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Article

Baseline Sensitivity of Leptosphaeria maculans to Succinate Dehydrogenase Inhibitor (SDHI) Fungicides and Development of Molecular Markers for Future Monitoring

by
Alec J. McCallum
,
Alexander Idnurm
and
Angela P. Van de Wouw
*
School of BioSciences, University of Melbourne, Victoria 3010, Australia
*
Author to whom correspondence should be addressed.
Agriculture 2025, 15(15), 1591; https://doi.org/10.3390/agriculture15151591
Submission received: 17 June 2025 / Revised: 14 July 2025 / Accepted: 16 July 2025 / Published: 24 July 2025
(This article belongs to the Section Crop Protection, Diseases, Pests and Weeds)
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Versions Notes

Abstract

Succinate dehydrogenase inhibitor (SDHI) fungicides are widely used in Australia for the control of blackleg disease (caused by Leptosphaeria maculans, also called Plenodomus lingam). Populations of L. maculans are highly variable and therefore at risk of evolving fungicide resistance. The baseline sensitivities of L. maculans isolates towards the SDHI fungicides pydiflumetofen and bixafen were determined through in vitro mycelial growth assays, and the mean EC50s were found to be 4.89 and 2.71 ng mL−1, respectively. L. maculans populations were also screened against three commercial SDHI fungicides, Saltro®, ILeVO®, and Aviator®, using an in planta assay to reveal very low levels of resistance. Nineteen of these ascospore populations from 2022 were analysed in a deep amplicon sequencing (DAS) assay and showed no mutations in the genes likely to be associated with resistance to SDHI chemistries. This study establishes baseline sensitivities of L. maculans isolates towards commonly used SDHI fungicides, importantly before and during the introduction of these new chemistries for blackleg control, and outlines monitoring techniques to allow timely identification of resistance if it evolves.

1. Introduction

Fungicides have become an integral part of controlling disease within agricultural crops, and the control of blackleg disease of canola is no exception. This disease of canola (Brassica napus, oilseed rape), caused by the pathogen Leptosphaeria maculans (also called Plenodomus lingam), is one of the major constraints to canola production worldwide [1]. Whilst management of the disease is achieved through the combination of genetic resistance, cultural practices, and fungicide applications, growers have become increasingly reliant on fungicides [2,3]. A survey of Australian canola growers revealed that fungicide applications had increased from 52% of growers using a single fungicide in 2000 to 95% of growers using at least one fungicide in 2018, with an average of two or three per season [3]. Similarly, in the UK, oilseed rape crops are exposed to an average of three fungicide applications per growing season, although not always targeted at blackleg [4]. While blackleg is also a significant problem in Canada [1,5], the main fungicide use is for the control of Sclerotinia, with 78% of crops receiving fungicides and an average of one application per growing season [6].
For blackleg disease of canola, there are 12 fungicides registered in Australia, representing three different modes of action—the demethylation inhibitors (DMI, Fungicide Resistance Action Committee [FRAC] group 3), quinone outside inhibitors (QOI, FRAC group 11), and succinate dehydrogenase inhibitors (SDHI, FRAC group 7). The DMI fungicides inhibit the ERG11/Cyp51 enzyme involved in ergosterol biosynthesis [7], and the first DMI fungicide, with flutriafol as the active ingredient, was released in Australia in 1997 as a fertiliser-amended fungicide (trade name Impact in Furrow®) [3]. Since then, fluquinconazole was released as a seed-dressing (2003, trade name Jockey Stayer®), and a mixture of prothioconazole and tebuconazole (trade name Prosaro®) was released as a foliar fungicide in 2011 [3]. The DMI actives prothioconazole, tebuconazole, and more recently, mefentrifluconazole are also used as mixing partners with both SDHI and QOI chemistries.
Both the QOI and SDHI fungicides target respiration and are relatively new options for controlling blackleg in Australia compared to the DMI fungicides, with the first SDHI fungicide registered in 2016. The QOI fungicides bind to the Quinone outside (QO) site of the cytochrome b, which is part of the cytochrome bc1 complex that is essential for respiration [8]. There are currently three QOI fungicides registered in Australia, each with the same active ingredient (azoxystrobin) and each used in combination with a DMI fungicide and only as a foliar application. The SDHI fungicides inhibit the mitochondrial SDH enzyme, which has a dual role of being involved in mitochondrial respiration and the citric acid cycle [9]. In Australia, there are four different SDHI actives registered for blackleg (bixafen, pydiflumetofen, fluopyram, and fluxapyroxad), and these are available as seed treatments or foliar fungicides and as either single chemistry solutions or as a mixture with a DMI.
While fungicides provide excellent control of diseases, unfortunately, with increased use comes the risk of fungicide resistance evolving. Resistance to the DMI fungicides has been detected in L. maculans populations in Australia and Europe [2,10,11,12,13,14]. Resistance is conferred by insertions within the promoter region of the ERG11 gene, leading to increased gene expression and therefore an increased tolerance to the DMI fungicides [10,12,13]. Despite the detection of these mutations, DMI fungicides are still providing effective control of blackleg in the field, and sensitivity is described as ‘stable’ by FRAC in Europe [15].
No resistance to the QOI fungicides has been reported for blackleg in Australia [16] or elsewhere [17]. However, decreased sensitivity has been reported in populations from Canada [18]. Resistance to the QOI fungicides has been reported in plant pathogens as conferred by mutations within the cytochrome b gene. The most common mutation results in an amino acid substitution of glycine with alanine at position 143 (G143A) of the protein, with other point mutations within the gene reported at a lower frequency [8].
Very little information is known about the current sensitivity of blackleg populations to the SDHI fungicides in Australia. In Europe, FRAC has not identified any SDHI resistance to date [19]. In other pathogenic species, resistance to the SDHI chemistries is often conferred by point mutations in one or multiple of the sdhB, sdhC, and/or sdhD genes, which encode subunits of the SDH complex that is targeted by these fungicides [9,20].
With the recent introduction of SDHI fungicides for the control of blackleg of canola in Australia, combined with the increased use of fungicides in general, there is a strong need to monitor populations for changes in fungicide resistance [21]. This paper details protocols and tools for such monitoring as well as the baseline status of blackleg populations in Australia.

