Plant disease最新文献

Fluazinam, a fungicide widely used in agriculture and turf management, was traditionally thought to pose a low risk of resistance. However, our in vitro sensitivity test conducted in 2021 revealed reduced sensitivity to fluazinam in dollar spot, highlighting the need for more vigilant field monitoring. In 2022 and 2023, we evaluated the field responses of four Clarireedia jacksonii isolates with varying in vitro sensitivity to fluazinam. Fluazinam was used at both a full labeled rate (0.5 oz/1,000 ft²) and a half-rate (0.25 oz/1,000 ft²) to evaluate the effectiveness in isolate-inoculated plots in the field. In 2022, both natural and sensitive isolates showed significantly better control compared to insensitive isolates under both half- and full-rate treatments. However, in 2023, half-rate fluazinam demonstrated limited control under high disease pressure, providing relative disease control of dollar spot less than 45% across all treatments. In contrast, full-rate fluazinam maintained significantly better control of natural and sensitive isolates compared with insensitive isolates. Our results, showing that in vitro insensitivity leads to field insensitivity under inoculated conditions, suggest the development of fluazinam insensitivity in the C. jacksonii population. This highlights the need for judicious use of fluazinam and the establishment of continuous resistance monitoring. Furthermore, the loss of control observed when fluazinam was applied at half-rates under high disease pressure highlights the importance of careful fungicide use.

Brown root rot disease (BRRD) is a highly destructive tree disease. Early diagnosis of BRRD has been challenging because the first symptoms and signs are often observed after extensive tissue colonization. Existing molecular detection methods, all based on the internal transcribed spacer (ITS) region, were developed without testing against global Phellinus noxius isolates, other wood-decay fungi, or host plant tissues. This study aimed to develop SYBR Green real-time quantitative PCR (qPCR) assays for P. noxius. The primer pair Pn_ITS_F/Pn_ITS_R targets the ITS, and the primer pair Pn_NLR_F/Pn_NLR_R targets a P. noxius-unique group of homologous genes identified through a comparative genomics analysis. The homologous genes belong to the nucleotide-binding-oligomerization-domain-like receptor (NLR) superfamily. The new primer pairs and a previous primer pair G1F/G1R were optimized for qPCR conditions and tested for specificity using 61 global P. noxius isolates, 5 other Phellinus species, and 22 non-Phellinus wood-decay fungal species. Although all three primer pairs could detect as little as 100 fg (approximately 2.99 copies) of P. noxius genomic DNA, G1F/G1R had the highest specificity and Pn_NLR_F/Pn_NLR_R had the highest efficiency. To avoid false positives, the cutoff quantification cycle values were determined as 34 for G1F/G1R, 29 for Pn_ITS_F/Pn_ITS_R, and 32 for Pn_NLR_F/Pn_NLR_R. We further validated these qPCR assays using Ficus benjamina seedlings artificially inoculated with P. noxius, six tree species naturally infected by P. noxius, rhizosphere soil, and bulk soil. The newly developed qPCR assays provide sensitive detection and quantification of P. noxius, which is useful for long-term monitoring of BRRD status.

Cotton leaf curl disease (CLCuD), caused by the whitefly transmitted geminivirus complex (Cotton leaf curl virus - CLCuV and their satellite molecules), is a serious threat to successful upland cotton production in northwest India, Pakistan, and China. The disease causes significant losses in fibre yield and the quality of cotton. Owing to the regular emergence of resistance breaking strains of CLCuV, all the previously available CLCuD resistant germplasms of upland cotton have become compromised and none of the extant upland cotton cultivars is resistant to this disease. Therefore, alternate sources of CLCuD resistance need to be explored, as genetic resistance is the only pragmatic and tenable management strategy to combat this malady. Here, we report for the first time the introgression and mapping of CLCuD resistance from a related non-progenitor wild diploid D-genome cotton species, G. armourianum into upland cotton. A backcross population (G. hirsutum/G. armourianum/G. hirsutum) was developed for this purpose. A single major QTL was found to be associated with resistance to CLCuD and was located on chromosome D01 through the genotyping-by-sequencing technique.

