Integration of mathematical modeling and target-based application of biocontrol agents for the control of Botrytis cinerea in vineyards.

BACKGROUND: Biocontrol agents (BCAs) are alternatives to synthetic fungicides with low risk to the environment and human health. Although several studies on the biocontrol of gray mold in vineyards have been performed, it is necessary to improve the usage of BCAs in fields conditions. Therefore, in the present study, BCAs were used both in calendar-based [based on four growth stages (GSs), i.e., flowering, pre-bunch closure, veraison, and before harvest] and predictive model-based strategies (only when Botrytis cinerea infection risk was predicted by the model). The BCAs applied during the seasons were selected considering the grapevine GSs. Treatments performed with BCAs were compared with synthetic fungicide treatments and an untreated control. The trials were conducted in three experimental vineyards with four epidemics. To evaluate the level of gray mold control of each treatment, disease severity was assessed at harvest and the presence of latent infection was evaluated. RESULTS: The integrative use of the predictive model and BCAs provided satisfactory levels of gray mold control, with gray mold severity levels significantly lower (P < 0.001) than those of the untreated control, which had severity values (< 7%) similar to those observed with synthetic fungicides following both calendar and model-based strategies. CONCLUSIONS: The integrative use of the predictive model and BCAs represents a valid alternative to conventional methods of gray mold control in vineyards, with more than 75% reduction in fungicide usage. © 2024 Society of Chemical Industry.

Temporal Dynamics and Dispersal Patterns of the Primary Inoculum of Coniella diplodiella, the Causal Agent of Grape White Rot.

Grape white rot can cause considerable yield losses in viticulture areas worldwide and is principally caused by Coniella diplodiella. The fungus overwinters in berry mummies on the soil surface or on the trellis and produces pycnidia and conidia that serve as primary inoculum. However, little is known about the temporal dynamics and dispersal pattern of C. diplodiella conidia. In this study, we investigated the production and dispersal of C. diplodiella conidia from a primary inoculum source, namely, affected mummified berries that overwintered in two vineyards in northern Italy in 2021 and 2022. Conidia of C. diplodiella were repeatedly produced in berry mummies from the budburst of vines to harvesting, with approximately 50 and 75% of the total conidia in a season being produced before fruit set and véraison, respectively. The production dynamics of C. diplodiella conidia over time were described by a Weibull equation in which the thermal time is the independent variable, with a concordance correlation coefficient of ≥0.964. A rainfall cutoff of ≥0.2 mm provided an overall accuracy of ≥0.86 in predicting conidial dispersal through rain splashes from berry mummies on the soil surface, with the number of dispersed conidia increasing with the amount of rainfall. The dispersal of conidia from mummies on the trellis by washing with rain required at least 6.1 mm of rain. The proposed mathematical equations and rain cutoffs can be used to predict periods with a high dispersal risk of C. diplodiella.

Temperature-dependent sporulation of the fungus Coniella diplodiella, the causal agent of grape white rot.

White rot, caused by the fungus Coniella diplodiella, can severely reduce grapevine yields worldwide. Currently, white rot control mainly relies on fungicides applied on a calendar basis or following hailstorms that favor disease outbreak; however, the control achieved with this strategy is often inconsistent or otherwise unsatisfactory. Realizing more rational control requires an improved understanding of white rot epidemiology. Toward this end, we conducted experiments with grapevine berries of two Vitis vinifera cultivars (either injured or not before artificial inoculation with a conidia suspension of C. diplodiella) to determine the effect of temperature on the length of latency (i.e., the time between infection and onset of mature pycnidia on berries) and the production of pycnidia and conidia. Sporulation occurred between 10°C and 35°C, with the optimum detected at 20°C. The latency period was shorter at 25-35°C than at lower temperatures; the shortest latency period was 120 h at 30°C on injured berries. Affected berries produced abundant conidia at 15-30℃ (the optimum was 20℃) for more than two months following inoculation. Mathematical equations were developed that fit the data, with strong associations with temperature for latency period (R2 = 0.831) and for the production dynamics of secondary conidia (R2 = 0.918). These equations may contribute to the development of a risk algorithm to predict infection periods, which can inform risk-based rather than calendar-based disease control strategies.