2. Materials and Methods

2.1. Isolate Collection and Preparation

Twenty-four isolates were selected from the University of Melbourne blackleg collection. These isolates were collected between 1988 and 2022, with half of them collected prior to the registration of the first SDHI fungicide (2016) and half of them collected after that time (Supplementary Table S1). All isolates were grown from long-term storage on cellulose discs on 10% V8 media. After 10 days, agar plugs were transferred to fresh 10% V8 media, and then these were used to inoculate fungicide-amended media. All isolates were grown at 22 °C with a 12–12 h photoperiod.

2.2. In Vitro Mycelial Inhibition Assays

The EC50s of 24 isolates were determined for two SDHI actives, bixafen and pydiflumetofen, using mycelial inhibition assays, as previously described [13]. Sterile stock solutions were made for each of the actives by mixing active powders with a 10% EtOH/90% DMSO solution. Eight concentrations (0.5–305.2 ng mL−1, 2.5-fold series) of each active were created through a serial dilution. Each experiment also included an untreated control with no fungicide active but still amended with 0.09% DMSO and 0.01% EtOH. Plugs (5 mm diameter) from actively growing cultures were placed on the different media left to grow for 5 days before the culture diameter was measured in two perpendicular directions. The 5 mm diameter of the plug was subtracted from the culture diameter, which was then averaged to determine the growth of the isolate. Using R Statistical Software v4.3.0 [22], growth as a function of fungicide concentration was fitted to a dose–response curve using the drm() function with EC50s estimated using the ED() function from the drc package [23]. Correlations between chemistries were analysed using the lm() function in the stats package [22].

