In 5 March 2001, a severe rust outbreak was recorded at Pitapó, Paraguay, and the causal organism was determined to be Phakopsora pachyrhizi using polymerase chain reaction (PCR) and DNA sequence analysis. In May, rust surveys showed spread throughout most of Paraguay and into western and northern Parana, Brazil. In the 2001-02 season, rust was widespread in Paraguay, but losses were reduced due to severe drought; however, in Brazil it spread to more than 60% of the soybean acreage, causing field losses estimated at 0.1 million metric tons (MMT). In 2003, the disease was observed in more than 90% of the fields in Brazil, and the projected losses in Mato Grosso and Bahia alone are 2.2 MMT (US$487.3 million). Approximately 80% of the soybean acreage in Brazil was sprayed twice with fungicides at the cost of US$544 million. Differences in efficacy have been observed among the commercial strobilurin and triazol fungicides.

A diagrammatic scale to assess soybean (Glycine max) rust severity, caused by the fungus Phakopsora pachyrhizi, was developed in this study. Leaflets showing different severity levels were collected for determination of the minimum and maximum severity limits; intermediate levels were determined according to "Weber-Fechner's stimulus-response law". The proposed scale showed the levels of 0.6; 2; 7; 18; 42, and 78.5%. Scale validation was performed by eight raters (four inexperienced and four experienced), who estimated the severity of 44 soybean leaflets showing rust symptoms, with and without the use of the scale. Except for rater number eight, all showed a tendency to overestimate severity without the aid of the diagrammatic scale. With the scale, the raters obtained better accuracy and precision levels, although the tendency to overestimate was maintained. Experienced raters were more accurate and precise than inexperienced raters, and assessment improvements with the use of the scale were more significant for inexperienced raters.

Asian soybean rust, caused by the fungus Phakopsora pachyrhizi, is the most severe disease of the crop and can cause yield losses of up to 90%. The disease was first reported in Brazil in 2001. Epidemics of the disease are common in the country, where the fungus can survive year-round. Regulatory measures to reduce the inoculum between seasons and avoid late-season soybean have been adopted to manage the disease. Disease control has relied mainly on chemical control, but a lower sensibility of the fungus to fungicides has been reported in Brazil. Major-resistance genes have been mapped and incorporated into the cultivars. With the reduced efficacy of the fungicides, the adoption of integrated measures to control the disease will be important for the sustainability of the crop. This review presents the main changes in the soybean crop system caused by the introduction of the fungus in Brazil, the current management strategies adopted to avoid losses, and the new trends that, together with biotechnological strategies, can improve management in the future.

Asian soybean rust (ASR), caused by Phakopsora pachyrhizi, is now established in all major soybean-producing countries. Currently, there is little information about the molecular basis of ASR–soybean interactions, which will be needed to assist future efforts to develop effective resistance. Toward this end, abundance changes of soybean mRNAs were measured over a 7-day ASR infection time course in mock-inoculated and infected leaves of a soybean accession (PI230970) carrying the Rpp2 resistance gene and a susceptible genotype (Embrapa-48). The expression profiles of differentially expressed genes (ASR-infected compared with the mock-inoculated control) revealed a biphasic response to ASR in each genotype. Within the first 12 h after inoculation (hai), which corresponds to fungal germination and penetration of the epidermal cells, differential gene expression changes were evident in both genotypes. mRNA expression of these genes mostly returned to levels found in mock-inoculated plants by 24 hai. In the susceptible genotype, gene expression remained unaffected by rust infection until 96 hai, a time period when rapid fungal growth began. In contrast, gene expression in the resistant genotype diverged from the mock-inoculated control earlier, at 72 h, demonstrating that Rpp2-mediated defenses were initiated prior to this time. These data suggest that ASR initially induces a non-specific response that is transient or is suppressed when early steps in colonization are completed in both soybean genotypes. The race-specific resistance phenotype of Rpp2 is manifested in massive gene expression changes after the initial response prior to the onset of rapid fungal growth that occurs in the susceptible genotype.

Over the last few years, considerable effort has been spent by Embrapa in the construction of a plant disease database representative enough for the development of effective methods for automatic plant disease detection and recognition. In October of 2016, this database, called PDDB, had 2326 images of 171 diseases and other disorders affecting 21 plant species. PDDB size, although considerable, is not enough to allow the use of powerful techniques such as deep learning. In order to increase its size, each image was subdivided according to certain criteria, increasing the number of images to 46,513. Both the original (PDDB) and subdivided (XDB) databases are now being made freely available for academic research purposes, thus supporting new studies and contributing to speed up the advances in the area. Both collections are expected to grow continuously in order to expand their reach. PDDB and XDB can be accessed in the link https://www.digipathos-rep.cnptia.embrapa.br/.

Although Asian soybean rust occurs in a broad range of environmental conditions, the most explosive and severe epidemics have been reported in seasons with warm temperature and abundant moisture. Associations between weather and epidemics have been reported previously, but attempts to identify the major factors and model these relationships with field data have been limited to specific locations. Using data from 2002-03 to 2004-05 from 34 field experiments at 21 locations in Brazil that represented all major soybean production areas, we attempted to identify weather variables using a 1-month time window following disease detection to develop simple models to predict final disease severity. Four linear models were identified, and these models explained 85 to 93% of variation in disease severity. Temperature variables had lower correlation with disease severity compared with rainfall, and had minimal predictive value for final disease severity. A curvilinear relationship was observed between 1 month of accumulated rainfall and final disease severity, and a quadratic response model using this variable had the lowest prediction error. Linear response models using only rainfall or number of rainy days in the 1-month period tended to overestimate disease for severity <30%. The study highlights the importance of rainfall in influencing soybean rust epidemics in Brazil, as well as its potential use to provide quantitative risk assessments and seasonal forecasts for soybean rust, especially for regions where temperature is not a limiting factor for disease development.