Seasonal periodicity of the airborne spores of fungi causing grapevine trunk diseases: an analysis of 247 studies published worldwide.

Grapevine trunk diseases (GTDs) are among the most devastating grapevine diseases globally. GTDs are caused by multiple fungi from various taxa, which release spores into the vineyard and infect wood tissue, mainly through wounds caused by viticultural operations. The timing of operations to avoid infection is critical concerning the periodicity of GTD spores in vineyards, and many studies have been conducted in different grape-growing areas worldwide. However, these studies provide conflicting and fragmented information. To synthesize current knowledge, we performed a systematic literature review, extracted quantitative data from published papers, and used these data to identify trends and knowledge gaps to be addressed in future studies. Our database included 26 papers covering 247 studies and 3,529 spore sampling records concerning a total of 29 fungal taxa responsible for Botryosphaeria dieback (BD), Esca complex (EC), and Eutypa dieback (ED). We found a clear seasonality in the presence and abundance of BD spores, with a peak from fall to spring, more in the northern than in the southern hemisphere, but not for EC and ED. Spores of these fungi were present throughout the growing season in both hemispheres, possibly due to higher variability in spore types, sporulation conditions, and spore release mechanisms in EC and ED fungi compared to BD. Our analysis has limitations due to knowledge gaps and data availability for some fungi (e.g., Basidiomycetes, causing EC). These limitations are discussed to facilitate further research.

A spatio-temporal dataset of plant pests' first introductions across the EU and potential entry pathways.

World trade has greatly increased in recent decades, together with a higher risk of introducing non-indigenous pests. Introduction trends show no sign of saturation, and it seems likely that many more species will enter and establish in new territories in the future. A key challenge in analysing pest invasion patterns is the paucity of historical data on pest introductions. A comprehensive dataset of pests' introductions in the EU, including their spatial occurrences, is not currently available and information is scattered across different sources or buried in the scientific literature. Therefore, we collected pests' introduction information (e.g., year, host) from online scientific databases and literature; we then gathered primary spatial data related to the site of first introductions. Finally, we identified the potential pathways of entry for each pest. The dataset contains expert-revised data on 278 pests introduced in the EU between 1999 and 2019, alongside their spatial occurrence and potential pathways of entry, providing a basis to better understand the factors associated with the likelihood of pest introduction. It is important to note that this dataset does not contain the current distribution of the introduced pests, but only records of their first introduction in the EU.

Biocontrol of Botrytis cinerea as Influenced by Grapevine Growth Stages and Environmental Conditions.

The growth of four commercial biocontrol agents (BCAs: Bacillus amyloliquefaciens (BAD), Aureobasidium pullulans (APD), Metschnikowia fructicola (MFN), and Trichoderma atroviride (TAS)) was evaluated using turbidimetric assays on artificial substrates mimicking the chemical berry composition at four stages: pea-sized berries, veraison, softening, and ripe berries. The response of BCA growth differed among BCAs. Subsequently, the BCAs' population size was assessed after 1 to 13 days of incubation on the substrate mimicking ripe berries at 15 to 35 °C. The population size of BAD increased with temperatures, while that of MFN decreased; the population sizes of APD and TAS showed bell-shaped patterns with lower growth at 15 or 35 °C. Finally, the BCAs were applied to ripe berries and then incubated at 15 to 30 °C. After 1 to 13 days, the berries were inoculated with B. cinerea and incubated for 7 days, after which the BCA control efficacy was assessed. The highest control was observed at 25 °C for BAD and APD, at 15 to 20 °C for MFN, and at 25 to 30 °C for TAS. The results confirm that the plant substrates and temperature affect the population size of the BCA following application; temperature also affects the preventative efficacy of BCA against B. cinerea.

Role of rain in the spore dispersal of fungal pathogens associated with grapevine trunk diseases.