2.3. Fungicide Resistance Survey of Leptosphaeria maculans Field Populations

A total of 710 L. maculans populations was screened for resistance to three commercially registered SDHI fungicides, Aviator XPro®, ILeVO®, Saltro®, and one DMI fungicide, Prosaro® between 2018 and 2023, as previously described [2,24]. The fungicides, active ingredients, and application rates are listed in Table 1. The data from 2018 to 2020 were previously reported by Van de Wouw et al. [2]. Canola stubble (crop debris) was collected from fields at the end of each growing season, then matured over the summer/autumn months before being used to inoculate seedlings treated with the commercially available fungicides. For 584 of the stubble samples, the growers or agronomists who collected the stubble also provided data on their fungicide use over time. To inoculate seedlings, stubble was suspended above the seedlings and kept at 100% humidity to promote ascospore release from the infected stubble. Seedlings were treated with fungicides at the commercial rates as previously described [2]. Fourteen days post inoculation, the presence of lesions was scored on all seedlings, and a normalised Disease Score (DS) was calculated for each fungicide treatment for each population, where the DS is the ratio of disease on the treatments compared to the untreated control [2]. A DS > 0.5 is categorised as high disease, between 0.1 and 0.5 is moderate, between 0 and 0.1 is low, and 0 is no disease.
Isolates were also collected from lesions that formed on SDHI-treated plants. Lesions were excised from cotyledons and surfaced sterilised with a 10% bleach solution. The lesions were then plated onto V8 media treated with ampicillin and pydiflumetofen at a concentration of 100 ng mL−1.

2.4. Sanger Sequencing of SDHI Target Genes

The sdhB, sdhC, and sdhD gene regions and promoters were sequenced for eight representative isolates used in the mycelial inhibition assays (Supplementary Table S1). Genomic DNA was extracted from mycelia of each of the isolates using the Qiagen DNeasy Plant Mini extraction kit according to the manufacturer’s instructions. Primers (Table 2) were designed to amplify the full coding region of each of the genes and amplified using the following PCR conditions: 95 °C for 3 min, then 35 cycles of 94 °C for 30 s, 62 °C for 30 s, and 72 °C for 120 s. The PCR conditions for the promoters were the same except with an extension time of 60 s. PCR products were purified using a Qiagen QIAquick PCR Purification Kit according to the manufacturer’s instructions. Amplicons were sequenced using Sanger chemistry at the Australian Genome Research Facility in Melbourne, Australia, and analysed using Geneious version R9.0.5.

2.5. Deep Amplicon Sequencing (DAS) Markers for Fungal Population Monitoring

Ascospores were liberated from 19 stubble samples from the 2023 fungicide resistance population survey using a Burkard spore liberator as previously described [25]. Following liberation, ascospores were germinated in 10% cleared liquid V8 media for 48 h before being freeze-dried. Genomic DNA was extracted using a Qiagen DNeasy Plant Mini extraction kit (Qiagen, Clayton, Australia) according to the manufacturer’s instructions.
Since resistances to the SDHI fungicides have been associated with mutations in the sdhB, sdhC, and sdhD genes in other pathogens, these genes were analysed by Deep Amplicon Sequencing (DAS) using protocols as previously described [13,26]. Using the primers described in Table 2, each of the three gene regions was amplified and then purified as described in Section 2.4. Amplicons were then sequenced at the Australian Genome Research Facility (AGRF) using a single NovaSeq X lane, generating 150 bp paired-end reads. The raw data are available at NCBI BioProject PRJNA1278777.
Sequence reads were analysed as previously described [26]. Briefly, raw sequencing reads were trimmed to remove adapters and decontaminated against phiX Illumina spike-in using bbduk.sh in BBMap v39.01 [13,27]. Reads were then filtered into ‘mapping reads’ with average quality > 25 and length > 40 and ‘assembly reads’ with average quality > 35 and length > 100 using bbduk.sh. Contigs were assembled de novo using the assembly reads with SPAdes v3.15.5 [28]. The contigs and assembly graphs from SPAdes were used with the mapping reads to extract and reconstruct haplotypes using Vstrains v1.1.0 [29]. These novel haplotypes were combined with known alleles and combined into a FASTA file. The indexed FASTA was used with kallisto v0.48.0 [30] and the mapping reads to quantify the frequency of each allele, calculated as transcripts per million (TPM). TPM was converted to allele frequency by dividing by 104.

