Effect of Initial Inoculum on the Temporal and Spatial Dynamics of Wheat Blast Under Field Conditions in Bolivia.

Epidemiological studies to better understand wheat blast (WB) spatial and temporal patterns were conducted in three field environments in Bolivia between 2019 and 2020. The temporal dynamics of wheat leaf blast (WLB) and spike blast (WSB) were best described by the logistic model compared with the Gompertz and exponential models. The nonlinear logistic infection rates were higher under defined inoculation in experiments two and three than under undefined inoculation in experiment one, and they were also higher for WSB than for WLB. The onset of WLB began with a spatial clustering pattern according to autocorrelation analysis and Moran's index values, with higher severity and earlier onset for defined than for undefined inoculation until the last sampling time. The WSB onset did not start with a spatial clustering pattern; instead, it was detected later until the last sampling date across experiments, with higher severity and earlier onset for defined than for undefined inoculation. Maximum severity (Kmax) was 1.0 for WSB and less than 1.0 for WLB. Aggregation of WLB and WSB was higher for defined than for undefined inoculation. The directionality of hotspot development was similar for both WLB and WSB, mainly occurring concentrically for defined inoculation. Our results show no evidence of synchronized development but suggest a temporal and spatial progression of disease symptoms on wheat leaves and spikes. Thus, we recommend that monitoring and management of WB should be considered during early growth stages of wheat planted in areas of high risk.

Peanut Smut in Argentina: An Analysis of the Disease, Advances, and Challenges.

Peanut (Arachis hypogaea L.) is a globally high-value food crop, with Argentina ranking third in global peanut exports. However, Argentine peanut production faces a severe threat from a fungal disease, peanut smut, caused by Thecaphora frezzii. This disease is particularly prevalent in the Córdoba Province, where recent surveys have documented a gradual increase in the prevalence and incidence of peanut smut, becoming a significant challenge to peanut production. First identified in Brazil in the 1960s in wild peanut and later in Argentina in 1995 in commercial peanut fields, the disease has rapidly spread owing to its distinctive pathogen characteristics, including the lack of visible symptoms on aerial plant parts, spore spread, and survival, and with a lack of proactive efforts to develop and apply management strategies. This results in the gradual accumulation of teliospores of T. frezzii in soil, further exacerbating the problem in subsequent growing seasons by increasing the intensity of the disease and driving a reduction in crop yield and quality. This review summarizes recent research on peanut smut, focusing on disease assessment, molecular characterization, diagnosis and detection, epidemiology, host range and environmental conditions, and the latest advancements in management approaches, including fungicide spraying, breeding programs, cultural management, and biological control, aimed to enhance understanding and support effective disease management strategies in peanut production systems.

Weather-Based Logistic Regression Models for Predicting Wheat Head Blast Epidemics.

Wheat head blast is a major disease of wheat in the Brazilian Cerrado. Empirical models for predicting epidemics were developed using data from field trials conducted in Patos de Minas (2013 to 2019) and trials conducted across 10 other sites (2012 to 2020) in Brazil, resulting in 143 epidemics, with each being classified as either outbreak (≥20% head blast incidence) or nonoutbreak. Daily weather variables were collected from the National Aeronautics and Space Administration (NASA) Prediction of Worldwide Energy Resources (POWER) website and summarized for each epidemic. Wheat heading date (WHD) served to define four time windows, with each comprising two 7-day intervals (before and after WHD), which combined with weather-based variables resulted in 36 predictors (nine weather variables × four windows). Logistic regression models were fitted to binary data, with variable selection using least absolute shrinkage and selection operator (LASSO) and sequentially best subset analyses. The models were validated using the leave-one-out cross-validation (LOOCV) technique, and their statistical performance was compared. One model was selected, implemented in a 24-year series, and assessed by experts and literature. Models with two to five predictors showed accuracies between 0.80 and 0.85, sensitivities from 0.80 to 0.91, specificities from 0.72 to 0.86, and area under the curve (AUC) from 0.89 to 0.91. The accuracy of LOOCV ranged from 0.76 to 0.81. The model applied to a historical series included temperature and relative humidity in preheading date, as well as postheading precipitation. The model accurately predicted the occurrence of outbreaks, aligning closely with real-world observations, specifically tailored for locations with tropical and subtropical climates.

