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Development and Validation of a Mechanistic, Weather-Based Model for Walnut Blight Caused by Xanthomonas arboricola pv. juglandis
Abstract
Walnut blight, caused by Xanthomonas arboricola pv. juglandis (Xaj), occurs worldwide in almost all areas where the Persian walnut (Juglans regia) is grown, causing significant reductions in nut yield via defoliation and fruit drop. The disease control relies on the calendar-based, repeated use of chemical bactericides, negatively impacting economic and environmental sustainability and potentially inducing Xaj resistance to chemicals. This study developed and validated a mechanistic model incorporating the main stages of the pathogen’s life cycle and the influence of weather under orchard conditions to improve the scheduling of disease control interventions. The model can simulate: i) the mobilization of primary inoculum; ii) the infection caused by bacteria; and iii) the lesion formation and production of secondary inoculum. We evaluated the model against 21 independent walnut blight epidemics in Italy (nine epidemics on leaves in five orchards) and the USA (12 epidemics on fruit in six orchards). Overall, the model provided accurate predictions for both the occurrence and non-occurrence of infection, with a precision and F1-score of 0.866 and 0.844, respectively. The model could accurately predict disease progression across the season, with a concordance correlation coefficient between observed and predicted disease severities of 0.951, a root mean square error of 0.069, and a coefficient of residual mass of 0.024. After further validation, the model can serve as a decision-making tool for the risk-based timing of chemical sprays in walnut blight management.
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Bacterial blight, caused by Xanthomonas arboricola pv. juglandis, is a significant disease affecting walnut production worldwide. Outbreaks are most severe in spring, and closely tied to host phenology and weather conditions. Pathogen infections are mainly observed in catkins, female flowers, leaves, and fruits. In this study, the effect of wetness duration and temperature on walnut infections by X. arboricola pv. juglandis was determined through two independent experiments conducted under controlled environmental conditions. The combined effect of both climatic parameters on disease severity was quantified using a third-order polynomial equation. The model obtained by linear regression and backward elimination technique fitted well to the data (R2 = 0.94 and R2adj = 0.93). The predictive capacity of the forecasting model was evaluated on pathogen-inoculated walnut plants exposed to different wetness duration–temperature combinations under Mediterranean field conditions. Observed disease severity in all events aligned with predicted infection risk. Additionally, the relationship between leaf and fruit age and the disease severity was quantified and modelled. A prediction model, which has been referred to as the WalBlight-risk model, is proposed for evaluation as an advisory system for timing bactericide sprays to manage bacterial blight in Mediterranean walnut orchards.
Fungi in the genus Colletotrichum cause serious pre- and post-harvest losses to several agricultural crops worldwide. Through a systematic literature review, we retrieved the published information on Colletotrichum anthracnose diseases on different host plants and developed a mechanistic model incorporating the main stages of the pathogen’s life cycle and the effect of weather. The model predicts anthracnose progress during the growing season on the aerial organs of different crops, and was parameterized for seven Colletotrichum clades (acutatum, dematium, destructivum, gloeosporioides, graminicola, and orbiculare) and the singleton species, C. coccodes. The model was evaluated for the anthracnose diseases caused by fungi belonging to five clades on six hosts by using data from 17 epidemics that occurred in Italy, the USA, Canada, and Japan. A comparison of observed versus predicted data showed a concordance correlation coefficient of 0.928 and an average distance between real data and the fitted line of 0.044. After further validation, the model could be used to support decision-making for crop protection.