3. Results

3.1. Baseline Sensitivity of the SDHI Chemistries

Mycelial inhibition assays were performed on 24 L. maculans isolates using the SDHI fungicides, bixafen and pydiflumetofen, to calculate their EC50s (Table 3). For bixafen, EC50s ranged from 0.52 to 14.69 ng mL−1 with a mean of 2.71 ng mL−1, while EC50s for pydiflumetofen ranged from 1.79 to 13.59 ng mL−1 and had a mean of 4.89 ng mL−1. Sensitivity of the isolates was significantly correlated (p < 0.001, R2 = 0.502) between the two chemistries (Figure 1).

3.2. Field Sensitivity of the SDHI Chemistries

The sensitivity of four commercial fungicides was tested towards 710 L. maculans populations, with 203 of these populations screened in 2021–2023 and the remaining 507 from 2018 to 2020 previously reported by Van de Wouw et al. [2]. Each population was given a disease rating of high, moderate, low, or none for Saltro® (SDHI), ILeVO® (SDHI), Aviator® (SDHI + DMI), and Prosaro® (DMI) (Figure 2). For the fungicides containing an SDHI, the level of disease remained low in each year compared to the DMI fungicide, Proviso. For Saltro®, the frequency of no disease (disease rating of None) varied from 94.6% in 2023 to 100% in 2021. ILeVO® had 100% no disease in 2021 and 2023 and had its lowest level of no resistance in 2019 with 94.7%. There was no disease on Aviator in 2020 or 2021, which decreased to 94.7% no disease in 2023. No populations had a high level of disease to any of the SDHI chemistries. There were much higher levels of disease in Prosaro®, with the frequency of high disease varying from 0.9% in 2018 to 60.7% in 2023.
Isolates were collected from lesions that formed on plants treated with Saltro®, ILeVO®, or Aviator® and grown on media treated with 100 ng mL−1 pydiflumetofen. None of the isolates grew on these plates, indicating they are likely not resistant to the SDHI chemistries.
Analysis of the fungicide use data provided with the canola stubble samples revealed changing strategies between 2018 and 2023 (Figure 3). Use of DMI chemistries varied from as high as 2.8 applications per year in 2021 to 1.4 in 2023. In contrast, the use of SDHI chemistries increased substantially from 2021 onwards. The average number of applications from 2018 to 2020 was just 0.06, with only 18 out of 326 samples having at least one SDHI application. In comparison, from 2021 to 2023, the average number of SDHI applications increased to 1.3, with 85% of samples having at least one SDHI application. The use of QOI fungicides has remained low across the entire period.

3.3. Genetic Variation Within the SDHI Target Genes and Development of DAS Markers for Population Monitoring

Ascospores were liberated from 19 L. maculans populations from 2022 and put through a DAS assay. Details of the 19 populations, including origin and the resistance rating to Saltro®, ILeVO®, Aviator®, and Prosaro®, are shown in Table 4. The DAS assay identified SNPs that differed from the reference sequence (Figure 4) and determined genotype frequencies for the sdhB (Figure 5), sdhC (Figure 6), and sdhD (Figure 7) genes. Sequences of the genotypes can be found in Supplementary Data S1 (sdhB), S2 (sdhC), and S3 (sdhD).
For sdhB, two SNPs were detected in the coding region, with non-synonymous mutation A resulting in a threonine to alanine substitution at residue 156 (T156A) and synonymous mutation B not altering the amino acid sequence. Both of these mutations are present at high frequencies across all populations, with the isolate JN3 reference allele being almost completely absent (Table 5). All the isolates that were Sanger sequenced had the genotype AB with no variation in the promoter region.
There is a high level of variation in the sdhC genotype frequencies, with all genotypes (Reference, A, B, C, and D) varying from 0% to over 90% (Table 5). Mutations A and B are both SNPs located in the 3′ UTR, while mutation D is an SNP in the promoter region. The synonymous mutation C is in the codon for residue 86. None of the mutations were detected in the Sanger sequencing, with 100% of the isolates screened having the same sequence as the JN3 reference, including the promoter region.
A single SNP in sdhD was detected in only two populations (populations 1 and 2), with a maximum frequency of 9.3% (Table 5). The mutation A resulted in a synonymous SNP at residue 183. Mutation A was also not detected in the Sanger sequencing of isolates, and no variation was detected in the promoter region.