A one-dimensional map to study multi-seasonal coffee infestation by the coffee berry borer.

The coffee berry borer (CBB, Hypothenemus hampei) is the most serious insect pest of coffee worldwide; understanding the dynamics of its reproduction is essential for pest management. The female CBB penetrates the coffee berry, eats the seed, and reproduces inside it. A mathematical model of the infestation progress of the coffee berry by the CBB during several coffee seasons is formulated. The model represents the interaction among five populations: uninfested, slightly infested, and severely infested coffee berries, and free and encapsulated CBBs. Coffee harvesting is also included in the model. A one-dimensional map is derived for tracking the population dynamics subject to certain coffee harvesting percentages over several seasons. Stability analysis of the map's fixed points shows that CBB infestation could be eliminated or controlled to a specific level over multiple seasons of coffee harvesting. However, the percent of coffee harvesting required is determined by the level of CBB infestation at the beginning of the first season and in some cases it is impossible to achieve that percentage.

Development and validation of a diagrammatic scale for quantifying maize leaf spots caused by Diplodia macrospora / Desenvolvimento e validação de escala diagramática para quantificação da mancha foliar de Diplodia macrospora em milho

The objective of this study was to develop and validate a diagrammatic scale to evaluate the severity of spots on maize leaves caused by the fungus Diplodia macrospora. Severity ranged between the minimal (0.5%) and maximal (55%) limits of disease severity, and intermediate severity levels were defined according to the "Weber-Fechner stimulus response law". The proposed scale describes six levels of severity based on how much of the leaf is affected: 0.5%, 3%, 8%, 23%, 36%, and 55%. Validation was carried out by eight evaluators, four inexperienced and four experienced. They estimated the severity of disease in 60 maize leaves, with and without the proposed diagrammatic scale. A relationship was shown by regression analysis between estimated and actual severity, with and without the use of the scale. When both inexperienced and experienced evaluators used the scale, they were able to estimate disease severity more accurately and precisely.

O objetivo deste estudo foi desenvolver e validar uma escala diagramática para avaliação da severidade da mancha foliar causada pelo fungo Diplodia macrospora, em folhas de milho, considerando os limites de severidade mínima e máxima da doença e os níveis intermediários de acordo com a "Lei de resposta ao estímulo de Weber-Fechner". A escala proposta apresenta seis níveis de severidade: 0,5%; 3%; 8%; 23%; 36% e 55% da área foliar afetada. A validação foi realizada por oito avaliadores sendo quatro inexperientes e quatro experientes, os quais estimaram a severidade de 60 folhas de milho que apresentavam níveis variados se sintomas da doença, primeiramente sem a utilização da escala diagramática e, posteriormente, com o uso da escala proposta. Pela análise de regressão verificou-se relação entre o grau de severidade real e o estimado por cada avaliador, com e sem o uso da escala. Com a utilização da escala, tanto os avaliadores inexperientes quanto os experientes demostraram maiores níveis de acurácia e precisão.

Development and validation of a diagrammatic scale for quantifying maize leaf spots caused by Diplodia macrospora / Desenvolvimento e validação de escala diagramática para quantificação da mancha foliar de Diplodia macrospora em milho

The objective of this study was to develop and validate a diagrammatic scale to evaluate the severity of spots on maize leaves caused by the fungus Diplodia macrospora. Severity ranged between the minimal (0.5%) and maximal (55%) limits of disease severity, and intermediate severity levels were defined according to the "Weber-Fechner stimulus response law". The proposed scale describes six levels of severity based on how much of the leaf is affected: 0.5%, 3%, 8%, 23%, 36%, and 55%. Validation was carried out by eight evaluators, four inexperienced and four experienced. They estimated the severity of disease in 60 maize leaves, with and without the proposed diagrammatic scale. A relationship was shown by regression analysis between estimated and actual severity, with and without the use of the scale. When both inexperienced and experienced evaluators used the scale, they were able to estimate disease severity more accurately and precisely.(AU)

