Evidence map›Paper›PMID 41656718›Full record

ArticleThe plant pathology journal2026

Quantitative Sequencing as a High-Throughput Tool for Monitoring QoI Fungicide Resistance in Colletotrichum scovillei Causing Pepper Anthracnose.

Dalha Abdulkadir Isa, Sohyeon An, Heung Tae Kim

Abstract read
In one paragraph

Article in The plant pathology journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Dalha Abdulkadir IsaDepartment of Plant Medicine, Chungbuk National University, Cheongju 28644, Korea.
Sohyeon AnDepartment of Plant Medicine, Chungbuk National University, Cheongju 28644, Korea.
Heung Tae KimDepartment of Plant Medicine, Chungbuk National University, Cheongju 28644, Korea.

Funding

Agriculture Science & Technology Development RS-2024-00398990
6 · The paper itself

Abstract

Anthracnose caused by Colletotrichum scovillei is a major constraint on red pepper (Capsicum annuum) production in South Korea. Intensive use of quinone outside inhibitor (QoI) fungicides has led to widespread resistance, mainly associated with the G143A mutation in the cytochrome b gene. Rapid and reliable resistance monitoring is required to support sustainable disease management. This study evaluated quantitative sequencing (QS) as a molecular tool for detecting and quantifying QoI resistance allele frequencies. Genomic DNA and spore suspensions of pyraclostrobin-sensitive and -resistant isolates were mixed at known ratios to generate pseudo-populations. QS accurately reflected the expected G143A allele frequencies, showing nearly perfect linear correlations (R² > 0.99) for both genomic DNA and spore pools. The applicability of QS was further confirmed using artificially inoculated pepper fruits, where allele frequencies determined from lesion-derived DNA were consistent with inoculum ratios. Field surveys conducted from 2020 to 2023 revealed that the frequency of pyraclostrobin-resistant isolates increased from 72.0% to 91.6%. Resistance frequencies obtained by QS were strongly correlated with those determined by the conventional mass agar dilution method (R² = 0.82-0.97), validating QS as a high-throughput monitoring tool. These results demonstrate that QS provides a robust, sensitive, and scalable approach for monitoring fungicide resistance in C. scovillei populations and can be implemented to guide fungicide use strategies and delay further resistance development.

Indexed as

Colletotrichum scovilleifungicide resistancepyraclostrobinquantitative sequencing

Identifiers

PMID41656718
PMCPMC12884051

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.