Field profiling for net blotch fungicide resistance in the low-medium rainfall zone

Key messages

  • Spot form net blotch was the most common form of the disease in the sampled fields.
  • Reduced sensitivity and resistance in net blotch to demethylation inhibitor (DMI; FRAC Group 3) fungicides is widespread across the low-medium rainfall zone.
  • Reduced sensitivity and resistance in net blotch to succinate dehydrogenase inhibitor (SDHI; FRAC Group 7) fungicides appears to be regionally isolated.
  • Fungicide application strategies should include mixed modes of action and can be informed by testing field samples.
  • Determine the presence and frequency of reduced sensitivity and resistance to DMI and SDHI fungicides in barley fields affected by net blotch.

Aims

  • Determine the presence and frequency of reduced sensitivity and resistance to DMI and SDHI fungicides in barley fields affected by net blotch.

Introduction

Fungicide resistance in the spot form (Pyrenophora teres f. maculata) and net form (P. teres f. teres) net blotch pathogens has become an important disease management issue. Control of these barley foliar diseases relies on three major classes of fungicides, DMIs, SDHIs and quinone outside inhibitors (QoI).

In Western Australia, reduced sensitivity and resistance to DMI fungicides in net blotch was first reported in 2016 (Mair et al 2016; Mair et al 2020), while reduced sensitivity and resistance to SDHI fungicides was reported in 2020 in areas surrounding Cunderdin (Mair et al 2021). Variation in genes of target proteins was identified and associated with reduced sensitivity or resistance. This information was used to enable detection of reduced sensitive or resistant types with a phenotyping and genotyping workflow (Knight et al 2021). Phenotyping uses fungal cultures grown directly from disease lesions and compares growth on discriminatory doses of the reference compounds tebuconazole (DMI) and fluxapyroxad (SDHI). Genotyping uses PCR to detect DNA sequences associated with sensitivity, reduced sensitivity or resistance to the DMI and SDHI fungicides.

This study used the phenotyping and genotyping workflows to investigate net blotch collections from twenty barley fields in the low-medium rainfall zone of Western Australia and determine the fungicide resistance frequency and diversity. The results from this study will aid in the development of improved strategies for the management of resistance to DMI and SDHI fungicides in net blotch diseases.

Method

Net blotch field sampling

Twenty barley fields across the Avon and Central East sub-regions were identified for sampling of net blotch disease (Figure 1). The sampling strategy consisted of leaf collection at four points across three zigzag transects in each field (Figure 2). A minimum of 10 symptomatic leaves were collected at each of the 12 sampling points in each field, preferentially targeting the upper three leaves. Sampling of leaves occurred at mid to late grain fill in September 2021. Within six hours, samples were placed at room temperature to dry.

Figure 1

Figure 2

Fungicide resistance phenotyping

Leaf samples were surface sterilised by washing for 30 seconds in 70% ethanol, 60 seconds in 1% NaOH and 2× 60 seconds in sterile water. Sections of lesions were removed and inserted into potato dextrose agar (PDA).

Fungal growth was assessed after seven days, and cultures morphologically determined to be P. teres were sampled and suspended in 500µL of sterile water. Hyphal fragments were generated by milling at 30 Hz for 2× 10 seconds (Retsch MM400). A 10µL volume of the hyphal suspension was placed onto control or fungicide amended media. Fungicide amended media included tebuconazole (DMI; 0µg/mL, 15µg/mL and 50µg/mL) in PDA or fluxapyroxad (SDHI; 0µg/mL, 2µg/mL, 5µg/mL and 10µg/mL) in yeast bacto acetate agar. Growth was assessed at seven days after plating on each discriminatory dose.

Genotyping for fungicide resistance alleles

For each field, a single lesion was taken from five leaves at each sampling point. These lesions were pooled across the 12 sampling points, resulting in 60 pooled lesions per field. Tissues were dried at 65°C overnight, ground for 60 seconds at 30Hz (Retsch MM400) and DNA extracted from two sub-samples (20mg) using a BioSprint 15 DNA Plant Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions.

Each sample was tested in a QX200 Droplet Digital PCR System (Bio-Rad, California, United Sates). PCR assays were initially used to detect and quantify the fungal form, either spot form or net form net blotch pathogens. Each sample was then assessed for the presence of a range of genotypes associated with sensitivity, reduced sensitivity or resistance to DMI and SDHI fungicides. Each PCR reaction was initially created in a 22μL volume containing 11μL ddPCR Supermix for Probes (No dUTP) (Bio-Rad) and 5μL of DNA template. Following droplet generation and PCR, droplets were read and analysed in the QX Manager (Bio-Rad) software. Results are reported as number of copies of each target in a reaction.