4. Discussion

The use of fungicides is an important strategy for controlling blackleg disease in Australian canola production systems. The DMI class of fungicides remains the most widely used for control of blackleg, but recent registration of new SDHI chemistries has seen a substantial rise in the use of these chemistries. The SDHIs are classed by FRAC as medium-high risk of having resistance evolve, and as such, require resistance management strategies to prevent or delay this from occurring [31]. Common resistance management tactics include mixing and rotating fungicide modes of action employing host genetic resistance and cultural practices to reduce disease pressure. A key aspect of fungicide resistance management is monitoring pathogen populations for the early detection of resistance [32]. This will allow for timely warnings to be supplied to growers to enable them to alter their fungicide practices to ensure effective disease control [33]. In order to detect resistance, it is important to establish a baseline sensitivity of the pathogen to be able to distinguish any changes over time.
There are currently four SDHI chemistries registered for the control of blackleg disease in Australia as follows: bixafen (in mixture with prothioconazole), pydiflumetofen, fluopyram, and fluxapyroxad (in mixture with mefentrifluconazole). In this study, baseline sensitivity of L. maculans was determined to the two most commonly used chemistries (bixafen and pydiflumetofen). EC50s for bixafen varied from 0.52 to 14.69 ng mL−1 and for pydiflumetofen varied from 1.79 to 13.59 ng mL−1. The EC50s for bixafen and pydiflumetofen were also significantly correlated, potentially indicating that cross-resistance may occur if resistance does arise. Sensitivity to bixafen has been characterised in other pathogens; for example, for Mycosphaerella graminicola [=Zymoseptoria tritici], EC50s varied from 19 to 664 ng mL−1 with a mean of 219 ng mL−1 [34], and for Sclerotinia sclerotiorum, EC50s varied from 41.7 to 409 ng mL−1 with a mean of 182 ng mL−1 [35]. Pydiflumetofen sensitivity has also been tested, for example, in Fusarium asiaticum with EC50s ranging from 19 to 208 ng mL−1 with a mean of 74.5 ng mL−1 [36] and Botrytis cinerea with EC50s ranging from 20 to 365 ng mL−1 with a mean of 196 ng mL−1 [37].
Two studies have previously assessed sensitivity of L. maculans to SDHI chemistries. Fajemisin et al. [38] found that the sensitivity to boscalid varied from 0.026 to 0.984 µg mL−1 with a mean of 0.17 µg mL−1 and did not find evidence of any resistance. The EC50s of three L. maculans isolates to pydiflumetofen were shown to be 362, 35, and 116 ng mL−1 for D1, D5, and D7, respectively [39]. This study also showed that pydiflumetofen was also effective at reducing disease symptoms in both glasshouse and field settings. D5 was also screened in the present study and was determined to have an EC50 of 2.58 ng mL−1 to pydiflumetofen, approximately 13.5 times lower than the finding of Padmathilake et al. [39].
The results of the field sensitivity screen indicate that disease occurring on plants treated with the SDHI chemistries is rare, with only a small number of samples having a low-moderate level of disease each year. The majority of the populations were collected from regions with intensive canola production and high fungicide use, potentially overestimating the frequency of low-moderate levels of disease across Australia. Even when low-moderate disease is exhibited in a sample, isolates collected from lesions were unable to grow on media treated with pydiflumetofen, further highlighting that resistance has likely not evolved. No mutations that are likely to be associated with resistance were detected in the sdhB, sdhC, or sdhD genes from the DAS assay. The only mutation that caused a substitution in the amino acid sequence was sdhB-T156A, but this mutation was present at high frequencies across all populations, and isolates with this polymorphism that were phenotyped had no resistance. The diversity of other mutations was highest in sdhC, with the four mutations and the reference varying between less than 5% and over 90% across populations. The least amount of variation was observed in sdhD, where only two populations contained an allele different from the reference. In this study, no target site mutations were observed in any isolates or populations, but there is the potential for mutations to exist in populations not screened or in these populations at frequencies below detectable levels. Alternatively, there may be non-target site mutations, such as increased efflux or detoxification, that are responsible for the low-moderate disease seen in the fungicide resistance survey [40,41].
The recent registration of new SDHI seed treatments and foliar fungicides for control of blackleg disease in Australia has considerably increased their use by growers. From 2018 to 2020, only 5.5% of canola crops received an SDHI fungicide, compared to 85% from 2021 to 2023, based on the stubble samples that were screened for resistance. This may not be representative of the entire canola industry, however, as samples typically came from high canola production and high fungicide use regions. This increase in fungicide use in canola has been shown previously, with the number of growers using at least one fungicide increasing from 52% in 2000 to 95% in 2018 [3]. This high use of fungicides has led to the evolution of resistance to the DMI chemistries [12,13] and may therefore also put the SDHI chemistries at high risk of resistance evolving.

