = 1426 trees), we conducted a field campaign simultaneously with an airborne campaign to collect high-resolution thermal images and hyperspectral images in the visible-near-infrared (VNIR, 400-850 nm) and short-wave infrared regions (SWIR, 950-1700 nm). The best performing RS-SVM model (OA = 75%; kappa = 0.50) included as predictors leaf protein content, nitrogen indices (NIs), fluorescence and a thermal indicator (Tc), alongside pigments and structural parameters. Leaf protein content together with NIs contributed 28% to the explanatory power of the model, followed by chlorophyll (22%), structural parameters (LAI and LIDFa), and chlorophyll indicators of photosynthetic efficiency. Coupling the RS model with an epidemic spread model increased the accuracy (OA = 80%; kappa = 0.48). In the almond trees where the presence of Xf was assayed by qPCR (n = 318 trees), the combined RS-spread model yielded an OA of 71% and kappa = 0.33, which is higher than the RS-only model and visual inspections (both OA = 64-65% and kappa = 0.26-31). Our work demonstrates how combining spatial epidemiological models and remote sensing can lead to highly accurate predictions of plant disease spatial distribution.

Unveiling contextual realities by microscopically entangling a neutron.

The development of qualitatively new measurement capabilities is often a prerequisite for critical scientific and technological advances. Here we introduce an unconventional quantum probe, an entangled neutron beam, where individual neutrons can be entangled in spin, trajectory and energy. The spatial separation of trajectories from nanometers to microns and energy differences from peV to neV will enable investigations of microscopic magnetic correlations in systems with strongly entangled phases, such as those believed to emerge in unconventional superconductors. We develop an interferometer to prove entanglement of these distinguishable properties of the neutron beam by observing clear violations of both Clauser-Horne-Shimony-Holt and Mermin contextuality inequalities in the same experimental setup. Our work opens a pathway to a future of entangled neutron scattering in matter.

Addressing the New Global Threat of Xylella fastidiosa.

Xylella fastidiosa is one of the most important threats to plant health worldwide. This bacterial pathogen has a long history, causing disease in the Americas on a range of agricultural crops and trees, with severe economic repercussions particularly on grapevine and citrus. In Europe, X. fastidiosa was detected for the first time in 2013 in association with a severe disease affecting olive trees in southern Italy. Subsequent mandatory surveys throughout Europe led to discoveries in France and Spain in various host species and environments. Detection of additional introductions of X. fastidiosa continue to be reported from Europe, for example from northern Italy in late 2018. These events are leading to a sea change in research, monitoring and management efforts as exemplified by the articles in this Focus Issue . X. fastidiosa is part of complex pathosystems together with hosts and vectors. Although certain X. fastidiosa subspecies and environments have been well studied, particularly those that pertain to established disease in North and South America, this represents only a fraction of the existing genetic, epidemiological, and ecological diversity. This Focus Issue highlights some of the key challenges that must be overcome to address this new global threat, recent advances in understanding the pathosystem, and steps toward improved disease control. It brings together the broad research themes needed to address the global threat of X. fastidiosa, encompassing topics from host susceptibility and resistance, genome sequencing, detection methods, transmission by vectors, epidemiological drivers, chemical and biological control, to public databases and social sciences. Open communication and collaboration among scientists, stakeholders, and the general public from different parts of the world will pave the path to novel ideas to understand and combat this pathogen.

Time of flight modulation of intensity by zero effort on Larmor.

A time-of-flight modulation of intensity by zero effort spectrometer mode has been developed for the Larmor instrument at the ISIS pulsed neutron source. The instrument utilizes resonant spin flippers that employ electromagnets with pole shoes, allowing the flippers to operate at frequencies up to 3 MHz. Tests were conducted at modulation frequencies of 103 kHz, 413 kHz, 826 kHz, and 1.03 MHz, resulting in a Fourier time range of ∼0.1 ns to 30 ns using a wavelength band of 4 Å-11 Å.

The enduring impact of neurulation stage alcohol exposure: A combined behavioral and structural neuroimaging study in adult male and female C57BL/6J mice.

