Fungicide Mixtures Research Articles

Alliumcepa exposed to Nativo® fungicide with and without swine liver enzyme biotransformation: A comparative genotoxicity study.

The biotransformation of compounds is a critical point in understanding their toxic effects in both toxicology and ecotoxicology. The objective of this study was to evaluate whether there is a difference in the phytogenotoxic potential of the commercial fungicide Nativo® between non-biotransformed samples and samples biotransformed by swine liver enzymes. The fungicide Nativo is a mixture of Tebuconazole (TEB; 200gL-1) and Trifloxystrobin (TRI; 100gL-1). The test organism used in this study was Allium cepa, and the mitotic index (MI), chromosomic aberrations, and micronucleus frequency in A. cepa cells were compared between samples of non-biotransformed Nativo and biotransformed Nativo. The results showed that the Nativo biotransformated products were less genotoxic than the non-biotransformed Nativo, with the no-observed effect concentration (NOEC) values for micronuclei formation being four times lower after swine enzymes biotransformation, while MI was not altered. The no observed effect concentration values for micronuclei formation by the fungicide mixture were 7.8 and 3.9mgL-1 for TEB and TRI, respectively, for the biotransformed samples, and 1.9 and 1.0mgL-1 for the non-biotransformed samples, demonstrating that swine liver enzyme activity decreased genotoxicity. The results obtained in this study demonstrate the importance of considering biotransformation in phytogenotoxicity studies, as this process can significantly alter phytogenotoxic effects.

Mixture of neonicotinoid and fungicide affects foraging activity of honeybees.

The use of plant protection products (PPPs) is a major factor contributing to global insect decline. We here use the honeybee (Apis mellifera) as a model to study combined effects of the last neonicotinoid in the EU (acetamiprid) and different fungicides on live-long foraging flights using radio frequency identification. The mixture of the sterol-biosynthesis-inhibiting fungicide difenoconazole and the insecticide acetamiprid significantly reduced the number of foraging trips per day compared to the control and each PPP alone, while a mixture of the insecticide with the non-sterol-biosynthesis inhibiting fungicide boscalid/dimoxystrobin did not affect behaviour. This potential synergistic effect of the fungicide/insecticide mixture supports the notion that some fungicides can enhance the effect of insecticides, which did not lead to significant changes in behaviour when applied on their own. Our results emphasize the need for more studies on the interaction of different PPP.

Evaluation of the combined toxicity of compound pollutants of azole fungicides to Raphidocelis subcapitata

In order to investigate the combined toxicity of compound contaminated azole fungicides on alage. Systematic investigation of Difenoconazole, Penconazole, Metconazole, Tetraconazole, Flutriafol, Fuberidazole, Triflumizole, Terrazole, HyMexazol, 9 azole fungicides as the components of the mixture. Thirty-five binary mixture systems with 173 mixture rays were designed by direct equipartition ray method. The growth inhibition toxicity of binary mixtures to Raphidocelis subcapitata was determined by 96-well microplates. Toxic interactions were qualitatively analyzed by Concentration addition (CA) and Independent Action (IA) models. Model Deviation Ratio (MDR) was used to quantitatively evaluate the toxic interaction of binary mixtures of azole fungicides, as well as the equivalent graph method, Toxic Unit (TU) method, additivity Index method (AI), Toxicity Index (MTI) and Combination Index (CI) methods were used to analyze the combined toxicity and toxic interaction of the mixture. The results showed that the frequency of synergistic effect was higher when mixed with Difenoconazole, Penconazole and Triflumizole, and the binary mixing with Flutriafol, Fuberidazole and Metconazole could reduce the toxicity of the mixture, showing additive and antagonistic effects. The toxicity of the mixture ranged from 3.053 to 6.415. In addition, at ambient concentrations, the mixture interaction is dominated by addition.

