Alternaria diseases of citrus - Novel pathosystems

Citrus is affected by four diseases caused by Alternaria spp. Brown spot of tangerines, leaf spot of rough lemon, postharvest black rot of fruit occur widely in citrus areas of the world and are caused by different pathotypes of A. alternata. Mancha foliar occurs only on Mexican lime in western Mexico and is caused by A. limicola. Tangerine and rough lemon pathotypes produce host-specific toxins that affect membranes and respiration, respectively. Black rot is always associated with wounds and is caused by most citrus-associated isolates of A. alternata that produce endopolygalacturonase. Alternaria brown spot is a serious disease of susceptible tangerines and their hybrids in semi-arid Mediterranean climates as well as in more humid areas. Conidia, produced on lesions on mature and senescent leaves and stems under humid conditions, are dispersed by wind, and infect all juvenile tissues of susceptible cultivars when temperature and leaf wetness conditions are favorable. Commercially acceptable cultivars resistant to brown spot are being developed. Disease severity can be reduced by planting disease-free nursery stock on wider spacings, pruning tree skirts, and reducing irrigation and nitrogen fertilization. However, fungicides such as dithiocarbamates, triazoles, strobilurins, iprodione, or copper fungicides are used in most areas for disease control. A disease-forecasting model, the Alter-Rater, has been developed in Florida to assist in timing fungicide sprays

Development of a Decision Support System for the Management of Mummy Berry Disease in Northwestern Washington

Mummy berry, caused by Monilinia vaccinii-corymbosi, is the most important disease of the northern highbush blueberry (Vaccinium corymbosum L.) in North America and can cause up to 70% yield losses in affected fields. A key event in the mummy berry disease cycle is the primary infection phase where ascospores are released by apothecia that infect emerging floral and vegetative tissues. Current management of mummy berry disease in northwestern Washington is predominantly reliant on the prevention of primary infections through prophylactic, calendar-based fungicide spray applications early in the growing season. To improve the understanding of risk during these periods and to help tailor management strategies, we developed a decision support system (DSS) based on field records spanning over five seasons and four locations in northwestern Washington. Environmental conditions across the region were highly uniform but different dynamics of apothecial development were observed under high- and low-management regimes. Based on our analysis, we suggest basing the initial iteration of the DSS on two sub-models. The first sub-model predicts the onset of apothecia based on chill-unit accumulation under high- and low-management regimes, and the second predicts primary infection risk, which provides opportunities to improve the timing of fungicide applications. The synoptic DSS proposed here is based on the current biological knowledge of the pathosystem and available data for the northwestern Washington region. We provide the analysis and the DSS implementation and evaluation as an open-source repository, providing opportunities for further improvements. Finally, we provide suggestions for future research and the operational efforts needed for improving the utility and accuracy of the mummy berry DSS.publishedVersio

Are We Ready to Ride Autonomous Vehicles? A Pilot Study on Austrian Consumers’ Perspective

Automotive manufacturers are competing to be the first to introduce customer-ready autonomous vehicles. Some manufacturers are claiming to launch their first self-driving cars as early as 2020. Which all sounds very good and futuristic; however, the question arises, are customers even ready to adopt this new technological advancement? Therefore, this pilot study is aimed at finding out the answer to this question in the Austrian market. This study discovers the standpoint of Austrian consumers concerning the acceptance of self-driving cars for daily usage and gives an overview of the current point of view regarding autonomous vehicles (AVs). The data for this study was collected using an online, user-friendly, Likert scale survey. The collected data were processed and analyzed for empirical significance in SPSS using Spearman’s rank correlation and the Mann–Whitney U test supported by descriptive analysis. The results of the study indicate that Austrian consumers are well aware of autonomous vehicles and their technology. However, they have specific concerns about reliability, cybersecurity, and futuristic car-sharing models. Therefore, these concerns about AVs should be addressed by auto manufactures in order to gain consumers’ trust and sell them a new form of mobility

Genetic diversity and population structure of Ascochyta rabiei from the western Iranian Ilam and Kermanshah provinces using MAT and SSR markers