Prenatal alcohol exposure (PAE) can cause behavioral and brain alterations over the lifespan. In animal models, these effects can occur following PAE confined to critical developmental periods, equivalent to the third and fourth weeks of human gestation, before pregnancy is usually recognized. The current study focuses on PAE during early neurulation and examines the behavioral and brain structural consequences that appear in adulthood. On gestational day 8 C57BL/6J dams received two alcohol (2.8g/kg, i.p), or vehicle, administrations, four hours apart. Male and female offspring were reared to adulthood and examined for performance on the elevated plus maze, rotarod, open field, Morris water maze, acoustic startle, social preference (i.e. three-chambered social approach test), and the hot plate. A subset of these mice was later evaluated using magnetic resonance imaging to detect changes in regional brain volumes and shapes. In males, PAE increased exploratory behaviors on the elevated plus maze and in the open field; these changes were associated with increased fractional anisotropy in the anterior commissure. In females, PAE reduced social preference and the startle response, and decreased cerebral cortex and brain stem volumes. Vehicle-treated females had larger pituitaries than did vehicle-treated males, but PAE attenuated this sex difference. In males, pituitary size correlated with open field activity, while in females, pituitary size correlated with social activity. These findings indicate that early neurulation PAE causes sex specific behavioral and brain changes in adulthood. Changes in the pituitary suggest that this structure is especially vulnerable to neurulation stage PAE.

Acute alcohol exposure during neurulation: Behavioral and brain structural consequences in adolescent C57BL/6J mice.

Prenatal alcohol exposure (PAE) can induce physical malformations and behavioral abnormalities that depend in part on thedevelopmental timing of alcohol exposure. The current studies employed a mouse FASD model to characterize the long-term behavioral and brain structural consequences of a binge-like alcohol exposure during neurulation; a first-trimester stage when women are typically unaware that they are pregnant. Time-mated C57BL/6J female mice were administered two alcohol doses (2.8g/kg, four hours apart) or vehicle starting at gestational day 8.0. Male and female adolescent offspring (postnatal day 28-45) were then examined for motor activity (open field and elevated plus maze), coordination (rotarod), spatial learning and memory (Morris water maze), sensory motor gating (acoustic startle and prepulse inhibition), sociability (three-chambered social test), and nociceptive responses (hot plate). Regional brain volumes and shapes were determined using magnetic resonance imaging. In males, PAE increased activity on the elevated plus maze and reduced social novelty preference, while in females PAE increased exploratory behavior in the open field and transiently impaired rotarod performance. In both males and females, PAE modestly impaired Morris water maze performance and decreased the latency to respond on the hot plate. There were no brain volume differences; however, significant shape differences were found in the cerebellum, hypothalamus, striatum, and corpus callosum. These results demonstrate that alcohol exposure during neurulation can have functional consequences into adolescence, even in the absence of significant brain regional volumetric changes. However, PAE-induced regional shape changes provide evidence for persistent brain alterations and suggest alternative clinical diagnostic markers.

Compact spherical neutron polarimeter using high-T(c) YBCO films.

We describe a simple, compact device for spherical neutron polarimetry measurements at small neutron scattering angles. The device consists of a sample chamber with very low (<0.01 G) magnetic field flanked by regions within which the neutron polarization can be manipulated in a controlled manner. This allows any selected initial and final polarization direction of the neutrons to be obtained. We have constructed a prototype device using high-T(c) superconducting films and mu-metal to isolate regions with different magnetic fields and tested device performance in transmission geometry. Finite-element methods were used to simulate the device's field profile and these have been verified by experiment using a small solenoid as a test sample. Measurements are reported using both monochromatic and polychromatic neutron sources. The results show that the device is capable of extracting sample information and distinguishing small angular variations of the sample magnetic field. As a more realistic test, we present results on the characterization of a 10 µm thick Permalloy film in zero magnetic field, as well as its response to an external magnetic field.

Porosity of silica Stöber particles determined by spin-echo small angle neutron scattering.

Stöber silica particles are used in a diverse range of applications. Despite their widespread industrial and scientific uses, information on the internal structure of the particles is non-trivial to obtain and is not often reported. In this work we have used spin-echo small angle neutron scattering (SESANS) in conjunction with ultra small angle X-ray scattering (USAXS) and pycnometry to study an aqueous dispersion of Stöber particles. Our results are in agreement with models which propose that Stöber particles have a porous core, with a significant fraction of the pores inaccessible to solvent. For samples prepared from the same master sample in a range of H2O : D2O ratio solutions we were able to model the SESANS results for the solution series assuming monodisperse, smooth surfaced spheres of radius 83 nm with an internal open pore volume fraction of 32% and a closed pore fraction of 10%. Our results are consistent with USAXS measurements. The protocol developed and discussed here shows that the SESANS technique is a powerful way to investigate particles much larger than those studied using conventional small angle scattering methods.

Early detection surveillance for an emerging plant pathogen: a rule of thumb to predict prevalence at first discovery.