Stem rust (or black rust) of wheat, caused by Puccinia graminis f. sp. tritici (Pgt), is a re-emerging, major threat to wheat production worldwide. Here, we retrieved, analyzed, and synthetized the available information about Pgt to develop a mechanistic, weather-driven model for predicting stem rust epidemics caused by uredospores. The ability of the model to predict the first infections in a season was evaluated using field data collected in three wheat-growing areas of Italy (Emilia-Romagna, Apulia, and Sardinia) from 2016 to 2021. The model showed good accuracy, with a posterior probability to correctly predict infections of 0.78 and a probability that there was no infection when not predicted of 0.96. The model’s ability to predict disease progress during the growing season was also evaluated by using published data obtained from trials in Minnesota, United States, in 1968, 1978, and 1979, and in Pennsylvania, United States, in 1986. Comparison of observed versus predicted data generated a concordance correlation coefficient of 0.96 and an average distance between real data and the fitted line of 0.09. The model could therefore be considered accurate and reliable for predicting epidemics of wheat stem rust and could be tested for its ability to support risk-based control of the disease.
Greenhouse Cucumber Canopy Condensation Leaf wetness duration (LWD) provides the necessary conditions for pathogen infection. Among them, dew condensation on the crop canopy due to high humidity in a greenhouse is a major cause of LWD formation. However, it would be costly to monitor the condensation of all the leaves in a greenhouse. A computational fluid dynamics model was studied for the spatial and temporal distribution of the indoor microclimate and leaf condensation in a single-slope Chinese solar greenhouse at night. Models were embedded to simplify the input parameters and enhance the practicality. Without compromising the performance of the model, the model inputs were reduced to five: outdoor solar radiation intensity, outdoor air temperature, outdoor relative humidity, outdoor average wind speed per hour, and soil temperature. The distributions of roof condensation and leaf condensation were simulated. Condensation always appeared first on the roof rather than on the leaves. The leaf condensation results were manually observed for comparison with the simulated results. Leaf condensation always occurred first in the area near the semi-transparent roof, both in the observations and the simulation. The LWD was simulated by considering the duration of the simulated leaf condensation at each point. The evaluation was conducted on 216 pairs of samples. The True Negative Rate (TNR), True Positive Rate (TPR), and Accuracy (ACC) were 1, 0.66, and 0.89, respectively. This paper can serve as a reference for an early warning model of disease based on the temporal and spatial distribution of leaf condensation.
Background:
The species Xanthomonas arboricola comprises up to nine pathovars, two of which affect nut crops: pv. juglandis, the causal agent of walnut bacterial blight, brown apical necrosis, and the vertical oozing canker of Persian (English) walnut; and pv. corylina, the causal agent of the bacterial blight of hazelnut. Both pathovars share a complex population structure, represented by different clusters and several clades. Here we describe our current understanding of symptomatology, population dynamics, epidemiology, and disease control.
Taxonomic status:
Bacteria; Phylum Proteobacteria; Class Gammaproteobacteria; Order Lysobacterales (earlier synonym of Xanthomonadales); Family Lysobacteraceae (earlier synonym of Xanthomonadaceae); Genus Xanthomonas; Species X. arboricola; Pathovars: pv. juglandis and pv. corylina.
Host range and symptoms:
The host range of each pathovar is not limited to a single species, but each infects mainly one plant species: Juglans regia (X. arboricola pv. juglandis) and Corylus avellana (X. arboricola. pv. corylina). Walnut bacterial blight is characterized by lesions on leaves and fruits, and cankers on twigs, branches, and trunks; brown apical necrosis symptoms consist of apical necrosis originating at the stigmatic end of the fruit. A peculiar symptom, the vertical oozing canker developing along the trunk, is elicited by a particular genetic lineage of the bacterium. Symptoms of hazelnut bacterial blight are visible on leaves and fruits as necrotic lesions, and on woody parts as cankers. A remarkable difference is that affected walnuts drop abundantly, whereas hazelnuts with symptoms do not.
Distribution:
Bacterial blight of walnut has a worldwide distribution, wherever Persian (English) walnut is cultivated; the bacterial blight of hazelnut has a more limited distribution, although disease outbreaks are currently more frequently reported. X. arboricola pv. juglandis is regulated almost nowhere, whereas X. arboricola pv. corylina is regulated in most European and Mediterranean Plant Protection Organization (EPPO) countries.