A comprehensive machine learning-based models for predicting mixture toxicity of azole fungicides toward algae (Auxenochlorella pyrenoidosa)

Quantitative structure–activity relationships (QSARs) have been used to predict mixture toxicity. However, current research faces gaps in achieving accurate predictions of the mixture toxicity of azole fungicides. To address this gap, the application of machine learning (ML) algorithms has emerged as an effective strategy. In this study, we applied 12 algorithms, namely, k-nearest neighbor (KNN), kernel k-nearest neighbors (KKNN), support vector machine (SVM), random forest (RF), stochastic gradient boosting (GBM), cubist, bagged multivariate adaptive regression splines (Bagged MARS), eXtreme gradient boosting (XGBoost), boosted generalized linear model (GLMBoost), boosted generalized additive model (GAMBoost), bayesian regularized neural networks (BRNN), and recursive partitioning and regression trees (CART) to build ML models for 225 mixture toxicity of azole fungicides towards Auxenochlorella pyrenoidosa. A total of 36 single ML models and 12 consensus models were developed. The results indicated that models employing concentration addition (CA), independent action (IA), and molecular descriptors (MD) as variables demonstrated superior predictive abilities. The consensus model combining SVM and RF algorithms (labeled as CM0) demonstrated the highest level of accuracy in fitting the data, with a coefficient of determination of 0.980. Additionally, it showed strong predictive abilities when tested with external data, achieving an external R2 value of 0.945 and a Concordance Correlation Coefficient of 0.967. This study provides a positive contribution to the ecological risk assessment of a mixture of azole fungicides.

THE EFFECTIVENESS OF FUNGICIDES AND FOLIAR FERTILIZATION IN PROTECTING SPRING SOFT WHEAT IN THE SOUTH OF WESTERN SIBERIA

In years with favorable moisture in the south of Western Siberia, the loss of springwheat grain yield from leaf-stem infections increases sharply to 30% or more. The use of fungicides in combination with foliar feeding allows not only to preserve the crop, but also to improve its quality indicators. The studies were conducted in 2018-2021. The soil of the experimental plot is chernozem-meadow, heavy loamy. Four-field grain-fallow crop rotation, predecessor – wheat after fallow. Two-factor field experiment, plot area 25 m2, four-fold repetition. The purpose of the work is to assess the biological effectiveness of tank mixtures of fungicides with urea and liquid complex fertilizer (LCF) on the yield and quality of spring wheat grain. The average infestation of crops by powdery mildew over 4 years is 21,8%, maximum in 2018 – 30,5, rust species in 2019 – 68, average – 52,4, in the dry year 2021 – 1.0%. The incidence of septoria is insignificant, with a maximum of 8,6% in 2019. Treatment of crops with complex fertilizer reduced the development of powdery mildew to 32, types of rust to 61,6, septoria to 28,8%, and to a lesser extent when working with urea. On average, the biological effectiveness of the variants with Abacus Ultra, a fungicide based on triazole and strobilurin, was higher and ranged from 52,5 to 99,8%, and the drug Title Trio based on triazoles was lower, from 45,7 to 97,3%. Tank mixtures of fungicides and fertilizers did not reduce their effectiveness against spring wheat diseases. Fertilizing with liquid complex fertilizer provided the most stable and significant increase in grain yield over the research period – 0,63, urea 10 kg/ha – 0,46, 15 kg/ha – 0,40 t/ha. The greatest increase – 1,21 t/ha – was provided by a tank mixture with Abacus Ultra + liquid and liquid fertilizers, and economic efficiency, respectively, was 23,8-37,5%. A fungicide containing strobilurin (pyraclostrobin) has been shown to be highly effective in increasing the quality parameters of wheat grain.

Effects of tillage intensity and pesticide treated seeds on epigeal arthropod communities and weed seed predation in a maize-soybean rotation