Emerging plant pathogens are a significant problem for conservation and food security. Surveillance is often instigated in an attempt to detect an invading epidemic before it gets out of control. Yet in practice many epidemics are not discovered until already at a high prevalence, partly due to a lack of quantitative understanding of how surveillance effort and the dynamics of an invading epidemic relate. We test a simple rule of thumb to determine, for a surveillance programme taking a fixed number of samples at regular intervals, the distribution of the prevalence an epidemic will have reached on first discovery (discovery-prevalence) and its expectation E(q*). We show that E(q*) = r/(N/Δ), i.e. simply the rate of epidemic growth divided by the rate of sampling; where r is the epidemic growth rate, N is the sample size and Δ is the time between sampling rounds. We demonstrate the robustness of this rule of thumb using spatio-temporal epidemic models as well as data from real epidemics. Our work supports the view that, for the purposes of early detection surveillance, simple models can provide useful insights in apparently complex systems. The insight can inform decisions on surveillance resource allocation in plant health and has potential applicability to invasive species generally.

Spin echo small angle neutron scattering using a continuously pumped (3)He neutron polarisation analyser.

We present a new instrument for spin echo small angle neutron scattering (SESANS) developed at the Low Energy Neutron Source at Indiana University. A description of the various instrument components is given along with the performance of these components. At the heart of the instrument are a series of resistive coils to encode the neutron trajectory into the neutron polarisation. These are shown to work well over a broad range of neutron wavelengths. Neutron polarisation analysis is accomplished using a continuously operating neutron spin filter polarised by Rb spin-exchange optical pumping of (3)He. We describe the performance of the analyser along with a study of the (3)He polarisation stability and its implications for SESANS measurements. Scattering from silica Stöber particles is investigated and agrees with samples run on similar instruments.

A generic risk-based surveying method for invading plant pathogens.

Invasive plant pathogens are increasing with international trade and travel, with damaging environmental and economic consequences. Recent examples include tree diseases such as sudden oak death in the Western United States and ash dieback in Europe. To control an invading pathogen it is crucial that newly infected sites are quickly detected so that measures can be implemented to control the epidemic. However, since sampling resources are often limited, not all locations can be inspected and locations must be prioritized for surveying. Existing approaches to achieve this are often species specific and rely on detailed data collection and parameterization, which is difficult, especially when new arrivals are unanticipated. Consequently regulatory sampling responses are often ad hoc and developed without due consideration of epidemiology, leading to the suboptimal deployment of expensive sampling resources. We introduce a flexible risk-based sampling method that is pathogen generic and enables available information to be utilized to develop epidemiologically informed sampling programs for virtually any biologically relevant plant pathogen. By targeting risk we aim to inform sampling schemes that identify high-impact locations that can be subsequently treated in order to reduce inoculum in the landscape. This "damage limitation" is often the initial management objective following the first discovery of a new invader. Risk at each location is determined by the product of the basic reproductive number (R0), as a measure of local epidemic size, and the probability of infection. We illustrate how the risk estimates can be used to prioritize a survey by weighting a random sample so that the highest-risk locations have the highest probability of selection. We demonstrate and test the method using a high-quality spatially and temporally resolved data set on Huanglongbing disease (HLB) in Florida, USA. We show that even when available epidemiological information is relatively minimal, the method has strong predictive value and can result in highly effective targeted surveying plans.

Superconducting magnetic Wollaston prism for neutron spin encoding.

A magnetic Wollaston prism can spatially split a polarized neutron beam into two beams with different neutron spin states, in a manner analogous to an optical Wollaston prism. Such a Wollaston prism can be used to encode the trajectory of neutrons into the Larmor phase associated with their spin degree of freedom. This encoding can be used for neutron phase-contrast radiography and in spin echo scattering angle measurement (SESAME). In this paper, we show that magnetic Wollaston prisms with highly uniform magnetic fields and low Larmor phase aberration can be constructed to preserve neutron polarization using high temperature superconducting (HTS) materials. The Meissner effect of HTS films is used to confine magnetic fields produced electromagnetically by current-carrying HTS tape wound on suitably shaped soft iron pole pieces. The device is cooled to ~30 K by a closed cycle refrigerator, eliminating the need to replenish liquid cryogens and greatly simplifying operation and maintenance. A HTS film ensures that the magnetic field transition within the prism is sharp, well-defined, and planar due to the Meissner effect. The spin transport efficiency across the device was measured to be ~98.5% independent of neutron wavelength and energizing current. The position-dependent Larmor phase of neutron spins was measured at the NIST Center for Neutron Research facility and found to agree well with detailed simulations. The phase varies linearly with horizontal position, as required, and the neutron beam shows little depolarization. Consequently, the device has advantages over existing devices with similar functionality and provides the capability for a large neutron beam (20 mm × 30 mm) and an increase in length scales accessible to SESAME to beyond 10 µm. With further improvements of the external coupling guide field in the prototype device, a larger neutron beam could be employed.