Grapevine trunk diseases are caused by a complex of fungi that belong to different taxa, which produce different spore types and have different spore dispersal mechanisms. It is commonly accepted that rainfall plays a key role in spore dispersal, but there is conflicting information in the literature on the relationship between rain and spore trapping in aerobiology studies. We conducted a systematic literature review, extracted quantitative data from published papers, and used the pooled data for Bayesian analysis of the effect of rain on spore trapping. We selected 17 papers covering 95 studies and 8,778 trapping periods, concerning a total of 26 fungal taxa causing Botryosphaeria dieback (BD), Esca complex (EC), and Eutypa dieback (ED). Results confirmed the role of rain in the spore dispersal of these fungi, but revealed differences among the different fungi. Rain was a good predictor of spore trapping for ED (AUROC = 0.820) and BD (0.766) but not for the Ascomycetes involved in EC (0.569) and not for the only Basidiomycetes, Fomitiporella viticola, studied as for spore discharge (AUROC not significant). Prediction of spore trapping was more accurate for negative than for positive prognosis; a rain cutoff of ≥0.2 mm provided an overall accuracy ≥0.61 for correct prognoses. Spores trapped in rainless periods accounted for only <10% of the total spores. Our analysis had some drawbacks, which were mainly caused by knowledge gaps and limited data availability; these drawbacks are discussed to facilitate further research.

Plant Resistance Inducers Affect Multiple Epidemiological Components of Plasmopara viticola on Grapevine Leaves.

Plant resistance inducers (PRIs) harbor promising potential for use in downy mildew (DM) control in viticulture. Here, the effects of six commercial PRIs on some epidemiological components of Plasmopara viticola (Pv) on grapevine leaves were studied over 3 years. Disease severity, mycelial colonization of leaf tissue, sporulation severity, production of sporangia on affected leaves, and per unit of DM lesion were evaluated by inoculating the leaves of PRI-treated plants at 1, 3, 6, 12, and 19 days after treatment (DAT). Laminarin, potassium phosphonate (PHO), and fosetyl-aluminium (FOS) were the most effective in reducing disease severity as well as the Pv DNA concentration of DM lesions on leaves treated and inoculated at 1 and 3 DAT; PHO and FOS also showed long-lasting effects on leaves established after treatment (inoculations at 6 to 19 DAT). PRIs also prevented the sporulation of Pv on lesions; all the PRI-treated leaves produced fewer sporangia than the nontreated control, especially in PHO-, FOS-, and cerevisane-treated leaves (>75% reduction). These results illustrate the broader and longer effect of PRIs on DM epidemics. The findings open up new perspectives for using PRIs in a defense program based on single, timely, and preventative field interventions.

Development of a model for Colletotrichum diseases with calibration for phylogenetic clades on different host plants.

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.

Susceptibility of pruning wounds to grapevine trunk diseases: A quantitative analysis of literature data.

Introduction: Pruning wounds are the main entry points for fungi causing grapevine trunk diseases (GTDs). Several studies identified factors influencing the temporal dynamics of wound susceptibility, which include the fungal species and inoculum dose, weather conditions, grape variety, pruning date, and so forth. Here, we conducted a quantitative analysis of literature data to synthesise outcomes across studies and to identify the factors that most affect the length of pruning wound susceptibility. Methods: We extracted data on the frequency at which the inoculated wounds showed GTD symptoms or an inoculated pathogen was reisolated following artificial inoculation at the time of pruning or in the following days. A negative exponential model was fit to these data to describe changes in wound susceptibility as a function of time since pruning, in which the rate parameter changed depending on specific factors. Results and Discussion: The results show that wound susceptibility is high at the time of pruning, and they remain susceptible to invasion by GTD fungi for months after pruning. Infection incidence on wounds was higher for fungi associated with Botryosphaeria dieback than those associated with Eutypa dieback or Esca complex, and wound susceptibility decreased faster for Eutypa dieback than for other GTD agents. Grapevine variety and pruning season also affected the wound susceptibility period. Sauvignon Blanc remains susceptible to GTDs longer than other varieties. We also found that the time of pruning can affect infection dynamics, especially for more susceptible varieties. The results increase our understanding of GTD epidemiology and should help growers control infections.