Tillage practices and the use of pesticide seed treatments (PST) both have the potential to influence epigeal arthropod communities and the ecosystem services they provide, yet few studies have examined both factors in conjunction. A three-year field study (2017–2019) was conducted to assess the independent and interactive effects of tillage and pesticide seed treatments on epigeal arthropod communities and weed seed predation in a long-term row crop tillage intensity experiment located in southeastern New Hampshire, USA. Throughout the study, maize and soybean were planted in rotation with and without pesticide seed treatments (seed coatings containing a mixture of systemic and contact fungicides and neonicotinoid insecticides) under three tillage systems (full-, strip-, and no-till) in a randomized complete block design with four replications. Epigeal arthropod communities were sampled with pitfall traps from September to October 2018–2019 and weed seed predation was assessed over the same period each year from 2017–2019. A total of 1669 individual arthropods, representing 47 taxonomic groups, were observed over the course of the study. In 2018, epigeal arthropod communities differed based only on pesticide seed treatment. The opposite response was observed in 2019, as epigeal arthropod communities differed based only on tillage. Activity densities of Pterostichus melanarius (Illiger) were higher in the strip-till compared to full-till treatment in 2018. Annual levels of post-dispersal weed seed predation by invertebrates (% total seeds removed) varied based on tillage treatment in 2017 and 2019, but not in 2018, and ranged from as low as 6.1 % to as much as 27.2 % depending on year and treatment. These data provide evidence that both pesticide seed treatments and tillage systems can influence the communities of epigeal arthropods that inhabit annual row crop agroecosystems relatively late in the growing season, when the majority of pesticide residues have likely dissipated, and that the weed seed predation services provided by members of this community can be strongly negatively impacted by intensive tillage.

New binary mixtures of fungicides against Macrophomina phaseolina: Machine learning-driven QSAR, read-across prediction, and molecular dynamics simulation

Quantitative Structure-Activity Relationship (QSAR) analysis greatly enhances the development and research of pesticides. This study employed Multiple Linear Regression (MLR), machine learning (ML), and read-across (RA) approaches to investigate the combined effects of binary mixtures of fungicides on Macrophomina phaseolina. Using the Fixed Ratio Ray Design (FRRD) method, 75 binary mixtures of six frequently used fungicides were generated, with many exhibiting additive interactions as indicated by the Concentration Addition (CA) and Independent Action (IA) models. The QSAR analysis revealed that Support Vector Regression (SVR) and Gaussian Process Regression (GPR) models were the most effective, outperforming the Least Squares Kernel (LSK), MLR, and RA methods. SVR achieved an outstanding R2 of 0.95 and Q2LMO of 0.81, whereas GPR demonstrated values of 0.93 and 0.81 for the same metrics. Internal and external validation confirmed the reliability and generalizability of these models, suggesting they could be applied to a wider array of data. Moreover, Molecular Dynamics (MD) simulations showed that the effects of the fungicides are linked to physiological mechanisms rather than intermolecular interactions within their formulations. This study establishes a robust framework for creating potent fungicide combinations that improve disease management efficacy while promoting environmental sustainability and reducing the chemical load to mitigate negative impacts.

Корневая гниль яровой пшеницы в условиях Зауралья, варианты оперативной защиты

Abstract. Root rot is a harmful and widespread disease of cereal crops. In the conditions of the Urals, Siberia, and Northern Kazakhstan, its causative agents are various species of fungi of the genus Fusarium and the fungus Bipolaris sorokiniana. The purpose of this study was to comparatively determine the effectiveness of microbiological, chemical and combined protection of spring wheat seeds. Field experiments were carried out on the experimental field of the Kurgan Scientific Research Institute of Agriculture – branch of the Ural Federal Agrarian Scientific Research Centre of the Ural Branch of the Russian Academy of Sciences (Kurgan SRIA – branch of FSBSI UrFASRC, UrB of RAS) in 2019, 2021, 2022. Scientific novelty lies in the determining the competitiveness of various methods of protecting spring wheat seeds in the conditions of the Trans-Urals within the framework of modern cultivation technology. The methods used are generally accepted in the Russian Federation. Results. In conditions of almost annual occurrence of negative natural phenomena for the growth and development of plants (droughts, frosts, sudden changes in temperature, dry winds, etc.), the use of seed treaters can be an additional stress for plants; the presence of the effect of shortening the underground internode can negatively affect field germination culture. To reduce these risks, as well as the pesticide load, we recommend using a combined method of seed protection. It involves the use of a mixture of a bacterial fungicide based on Bacillus subtilis with a chemical disinfectant at half the consumption rate. At the same time, the level of control of phytopathogens is maintained, there is no retardant effect, and economic efficiency is not inferior to the level of using a two-component chemical seed protectant (113–114 %). Chemical protection of seeds reduced the development of root rot pathogens by 63–72 %. The use of combined protection provided good control of phytopathogens, including the dominant fungi Fusarium. The predominant species from the genus Fusarium were the highly dangerous F. oxysporum, F. graminearum, F. sporotrichioides.

