Key Discoveries in Plant Pathology During the Past Half Century: Impacts on the Life Sciences and on Plant Disease Management.

Plant pathology plays a critical role in safeguarding plant health, food security, and food safety through science-based solutions to protect plants against recurring and emerging diseases. In addition, plant pathology contributed significantly to basic discoveries that have had broad impacts on the life sciences beyond plant pathology. In December 2021, The American Phytopathological Society (APS) conducted a survey among its members and among the readership of its journals to identify and rank key discoveries in plant pathology that have had broad impacts on science and/or practical disease management during the past half century. Based on the responses received, key discoveries that have broadly impacted the life sciences during that period include the Agrobacterium Ti plasmid and its mechanism in T-DNA transfer, bacterial ice nucleation, cloning of resistance genes, discovery of viroids, effectors and their mechanisms, pattern-triggered immunity and effector-triggered immunity, RNA interference and gene silencing, structure and function of R genes, transcription activator-like effectors, and type-III secretion system and hrp/hrc. Major advances that significantly impacted practical disease management include the deployment and management of host resistance genes; the application of disease models and forecasting systems; the introduction of modern systemic fungicides and host resistance inducers, along with a better understanding of fungicide resistance mechanisms and management; and the utilization of biological controls and suppressive soils, including the implementation of methyl-bromide alternatives. In this special issue, experts from the pertinent fields review the discovery process, recent progress, and impacts of some of the highest ranked discoveries in each category while also pointing out future directions for new discoveries in fundamental and applied plant pathology.

Yield Response to Orange Cane Blotch of Blackberry Grown in the Georgia Coastal Plain.

Orange cane blotch (OCB), an algal disease on commercial blackberry plants in the southeastern United States, has been an increasing concern among producers. The causal agent, Cephaleuros virescens, produces brightly colored green to orange lesions on blackberry stems, but proof of actual damage and impact on crop yield has not been documented. Naturally infected stem sections were viewed using transmission and scanning electron microscopy to evaluate cane damage. Surface abrasions, intercellular growth, and occasional intracellular growth were observed on the surface and epidermal layers. Field studies at four commercial sites over 2 years were conducted to assess the impact of OCB on yield in 'Ouachita' blackberry plants not treated with algicidal chemicals. Neither cane diameter nor berry size was impacted by severity of OCB; however, berry number decreased with increasing OCB intensity in a nonlinear manner, thereby resulting in reduced yields.

Blueberry necrotic ring blotch virus in Southern Highbush Blueberry: Insights into In Planta and In-Field Movement.

Blueberry necrotic ring blotch virus (BNRBV) causes an emerging disease of southern highbush blueberry (SHB) in the southeastern United States. Disease incidence and severity vary considerably from year to year within the same planting. Experiments were conducted to determine how the virus spreads in the field. Leaf tissue from symptomatic field plants tested positive for BNRBV in 2011, whereas the same plants were asymptomatic in 2012 and tested negative for the virus. Symptomatic and asymptomatic leaves from individual shoots were tested for the presence of the virus, and symptomatic leaves tested positive (100%), whereas 65.4% of the asymptomatic leaves from the same shoots tested negative. Leaves were selected in which half the leaf blade was symptomatic and the other half was not; symptomatic leaf halves tested positive (100%), whereas 76.0% of the asymptomatic halves from the same leaf tested negative for the virus. When virus-free, potted trap plants were interspersed in the field among established plants that had shown disease symptoms the previous year, disease onset in trap plants was observed 2 to 3 weeks after disease onset in field plants. In a separate experiment, asymptomatic softwood cuttings were collected from mother plants symptomatic for BNRBV, rooted, and monitored for symptom development for a period of 12 to 27 months. No BNRBV symptoms were observed in the progeny, whereas disease incidence was high for cuttings taken at the same time from plants infected with Blueberry red ringspot virus used as a control. Collectively, these studies suggest that BNRBV does not infect SHB plants systemically and is not transmitted through vegetative propagation, and that the virus likely does not persist in plants after natural defoliation in the fall.