O objetivo deste estudo foi desenvolver e validar uma escala diagramática para avaliação da severidade da mancha foliar causada pelo fungo Diplodia macrospora, em folhas de milho, considerando os limites de severidade mínima e máxima da doença e os níveis intermediários de acordo com a "Lei de resposta ao estímulo de Weber-Fechner". A escala proposta apresenta seis níveis de severidade: 0,5%; 3%; 8%; 23%; 36% e 55% da área foliar afetada. A validação foi realizada por oito avaliadores sendo quatro inexperientes e quatro experientes, os quais estimaram a severidade de 60 folhas de milho que apresentavam níveis variados se sintomas da doença, primeiramente sem a utilização da escala diagramática e, posteriormente, com o uso da escala proposta. Pela análise de regressão verificou-se relação entre o grau de severidade real e o estimado por cada avaliador, com e sem o uso da escala. Com a utilização da escala, tanto os avaliadores inexperientes quanto os experientes demostraram maiores níveis de acurácia e precisão.(AU)

Genetic Structure and Subclonal Variation of Extant and Recent U.S. Lineages of Phytophthora infestans.

The oomycete Phytophthora infestans is an important plant pathogen on potato and tomato crops. We examined the genetic structure of extant 20th and 21st century U.S. lineages of P. infestans and compared them with populations from South America and Mexico to examine genetic relationships and potential sources of lineages. US-23, currently the most prevalent lineage detected in the United States, shared genetic similarity primarily with the BR-1 lineage identified in the 1990s from Bolivia and Brazil. Lineages US-8, US-14, and US-24, predominantly virulent on potato, formed a cluster distinct from other U.S. lineages. Many of the other U.S. lineages shared significant genetic similarity with Mexican populations. The US-1 lineage, dominant in the mid-20th century, clustered with US-1 lineages from Peru. A survey of the presence of RXLR effector PiAVR2 revealed that some lineages carried PiAVR2, its resistance-breaking variant PiAVR2-like, or both. Minimum spanning networks developed from simple sequence repeat genotype datasets from USABlight outbreaks clearly showed the expansion of US-23 over a 6-year time period and geographic substructuring of some lineages in the western United States. Many clonal lineages of P. infestans in the United States have come from introductions from Mexico, but the US-23 and US-1 lineages were most likely introduced from other sources.

Megastigmus seed wasp damage on native Schinus terebinthifolia drupes in ecological restoration area in Brazil.

Megastigmus transvaalensis Hussey (Hymenoptera: Torymidae) parasitizes drupes of Rhus genus plants in Africa and Schinus (Anacardiaceae) in South America. This exotic wasp damages Schinus terebinthifolia Raddi drupes in native forests and ecological restoration areas in Brazil. The objective of the present study was to investigate the precipitation, temperature and relative humidity effects on M. transvaalensis flight activity, and to determine the parasitism rate and sex ratio of this wasp on S. terebinthifolia plants. The study was conducted with yellow sticky traps and S. terebinthifolia drupes collected in an ecological restoration area, from August 2014 to September 2015, in the Sorocaba municipality, São Paulo state, Brazil. Megastigmus transvaalensis populations were negatively correlated with maximum and minimum temperatures and precipitation, with population peaks at the end of May 2015, with 927 insects per evaluation (48.8 adults per trap). The M. transvaalensis sex ratio was higher in the laboratory (0.42) than in the field (0.08). The parasitism rate of S. terebinthifolia drupes by M. transvaalensis ranged from zero to 36.3% under natural environmental conditions. Megastigmus transvaalensis can be monitored with yellow sticky traps. Damage by M. transvaalensis in S. terebinthifolia drupes may decrease the germination of the seeds and the establishment of this plant in native and restoration ecological areas.