P13-20 Exposure to mixtures of fungicides promotes hallmarks of cancer in human colon cancer cells

P13-20 Exposure to mixtures of fungicides promotes hallmarks of cancer in human colon cancer cells

Mixing Elemental Sulfur or Chlorothalonil with QoI and DMI Fungicides for Management of Late Leaf Spot of Peanut.

Reduced sensitivity to demethylation inhibitor (DMI) and quinone outside inhibitor (QoI) fungicides in Nothopassalora personata, the cause of late leaf spot of peanut (Arachis hypogaea) complicates management of this disease in the southeastern U.S. Mixtures with protectant fungicides may help preserve the utility of members of both DMI and QoI fungicide groups for leaf spot management. Field experiments were conducted in Tifton, GA from 2019 to 2021 and in Plains, GA during 2019 and 2020. The primary objective was to determine the effects of mixtures of DMI fungicides, tebuconazole and mefentrifluconazole, and QoI fungicides, azoxystrobin and pyraclostrobin, with micronized elemental sulfur on late leaf spot in fields with populations of N. personata with suspected reduced sensitivity to DMI and QoI fungicides. In four of the experiments, the efficacies of elemental sulfur and chlorothalonil as mixing partners were also compared. In most cases, standardized area under the disease progress curve (sAUDPC) and final percent defoliation were less for all DMI and QoI fungicides mixed with sulfur or chlorothalonil than for the respective fungicides alone. In most cases, sAUDPC and final percent defoliation were similar for sulfur and chlorothalonil when mixed with the respective DMI or QoI fungicide. These results indicate that mixtures of DMI or QoI fungicides with either micronized sulfur or chlorothalonil can improve control of late leaf spot compared to the DMI or QoI fungicide alone. These results also indicate that elemental sulfur has potential as an alternative to chlorothalonil in tank mixes where that protectant fungicide is currently being used as a mixing partner to improve leaf spot control.

Bioproducts of Pseudomonas chlororaphis Suppress DMI Fungicide-Induced CsCYP51A and CsCYP51B Gene Expression in Colletotrichum siamense and Generate Synergistic Effects with Metconazole and Propiconazole.

Mixtures of fungicides with different modes of action are commonly used as disease and resistance management tools, but little is known of mixtures of natural and synthetic products. In this study, mixtures of metabolites from the rhizobacterium Pseudomonas chlororaphis strain ASF009 formulated as Howler EVO with below-label rates (50 µg/ml) of conventional sterol demethylation inhibitor (DMI) fungicides were investigated for control of anthracnose of cherry (Prunus avium) caused by Colletotrichum siamense. Howler mixed with metconazole or propiconazole synergistically reduced disease severity through lesion growth. Real-time PCR showed that difenoconazole, flutriafol, metconazole, and propiconazole induced the expression of DMI target genes CsCYP51A and CsCYP51B in C. siamense. The addition of Howler completely suppressed the DMI fungicide-induced expression of both CYP51 genes. We hypothesize that the downregulation of DMI fungicide-induced expression of the DMI target genes may, at least in part, explain the synergism observed in detached fruit assays.

The neonicotinoid acetamiprid reduces larval and adult survival in honeybees (Apis mellifera) and interacts with a fungicide mixture