Results

Fungicide resistance phenotyping

Twenty barley fields were sampled in September 2021 across the Avon and Central East sub-regions. Samples were phenotyped to detect the presence of reduced sensitive and resistant types on tebuconazole and fluxapyroxad. Phenotyping indicated 80% and 95% of fields had reduced sensitive and resistant types to DMI fungicides, while 45% and 30% had reduced sensitive and resistant types to SDHI fungicides, respectively (Table 1).

Within fields the frequency of reduced sensitivity and resistance to DMI fungicides ranged from 38 to 100%, while the frequency of reduced sensitivity and resistance to SDHI fungicides ranged from 0 to 100%. Across the entire collection the frequency of reduced sensitivity and resistance to DMI fungicides was 69%, while the frequency of reduced sensitivity and resistance to SDHI fungicides was 34%.

Table 1

Genotyping for fungicide resistance alleles

Genotyping with digital PCR indicated all fields were primarily affected by spot form net blotch. Within field populations, the prevalence of genotypes associated with DMI reduced sensitivity or resistance ranged from 5 to 92%, while genotypes associated with SDHI reduced sensitivity or resistance ranged from 0 to 81% (Table 2).

Across the entire collection the frequency of genotypes associated with DMI resistance was 31%, while the frequency of genotypes associated with SDHI resistance was 18%.

Fungicide applications varied between fields, however no strategy resulted in populations with less than 10% of both DMI and SDHI resistant types.

Table 2

Conclusion

The widespread and frequent detection of net blotch fungi with reduced sensitivity and resistance to DMI and SDHI fungicides highlights the need to manage fungicide strategies by rotating modes of action and use mixtures when available. These strategies may need to encompass multiple seasons to allow adequate rotations.

Phenotyping and genotyping both indicated the greater frequency of reduced sensitivity and resistance to DMI fungicides compared to SDHI fungicides. This may reflect the usage patterns of these modes of action across seasons.

The comprehensive assessment of resistance frequencies provides an in-depth view of fungicide resistance in net blotch field populations. This will inform the next important research questions, primarily investigating the impact of these frequencies on disease control and the potential association with fungicide usage patterns.

Acknowledgments

The research undertaken as part of this project is made possible by the significant contributions of growers and advisors through both field identification and access and the support of the GRDC, the authors would like to thank them for their continued support. The authors would like to specifically thank Dan Taylor (DKT Rural Agencies) and Dani Whyte (Braeleigh Consulting) for field identification, students from the Integrated Pest Management unit taught at Curtin University for sample contribution and the Fungicide Resistance Group (CCDM, Curtin University) for excellent technical support.

References

Knight, N., Mair, W., Chandra, K., and Lopez-Ruiz, F. 2021. New horizons in the detection of fungicide resistance – combining genetic testing with in vitro assessment of fungicide performance. in: GRDC Grains Research Update, Crown Perth, Burswood.

Mair, W., Lopez-Ruiz, F., Knight, N., Chandra, K., and Taylor, D. 2021. First report of SDHI resistance in barley spot form net blotch in WA. in: GRDC Grains Research Update, Crown Perth, Burswood.

Mair, W. J., Deng, W., Mullins, J. G. L., West, S., Wang, P., Besharat, N., Ellwood, S. R., Oliver, R. P., and Lopez-Ruiz, F. J. 2016. Demethylase inhibitor fungicide resistance in Pyrenophora teres f. sp. teres associated with target site modification and inducible overexpression of Cyp51. Front. Microbiol. 7:1279.

Mair, W. J., Thomas, G. J., Dodhia, K., Hills, A. L., Jayasena, K. W., Ellwood, S. R., Oliver, R. P., and Lopez-Ruiz, F. J. 2020. Parallel evolution of multiple mechanisms for demethylase inhibitor fungicide resistance in the barley pathogen Pyrenophora teres f. sp. maculata. Fungal Genet. Biol. 145:103475.

Contact details

Noel Knight
Centre for Crop and Disease Management
Curtin University
Email: noel.knight@curtin.edu.au

GRDC Project code: CUR00023