Epidemics on plants: Modeling long-range dispersal on spatially embedded networks.

Here we develop an epidemic model that accounts for long-range dispersal of pathogens between plants. This model generalizes the classical compartmental models-Susceptible-Infected-Susceptible (SIS) and Susceptible-Infected-Recovered (SIR)-to take into account those factors that are key to understand epidemics in real plant populations. These ingredients are the spatial characteristics of the plots and fields in which plants are embedded and the effect of long-range dispersal of pathogens. The spatial characteristics are included through the use of random rectangular graphs which allow to consider the effects of the elongation of plots and fields, while the long-range dispersal is implemented by considering transformations, such as the Mellin and Laplace transforms, of a generalization of the adjacency matrix of the geometric graph. Our results point out that long-range dispersal favors the propagation of pathogens while the elongation of plant plots increases the epidemic threshold and decreases dramatically the number of affected plants. Interestingly, our model is able of reproducing the existence of patchy regions of infected plants and the absence of a clear propagation front centered in the initial infected plants, as it is observed in real plant epidemics.

Epidemic Network Analysis for Mitigation of Invasive Pathogens in Seed Systems: Potato in Ecuador.

Seed systems have an important role in the distribution of high-quality seed and improved varieties. The structure of seed networks also helps to determine the epidemiological risk for seedborne disease. We present a new approach for evaluating the epidemiological role of nodes in seed networks, and apply it to a regional potato farmer consortium (Consorcio de Productores de Papa [CONPAPA]) in Ecuador. We surveyed farmers to estimate the structure of networks of farmer seed tuber and ware potato transactions, and farmer information sources about pest and disease management. Then, we simulated pathogen spread through seed transaction networks to identify priority nodes for disease detection. The likelihood of pathogen establishment was weighted based on the quality or quantity of information sources about disease management. CONPAPA staff and facilities, a market, and certain farms are priorities for disease management interventions such as training, monitoring, and variety dissemination. Advice from agrochemical store staff was common but assessed as significantly less reliable. Farmer access to information (reported number and quality of sources) was similar for both genders. However, women had a smaller amount of the market share for seed tubers and ware potato. Understanding seed system networks provides input for scenario analyses to evaluate potential system improvements. [Formula: see text] Copyright © 2017 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .

Genetic variability affecting Exserohilum turcicum resistance in popcorn lines grown under high and low phosphorus conditions.

Northern leaf blight (NLB), caused by Exserohilum turcicum, is one of the main foliar diseases that affect popcorn culture. Farmers use many control measures to minimize damage caused by this disease, among which, the use of cultivars with genetic resistance is the most effective and economical. The aim of this study was to investigate genetic variability influencing resistance to NLB in 25 popcorn maize lines grown under high and low phosphorus conditions in relation to foliar fungal disease caused by E. turcicum. We evaluated the disease incidence and severity, by analysis of variance and cluster test (Scott-Knott). There was sufficient genetic variability between strains for resistance traits. Genotypic variance was higher than environmental variance, and had more discriminatory power. We conclude that new progenies could be selected for the establishment of future populations. P-7, P-9, L-59, L-71, and L-76 progenies possess promising characteristics that simultaneously reduce the severity and the incidence of NLB in popcorn plants.

Mapping Global Potential Risk of Mango Sudden Decline Disease Caused by Ceratocystis fimbriata.