Plant protection products (PPPs), which are frequently used in agriculture, can be major stressors for honeybees. They have been found abundantly in the beehive, particularly in pollen. Few studies have analysed effects on honeybee larvae, and little is known about effects of insecticide-fungicide-mixtures, although this is a highly realistic exposure scenario. We asked whether the combination of a frequently used insecticide and fungicides would affect developing bees. Honeybee larvae (Apis mellifera carnica) were reared in vitro on larval diets containing different PPPs at two concentrations, derived from residues found in pollen. We used the neonicotinoid acetamiprid, the combined fungicides boscalid/dimoxystrobin and the mixture of all three substances. Mortality was assessed at larval, pupal, and adult stages, and the size and weight of newly emerged bees were measured. The insecticide treatment in higher concentrations significantly reduced larval and adult survival. Interestingly, survival was not affected by the high concentrated insecticide-fungicides-mixture. However, negative synergistic effects on adult survival were caused by the low concentrated insecticide-fungicides-mixture, which had no effect when applied alone. The lower concentrated combined fungicides led to significantly lighter adult bees, although the survival was unaffected. Our results suggest that environmental relevant concentrations can be harmful to honeybees. To fully understand the interaction of different PPPs, more combinations and concentrations should be studied in social and solitary bees with possibly different sensitivities.

Classification and regression machine learning models for predicting the combined toxicity and interactions of antibiotics and fungicides mixtures

Antibiotics and triazole fungicides coexist in varying concentrations in natural aquatic environments, resulting in complex mixtures. These mixtures can potentially affect aquatic ecosystems. Accurately distinguishing synergistic and antagonistic mixtures and predicting mixture toxicity are crucial for effective mixture risk assessment. We tested the toxicities of 75 binary mixtures of antibiotics and fungicides against Auxenochlorella pyrenoidosa. Both regression and classification models for these mixtures were developed using machine learning models: random forest (RF), k-nearest neighbors (KNN), and kernel k-nearest neighbors (KKNN). The KKNN model emerged as the best regression model with high values of determination coefficient (R2 = 0.977), explained variance in prediction leave-one-out (Q2LOO = 0.894), and explained variance in external prediction (Q2F1 = 0.929, Q2F2 = 0.929, and Q2F3 = 0.923). The RF model, the leading classifier, exhibited high accuracy (accuracy = 1 for the training set and 0.905 for the test set) in distinguishing the synergistic and antagonistic mixtures. These results provide crucial value for the risk assessment of mixtures.

Chemical management of Phakopsora pachyrhizi: Effect on incidence, severity, and yield in soybean

Asian soybean rust (Phakopsora pachyrhizi) is one of the main diseases in soybean crops. In Mexico, there is limited knowledge regarding its management, therefore the objective of this research was to evaluate the effect of mixtures of fungicides of the families: Carboxamides, Strobilurins, and Triazoles on incidence, severity, fungicide efficiency, and yield in soybean variety ‘Huasteca 700’. Three commercial combinations of fungicides were evaluated: Tebuconazole + Trifloxystrobin, Fluxapyroxad + Pyraclostrobin, Cyproconazole + Azoxystrobin, with surfactant (Agrega®) at 0.1%, and a control which consisted only of surfactant. The highest incidence and severity occurred in the control treatment; fungicide application formulated with Strobilurins, and Triazoles significantly reduced incidence (54 to 98%) and severity (82 to 100%) and provided a crop protection period of 35 to 54 days post-application. The incidence and severity by stratum plant were lower in the second evaluation cycle, with respect the first evaluation. Damage remained below 1.24, 0.5, and 0.03% in the low, middle, and upper stratum, respectively in treatments treated with fungicides 56 days after the first application. With two applications of chemical fungicides formulated with Strobilurins and Triazoles, in a natural infestation of Asian soybean rust, the damage and incidence were significantly reduced compared to the control treatment.

Combined interaction of fungicides binary mixtures: experimental study and machine learning-driven QSAR modeling

Fungicide mixtures are an effective strategy in delaying the development of fungicide resistance. In this research, a fixed ratio ray design method was used to generate fifty binary mixtures of five fungicides with diverse modes of action. The interaction of these mixtures was then analyzed using CA and IA models. QSAR modeling was conducted to assess their fungicidal activity through multiple linear regression (MLR), support vector machine (SVM), and artificial neural network (ANN). Most mixtures exhibited additive interaction, with the CA model proving more accurate than the IA model in predicting fungicidal activity. The MLR model showed a good linear correlation between selected theoretical descriptors by the genetic algorithm and fungicidal activity. However, both ML-based models demonstrated better predictive performance than the MLR model. The ANN model showed slightly better predictability than the SVM model, with R2 and R2cv at 0.91 and 0.81, respectively. For external validation, the R2test value was 0.845. In contrast, the SVM model had values of 0.91, 0.78, and 0.77 for the same metrics. In conclusion, the proposed ML-based model can be a valuable tool for developing potent fungicidal mixtures to delay fungicidal resistance emergence.

