Australasian Plant Pathology最新文献

Chilli leaf curl virus (ChiLCV) is a significant begomovirus that infects chili plants. To detect ChiLCV infection, a loop-mediated isothermal amplification (LAMP) assay was designed to be easy, quick, and efficient. The assay uses a set of five specific primers that target the coat protein gene (av1) of the target virus to detect the presence of the virus. The LAMP reaction amplifies the target gene within 45 min at 63 °C, with an 8mM dNTP concentration. This method showed no cross-reactivity with other tested begomoviruses that confirmed selective ChiLCV amplification. The sensitivity test revealed that LAMP was more sensitive than PCR. The LAMP assay displayed a remarkable detection limit of 10 fg/μL, which is superior than the PCR sensitivity of 10 pg/μL. Field sample validation yielded concordant results with PCR. This study introduces a cost-effective, and highly sensitive method for ChiLCV detection. Validation of LAMP with symptomatic leaves samples produced consistent results with PCR, demonstrating that the LAMP method could detect all infected samples.

Plant pathology researchers play a pivotal role in thought leadership and its translation to action regarding the recognition and demonstration of the value of Indigenous knowledge and science. For many scientists, navigating the space of Indigenous rights and perspectives is challenging. In pursuit of a cultural shift in research and development within the field of plant pathology, the 2019–2021 Management Committee of the Australasian Plant Pathology Society (APPS) undertook a review and modernization of the Society’s Constitution. The aim was to ensure its alignment with principles that foster inclusivity of Indigenous peoples in the development and implementation of relevant research projects impacting their communities. Additionally, a dynamic repository of guidelines and resources was compiled. These resources are designed to assist plant pathologists, while respecting and not superseding the guidance provided by local Indigenous researchers, practitioners, and advisors. The collective efforts of plant pathologists hold immense potential in championing Indigenous Peoples and their rights, steering the field toward a more inclusive and equitable future. This paper builds upon the thesis presented in the APPS Presidential Address at the Biennial APPS Conference in 2021, held virtually in lutruwita (Tasmania) on the unceded lands of the Palawa people. It underscores the potential impact when plant pathologists unite in advocating for Indigenous Peoples and their rightful place within the field.

Molecular diagnostics in combination with morphological identification is the method of choice for several cryptic microbial plant pathogens. For some diagnostic applications, traditional sequencing techniques can be time consuming, making them ill-suited for biosecurity incursion responses, where accurate results are needed in real time. More rapid next generation sequencing tools must be tested and compared with traditional methods to assess their utility in biosecurity applications. Here utilizing 95 samples infected with fungal pathogen Phyllosticta cavendishii, from a recent incursion in Australia, we compare species identification success using Internal Transcribed Spacer (ITS) gene barcode on conventional Sanger and Oxford Nanopore MinION sequencing platforms. For Sanger sequencing, the average pairwise identity percentage score between generated consensus sequences and P. cavendishii sequence from holotype material on NCBI database was 99.9% ± SE 0.0 whereas for MinION sequencing the average pairwise identity percentage was 99.1% ± SE 0.1. Relatively larger consensus sequences (mean 486 bp ± SE 2.4) were generated by Sanger sequencing compared to MinION sequencing (mean 435 bp ± SE 4.6). Our results confirm that both sequencing methods can reliably identify P. cavendishii. MinION sequencing, provided quicker results compared to Sanger sequencing and demonstrated diagnostic competence, with the added advantage of being portable, for front-line “point of incursion” biosecurity applications.

The Spanish bunch (Arachis hypogaea subsp fastigiata var vulgaris) cultivars of peanut are early maturing and extensively cultivated in India, but they suffer more from biotic and abiotic stresses than the Virginia types (Arachis hypogaea subsp hypogaea var hypogaea). The loss due to fungal foliar diseases viz., late leaf spot (LLS) and rust is an important constraint world over. Previous attempts to transfer these favourable traits have met with limited success. A high level of resistance is available in Virginia-type germplasm developed through interspecific hybridization. Systematic utilization of these resistance sources was initiated in improving locally adapted Spanish bunch varieties through extensive hybridization and development of large-scale segregating populations. Intensive evaluation of these breeding lines under high disease pressure led to the identification of early maturing, high-yielding and disease-resistant Spanish bunch variety, GPBD 4. Extensive testing and release for cultivation by the AICRIP system, widespread demonstrations on farmers’ fields and organized seed production under public systems led to its quick popularization, and it continued to benefit the farmers and consumers. An estimated economic benefit of INR 17.60 billion was derived from GPBD 4 for the period spanning from 2006 to 2022. GPBD 4 served as the source of resistance to breed at least five released varieties. The development of GPBD 4-based mapping populations, generation of phenotypic data, next-generation sequencing, mapping with molecular markers and narrowing down of genomic regions to identify the candidate genes governing disease resistance under collaborative efforts led to its immense utilization in marker-assisted breeding thereby refining the genomics-driven peanut improvement.

Abstract

Two standard area diagrams (SADs) were developed to quantify the severity of tomato early blight (EB), caused by Alternaria solani, on leaves and leaflets. The SADs were composed by sets of images with distinct EB severity for leaflets (0–40%) and leaves (0-46.4%). To validate the diagrams, 13 evaluators with no experience in quantifying the plant disease severity estimated EB severity by using a 50-image sample of tomato leaves and leaflets, first without SADs and then using the proposed SADs. The data were submitted to regression analysis and Lin’s concordance correlation coefficient, and the accuracy, precision, repeatability, and reproducibility of the estimates for EB severity were assessed. Based on the parameters of Lin’s coefficients and intraclass correlations, EB severity estimates were consistent and more reliable using SADs, improving evaluators’ performance. The diagrams proposed in this study improved the quantification of EB severity performed by 13 evaluators, increasing the accuracy, precision, and reliability of the estimates. Therefore, the proposed diagrams can be used in further studies on the epidemiology, resistance, and management strategies of this pathosystem.