The Mango Sudden Decline (MSD), also referred to as Mango Wilt, is an important disease of mango in Brazil, Oman and Pakistan. This fungus is mainly disseminated by the mango bark beetle, Hypocryphalus mangiferae (Stebbing), by infected plant material, and the infested soils where it is able to survive for long periods. The best way to avoid losses due to MSD is to prevent its establishment in mango production areas. Our objectives in this study were to: (1) predict the global potential distribution of MSD, (2) identify the mango growing areas that are under potential risk of MSD establishment, and (3) identify climatic factors associated with MSD distribution. Occurrence records were collected from Brazil, Oman and Pakistan where the disease is currently known to occur in mango. We used the correlative maximum entropy based model (MaxEnt) algorithm to assess the global potential distribution of MSD. The MaxEnt model predicted suitable areas in countries where the disease does not already occur in mango, but where mango is grown. Among these areas are the largest mango producers in the world including India, China, Thailand, Indonesia, and Mexico. The mean annual temperature, precipitation of coldest quarter, precipitation seasonality, and precipitation of driest month variables contributed most to the potential distribution of MSD disease. The mango bark beetle vector is known to occur beyond the locations where MSD currently exists and where the model predicted suitable areas, thus showing a high likelihood for disease establishment in areas predicted by our model. Our study is the first to map the potential risk of MSD establishment on a global scale. This information can be used in designing strategies to prevent introduction and establishment of MSD disease, and in preparation of efficient pest risk assessments and monitoring programs.

Bud Rot Caused by Phytophthora palmivora: A Destructive Emerging Disease of Oil Palm.

Oomycetes from the genus Phytophthora are among the most important plant pathogens in agriculture. Epidemics caused by P. infestans precipitated the great Irish famine and had a major impact on society and human history. In the tropics, P. palmivora is a pathogen of many plant species including cacao (Theobroma cacao), citrus (Citrus sp.), durian (Durio zibethines), jackfruit (Artrocarpus heterophyllus), rubber (Hevea brasiliensis), and several palm species including coconut (Cocos nucifera), and the African oil palm (Elaeis guineensis) as determined recently. The first localized epidemics of bud rot in oil palm in Colombia were reported in 1964. However, recent epidemics of bud rot have destroyed more than 70,000 ha of oil palm in the Western and Central oil palm growing regions of Colombia. The agricultural, social, and economic implications of these outbreaks have been significant in Colombia. Identification of the pathogen after 100 years of investigating the disease in the world enabled further understanding of infection, expression of a range of symptoms, and epidemiology of the disease. This review examines the identification of P. palmivora as the cause of bud rot in Colombia, its epidemiology, and discusses the importance of P. palmivora as a major threat to oil palm plantings globally.

Incidence of 'Candidatus Liberibacter asiaticus'-Infected Plants Among Citrandarins as Rootstock and Scion Under Field Conditions.

Huanglongbing (HLB), caused by the bacterium 'Candidatus Liberibacter' spp., is currently one of the most serious diseases of citrus plants and has caused substantial economic losses. Thus far, there is no source of genetic resistance to HLB in the genus Citrus or its relatives. However, several studies have reported Poncirus trifoliata and some of its hybrids to be more tolerant to the disease. The main objective of this study was to report differences in the incidence of 'Ca. L. asiaticus' infection in citrandarin plants, hybrids from Sunki mandarin (Citrus sunki (Hayata) hort. ex Tanaka), and trifoliate orange Rubidoux (P. trifoliata (L.) Raf.)), after conducting an extensive survey under field conditions. These hybrid plants were established for approximately 7 years in an area with a high incidence of 'Ca. L. asiaticus'-infected plants. We selected two experimental areas (area A and area B), located approximately 10 m apart. Area A consists of Pera sweet orange (C. sinensis (L.) Osb.) grafted onto 56 different citrandarin rootstocks. Area B consists of citrandarin scions grafted onto Rangpur lime (C. limonia Osb.) rootstock. Bacteria in the leaves and roots were detected using real-time quantitative polymerase chain reaction. The incidence of 'Ca. L. asiaticus'-infected plants was 92% in area A and 14% in area B. Because infected plants occurred in both areas, we examined whether the P. trifoliata hybrid rootstock influenced HLB development and also determined the distribution of 'Ca. L. asiaticus' in Citrus tree tissues. Although this survey does not present evidence regarding the resistance of P. trifoliata and its hybrids in relation to bacteria or psyllids, future investigation, mainly using the most promising hybrids for response to 'Ca. L. asiaticus', will help us to understand the probable mechanism of defense or identifying compounds in P. trifoliata and its hybrids that are very important as strategy to combat HLB. Details of these results are presented and discussed in this article.