Pesticide Translocation Using Nonpressurized and Pressurized Endotherapeutic Treatments in Coconut Palms

Coconut cultivation faces serious challenges caused by pests and diseases, whose targets are often not reached by conventional application methods such as spraying and soil application. New control strategies, such as vegetative endotherapy, have emerged, but knowledge gaps persist regarding many aspects, especially in pesticide translocation within palm trees, which is crucial for an efficient practical field application. This study investigated the translocation of a mixture of commercial insecticides and fungicides—difenoconazole, imidacloprid, thiabendazole, cyproconazole, thiamethoxam, spirodiclofen, and carbosulfan—applied via pressurized and nonpressurized endotherapeutic methods to coconut stems. This assessment aimed to quantify the concentrations of pesticide translocation through the stem, from the application site to the plant canopy. Due to the difficulty of applying the solution to the instrument used for pressurized endotherapy, the solution had to be diluted and used at a lower volume. In experimental field conditions, stem samples were assessed at 50 and 100 cm above the application point following endotherapy treatments conducted over a period ranging from 2 to 45 days. The analyses were performed using LC-MS/MS. In the pressurized method, the highest concentrations were observed for difenoconazole (1684 µg kg−1), imidacloprid (1278 µg kg−1), and thiabendazole (781 µg kg−1). Conversely, in the nonpressurized method, the highest concentrations were recorded for imidacloprid (5803 µg kg−1), followed by difenoconazole (3660 µg kg−1) and thiabendazole (2598 µg kg−1). To address the issue with formulation conditions in the pressurized method and to allow a comparison between the two application methods, we simulated extrapolated results for comparison with the nonpressurized method. This evaluation aimed to evaluate both methods under similar formulation conditions (volume and concentration). The results predicted that if the solution had not been diluted, the pressurized method would present the best translocations, mainly near the plant canopy, except for carbofuran. All pesticides were translocated independently of their physical–chemical properties or formulation. No pesticide residues were detected in the coconut water and pulp up to 120 days after the endotherapy application.

Functional Roles of Two β-Tubulin Isotypes in Regulation of Sensitivity of Colletotrichum fructicola to Carbendazim.

Colletotrichum fructicola is the major pathogen of anthracnose in tea-oil trees in China. Control of anthracnose in tea-oil trees mainly depends on the application of chemical fungicides such as carbendazim. However, the current sensitivity of C. fructicola isolates in tea-oil trees to carbendazim has not been reported. Here, we tested the sensitivity of 121 C. fructicola isolates collected from Guangdong, Guangxi, Guizhou, Hainan, Hunan, Jiangsu, and Jiangxi provinces in China to carbendazim. One hundred and ten isolates were sensitive to carbendazim, and 11 isolates were highly resistant to carbendazim. The growth rates, morphology, and pathogenicity of three resistant isolates were identical to those of three sensitive isolates, which indicates that these resistant isolates could form a resistant population under carbendazim application. These results suggest that carbendazim should not be the sole fungicide in control of anthracnose in tea-oil trees; other fungicides with different mechanisms of action or mixtures of fungicides could be considered. In addition, bioinformatics analysis identified two β-tubulin isotypes in C. fructicola: Cfβ1tub and Cfβ2tub. E198A mutation was discovered in the Cfβ2tub of three carbendazim-resistant isolates. We also investigated the functional roles of two β-tubulin isotypes. CfΔβ1tub exhibited slightly increased sensitivity to carbendazim and normal phenotypes. Surprisingly, CfΔβ2tub was highly resistant to carbendazim and showed a seriously decreased growth rate, conidial production, pathogenicity, and abnormal hyphae morphology. Promoter replacement mutant CfΔβ2-2×β1 showed partly restored phenotypes, but it was still highly resistant to carbendazim, which suggests that Cfβ1tub and Cfβ2tub are functionally interchangeable to a certain degree.