5. Conclusions

The study presented is a unique situation, as we have been able to monitor and determine the baseline sensitivity of blackleg populations as the SDHI chemistries have been introduced. As increased use of the SDHI chemistries continues, we are in a position to continue monitoring and hopefully identify changes in population structure early and provide warnings to growers when needed.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agriculture15151591/s1, Table S1: Leptosphaeria maculans isolates used in this study; Supplementary Data S1–S3.

Author Contributions

Conceptualization, all; methodology, all; investigation, A.J.M. and A.P.V.d.W.; data analysis, A.J.M. and A.P.V.d.W.; writing—original draft preparation, A.J.M. and A.P.V.d.W.; writing—review and editing, all; supervision, A.P.V.d.W. and A.I.; project administration, A.P.V.d.W. and A.I.; funding acquisition, all. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by the Australian Research Council mid-career industry fellowship (IM230100025) with Syngenta and Marcroft Grains Pathology as industry partners as well as the Grains Research and Development Corporation (UOM2304-004RSX).

Data Availability Statement

The raw sequencing data are available at NCBI BioProject PRJNA1278777. The remaining data presented in this study are available on request from the corresponding author.

Acknowledgments

We thank the growers and agronomists for submitting their samples for analysis.

Conflicts of Interest

The authors have no conflicts of interest to declare.