Physiological Effects of Meloidogyne incognita Infection on Cotton Genotypes with Differing Levels of Resistance in the Greenhouse.

Greenhouse tests were conducted to evaluate (i) the effect of Meloidogyne incognita infection in cotton on plant growth and physiology including the height-to-node ratio, chlorophyll content, dark-adapted quantum yield of photosystem II, and leaf area; and (ii) the extent to which moderate or high levels of resistance to M. incognita influenced these effects. Cultivars FiberMax 960 BR (susceptible to M. incognita) and Stoneville 5599 BR (moderately resistant) were tested together in three trials, and PD94042 (germplasm, susceptible) and 120R1B1 (breeding line genetically similar to PD94042, but highly resistant) were paired in two additional trials. Inoculation with M. incognita generally resulted in increases in root gall ratings and egg counts per gram of root compared with the noninoculated control, as well as reductions in plant dry weight, root weight, leaf area, boll number, and boll dry weight, thereby confirming that growth of our greenhouse-grown plants was reduced in the same ways that would be expected in field-grown plants. In all trials, M. incognita caused reductions in height-to-node ratios. Nematode infection consistently reduced the area under the height-to-node ratio curves for all genotypes, and these reductions were similar for resistant and susceptible genotypes (no significant genotype × inoculation interaction). Our study is the first to show that infection by M. incognita is associated with reduced chlorophyll content in cotton leaves, and the reduction in the resistant genotypes was similar to that in the susceptible genotypes (no interaction). The susceptible PD94042 tended to have increased leaf temperature compared with the genetically similar but highly resistant 120R1B1 (P < 0.08), likely attributable to increased water stress associated with M. incognita infection.

Characterization of three-dimensional spatial aggregation and association patterns of brown rot symptoms within intensively mapped sour cherry trees.

BACKGROUND AND AIMS: Characterization of spatial patterns of plant disease can provide insights into important epidemiological processes such as sources of inoculum, mechanisms of dissemination, and reproductive strategies of the pathogen population. Whilst two-dimensional patterns of disease (among plants within fields) have been studied extensively, there is limited information on three-dimensional patterns within individual plant canopies. Reported here are the detailed mapping of different symptom types of brown rot (caused by Monilinia laxa) in individual sour cherry tree (Prunus cerasus) canopies, and the application of spatial statistics to the resulting data points to determine patterns of symptom aggregation and association. METHODS: A magnetic digitizer was utilized to create detailed three-dimensional maps of three symptom types (blossom blight, shoot blight and twig canker) in eight sour cherry tree canopies during the green fruit stage of development. The resulting point patterns were analysed for aggregation (within a given symptom type) and pairwise association (between symptom types) using a three-dimensional extension of nearest-neighbour analysis. KEY RESULTS: Symptoms of M. laxa infection were generally aggregated within the canopy volume, but there was no consistent pattern for one symptom type to be more or less aggregated than the other. Analysis of spatial association among symptom types indicated that previous year's twig cankers may play an important role in influencing the spatial pattern of current year's symptoms. This observation provides quantitative support for the epidemiological role of twig cankers as sources of primary inoculum within the tree. CONCLUSIONS: Presented here is a new approach to quantify spatial patterns of plant disease in complex fruit tree canopies using point pattern analysis. This work provides a framework for quantitative analysis of three-dimensional spatial patterns within the finite tree canopy, applicable to many fields of research.

Meta-analysis to determine the effects of plant disease management measures: review and case studies on soybean and apple.