Preliminary study for evaluation of some fungicides against Aspergillus flavus isolated from historical illuminated paper manuscript dated back to the Mamluk period

Various valuable illuminated paper manuscripts in museums and libraries suffer from fungal deterioration. The treatment and protection of illuminated paper manuscripts from fungal damage is an important process. Therefore, the current study aimed to evaluate different fungicides against fungi isolated from historical illuminated paper manuscript dated back to the Mamluk period (1250–1516 AD). Fungi isolated from infected historical illuminated paper manuscripts were identified and their cellulolytic enzyme activity was performed. The identified fungi were A. fumigatus, A. niger, A. flavus, Alternaria alternate, and Trichoderma sp. Isolate (4-1), identified as Aspergillus flavus, possessed the highest cellulase activity. This isolate was tested against the following fungicides: azoxystrobin, boscalid, difenoconazole, dimethomorph, propiconazole, pyraclostrobin, and thiophanate-methyl at concentrations from 1 to 200 ppm, nanoparticles of TiO2 and SiO2 at concentrations of 0.5%, and 1% and mixtures of fungicides [difenoconazole + propiconazole (1:1)] at 100 and 200 ppm and [boscalid + pyraclostrobin (2:1)] at 150 and 300 ppm. The disc diffusion method (DDM) was used to evaluate the efficiency of the prepared individual and mixed fungicides against Aspergillus flavus (4-1) isolate. The results of this study revealed that treatments with individual difenoconazole at 200 ppm exhibited the best antifungal activity, followed by the propiconazole fungicide. Further research is needed to evaluate the in vitro practical application of these fungicides with infected illuminated paper samples with Aspergillus flavus agents in the field.

Do Growers Using Solo Fungicides Affect the Durability of Disease Control of Growers Using Mixtures and Alternations? The Case of Spot-Form Net Blotch in Western Australia.

Growers often use alternations or mixtures of fungicides to slow down the development of resistance to fungicides. However, within a landscape, some growers will implement such resistance management methods, whereas others do not, and may even apply solo components of the resistance management program. We investigated whether growers using solo components of resistant management programs affect the durability of disease control in fields of those who implement fungicide resistance management. We developed a spatially implicit semidiscrete epidemiological model for the development of fungicide resistance. The model simulates the development of epidemics of spot-form net blotch disease, caused by the pathogen Pyrenophora teres f. maculata. The landscape comprises three types of fields, grouped according to their treatment program, with spore dispersal between fields early in the cropping season. In one field type, a fungicide resistance management method is implemented, whereas in the two others, it is not, with one of these field types using a component of the fungicide resistance management program. The output of the model suggests that the use of component fungicides does affect the durability of disease control for growers using resistance management programs. The magnitude of the effect depends on the characteristics of the pathosystem, the degree of inoculum mixing between fields, and the resistance management program being used. Additionally, although increasing the amount of the solo component in the landscape generally decreases the lifespan within which the resistance management program provides effective control, situations exist where the lifespan may be minimized at intermediate levels of the solo component fungicide. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Sensitivity of Argentine Pyrenophora teres f. teres isolates to different fungicide mixtures

Net blotch disease, caused by Pyrenophora teres f. teres (Ptt), is one of the most serious diseases of barley in Argentina. The in vitro sensitivity profile of Ptt to different fungicide mixtures currently used in Argentina was determined in isolates from different localities. Mycelial growth inhibition was measured, and the 50% inhibitory concentration (EC50) was estimated by simple logarithmic regression. In addition, the in vivo sensitivity of Ptt to the application of fluxapyroxad 5% + epoxiconazole 5% + pyraclostrobin 8.1% (FEP) was evaluated in greenhouse and field trials. The EC50 values ranged from 0.004 to 0.527 µg/mL, indicating that the fungicide mixtures tested were highly fungitoxic to all Ptt isolates tested. The in vivo and field fungicide efficacy averaged 99.9% and 79.5%, confirming a correlation between in vitro and in vivo sensitivity. The fungicide mixtures evaluated here were all highly fungitoxic and efficient for managing net blotch.