An improved regulatory sampling method for mapping and representing plant disease from a limited number of samples.

A key challenge for plant pathologists is to develop efficient methods to describe spatial patterns of disease spread accurately from a limited number of samples. Knowledge of disease spread is essential for informing and justifying plant disease management measures. A mechanistic modelling approach is adopted for disease mapping which is based on disease dispersal gradients and consideration of host pattern. The method is extended to provide measures of uncertainty for the estimates of disease at each host location. In addition, improvements have been made to increase computational efficiency by better initialising the disease status of unsampled hosts and speeding up the optimisation process of the model parameters. These improvements facilitate the practical use of the method by providing information on: (a) mechanisms of pathogen dispersal, (b) distance and pattern of disease spread, and (c) prediction of infection probabilities for unsampled hosts. Two data sets of disease observations, Huanglongbing (HLB) of citrus and strawberry powdery mildew, were used to evaluate the performance of the new method for disease mapping. The result showed that our method gave better estimates of precision for unsampled hosts, compared to both the original method and spatial interpolation. This enables decision makers to understand the spatial aspects of disease processes, and thus formulate regulatory actions accordingly to enhance disease control.

Estimating the incidence of an epidemic when it is first discovered and the design of early detection monitoring.

The early detection of an invading epidemic is crucial for successful disease control. Although models have been used extensively to test control strategies following the first detection of an epidemic, few studies have addressed the issue of how to achieve early detection in the first place. Moreover, sampling theory has made great progress in understanding how to estimate the incidence or spatial distribution of an epidemic but how to sample for early detection has been largely ignored. Using a simple epidemic model we demonstrate a method to calculate the incidence of an epidemic when it is discovered for the first time (given a monitoring programme taking samples at regular intervals). We use the method to explore how the intensity and frequency of sampling influences early detection. In particular, we find that for epidemics characterised by high population growth rates it is most effective to spread sampling resources evenly in time. In addition we derive a useful approximation to our method which results in a simple equation capturing the relation between monitoring and epidemic dynamics. Not only does this provide valuable new insight but it provides a simple rule of thumb for the design of monitoring programmes in practice.

A stochastic optimization method to estimate the spatial distribution of a pathogen from a sample.

Information on the spatial distribution of plant disease can be utilized to implement efficient and spatially targeted disease management interventions. We present a pathogen-generic method to estimate the spatial distribution of a plant pathogen using a stochastic optimization process which is epidemiologically motivated. Based on an initial sample, the method simulates the individual spread processes of a pathogen between patches of host to generate optimized spatial distribution maps. The method was tested on data sets of Huanglongbing of citrus and was compared with a kriging method from the field of geostatistics using the well-established kappa statistic to quantify map accuracy. Our method produced accurate maps of disease distribution with kappa values as high as 0.46 and was able to outperform the kriging method across a range of sample sizes based on the kappa statistic. As expected, map accuracy improved with sample size but there was a high amount of variation between different random sample placements (i.e., the spatial distribution of samples). This highlights the importance of sample placement on the ability to estimate the spatial distribution of a plant pathogen and we thus conclude that further research into sampling design and its effect on the ability to estimate disease distribution is necessary.

Some consequences of using the Horsfall-Barratt scale for hypothesis testing.

Comparing treatment effects by hypothesis testing is a common practice in plant pathology. Nearest percent estimates (NPEs) of disease severity were compared with Horsfall-Barratt (H-B) scale data to explore whether there was an effect of assessment method on hypothesis testing. A simulation model based on field-collected data using leaves with disease severity of 0 to 60% was used; the relationship between NPEs and actual severity was linear, a hyperbolic function described the relationship between the standard deviation of the rater mean NPE and actual disease, and a lognormal distribution was assumed to describe the frequency of NPEs of specific actual disease severities by raters. Results of the simulation showed standard deviations of mean NPEs were consistently similar to the original rater standard deviation from the field-collected data; however, the standard deviations of the H-B scale data deviated from that of the original rater standard deviation, particularly at 20 to 50% severity, over which H-B scale grade intervals are widest; thus, it is over this range that differences in hypothesis testing are most likely to occur. To explore this, two normally distributed, hypothetical severity populations were compared using a t test with NPEs and H-B midpoint data. NPE data had a higher probability to reject the null hypothesis (H0) when H0 was false but greater sample size increased the probability to reject H0 for both methods, with the H-B scale data requiring up to a 50% greater sample size to attain the same probability to reject the H0 as NPEs when H0 was false. The increase in sample size resolves the increased sample variance caused by inaccurate individual estimates due to H-B scale midpoint scaling. As expected, various population characteristics influenced the probability to reject H0, including the difference between the two severity distribution means, their variability, and the ability of the raters. Inaccurate raters showed a similar probability to reject H0 when H0 was false using either assessment method but average and accurate raters had a greater probability to reject H0 when H0 was false using NPEs compared with H-B scale data. Accurate raters had, on average, better resolving power for estimating disease compared with that offered by the H-B scale and, therefore, the resulting sample variability was more representative of the population when sample size was limiting. Thus, there are various circumstances under which H-B scale data has a greater risk of failing to reject H0 when H0 is false (a type II error) compared with NPEs.