Epidemiology and control:
For both pathogens infected nursery material is the main pathway for their introduction and spread into newly cultivated areas; additionally, infected nursery material is the source of primary inoculum. X. arboricola pv. juglandis is also disseminated through pollen. Disease control is achieved through the phytosanitary certification of nursery material (hazelnut), although approved certification schemes are not currently available. Once the disease is present in walnut/hazelnut groves, copper compounds are widely used, mostly in association with dithiocarbamates; where allowed, antibiotics (preferably kasugamycin) are sprayed. The emergence of strains highly resistant to copper currently represents the major threat for effective management of the bacterial blight of walnut. USEFUL WEBSITES: https://gd.eppo.int/taxon/XANTJU, https://gd.eppo.int/taxon/XANTCY, https://www.euroxanth.eu, http://www.xanthomonas.org.
The rational control of harmful organisms for plants (pests) forms the basis of the integrated pest management (IPM), and is fundamental for ensuring agricultural productivity while maintaining economic and environmental sustainability. The high level of complexity of the decision processes linked to IPM requires careful evaluations, both economic and environmental, considering benefits and costs associated with a management action. Plant protection models and other decision tools (DTs) have assumed a key role in supporting decision-making process in pest management. The advantages of using DTs in IPM are linked to their capacity to process and analyze complex information and to provide outputs supporting the decision-making process. Nowadays, several DTs have been developed, tackling different issues, and have been applied in different climatic conditions and agricultural contexts. However, their use in crop management is restricted to only certain areas and/or to a limited group of users. In this paper, we review the current state-of-the-art related to DTs for IPM, investigate the main modelling approaches used, and the different fields of application. We also identify key drivers influencing their adoption and provide a set of critical success factors to guide the development and facilitate the adoption of DTs in crop protection.
Stone fruit, almond and walnut are among the most important woody crops worldwide. Xanthomonas arboricola causes severe damages on these plants with losses worth millions of US dollars annually. The European Union phytosanitary legislation (EU Directive 2000/29/CE) and the European and Mediterranean Plant Protection Organizations included plant-pathogenic X. arboricola pv. pruni, a cause of diseases on Prunus spp., in the A2 list of quarantine microorganisms. Because of the economic importance of the diseases it causes and the pathogen regulatory status, X. arboricola has created concern in recent years. Despite a high similarity in the biology and epidemiology of X. arboricola and the diseases it causes on stone fruit, almond and walnut, the literature on this bacterial species is fragmentary and restricted to the pathovar level. This review of the literature summarizes main aspects of X. arboricola and its pathogenesis on these species. Specific topics include: taxonomy, disease symptoms, epidemiology, pathogen diversity, the molecular basis of the pathogenesis, recent efforts on breeding for resistance and possible approaches to disease management.
Epidemiology involves the study of the temporal, spatial, and spatio-temporal dynamics of disease in populations, and the utilization of results of experiments and surveys to describe, understand, compare, and predict epidemics. Such understanding and description of epidemics can lead directly to the development and evaluation of efficient control strategies and tactics. Mathematical and statistical models are key tools of the epidemiologist. Recent advances in statistics, including linear and nonlinear mixed models, are allowing a more appropriate matching of data type and experimental (or survey) design to the statistical model used for analysis, in order to meet the objectives of the investigator. Coupled ordinary and partial differential equations, as well as simpler growth-curve equations, are especially useful deterministic models for representing plant disease development in fields in time and space over single seasons or many years, and their use can lead to appraisal of control strategies through metrics such as the basic reproduction number, a summary parameter that may be calculated for many general epidemic scenarios. Recently, compelling arguments have been made for the use of Bayesian decision theory in developing and evaluating real-time disease prediction rules, based on measured disease or weather conditions and either empirical or mechanistic models for disease or control intervention. Through some simple calculations of predictor accuracy and (prior) probability of an epidemic (or the need for control), the success of any predictor can be quantified in terms of the estimated probability of random observations being epidemics when predicted to be epidemics or not epidemics. Overall, despite the many contributions in epidemiology over the past four decades, more effort is still needed to convince those outside of epidemiology to more fully use epidemiological results and insights into the development and evaluation of disease controls.