Efficacy of preharvest application of biocontrol agents against gray mold in grapevine.

The use of biocontrol agents (BCAs) represents a promising alternative to conventional methods for the management of gray mold in vineyards during the berry ripening stage. The main advantages of BCAs are the short preharvest interval and lack of chemical fungicide residues in wine. In this study, eight commercial BCAs (based on different Bacillus or Trichoderma species and strains, Aureobasidium pullulans, Metschnikowia fructicola, and Pythium oligandrum) and a reference fungicide (boscalid) were applied to a vineyard during berry ripening over three seasons to evaluate the dynamics over time in terms of their relative efficacies in gray mold control. At 1-13 days after application of BCAs to the berry surfaces in field conditions, the berries were collected and artificially inoculated with conidia of Botrytis cinerea under controlled laboratory conditions, and gray mold severity was observed after 7 days of incubation. Significant differences were observed in gray mold severity among years, according to the number of days the BCAs grew on the berry surface before B. cinerea inoculation, and the season by day interaction (altogether accounting for >80% of the experimental variance). The variability in BCA efficacy was closely related to the environmental conditions at the time of application and in the following days. Overall, the BCA efficacy increased with the degree days accumulated between BCA application in the vineyard and B. cinerea inoculation in the dry (no rain) periods (r = 0.914, P = 0.001). Rainfall and the associated drop in temperature caused a relevant reduction of BCA efficacy. These results demonstrate that BCAs are an effective alternative to conventional chemicals for the preharvest control of gray mold in vineyards. However, environmental conditions can considerably affect the BCA efficacy.

Plant Disease Models and Forecasting: Changes in Principles and Applications over the Last 50 Years.

This review gives a perspective of selected advances made since the middle of the 20th century in plant disease modeling, and the associated increase in the number of models published during that time frame. This progress can be mainly attributed to advances in (i) sensors and automatic environmental data collection technology, (ii) instrumentation and methods for studying botanical epidemiology, and (iii) data analytics and computer science. We review the evolution of techniques for developing data-based (empirical) models and process-based (mechanistic) models using the wheat rusts as a case study. We also describe the increased importance of knowledge about biological processes for plant disease modeling by using apple scab as a second case study. For both wheat rusts and apple scab, we describe how the models have evolved over the last 50 years by considering certain milestones that have been achieved in disease modeling. Finally, we describe how plant disease models are used as part of a multi-modeling approach to develop decision-making tools in the application of integrated pest management.

A Mechanistic Model Accounting for the Effect of Soil Moisture, Weather, and Host Growth Stage on the Development of Sclerotinia sclerotiorum.

The fungus Sclerotinia sclerotiorum causes serious losses to several agricultural crops worldwide. By using systems analysis, we retrieved the available knowledge concerning S. sclerotiorum from the literature and then analyzed and synthesized the data to develop a mechanistic, dynamic, weather-driven model for the prediction of epidemics on different crops. The model accounts for i) the production and survival of apothecia; ii) the production, dispersal, and survival of ascospores; iii) infection by ascospores; and iv) lesion onset. The ability of the model to predict the occurrence of apothecia was evaluated for epidemics observed with different climates, soil types, and host crops (soybean, white bean, and carrot) using independent data obtained from trials conducted in Ontario (Canada) in 1981, 1982, and from 1999 to 2002; in Michigan (U.S.A.) in 2015 and 2016; and in Wisconsin (U.S.A.) in 2016. The model showed 0.82 accuracy and 0.73 specificity in predicting the presence of apothecia, with a posterior probability of correctly predicting apothecia to be present or absent of 0.804 and 0.876, respectively. The model was also validated for its ability to predict disease progress on soybean and sunflower in Ontario in 1981 and 1982, in Manitoba (Canada) in 2001 and 2002, and in Michigan in 2015 and 2016. Comparison of model output with observations showed a concordance correlation coefficient of 0.948, and a root mean square error of 0.122. The model represents an improvement of previous S. sclerotiorum models and could be useful for making decisions on disease control.

