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Evolution-Smart Integrated Disease Management Strategies against Fungicide Resistance in the Agroecosystem

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A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Pest and Disease Management".

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 13879

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Dr. Paulo Cezar Ceresini

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Department of Plant Health, Rural Engineering and Soils, College of Engineering of Ilha Solteira, São Paulo State University (UNESP), Ilha Solteira, SP 15385-000, Brazil
Interests: evolution of plant pathogens in the agroecosystem; molecular detection and diagnostics of fungicide resistance alleles; pathogen inoculum and disease surveillance; platform for fungicide resistance monitoring; smart integrated fungicide resistance management strategies

Special Issue Information

Dear Colleagues,

Resistance to fungicides used to control plant pathogens is a threat to effective crop protection and therefore to food security. Tighter regulations and a slowing pipeline of new products have also reduced the range of available chemical classes. This has led to a greater dependence on fewer fungicides and mode of actions, increasing selection for further cases of resistance. The limited availability of effective crop protection products, coupled with lack of genetic resistance in major crop varieties, is making key pathogens increasingly difficult to control. In addition, because the onset of disease epidemics is poorly understood for most pathosystems, appropriate antiresistance strategies and optimal disease control cannot be achieved. In order to rationalize fungicide inputs (e.g., product choice, dose rate, spray frequency and timing, and mixing/alternation of fungicides) and to test antiresistance strategies aiming to reduce disease inoculum and delay evolution and spread of resistance against current and new fungicides, high throughput monitoring tools, enabling quantitative measurement of pathogen levels and detection of fungicide resistant alleles, in combination with disease forecasting, are needed. In this Special Issue, we aim to exchange knowledge on evolution-smart integrated disease management strategies against fungicide resistance in the agroecosystem.

Dr. Paulo Cezar Ceresini
Guest Editor

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Keywords

disease surveillance tools
DNA-based diagnostics of fungicide resistance
inoculum and disease epidemic monitoring
fungicide resistance mechanisms
fitness and competitive advantage of fungicide resistance traits
molecular detection of fungicide resistance alleles
platform for fungicide resistance phenotyping
smart-integrated disease management strategies
stability and persistence of mutations for fungicide resistance
Asian soybean rust
brown rot of stone fruits
citrus black spot disease
corn leaf diseases
cotton foliar diseases
Glomerella leaf spot and scab disease on apples
Sigatoka diseases complex on bananas
soybean target spot
soybean anthracnose
wheat blast

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Published Papers (5 papers)

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Research

17 pages, 6779 KiB

Open AccessArticle

Aerobiology of the Wheat Blast Pathogen: Inoculum Monitoring and Detection of Fungicide Resistance Alleles

by Samara Nunes Campos Vicentini, Nichola J. Hawkins, Kevin M. King, Silvino Intra Moreira, Adriano Augusto de Paiva Custódio, Rui Pereira Leite Júnior, Diego Portalanza, Felipe Rafael Garcés-Fiallos, Loane Dantas Krug, Jonathan S. West, Bart A. Fraaije, Waldir Cintra De Jesus Júnior and Paulo Cezar Ceresini

Agronomy 2023, 13(5), 1238; https://doi.org/10.3390/agronomy13051238 - 27 Apr 2023

Cited by 7 | Viewed by 2861

Abstract

Wheat blast, caused by the ascomycetous fungus Pyricularia oryzae Triticum lineage (PoTl), is mainly controlled by fungicide use, but resistance to the main fungicide groups—sterol demethylase (DMI), quinone outside (QoI), and succinate dehydrogenase inhibitors (SDHI)—has been reported in Brazil. In order to rationalize fungicide inputs (e.g., choice, timing, dose-rate, spray number, and mixing/alternation) for managing wheat blast, we describe a new monitoring tool, enabling the quantitative measurement of pathogen’s inoculum levels and detection of fungicide resistance alleles. Wheat blast airborne spores (aerosol populations) were monitored at Londrina in Paraná State, a major wheat cropping region in Brazil, using an automated high-volume cyclone coupled with a lab-based quantitative real-time PCR (qPCR) assay. The objectives of our study were as follows: (1) to monitor the amount of PoTl airborne conidia during 2019–2021 based on DNA detection, (2) to reveal the prevalence of QoI resistant (QoI-R) cytochrome b alleles in aerosol populations of wheat blast, and (3) to determine the impact of weather on the dynamics of wheat blast aerosol populations and spread of QoI resistant alleles. PoTl inoculum was consistently detected in aerosols during the wheat cropping seasons from 2019 to 2021, but amounts varied significantly between seasons, with highest amounts detected in 2019. High peaks of PoTl DNA were also continuously detected during the off-season in 2020 and 2021. The prevalence of QoI resistant (QoI-R) cytochrome b G143A alleles in aerosol populations was also determined for a subset of 10 PoTl positive DNA samples with frequencies varying between 10 and 91% using a combination of PCR-amplification and SNP detection pyrosequencing. Statistically significant but low correlations were found between the levels of pathogen and the weather variables. In conclusion, for wheat blast, this system provided prior detection of airborne spore levels of the pathogen and of the prevalence of fungicide resistance alleles. Full article