Development of a disease risk prediction model for downy mildew (Peronospora sparsa) in boysenberry.

Downy mildew caused by Peronospora sparsa has resulted in serious production losses in boysenberry (Rubus hybrid), blackberry (Rubus fruticosus), and rose (Rosa sp.) in New Zealand, Mexico, and the United States and the United Kingdom, respectively. Development of a model to predict downy mildew risk would facilitate development and implementation of a disease warning system for efficient fungicide spray application in the crops affected by this disease. Because detailed disease observation data were not available, a two-step approach was applied to develop an empirical risk prediction model for P. sparsa. To identify the weather patterns associated with a high incidence of downy mildew berry infections (dryberry disease) and derive parameters for the empirical model, classification and regression tree (CART) analysis was performed. Then, fuzzy sets were applied to develop a simple model to predict the disease risk based on the parameters derived from the CART analysis. High-risk seasons with a boysenberry downy mildew incidence >10% coincided with months when the number of hours per day with temperature of 15 to 20°C averaged >9.8 over the month and the number of days with rainfall in the month was >38.7%. The Fuzzy Peronospora Sparsa (FPS) model, developed using fuzzy sets, defined relationships among high-risk events, temperature, and rainfall conditions. In a validation study, the FPS model provided correct identification of both seasons with high downy mildew risk for boysenberry, blackberry, and rose and low risk in seasons when no disease was observed. As a result, the FPS model had a significant degree of agreement between predicted and observed risks of downy mildew for those crops (P = 0.002).

Spatial and temporal analysis of stem bleeding disease in coconut palm in the state of Sergipe, Brazil.

Stem bleeding disease (resinosis) of coconut palm is caused by Thielaviopsis paradoxa and is very important in the state of Sergipe, Brazil. Understanding the epidemiological behavior of the disease is essential for establishing more efficient control strategies. Thus, we characterized the temporal progression and spatial distribution of stem bleeding in a commercial orchard under conditions of natural infection in the area of Neopolis, Sergipe. Three plots with 729 plants each were selected and evaluated every two months for stem bleeding incidence. In the temporal analysis, the monomolecular model gave the best fit to data on disease incidence, as it accurately showed the temporal dynamics of the disease during the experiment period. The spatial pattern of stem bleeding varied over time, with initial infections presenting random pattern and then evolving to aggregate pattern during evaluations. This indicates that the disease may have originated from the pathogen survival structures, followed by auto infections caused by dissemination from plant to plant, either by humans, by contact between roots, or by the vector Rhynchophorus palmarum.

Phytophthora capsici epidemic dispersion on commercial pepper fields in Aguascalientes, Mexico.

Chili pepper blight observed on pepper farms from north Aguascalientes was monitored for the presence of Phytophthora capsici during 2008-2010. Initially, ELISA tests were directed to plant samples from greenhouses and rustic nurseries, showing an 86% of positive samples. Later, samples of wilted plants from the farms during the first survey were tested with ELISA. The subsequent survey on soil samples included mycelia isolation and PCR amplification of a 560 bp fragment of ITS-specific DNA sequence of P. capsici. Data was analyzed according to four geographical areas defined by coordinates to ease the dispersal assessment. In general, one-third of the samples from surveyed fields contained P. capsici, inferring that this may be the pathogen responsible of the observed wilt. Nevertheless, only five sites from a total of 92 were consistently negative to P. capsici. The presence of this pathogen was detected through ELISA and confirmed through PCR. The other two-thirds of the negative samples may be attributable to Fusarium and Rhizoctonia, both isolated instead of Phytophthora in these areas. Due to these striking results, this information would be of interest for local plant protection committees and farmers to avoid further dispersal of pathogens to new lands.