Effects of Temperature and Moisture Duration on Spore Germination of Four Fungi that Cause Grapevine Trunk Diseases.

Grapevine trunk diseases (GTDs) are serious threats worldwide and are difficult to control, in part because the environmental requirements for epidemiological processes of the causal fungi are poorly understood. Therefore, we investigated the effects of temperature and moisture duration on spore germination of four fungi associated with two GTDs (esca complex and Eutypa dieback): Phaeomoniella chlamydospora, Phaeoacremonium minimum, Cadophora luteo-olivacea, and Eutypa lata. Conidia of Phaeomoniella chlamydospora, Phaeoacremonium minimum, and C. luteo-olivacea were similar: conidia of these fungi germinated profusely (>90%) between 20 and 30°C; Phaeomoniella chlamydospora and Phaeoacremonium minimum tended to germinate at higher temperatures (up to 40°C for P. minimum), and C. luteo-olivacea at lower temperatures (as low as 5°C). E. lata ascospores germinated between 10 and 30°C. The required duration of moist periods for germination was shortest for C. luteo-olivacea (about 6 h), followed by P. minimum and E. lata (about 12 h) and Phaeomoniella chlamydospora (about 24 h). Further research on the environmental requirements of GTD fungi may increase our ability to predict infection periods and, thereby, improve disease control.

Temperature-Dependent Growth and Spore Germination of Fungi Causing Grapevine Trunk Diseases: Quantitative Analysis of Literature Data.

Grapevine trunk diseases (GTDs) are serious threats in all viticultural areas of the world, and their management is always complex and usually inadequate. Fragmented and inconsistent information on the epidemiology and environmental requirements of the causal fungi is among the reasons for poor disease control. Therefore, we conducted a quantitative analysis of literature data to determine the effects of temperature on mycelial growth and the effects of temperature and moisture duration on spore germination. Using the collected information, we then developed mathematical equations describing the response of mycelial growth to temperature, and the response of spore germination to temperature and moisture for the different species and disease syndromes. We considered 27 articles (selected from a total of 207 articles found through a systematic literature search) and 116 cases; these involved 43 fungal species belonging to three disease syndromes. The mycelial growth of the fungi causing Botryosphaeria dieback (BD) and the esca complex (EC) responded similarly to temperature, and preferred higher temperatures than those causing Eutypa dieback (ED) (with optimal temperature of 25.3, 26.5, and 23.3°C, respectively). At any temperature, the minimal duration of the moist period required for 50% spore germination was shorter for BD (3.0 h) than for EC (17.2 h) or ED (15.5 h). Mathematical equations were developed accounting for temperature-moisture relationships of GTD fungi, which showed concordance correlation coefficients ≥0.888; such equations should be useful for reducing the risk of infection.

Information on disease resistance patterns of grape varieties may improve disease management.

Resistance to downy mildew (DM) and powdery mildew (PM) contributes to sustainable vineyard management by reducing the diseases and the need for fungicide applications. Resistant varieties vary in their degree of resistance to DM and PM, and in their susceptibility to other diseases. As a consequence, fungicide use may differ among varieties depending on their "resistance patterns" (i.e., the resistance level of a variety toward all of the diseases in the vineyard). The resistance patterns of 16 grapevine varieties to DM, PM, black rot (BR), and gray mold (GM) were evaluated over a 4-year period under field conditions. Disease severity was assessed on leaves and bunches, and the AUDPC (Area Under Disease Progress Curve) was calculated to represent the epidemic progress. GM was found only on bunches and only at very low levels, irrespective of the year or variety, and was therefore excluded from further analyses. The varieties were then grouped into four resistance patterns: i) low resistance to DM and PM, intermediate resistance to BR; ii) high resistance to DM, intermediate resistance to PM, low resistance to BR; iii) intermediate resistance to DM and BR, low resistance to PM; and iv) high resistance to DM, PM, and BR. AUDPC values on leaves were positively correlated with AUDPC values on bunches for susceptible varieties but not for resistant ones, with the exception of PM. Therefore, bioassays with leaves can be used to predict the resistance of bunches to DM and BR for susceptible varieties but not for resistant ones. These results may facilitate both strategic and tactical decisions for the sustainable management of grapevine diseases.