ABSTRACT Knowledge of the distribution of diseased plant units (such as leaves, plants, or roots) or of the relationship between the variance and mean incidence is essential to efficiently sample for diseased plant units. Cluster sampling, consisting of N sampling units of n individuals each, is needed to determine whether the binomial or beta-binomial distribution describes the data or to estimate parameters of the binary power law for disease incidence. The precision of estimated disease incidence can then be evaluated under a wide range of settings including the hierarchical sampling of groups of individuals, the various levels of spatial heterogeneity of disease, and the situation when all individuals are disease free. Precision, quantified with the standard error or the width of the confidence interval for incidence, is directly related to N and inversely related to the degree of heterogeneity (characterized by the intracluster correlation, rho). Based on direct estimates of rho (determined from the theta parameter of the beta-binomial distribution or from the observed variance) or a model predicting rho as a function of incidence (derived from the binary power law), one can calculate, before a sampling bout, the value of N needed to achieve a desired level of precision. The value of N can also be determined during a sampling bout using sequential sampling methods, either to estimate incidence with desired precision or to test a hypothesis about true disease incidence. In the latter case, the sequential probability ratio test is shown here to be useful for classifying incidence relative to a hypothesized threshold when the data follows the beta-binomial distribution with either a fixed rho or a rho that depends on incidence.
Copper-resistant strains of Xanthomonas campestris pv. juglandis occur in walnut orchards throughout northern California. The copper resistance genes from a copper-resistant strain C5 of X. campestris pv. juglandis were cloned and located on a 4.9-kb ClaI fragment, which hybridized only to DNA of copper-resistant strains of X. campestris pv. juglandis, and was part of an approximately 20-kb region which was conserved among such strains of X. campestris pv. juglandis. Hybridization analysis indicated that the copper resistance genes were located on the chromosome. Plasmids conferring copper resistance were not detected in copper-resistant strains, nor did mating with copper-sensitive strains result in copper-resistant transconjugants. Copper resistance genes from X. campestris pv. juglandis shared nucleotide sequence similarity with copper resistance genes from Pseudomonas syringae pv. tomato, P. syringae, and X. campestris pv. vesicatoria. DNA sequence analysis of the 4.9-kb fragment from strain C5 revealed that the sequence had an overall G+C content of 58.7%, and four open reading frames (ORF1 to ORF4), oriented in the same direction. All four ORFs were required for full expression of copper resistance, on the basis of Tn3-spice insertional inactivation and deletion analysis. The predicted amino acid sequences of ORF1 to ORF4 showed 65, 45, 47, and 40% identity with CopA, CopB, CopC, and CopD, respectively, from P. syringae pv. tomato. The most conserved regions are ORF1 and CopA and the C-terminal region (166 amino acids from the C terminus) of ORF2 and CopB. The hydrophobicity profiles of each pair of predicted polypeptides are similar except for the N terminus of ORF2 and CopB. Four histidine-rich polypeptide regions in ORF1 and CopA strongly resembled the copper-binding motifs of small blue copper proteins and multicopper oxidases, such as fungal laccases, plant ascorbate oxidase, and human ceruloplasmin. Putative copper ligands of the ORF1 polypeptide product are proposed, indicating that the polypeptide of ORF1 might bind four copper ions: one type 1, one type 2, and two type 3.