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Agriculture 15 01591 g001
Figure 1. Correlation between the effective concentration for 50% inhibition (EC50) of bixafen (y-axis) and pydiflumetofen (x-axis) for the 24 Australian Leptosphaeria maculans isolates. The blue line indicates the linear regression.
Figure 1. Correlation between the effective concentration for 50% inhibition (EC50) of bixafen (y-axis) and pydiflumetofen (x-axis) for the 24 Australian Leptosphaeria maculans isolates. The blue line indicates the linear regression.
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Agriculture 15 01591 g002
Figure 2. Fungicide disease rating for the fungicides Prosaro®, Aviator XPro®, ILeVO®, and Saltro® in 2018–2023. Ratings are determined by the Disease Score (DS) for each Leptosphaeria maculans population are grouped into High (DS ≥ 0.5), Moderate (DS ≥ 0.1 and DS < 0.5), Low (DS > 0 and DS < 0.1), and None (DS = 0). The numbers of populations in each year were 107, 207, 78, 20, 103, and 56 for 2018–2023, respectively.
Figure 2. Fungicide disease rating for the fungicides Prosaro®, Aviator XPro®, ILeVO®, and Saltro® in 2018–2023. Ratings are determined by the Disease Score (DS) for each Leptosphaeria maculans population are grouped into High (DS ≥ 0.5), Moderate (DS ≥ 0.1 and DS < 0.5), Low (DS > 0 and DS < 0.1), and None (DS = 0). The numbers of populations in each year were 107, 207, 78, 20, 103, and 56 for 2018–2023, respectively.
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Agriculture 15 01591 g003
Figure 3. Mean number of DMI (red), QOI (green), or SDHI (blue) fungicide active applications per year from 2018 to 2023. Data are from fungicides applied to canola crop, from which stubble was collected. Error bars indicate standard error.
Figure 3. Mean number of DMI (red), QOI (green), or SDHI (blue) fungicide active applications per year from 2018 to 2023. Data are from fungicides applied to canola crop, from which stubble was collected. Error bars indicate standard error.
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Agriculture 15 01591 g004
Figure 4. Visualisation of the gene regions of sdhB (top), sdhC (middle), and sdhD (bottom). Locations of mutations are denoted by a red vertical line, and SNPs and amino acid substitutions are highlighted in red. Coding regions are indicated by blue rectangles. Mutations inside the coding region show the reference nucleotide and amino acid sequences (top two lines) and the mutated nucleotide and amino acid sequences (bottom two lines). Mutations outside of the coding region show the nucleotide sequences of the reference (top) and mutations (bottom). A 1 kb scale bar is indicated.
Figure 4. Visualisation of the gene regions of sdhB (top), sdhC (middle), and sdhD (bottom). Locations of mutations are denoted by a red vertical line, and SNPs and amino acid substitutions are highlighted in red. Coding regions are indicated by blue rectangles. Mutations inside the coding region show the reference nucleotide and amino acid sequences (top two lines) and the mutated nucleotide and amino acid sequences (bottom two lines). Mutations outside of the coding region show the nucleotide sequences of the reference (top) and mutations (bottom). A 1 kb scale bar is indicated.
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Figure 5. Frequency of sdhB genotypes for 19 L. maculans populations from 2022.
Figure 5. Frequency of sdhB genotypes for 19 L. maculans populations from 2022.
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Figure 6. Frequency of sdhC genotypes for 19 L. maculans populations from 2022.
Figure 6. Frequency of sdhC genotypes for 19 L. maculans populations from 2022.
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Figure 7. Frequency of sdhD genotypes for 19 L. maculans populations from 2022.
Figure 7. Frequency of sdhD genotypes for 19 L. maculans populations from 2022.
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Table 1. The trade name, active ingredient/s, FRAC group/s, and application rates of four fungicides used in the fungicide resistance survey.
Table 1. The trade name, active ingredient/s, FRAC group/s, and application rates of four fungicides used in the fungicide resistance survey.
Trade NameManufacturer 1Active Ingredients/sFRAC Group/s Application Rate
Aviator XPro®Bayer CropscienceBixafen +
prothioconazole		7 + 3550 mL ha−1
Saltro®SyngentaPydiflumetofen72 mL kg−1 seed
ILeVO®BASFFluopyram78 mL kg−1 seed
Prosaro®Bayer AustraliaProthioconazole +
tebuconazole		3 + 3375 mL ha−1