The effect of landscape pattern on the optimal eradication zone of an invading epidemic.

A number of high profile eradication attempts on plant pathogens have recently been attempted in response to the increasing number of introductions of economically significant nonnative pathogen species. Eradication programs involve the removal of a large proportion of a host population and can thus lead to significant social and economic costs. In this paper we use a spatially explicit stochastic model to simulate an invading pathogen and show that it is possible to identify an optimal control radius, i.e., one that minimizes the total number of hosts removed during an eradication campaign that is effective in eradicating the pathogen. However, by simulating the epidemic and eradication processes in multiple landscapes, we demonstrate that the optimal radius depends critically on landscape pattern (i.e., the spatial configuration of hosts within the landscape). In particular, we find that the optimal radius, and also the number of host removals associated with it, increases with both the level of aggregation and the density of hosts in the landscape. The result is of practical significance and demonstrates that the location of an invading epidemic should be a key consideration in the design of future eradication strategies.

Experimental investigation and numerical simulation of 3He gas diffusion in simple geometries: implications for analytical models of 3He MR lung morphometry.

Models of lung acinar geometry have been proposed to analytically describe the diffusion of (3)He in the lung (as measured with pulsed gradient spin echo (PGSE) methods) as a possible means of characterizing lung microstructure from measurement of the (3)He ADC. In this work, major limitations in these analytical models are highlighted in simple diffusion weighted experiments with (3)He in cylindrical models of known geometry. The findings are substantiated with numerical simulations based on the same geometry using finite difference representation of the Bloch-Torrey equation. The validity of the existing "cylinder model" is discussed in terms of the physical diffusion regimes experienced and the basic reliance of the cylinder model and other ADC-based approaches on a Gaussian diffusion behaviour is highlighted. The results presented here demonstrate that physical assumptions of the cylinder model are not valid for large diffusion gradient strengths (above approximately 15 mT/m), which are commonly used for (3)He ADC measurements in human lungs.

Optimal strategies for the eradication of asiatic citrus canker in heterogeneous host landscapes.

ABSTRACT The eradication of nonnative plant pathogens is a key challenge in plant disease epidemiology. Asiatic citrus canker is an economically significant disease of citrus caused by the bacterial plant pathogen Xanthomonas citri subsp. citri. The pathogen is a major exotic disease problem in many citrus producing areas of the world including the United States, Brazil, and Australia. Various eradication attempts have been made on the disease but have been associated with significant social and economic costs due to the necessary removal of large numbers of host trees. In this paper, a spatially explicit stochastic simulation model of Asiatic citrus canker is introduced that describes an epidemic of the disease in a heterogeneous host landscape. We show that an optimum eradication strategy can be determined that minimizes the adverse costs associated with eradication. In particular, we show how the optimum strategy and its total cost depend on the topological arrangement of the host landscape. We discuss the implications of the results for invading plant disease epidemics in general and for historical and future eradication attempts on Asiatic citrus canker.

Large-scale fungicide spray heterogeneity and the regional spread of resistant pathogen strains.

ABSTRACT Most models for the spread of fungicide resistance in plant pathogens are focused on within-field dynamics, yet regional invasion depends upon the interactions between field populations. Here, we use a spatially implicit metapopulation model to describe the dynamics of regional spread, in which subpopulations correspond to single fields. We show that the criterion for the regional invasion of pathogens between fields differs from that for invasion within fields. That is, the ability of a fungicide-resistant strain of a pathogen to invade a field population does not necessarily imply an ability to spread through many fields at the regional scale. This depends upon an interaction between the fraction of fields that is sprayed and the reproductive capacity of the pathogen. This result is of practical significance and indicates that resistance management strategies which currently target within-field processes, such as the use of mixtures and alternations of fungicides, may be more effective if between-field processes also were targeted; for example, through the restricted deployment of fungicides over large areas. We also show that the fraction of disease-free fields is maximized when the proportion of fields that is sprayed is just below the threshold for invasion of the resistant strain.