Walnut blight (WB), caused by the bacterium Xanthomonas arboricola pv. juglandis,continues to be a serious disease of walnut in northern China, where weather conditions favor disease development. From 2013 to 2017, WB incidences in walnut cv. ‘Liaoning 1’ were investigated in three areas (Dalian,Suizhong and Jianchang areas) in the Liaoning province, northeastern China. WB incidence was high in Dalian (23.72%) and Suizhong (24.31%) but was low in Jianchang (12.98%). Relative humidity is a key meteorological factor that affected the differences between areas. Ten walnut cultivars were surveyed in 2013, 2015, and 2017 for their susceptibility to blight. Lateral-bearing walnut cultivars showed a higher incidence and were found more susceptible to WB compared with terminal-bearing cultivars. In order to test the most effective chemical spray methods, bactericide screening trials were conducted comprising 12 different types of bactericides and mixtures in 2015. The combination of kasugamycin+mancozeb was most effective in controlling WB incidence resulting in lowest fruit disease incidence (2.63%). Subsequently, minimal spray trials were studied to determine the most effective chemical control as well as timing and frequency of application in 2017. The study confirmed these results of studies done in California: the best timing for the first spray application was at 30%–40% pistillate flower emergence and subsequently spray times were at 6 days and 16 days interval. Results of this study provide essential information to better understand the complexity of this walnut disease toward developing effective control management strategies globally.
The ecology of Xanthomonas involves the mutual relationships of the bacterium with biotic and abiotic environments. Increase, stationary and decline phases of growth of the bacterium result from the relationships. Special environmental conditions are also involved in the epidemiology of the bacterium. The purpose of this chapter is to review the interaction of Xanthomonas with various environmental factors.
Four years of surveying walnut blight and the causal pathogen in Tehama County California (Ca.) and three years in Butte County (Ca.) revealed a linkage of a history of Xanthomonas arboricola pv. juglandis populations in orchards with current season disease and temporal dynamics explained by differences in disease control measures. In the Tehama County (Ca.) orchards, walnut blight control has been very good and aggressive spray programs are maintaining bud pathogen populations at low levels. In the Butte County (Ca.) locations, although there are only three years of data, less effective spray programs have allowed disease damage and the initial inoculum overwintering in dormant buds to increase. The incidence of walnut blight damage differed greatly between different trees in a linear transect through a 'Vina' orchard and disease was strongly related to the population of pathogen in the developing buds, suggesting that the disease history of individual trees also varies, and is predictive of the risk of disease on those trees and that spatial segregation of disease occurs within an orchard. Assessments of the population sizes of the pathogen in dormant buds is thus a good predictor of the risk of walnut blight in a given year since the walnut buds are the primary source of initial inoculum that can spread to susceptible leaf and nut tissues after they open.
Brown apical necrosis (BAN) is a most recently described disease affecting English (Persian) walnut fruit. BAN was only recorded in intensively managed walnut orchards and was found to be a disease complex mainly caused by Fusarium species. All fungi associated with this disease are polyphagous and ubiquitous, not specific to walnut. Consequently, BAN occurrence is more strictly dependent, than generally, on the interaction between pathological features and environmental conditions. Environmental variables identified with regression analysis showed that maximum temperature, angle of main wind direction vs tree row orientation, and orchard distance to the closest river/canal, all representative of climatic conditions occurring in the orchard, were related to fruit drop. The factor displaying the highest influence on severity of BAN fruit drop was maximum temperature and only subordinately factors are associated with relative humidity. BAN symptoms were reproduced with in planta artificial inoculation, and fruit drop of symptomatic fruit was significantly higher than that of the non-inoculated trees for each type of inoculum (Fusarium semitectum, F. graminearum, and Alternaria spp.). F. semitectum and F. graminearum were more aggressive than Alternaria species, and the earliest artificial inoculations in mid-May resulted in the highest fruit drop. The extension of walnut fruit susceptibility and the conducive environmental factors to BAN are discussed.
Policy makers and researchers need to develop long-term priorities using reliable, quantitative tools to assess the risks associated with plant diseases over a range of plant pathogens and over space. EPIWHEAT is a generic simulation model designed to analyse potential disease epidemics in wheat, i.e., epidemics that depend only on the physical environment, and that are not constrained by any disease control. The model is developed on a core structure involving healthy, latent, infectious, and removed sites, and accounts for lesion expansion. It simulates in a simple way host dynamics (growth and senescence). The model involves as few parameters as possible, and a few driving functions. Here, EPIWHEAT is populated with parameters for brown rust (leaf rust; Puccinia triticina) and Septoria tritici blotch (Zymoseptoria tritici). Simulated epidemics are compared to observations at the field, national (France), and European scales. The model appears to represent a sound basis for predicting potential epidemics of wheat foliar diseases at large scales. Areas for model development are documented and discussed. EPIWHEAT appears to provide a simple, generic, transparent, flexible, and reliable platform to modelling potential epidemics caused by leaf pathogens of wheat.