1 All chemicals sources directly from the Australian based manufacturers.
Table 2. Primers used in this study.
Table 2. Primers used in this study.
GenePrimer NamePrimer SequenceRegion Description
sdhBLmsdhB-1FCGGTCCAACTCGATGATTGCCodingSanger sequencing and Deep Amplicon Sequencing
LmsdhB-1RTGATGAAAAAGAATTTGTGACTCGCCodingSanger sequencing and Deep Amplicon Sequencing
LmsdhBp-1FTTTTGCCGTTGGTTGTGAGGPromoterSanger sequencing
LmsdhBp-1RCTTCTCCGAGACAGGCTTCCPromoterSanger sequencing
sdhCLmsdhC-1FCGGGTTGTTCTTTTCTTCCGCCodingSanger sequencing and Deep Amplicon Sequencing
LmsdhC-1RATCGAGACGTGACTAAGCAGCCodingSanger sequencing and Deep Amplicon Sequencing
LmsdhCp-1FGCTTGGCAGGTGCATACCTAPromoterSanger sequencing
LmsdhCp-1RAGGGGTGGGAGAGTTCCAAAPromoterSanger sequencing
sdhDLmsdhD-1FAAACCATTTTTCAGCGTTGTCGCodingSanger sequencing and Deep Amplicon Sequencing
LmsdhD-1RTATCAAGATGCCACGCCTACCodingSanger sequencing and Deep Amplicon Sequencing
LmsdhDp-1FCAGAATGACATCACGCTCGCPromoterSanger sequencing
LmsdhDp-1RCGGGTAGTAGAGGTGGTGACPromoterSanger sequencing
Table 3. The effective concentration for 50% inhibition (EC50) of the succinate dehydrogenase inhibiting (SDHI) fungicides pydiflumetofen and bixafen for 24 Australian Leptosphaeria maculans isolates.
Table 3. The effective concentration for 50% inhibition (EC50) of the succinate dehydrogenase inhibiting (SDHI) fungicides pydiflumetofen and bixafen for 24 Australian Leptosphaeria maculans isolates.
BixafenPydiflumetofen
IsolateEC50 (ng mL−1)seEC50 (ng mL−1)se
D21.370.365.432.00
D31.380.094.220.66
D40.660.073.20.31
D52.90.232.580.21
D80.520.122.890.29
D92.690.554.121.58
D142.170.226.090.75
D162.090.135.630.79
D1714.692.1413.593.79
D202.180.737.621.47
D212.320.118.361.07
D221.920.421.790.66
D231.670.183.810.51
D254.10.884.170.61
D260.960.083.390.47
D271.570.193.10.36
15BL9971.20.265.381.17
15BL10022.130.245.260.88
18BL1512.310.274.120.80
20BL2001.880.413.520.54
22BL1217.521.744.30.50
22BL1231.390.144.610.62
22BL1312.790.384.550.49
22BL1322.571.605.682.17
Table 4. Location details of the 19 Leptosphaeria maculans stubble populations from 2022 and the level of resistance towards Saltro®, ILeVO®, Aviator®, and Prosaro®.
Table 4. Location details of the 19 Leptosphaeria maculans stubble populations from 2022 and the level of resistance towards Saltro®, ILeVO®, Aviator®, and Prosaro®.
Population DetailsResistance Rating
NumberLocalityStateSaltro®ILeVO®Aviator®Prosaro®
1Edilillie SANoneNoneNoneModerate
2KarkooSANoneNoneNoneNone
3KapinnieSANoneNoneNoneNone
4HincksSANoneNoneNoneNone
5HincksSANoneNoneNoneModerate
6WangarySANoneNoneNoneLow
7CockaleechieSANoneNoneLowModerate
8CockaleechieSANoneModerateNoneLow
9YeelannaSANoneNoneNoneNone
10Wagga WaggaNSWNoneNoneNoneModerate
11GalongNSWNoneNoneNoneModerate
12YoungNSWNoneLowNoneModerate
13IandraNSWNoneNoneNoneLow
14GreenethorpeNSWNoneNoneNoneNone
15BerthongNSWNoneNoneNoneNone
16YoungNSWNoneNoneNoneModerate
17CunningarNSWNoneNoneNoneModerate
18CowraNSWNoneNoneNoneNone
19CudalNSWLowNoneNoneNone
Table 5. Variation (minimum and maximum) in genotype frequencies for sdhB, sdhC, and sdhD.
Table 5. Variation (minimum and maximum) in genotype frequencies for sdhB, sdhC, and sdhD.
GenotypesdhBsdhCsdhD
Ref0–0.540–90.390.7–100
A55.3–99.80.04–90.90–9.3
B97.1–1002.7–99.1-
C-3.3–99.3-
D-3.2–99-
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McCallum, A.J.; Idnurm, A.; Van de Wouw, A.P. Baseline Sensitivity of Leptosphaeria maculans to Succinate Dehydrogenase Inhibitor (SDHI) Fungicides and Development of Molecular Markers for Future Monitoring. Agriculture 2025, 15, 1591. https://doi.org/10.3390/agriculture15151591

AMA Style

McCallum AJ, Idnurm A, Van de Wouw AP. Baseline Sensitivity of Leptosphaeria maculans to Succinate Dehydrogenase Inhibitor (SDHI) Fungicides and Development of Molecular Markers for Future Monitoring. Agriculture. 2025; 15(15):1591. https://doi.org/10.3390/agriculture15151591

Chicago/Turabian Style

McCallum, Alec J., Alexander Idnurm, and Angela P. Van de Wouw. 2025. "Baseline Sensitivity of Leptosphaeria maculans to Succinate Dehydrogenase Inhibitor (SDHI) Fungicides and Development of Molecular Markers for Future Monitoring" Agriculture 15, no. 15: 1591. https://doi.org/10.3390/agriculture15151591

APA Style

McCallum, A. J., Idnurm, A., & Van de Wouw, A. P. (2025). Baseline Sensitivity of Leptosphaeria maculans to Succinate Dehydrogenase Inhibitor (SDHI) Fungicides and Development of Molecular Markers for Future Monitoring. Agriculture, 15(15), 1591. https://doi.org/10.3390/agriculture15151591

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