Austropuccinia psidii causes rust disease on species within the family Myrtaceae. It was first detected in Australia in 2010, with the first detection in Western Australia in 2022. While species within the genus Melaleuca from eastern Australia show variable responses to the pathogen, little is known of the response of species from Western Australia. This study established that 13 previously unscreened species of Melaleuca, including Threatened and Priority listed species that were grown from seeds sourced from Western Australian populations, were susceptible four months post-germination to the pandemic strain of the pathogen. The proportion of highly susceptible plants within a single species ranged from 2 to 94%, with several species displaying highly variable levels of resistance to A. psidii. These results highlight the importance of disease screening and may direct conservation efforts.

Anthracnose caused by Colletotrichum species is an important disease of mango (Mangifera indica L.) affecting leaf, flowers and fruits in mango orchards worldwide. The fungus Colletotrichum sp. usually invade the fruits during its developmental stage but remains quiescent until fruit ripening culminating in devastating anthracnose disease, especially during post-harvest stage. In contrary, new kind of pre-harvest anthracnose symptoms were observed on green unripe mangoes with varying level of incidence at field level in the state of Odisha, situated in Eastern India. This study attempted to characterize the Colletotrichum species affecting mango cultivars and causing new kind of symptoms under field condition on maturing green mangoes in comparison to post-harvest phase using morphological methods and molecular tools as well as by pathogenicity tests on intact green as well as on detached mature fruits. Eight Colletotrichum isolates from pre-harvest phase and two from post-harvest phase isolated from different mango varieties were studied for their diversity through morphological examination as well as sequence analysis of internal transcribed spacer (ITS), chitin synthase (CHS-1), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), β-tubulin (TUB2) and ApMat genomic regions. Multigene phylogeny of all ten isolates revealed the identification of C. siamense. Pathogenicity assay of all 10 Colletotrichum isolates on green intact fruits in field as well as on detached ripening fruits in laboratory resulted in similar anthracnose symptoms on two selected test varieties Arka Anmol and Mallika. Results confirmed the association of C. siamense with both pre as well as post-harvest anthracnose symptoms of mango. Accurate pathogen identification provides a reliable basis for devising disease management schedules against anthracnose occurring at different phenological stages of the mangoes.

Abstract

Urad bean (Vigna mungo L.), commonly known as black gram, is an important pulse crop in Indian agriculture. However, the crop confronts significant challenges due to diseases, including pod rot caused by Fusarium sp, and pest attacks by the pod bug (Clavigralla gibbosa). Accurate prediction of disease severity and pest incidence is essential for formulating effective management strategies to ensure sustainable crop production. A comprehensive field experiment was conducted at the Crop Research Center, Pantnagar, Uttarakhand, during the rainy seasons of 2021 and 2022. The primary objective was to analyze the behavioral patterns of disease severity and pod bug infestations in urad bean. Data on pod rot disease severity and pest incidence were meticulously recorded on a weekly basis. Four Machine Learning approaches, namely ANN, Lasso, Ridge, and Random Forest, were trained and tested to understand the influence of meteorological parameters on pod rot and pest severity. The Random Forest model exhibited superior generalization performance in predicting both disease severity and pest incidence, closely followed by Ridge regression and Lasso regression. The ANN model showed slightly higher testing error metrics. Notably, the Random Forest model demonstrated effective control overfitting, yielding maximum R-squared values of 0.70 and 0.82 for pod rot and pest incidence, respectively. The study’s findings offer valuable insights for agricultural stakeholders in selecting appropriate prediction models to optimize crop management practices and promote sustainable agriculture.

Wheat stripe/yellow rust (WYR), caused by Puccinia striiformis f. sp. tritici (Pst), is a major constraint in global wheat production. A set of 766 hexaploid synthetic wheat lines, including primary crosses of Triticum turgidum x Aegilops tauschii and their derivatives, were screened in artificially rust inoculated field nurseries for three seasons. From this set, a core set of 94 non-lodging lines with unique pedigrees and resistance to Pst that was consistent across years was established. The core set was tested for adult plant field response under field conditions for three seasons in Australia and at least one crop season in Ethiopia, India, Kenya, Nepal and Pakistan. It was also challenged with an array of well-defined Pst pathotypes at seedling growth stages in the greenhouse, and genotyped with molecular markers linked to the adult plant resistance (APR) genes Yr18, Yr36 and Yr46. Combined analysis of field rust responses, multi-pathotype seedling phenotyping and marker genotyping resolved seven classes of Pst resistance: uncatalogued (new) APR (UAPR, 11%), uncatalogued seedling resistance (USR, 46%), known seedling resistance (KSR, 5%), KSR + USR (2%), Yr18 + UAPR (4%), Yr18 + USR (29%) and Yr18 + KSR (3%). A majority of the lines carrying UAPR and USR either singly or in combination showed high levels of field resistance across all field sites and years of testing, demonstrating that these lines represent a valuable resource for breeding wheat for resistance to Pst.