The available knowledge on black-rot of grape was retrieved from literature, analyzed, and synthesized to develop a mechanistic model of the life cycle of the pathogen (Guignardia bidwelii) based on the systems analysis. Three life-cycle compartments were defined: (i) production and maturation of inoculum in overwintered sources (i.e., ascospores from pseudothecia and conidia from pycnidia in berry mummies and cane lesions); (ii) infection caused by ascospores and conidia; and (iii) disease onset and production of secondary inoculum. An analysis of published, quantitative information was conducted to develop a mechanistic model driven by weather and vine phenology; equations were developed for ascospore and conidial maturation in overwintered fruiting bodies, spore release and survival, infection occurrence and severity, incubation and latency periods, onset of lesions, production of pycnidia, and infectious periods. The model was then evaluated for its ability to represent the real system and its usefulness for understanding black-rot epidemics by using three typical epidemics. Finally, weaknesses in our knowledge are discussed. Additional research is needed concerning the influence of wetness duration and temperature on infection by ascospores, production dynamics of pycnidia and conidia in black-rot lesions, and the dynamics of conidia exudation from pycnidia.
ABSTRACT The potential role of walnut buds as a driver of walnut blight disease, caused by Xanthomonas arboricola pv. juglandis, was addressed by quantifying its temporal dynamics in a large number of orchards in California. The abundance of X. arboricola pv. juglandis on individual dormant and developing buds and shoots of walnut trees varied by >10(6)-fold at any sample time and within a given tree. X. arboricola pv. juglandis population size in shoots was often no larger than that in the buds from which the shoots were derived but was strongly correlated with prior pathogen population sizes in buds. X. arboricola pv. juglandis populations on developing nuts were strongly related to that on the shoots on which they were borne. The incidence of disease of nuts in June was strongly correlated with the logarithm of the population size of X. arboricola pv. juglandis in dormant buds in March. Inoculum efficiency, the slope of this linear relationship, varied between years but was strongly related to the number of rain events following bud break in each year. Thus, inoculum of X. arboricola pv. juglandis present on dormant buds is the primary determinant of nut infections and the risk of disease can be predicted from both the numbers of X. arboricola pv. juglandis in buds and the incidence of early spring rain.
Walnut blight, caused by Xanthomonas arboricola pv. juglandis, is present in all walnut growing regions of Australia, and has been responsible for significant losses of walnut fruits in Tasmania. The pathogen has been isolated from buds just prior to bud-burst in Tasmania, and disease symptoms on fruit of introduced cultivars of Juglans regia are similar to those observed in other growing regions of the world. This review focuses on the approach taken to model disease progression and describes how these models can help interpret the effi-cacy of spray programs, identify key factors influencing epidemic development and build tools for supporting decisions about spray timing. Considerable differences in the temporal progression of disease incidence on cvs Franquette and Vina fruits were found between three growing years in Tasmania, with incidences near harvest ranging from 19 to 100%. Final disease incidence was correlated positively to the quantity of rainfall during the first 4 weeks after bud-burst. Disease incidence was then used for modelling these epidemics because inci-dence on half full-size diameter fruit accounted for 97% of the variance in yield of Vina walnuts. The monomole-cular growth model with K = 1 obtained a good fit for the ten epidemics analysed. In a dry year, two sprays of copper-based biocide (300 g/kg of copper hydroxide formulated with 150 g/kg mancozeb) applied one week apart from 5% terminal bud-burst provided commer-cially acceptable control whereas up to nine sprays in a wetter year failed to control this disease. It was conclud-ed that copper-based biocides could be timed strategi-cally and according to the slow rate of disease develop-ment in drier years.