Austropuccinia psidii is the causal agent of myrtle rust in over 480 species within the family Myrtaceae. Lineages of A. psidii are structured by their hosts in the native range, and some have success in infecting newly encountered hosts. For example, the pandemic biotype has spread beyond South America, and proliferation of other lineages is an additional risk to biodiversity and industries. Efforts to manage A. psidii incursions, including lineage differentiation, relies on variable microsatellite markers. Testing these markers is time-consuming, complex, and requires reference material that is not always readily available. We designed a novel diagnostic approach targeting eight selectively chosen loci including the fungal mating-type HD (homeodomain) transcription factor locus. The HD locus (bW1/2-HD1 and bE1/2-HD2) is highly polymorphic, facilitating clear biological predictions about its inheritance from founding populations. To be considered as potentially derived from the same lineage, all four HD alleles must be identical. If all four HD alleles are identical six additional markers can further differentiate lineage identity. Our lineage diagnostics relies on PCR amplification of eight loci in different genotypes of A. psidii followed by amplicon sequencing using Oxford Nanopore Technologies (ONT) and comparative analysis. The lineage-specific assay was validated on four isolates with existing genomes, uncharacterized isolates, and directly from infected leaf material. We reconstructed alleles from amplicons and confirmed their sequence identity relative to their reference. Genealogies of alleles confirmed the variations at the loci among lineages/isolates. Our study establishes a robust diagnostic tool for differentiating known lineages of A. psidii based on biological predictions and available nucleotide sequences. This tool is suited to detecting the origin of new pathogen incursions.

This study characterized 52 isolates of Monilinia fructicola from peach and nectarine orchards for their multiresistance patterns to thiophanate-methyl (TF), tebuconazole (TEB), and azoxystrobin (AZO) using in vitro sensitivity assays and molecular analysis. The radial growth of M. fructicola isolates was measured on media amended with a single discriminatory dose of 1 μg/ml for TF and AZO and 0.3 μg/ml for TEB. Cyt b, CYP51, and β-tubulin were tested for point mutations that confer resistance to quinone outside inhibitors (QoIs), demethylation inhibitors (DMIs), and methyl benzimidazole carbamates (MBCs), respectively. Eight phenotypes were identified, including isolates with single, double, and triple in vitro resistance to QoI, MBC, and DMI fungicides. All resistant phenotypes to TF and TEB presented the H6Y mutation in β-tubulin and the G641S mutation in CYP51. None of the point mutations typically linked to QoI resistance were present in the Monilinia isolates examined. Moreover, fitness of the M. fructicola phenotypes was examined in vitro and in detached fruit assays. Phenotypes with single resistance displayed equal fitness in vitro and in fruit assays compared with the wild type. In contrast, the dual- and triple-resistance phenotypes suffered fitness penalties based on osmotic sensitivity and aggressiveness on peach fruit. In this study, multiple resistance to MBC, DMI, and QoI fungicide groups was confirmed in M. fructicola. Results suggest that Monilinia populations with multiple resistance phenotypes are likely to be less competitive in the field than those with single resistance, thereby impeding their establishment over time and facilitating disease management.

Fusarium head blight (FHB) represents a critical threat to wheat production globally, not only reducing yields but also contaminating crops with harmful mycotoxins. This study aimed to elucidate new spatiotemporal patterns of FHB incidence and to develop a comprehensive meteorological risk index to enhance scientific prevention and control of the disease. Through the analysis of annual and decadal variations from 1965 to 2023, the study assessed FHB trends across four agricultural regions (I, II, III, and IV) in Jiangsu Province, located in the middle and lower reaches of the Yangtze River-a hotspot for FHB in China. Key findings include: Since 1965, Regions I and III consistently exhibited higher FHB incidence rates compared to Regions II and IV. Post-2000, there was a notable increase in years with high incidence rates, with Region III overtaking Region I as the region with the highest incidence. Since 2010, occurrences of FHB reaching the most severe grade (Grade 5) have surpassed those in previous decades across all regions. The study also revealed a stronger correlation between meteorological factors (cumulative precipitation, number of days with rainfall ≥ 0.1 mm, total rainy days with ≥ 2 and ≥3 consecutive days of rain, total rainy days with both average daily air temperature ≥ 15 °C and daily rainfall ≥ 0.1 mm, days with average daily relative humidity ≥ 85%, cumulative sunshine hours, and cumulative cloudy days) and the FHB incidence rates during the heading-flowering-grain filling period in Regions I, II, and III, compared to the heading-flowering period alone. This indicates that optimal temperature and high humidity during the grain filling stage significantly contribute to the final FHB incidence rates. Despite the less apparent correlation between temperature changes and disease rates, the significant warming trend observed since 2000 has likely fostered conditions conducive to the proliferation of FHB. The comprehensive meteorological risk index, constructed to incorporate key meteorological factors during the heading-flowering-filling period, showed a strong correlation with actual disease incidences. The index demonstrated fitting accuracy rates of 84.7% for Region I, 72.9% for Region II, 83.1% for Region III, and 90.9% for Region IV, underscoring its effectiveness in predicting FHB occurrences. This tool offers both convenience and practicality, providing valuable insights for strategically managing FHB risks based on local weather conditions.