Temperature requirements of Colletotrichum spp. belonging to different clades.

The fungal genus Colletotrichum includes plant pathogens that cause substantial economic damage to horticultural, ornamental, and fruit tree crops worldwide. Here, we conducted a systematic literature review to retrieve and analyze the metadata on the influence of temperature on four biological processes: (i) mycelial growth, (ii) conidial germination, (iii) infection by conidia, and (iv) sporulation. The literature review considered 118 papers (selected from a total of 1,641 papers found with the literature search), 19 Colletotrichum species belonging to eight clades (acutatum, graminicola, destructivum, coccodes, dematium, gloeosporioides, and orbiculare), and 27 host plants (alfalfa, almond, apple, azalea, banana, barley, bathurst burr, blueberry, celery, chilli, coffee, corn, cotton, cowpea, grape, guava, jointvetch, lentil, lupin, olive, onion, snap bean, spinach, strawberry, tomato, watermelon, and white bean). We used the metadata to develop temperature-dependent equations representing the effect of temperature on the biological processes for the different clades and species. Inter- and intra-clades similarities and differences are analyzed and discussed. A multi-factor cluster analysis identified four groups of clades with similar temperature dependencies. The results should facilitate further research on the biology and epidemiology of Colletotrichum species and should also contribute to the development of models for the management of anthracnose diseases.

Development and Validation of a Mechanistic, Weather-Based Model for Predicting Puccinia graminis f. sp. tritici Infections and Stem Rust Progress in Wheat.

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.

Development and Validation of a Mechanistic Model That Predicts Infection by Diaporthe ampelina, the Causal Agent of Phomopsis Cane and Leaf Spot of Grapevines.

Phomopsis cane and leaf spot (PCLS), known in Europe as "excoriose," is an important fungal disease of grapevines caused by Diaporthe spp., and most often by Diaporthe ampelina (synonym Phomopsis viticola). PCLS is re-emerging worldwide, likely due to climate change, changes in the management of downy mildew from calendar- to risk-based criteria that eliminate early-season (unnecessary) sprays, and the progressive reduction in the application of broad-spectrum fungicides. In this study, a mechanistic model for D. ampelina infection was developed based on published information. The model accounts for the following processes: (i) overwintering and maturation of pycnidia on affected canes; (ii) dispersal of alpha conidia to shoots and leaves; (iii) infection; and (iv) onset of disease symptoms. The model uses weather and host phenology to predict infection periods and disease progress during the season. Model output was validated against 11 independent PCLS epidemics that occurred in Italy (4 vineyards in 2019 and 2020) and Montenegro (3 vineyards in 2020). The model accurately predicted PCLS disease progress, with a concordance correlation coefficient (CCC) = 0.925 between observed and predicted data. A ROC analysis (AUROC>0.7) confirmed the ability of the model to predict the infection periods leading to an increase in PCLS severity in the field, indicating that growers could use the model to perform risk-based fungicide applications.

A Systematic Map of the Research on Disease Modelling for Agricultural Crops Worldwide.

In this work, we developed a systematic map to identify and catalogue the literature pertaining to disease modelling for agricultural crops worldwide. Searches were performed in 2021 in the Web of Science and Scopus for papers reporting any type of disease model for 103 crops. In total, 768 papers were retrieved, and their descriptive metadata were extracted. The number of papers found increased from the mid-1900s to 2020, and most of the studies were from North America and Europe. More disease models were retrieved for wheat, potatoes, grapes, and apples than for other crops; the number of papers was more affected by the crop's economic value than by its cultivated area. The systematic map revealed an underrepresentation of disease models for maize and rice, which is not justified by either the crop economic value or by disease impact. Most of the models were developed to understand the pathosystem, and fewer were developed for tactical disease management, strategic planning, or scenario analysis. The systematic map highlights a variety of knowledge gaps and suggests questions that warrant further research.