Walnut blight, caused by Xanthomonas arboricola pr. juglandis, is currently controlled in western Europe through a standard schedule of seven applications of sprayed copper from bud break until harvest. A reduced spray schedule, with the last four applications omitted, was compared to the standard program in experimental plots for 3 years. Bacterial population levels in the spring were not significantly different between trees subjected to reduced sprays and those subjected to the standard schedule, but in summer they were higher in the trees that received fewer sprays compared with the standard program. However, disease control on nuts was similar or even better with the reduced spraying program than with the standard program, with the additional economic benefit of four fewer copper applications. After 3 years of using the reduced spray program, the amount of copper accumulated in the soil was significantly lower (about half) than that found in the soil where the standard spray program was implemented.
A dynamic model for Plasmopara viticola primary infections on grapevine was elaborated according to a mechanistic approach. Development of the sexual stage of the pathogen was split into different state variables, in which changes from one state to another were regulated by rates depending on environmental conditions. The conceptual model was based on the definition of a primary inoculum season, a seasonal oospore (inoculum) dose, and its division into many coeval cohorts. Each cohort progresses along the primary infection cycle (production and survival of sporangia, release, survival and dispersal of zoospores, infection, appearance of disease symptoms) simultaneously, with a time step of one hour. The model was evaluated over a 12-year period (1995–2006) in Emilia-Romagna (Northern Italy) by comparing simulations with actual observations of the first seasonal symptoms of downy mildew in 43 vineyards. This data set was not used in model building and represents different environmental conditions, with both early and late primary infections. The model showed high sensitivity, specificity and accuracy. The achieved probabilities that an oospore cohort produce or not an infection were 0.994 and 0.999, respectively, while there was practically no probability that an oospore cohort produce infection when infection is not predicted by the model. Because of a small probability (
Plasmopara viticola, the causal agent of grapevine downy mildew, requires fungicide treatments to avoid severe yield losses, so epidemiological models have been elaborated to better manage fungicide scheduling. Primary oosporic inoculum plays a key role in epidemic development, and some of these models have been elaborated following an empirical approach to define quantitative relationships between occurrences of primary infections and weather factors influencing them. Recently, a mechanistic dynamic model was elaborated which accounts for the biological effects of weather on the different stages of the primary infection chain, from the progressive breaking of dormancy in the overwintering oospore population to infection establishment. In this work, three widely used models (3–10 rule, EPI and DMCast) were compared with this model (named UCSC model) on the basis of their theoretical approaches and their accuracy was tested against real data collected over a 9-year period in Sardinia (Italy). The two empirical models, 3–10 and EPI, seem to be too over-simplified to simulate correctly a complex biological phenomenon such as the sexual stage of P. viticola they lack consideration of some key stages of the infection chain and simultaneously simulate various biological events, each of which are influenced by specific weather conditions. EPI, in particular, needs specific calibrations and ongoing processes of adaptation that make its use in disease warning difficult. DMCast overcomes these problems because of its mechanistic approach; nevertheless, the empirical method used to model oospore maturation requires validations and, as in the present case, modifications before practical use. The UCSC model, due to its fully mechanistic approach, does not present this problem and provides accurate dynamic simulations of the sexual stage of P. viticola, with a high degree of detail and requiring neither calibrations nor corrections.