(This article belongs to the Special Issue Evolution-Smart Integrated Disease Management Strategies against Fungicide Resistance in the Agroecosystem)

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19 pages, 32853 KiB

Open AccessArticle

An Accurate, Affordable, and Precise Resazurin-Based Digital Imaging Colorimetric Assay for the Assessment of Fungicide Sensitivity Status of Fungal Populations

by Tatiane Carla Silva, Silvino Intra Moreira, Fabio Gomes Assis, Jr., Samara Nunes Campos Vicentini, Abimael Gomes Silva, Tamiris Yoshie Kitayama Oliveira, Félix Sebastião Christiano, Jr., Adriano Augusto Paiva Custódio, Rui Pereira Leite, Jr., Maria Cândida Godoy Gasparoto, Waldir Cintra de Jesus, Jr. and Paulo Cezar Ceresini

Agronomy 2023, 13(2), 343; https://doi.org/10.3390/agronomy13020343 - 25 Jan 2023

Cited by 1 | Viewed by 2482

Abstract

This study aimed at the development and validation of an accurate, more affordable, and precise digital imaging resazurin-based fungicide sensitivity colorimetric assay (COL-assay) for fungal plant pathogens from the genera Mycosphaerella and Pyricularia. This proposed digital imaging assay was based on colorimetric estimates of resazurin reduction, which was used as a metabolic indicator of fungal respiration activity on microplate cultures. As fungal model systems, we used the yellow and black Sigatoka pathogens [Mycosphaerella musicola (Mm) and M. fijiensis (Mf), respectively] and the wheat blast pathogen, Pyricularia oryzae Triticum lineage (PoTl), which were previously characterized for QoI, DMI, and SDHI fungicide sensitivity. We then compared the classical spectrophotometry detection assay (SPEC-assay) with the proposed COL-assay based on the analyses of digital images of the microplates’ cultures captured with mobile phone cameras on a handmade trans-illuminator built for poorly equipped labs. Qualitatively, in terms of accuracy, there was full correspondence between the SPEC-assay and the COL-assay according to the fungal EC₅₀ or the relative growth classes on QoI, SDHI, and DMI fungicides for both Mycosphaerella and Pyricularia pathogens. We also observed a strong to very strong correlation coefficient between the COL-assay and the SPEC-assay fungicide sensitivity values for the QoI azoxystrobin, the SDHI fluxapyroxad, and the DMI tebuconazole. Our conclusion was that the COL-assay had a similar accuracy as the SPEC-assay (i.e., resulted in similar fungicide-sensitivity categories for both resistant or sensitive fungal isolates) and high precision. By openly sharing here the COL-assay’s full methodology, and the blueprints of the handmade trans-illuminator, we foresee its adoption by poorly equipped labs throughout the country as an affordable venue for monitoring the fungicide resistance status of populations of important fungal plant pathogens such as M. fijiensis, M. musicola, and P. oryzae Triticum and Oryza lineages. Full article

(This article belongs to the Special Issue Evolution-Smart Integrated Disease Management Strategies against Fungicide Resistance in the Agroecosystem)

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19 pages, 3286 KiB

Open AccessArticle

Evidence of Resistance to QoI Fungicides in Contemporary Populations of Mycosphaerella fijiensis, M. musicola and M. thailandica from Banana Plantations in Southeastern Brazil

by Tamiris Y. K. Oliveira, Tatiane C. Silva, Silvino I. Moreira, Felix S. Christiano, Jr., Maria C. G. Gasparoto, Bart A. Fraaije and Paulo C. Ceresini

Agronomy 2022, 12(12), 2952; https://doi.org/10.3390/agronomy12122952 - 24 Nov 2022

Cited by 10 | Viewed by 2933

Abstract

Yellow and black Sigatoka, caused by Mycosphaerella fijiensis and M. musicola, respectively, are the most important worldwide foliar diseases of bananas. Disease control is heavily dependent on intensive fungicide sprays, which increase selection pressure for fungicide resistance in pathogen populations. The primary objective of this study was to assess the level and spread of resistance to quinone-outside inhibitors (QoI—strobilurin) fungicides in populations of both pathogens sampled from banana fields under different fungicide spray regimes in Southeastern Brazil. Secondly, we aimed to investigate when QoI resistance was confirmed if this was associated with the target-site alteration G143A caused by a mutation in the mitochondrial encoded cytochrome b gene. QoI resistance was detected in fungicide treated banana fields, while no resistance was detected in the organic banana field. A total of 18.5% of the isolates sampled from the pathogens’ populations were resistant to QoI. The newly described M. thailandica was also found. It was the second most abundant Mycosphaerella species associated with Sigatoka-like leaf spot symptoms in the Ribeira Valley and the highest level of QoI resistance was found for this pathogen. The G143A cytochrome b alteration was associated with the resistance to the QoI fungicides azoxystrobin and trifloxystrobin in M. fijiensis, M. musicola and M. thailandica strains. In order to reduce resistance development and maintain the efficacy of QoI fungicides, anti-resistance management strategies based on integrated disease management practices should be implemented to control the Sigatoka disease complex. Full article