Knowledge of genetic diversity in A. rabiei provides different levels of information that are important in the management of crop germplasm resources. Gene flow on a regional level indicates a significant potential risk for the regional spread of novel alleles that might contribute to fungicide resistance or the breakdown of resistance genes. Simple sequence repeat (SSR) and mating type (MAT) markers were used to determine the genetic structure, and estimate genetic diversity and the prevalence of mating types in 103 Ascochyta rabiei isolates from seven counties in the Ilam and Kermanshah provinces of western Iran (Ilam, Aseman abad, Holaylan, Chardavol, Dareh shahr, Gilangharb, and Sarpul). A set of 3 microsatellite primer pairs revealed a total of 75 alleles; the number of alleles varied from 15 to 34 for each marker. A high level of genetic variability was observed among A. rabiei isolates in the region. Genetic diversity was high (He = 0.788) within populations with corresponding high average gene flow and low genetic distances between populations. The smallest genetic distance was observed between isolates from Ilam and Chardavol. Both mating types were present in all populations, with the majority of the isolates belonging to Mat1-1 (64%), but within populations the proportions of each mating type were not significantly different from 50%. Results from this study will be useful in breeding for Ascochyta blight-resistant cultivars and developing necessary control measures

Demethylase Inhibitor Fungicide Resistance in Pyrenophora teres f. sp. teres Associated with Target Site Modification and Inducible Overexpression of Cyp51

Pyrenophora teres f. sp. teres is the cause of net form of net blotch, an economically important foliar disease in barley (Hordeum vulgare). Net and spot forms of net blotch are widely controlled using site-specific systemic fungicides. Although resistance to succinate dehydrogenase inhibitors and quinone outside inhibitors has been addressed before in net blotches, mechanisms controlling demethylation inhibitor resistance have not yet been reported at the molecular level. Here we report the isolation of strains of net form of net blotch in Australia since 2013 resistant to a range of demethylase inhibitor fungicides. Cyp51A:KO103-A1, an allele with the mutation F489L, corresponding to the archetype F495I in Aspergillus fumigatus, was only present in resistant strains and was correlated with resistance factors to various demethylase inhibitors ranging from 1.1 for epoxiconazole to 31.7 for prochloraz. Structural in silico modelling of the sensitive and resistant CYP51A proteins docked with different demethylase inhibitor fungicides showed how the interaction of F489L within the heme cavity produced a localised constriction of the region adjacent to the docking site that is predicted to result in lower binding affinities. Resistant strains also displayed enhanced induced expression of the two Cyp51A paralogs and of Cyp51B genes. While Cyp51B was found to be constitutively expressed in the absence of fungicide, Cyp51A was only detected at extremely low levels. Under fungicide induction, expression of Cyp51B, Cyp51A2 and Cyp51A1 was shown to be 1.6-, 3- and 5.3-fold higher, respectively in the resistant isolate compared to the wild type. These increased levels of expression were not supported by changes in the promoters of any of the three genes. The implications of these findings on demethylase inhibitor activity will require current net blotch management strategies to be reconsidered in order to avoid the development of further resistance and preserve the lifespan of fungicides in use

Poppr: an R package for genetic analysis of populations with clonal, partially clonal, and/or sexual reproduction

Many microbial, fungal, or oomcyete populations violate assumptions for population genetic analysis because these populations are clonal, admixed, partially clonal, and/or sexual. Furthermore, few tools exist that are specifically designed for analyzing data from clonal populations, making analysis difficult and haphazard. We developed the R package poppr providing unique tools for analysis of data from admixed, clonal, mixed, and/or sexual populations. Currently, poppr can be used for dominant/codominant and haploid/diploid genetic data. Data can be imported from several formats including GenAlEx formatted text files and can be analyzed on a user-defined hierarchy that includes unlimited levels of subpopulation structure and clone censoring. New functions include calculation of Bruvo’s distance for microsatellites, batch-analysis of the index of association with several indices of genotypic diversity, and graphing including dendrograms with bootstrap support and minimum spanning networks. While functions for genotypic diversity and clone censoring are specific for clonal populations, several functions found in poppr are also valuable to analysis of any populations. A manual with documentation and examples is provided. Poppr is open source and major releases are available on CRAN: http://cran.r-project.org/package=poppr. More supporting documentation and tutorials can be found under ‘resources’ at: http://grunwaldlab.cgrb.oregonstate.edu/