Bacterial blight is considered one of the most serious diseases affecting the genus Juglans. Artificial inoculations with Xanthomonas campestris pv. Juglandis were performed in the field by spraying seedlings of Juglans cinerea, Juglans hindsii, Juglans mandshurica, Juglans nigra, Juglans regia and Juglans sieboldiana. Juglans nigra, J. cinerea ana J. sieboldiana proved to be the most resistant. The multiplication ability of Xanthomonas campestris pv. corylina, X. c. pv. juglandis, and X. c. pv. campestris was evaluated by injecting 2-year-old seedling leaves of J. mandshurica, J. nigra and J. regia. The bacterial growth was monitored in the infected tissue over 12 days. Xanthomonas c. pv. juglandis exhibited a high growth rate and induced black greasy spots in J. mandshurica and J. regia; X. c. pv. campestris grew in leaf tissues without inducing symptoms, X. c. pv. corylina showed a very low growth rate. None of the tested bacterial strains multiplied in the leaves of J. nigra. This confirms the results obtained in the field tests. Juglans regia was the most susceptible among the walnut species tested.
A new dynamic model for Erysiphe necator ascosporic infections on grapevine was developed. Between budbreak of vines and the time when the pool of ascospores is depleted, the model uses weather data for calculating, at daily intervals: curve of ascospore maturation; ascospore discharge events and relative proportion of the discharged ascospores; infection periods and their relative infection severity; and progress of latency period and time when secondary infections should begin. The model was validated over a 4-year period (2005–2008) in 26 vineyards in Italy by comparing model predictions with actual observations of the first seasonal symptoms of powdery mildew. The model showed high sensitivity, specificity and accuracy. Proportions of true and false positive predictions were TPP = 0·94 and FPP = 0·26, respectively. Because a proportion of predicted infection periods did not result in actual disease onset, confidence was higher for prediction of non-infections than for prediction of infections. Most of the false positive predictions occurred in the earlier growth stages of the host, when the surface area of susceptible tissue may be very small so that the probability that ejected ascospores land on susceptible tissue is low. An equation was then developed to describe the probability that a predicted infection period results in disease onset as a function of the growth stage of vines at the time of prediction. The new model should improve early season powdery mildew management by helping vineyard managers schedule fungicide sprays or schedule the scouting of the vineyard for detection of first disease signs.
Rule-based systems for the prediction of the occurrence of disease can be evaluated in a number of different ways. One way is to examine the probability of disease occurrence before and after using the predictor. Bayes's Theorem can be a useful tool to examine how a disease forecast (either positive or negative) affects the probability of occurrence, and simple analyses can be conducted without knowing the risk preferences of the targeted decision makers. Likelihood ratios can be calculated from the sensitivity and specificity of the forecast, and provide convenient summaries of the forecast performance. They can also be used in a simpler form of Bayes's Theorem. For diseases where little or no prior information on occurrence is available, most forecasts will be useful in that they will increase or decrease the probability of disease occurrence. For extremely common or extremely rare diseases, likelihood ratios may not be sufficiently large or small to substantially affect the probability of disease occurrence or make any difference to the actions taken by the decision maker.
Integrates the analysis of ecological systems, the development of their models in terms of relational diagrams and differentiation equations, and the solution of these equations by developing small computer models in a simulation language. In part A the fundamentals of systems analysis are treated: the philosophy is presented; definitions of the terms system, model, and simulation; state, rate and driving variables; feedback and the simplest numerical integration method; time coefficient; static and dynamic equilibria; and an introduction to the simulation language CSMP (Continuous System Modelling Program) are discussed. The subject matter is illustrated with two yeast growth models. In part B more complicated integration techniques are discussed, as well as the use of FORTRAN in CSMP programs, and a simulation method to describe delays and dispersion. The phenomenon of numerical dispersion is discussed in examples of mass flow and diffusion of dissolved material in a soil column. Exercises form an integrated part of the book. -from Editor
A new reproducibility index is developed and studied. This index is the correlation between the two readings that fall on the 45 degree line through the origin. It is simple to use and possesses desirable properties. The statistical properties of this estimate can be satisfactorily evaluated using an inverse hyperbolic tangent transformation. A Monte Carlo experiment with 5,000 runs was performed to confirm the estimate's validity. An application using actual data is given.
Epidemiology and management of walnut blight
- J E Adaskaveg
- H Förster
- J Dieguez-Uribeondo
- D Thompson
- C J Adams
- C Thomas
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