(This article belongs to the Special Issue Evolution-Smart Integrated Disease Management Strategies against Fungicide Resistance in the Agroecosystem)

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23 pages, 4092 KiB

Open AccessArticle

Impact of Fungicide Application Timing Based on Soybean Rust Prediction Model on Application Technology and Disease Control

by Matheus Mereb Negrisoli, Flávio Nunes da Silva, Raphael Mereb Negrisoli, Lucas da Silva Lopes, Francisco de Sales Souza Júnior, Bianca Rezende de Freitas, Edivaldo Domingues Velini and Carlos Gilberto Raetano

Agronomy 2022, 12(9), 2119; https://doi.org/10.3390/agronomy12092119 - 7 Sep 2022

Viewed by 2271

Abstract

The application of remote sensing techniques and prediction models for soybean rust (SBR) monitoring may result in different fungicide application timings, control efficacy, and spraying performance. This study aimed to evaluate the applicability of a prediction model as a threshold for disease control decision-making and to identify the effect of different application timings on SBR control as well as on the spraying technology. There were two experimental trials that were conducted in a 2 × 4 factorial scheme: 2 cultivars (susceptible and partially resistant to SBR); and four application timings (conventional chemical control at a calendarized system basis; based on the prediction model; at the appearance of the first visible symptoms; and control without fungicide application). Spray deposit and coverage at each application timing were evaluated in the lower and upper region of the soybean canopy through quantitative analysis of a tracer and water-sensitive papers. The prediction model was calculated based on leaf reflectance data that were collected by remote sensing. Application timings impacted the application technology as well as control efficacy. Calendarized system applications were conducted earlier, promoting different spray performances. Spraying at moments when the leaf area index was higher obtained poorer distribution. None of the treatments were capable of achieving high spray penetration into the canopy. The partially resistant cultivar was effective in holding disease progress during the crop season, whereas all treatments with chemical control resulted in less disease impact. The use of the prediction model was effective and promising to be integrated into disease management programs. Full article

(This article belongs to the Special Issue Evolution-Smart Integrated Disease Management Strategies against Fungicide Resistance in the Agroecosystem)

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12 pages, 1338 KiB

Open AccessArticle

Efflux Pumps and Multidrug-Resistance in Pyricularia oryzae Triticum Lineage

by Samara Nunes Campos Vicentini, Silvino Intra Moreira, Abimael Gomes da Silva, Tamiris Yoshie Kiyama de Oliveira, Tatiane Carla Silva, Fabio Gomes Assis Junior, Loane Dantas Krug, Adriano Augusto de Paiva Custódio, Rui Pereira Leite Júnior, Paulo Eduardo Teodoro, Bart Fraaije and Paulo Cezar Ceresini

Agronomy 2022, 12(9), 2068; https://doi.org/10.3390/agronomy12092068 - 30 Aug 2022

Cited by 6 | Viewed by 2380

Abstract

Widespread resistance to QoIs, DMI and SDHIs fungicides has been reported for Brazilian populations of the wheat blast pathogen Pyricularia oryzae Triticum lineage (PoTl). A pre-existing resistance mechanism not associated with target site mutations has been indicated for resistance to DMIs and SDHIs, with strong indication that PoTl has multidrugresistance (MDR). Therefore, the main objective of this study was to test the hypothesis that resistance to DMI and SDHI fungicides detected in PoTl was due to efflux pump mediated MDR mechanism(s) by characterizing the sensitivity to antifungal efflux pump substrates. Four antifungal substrates were tested: tolnaftate (TOL), cycloheximide (CHX), rhodamine 6G (RH6G) and triphenyltin chloride (TPCL). TPCL and RH6G were considered the most relevant indicators for enhanced MDR activity. Among the 16 PoTl isolates tested, 9 were insensitive to TPCL, 1 to TOL, 16 to RH6G and 1 to CHX. The PoTl isolates were grouped into four distinct multidrug resistance phenotypes (MDRPs) based on resistance to combinations of fungicides and antifungal efflux pump substrates. Insensitivity to TPCL, RH6G and or TOL correlated well with DMI insensitivity, but MDR was not associated with SDHI resistance. The identification of multiple MDRP phenotypes associated with DMI resistance in our study warrants further research aimed at revealing the exact mechanisms of multidrug resistance in the wheat blast pathogen, including efflux pumps overexpression via transcriptomic analyses of differentially expressed genes; identification and discovery of mutations associated with changes in promoter regions or transcription factors of efflux transporters associated with multidrug resistance. Full article

(This article belongs to the Special Issue Evolution-Smart Integrated Disease Management Strategies against Fungicide Resistance in the Agroecosystem)

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