The continuing exponential increase in scientific knowledge, the growing availability of large databases containing raw or partially annotated information, and the increased need to document impacts of large-scale research and funding programs provide a great incentive for integrating and adding value to previously published (or unpublished) research through quantitative synthesis. Meta-analysis has become the standard for quantitative evidence synthesis in many disciplines, offering a broadly accepted and statistically powerful framework for estimating the magnitude, consistency, and homogeneity of the effect of interest across studies. Here, we review previous and current uses of meta-analysis in plant pathology with a focus on applications in epidemiology and disease management. About a dozen formal meta-analyses have been published in the plant pathological literature in the past decade, and several more are currently in progress. Three broad research questions have been addressed, the most common being the comparative efficacy of chemical treatments for managing disease and reducing yield loss across environments. The second most common application has been the quantification of relationships between disease intensity and yield, or between different measures of disease, across studies. Lastly, meta-analysis has been applied to assess factors affecting pathogen-biocontrol agent interactions or the effectiveness of biological control of plant disease or weeds. In recent years, fixed-effects meta-analysis has been largely replaced by random- (or mixed-) effects analysis owing to the statistical benefits associated with the latter and the wider availability of computer software to conduct these analyses. Another recent trend has been the more common use of multivariate meta-analysis or meta-regression to analyze the impacts of study-level independent variables (moderator variables) on the response of interest. The application of meta-analysis to practical problems in epidemiology and disease management is illustrated with case studies from our work on Phakopsora pachyrhizi on soybean and Erwinia amylovora on apple. We show that although meta-analyses are often used to corroborate and validate general conclusions drawn from more traditional, qualitative reviews, they can also reveal new patterns and interpretations not obvious from individual studies.

Rhizoctonia Web Blight Development on Container-Grown Azalea in Relation to Time and Environmental Factors.

Rhizoctonia web blight, caused by binucleate Rhizoctonia spp., is an annual problem in the southern United States on container-grown azaleas (Rhododendron spp.) that receive daily irrigation. Disease progress was assessed weekly from mid-May to mid-September on nursery-grown plants at three locations in Mississippi and Alabama in 2006, 2007, and 2008. Disease onset, defined as the appearance of blighted leaves at the exterior canopy of at least one plant, occurred on average on 20 July, and calendar date was a more precise predictor of disease onset than several combined time-weather variables. Disease progress curves exhibited weekly fluctuations around a typically exponential increase in the mean number of symptomatic leaves per plant until early to mid-September, after which web blight severity leveled off or declined due to disease-induced leaf dehiscence and the appearance of new, asymptomatic leaves. Based on the relative increase in the log-transformed number of infected leaves per plant, weekly assessment periods were classified as having slow (≤0%), intermediate (>0 to <10%), or rapid (≥10% increase) disease progress. Three-day moving averages (MA) of various weather variables were calculated, and lagged values (by 5 days) of the MA were used in an attempt to predict disease progress as slow, intermediate, or rapid. Of the periods assessed as having slow disease progress in the 2006-2007 data set (model development data), 90.6% (29 of 32) met at least one of the following heuristically derived criteria for the lagged MA: min. temperature < 20.0°C, max. temperature > 35.0°C, avg. vapor pressure deficit < 2.50 hPa, or day of the year > 240 (28 August). One or more of these same criteria were met in 5 of 16 (31.2%) assessment periods with rapid disease progress, indicating that periods with slow versus rapid disease progression could be distinguished reasonably well based on weather. Results were similar for the 2008 validation data. However, weather variables were not useful in separating periods with either slow or rapid disease progress from those having intermediate progress. Instead, weather variables were most useful when used in a negative-prognosis approach to predict disease progression as being "not rapid" (which includes slow and intermediate periods) or "not slow" (including intermediate and rapid periods). The data set was further analyzed using Classification and Regression Tree (CART) analysis to relate weekly disease progress periods to weather variables. The resulting CART model agreed with the heuristic approach in that temperature variables were more prominent than moisture variables in classifying disease progress periods. With both approaches, satisfactory accuracy was accomplished only with negative-prognoses that classified disease progress periods as not rapid or not slow based on temperature and moisture limits.

Biology of flower-infecting fungi.

The ability to infect host flowers offers important ecological benefits to plant-parasitic fungi; not surprisingly, therefore, numerous fungal species from a wide range of taxonomic groups have adopted a life style that involves flower infection. Although flower-infecting fungi are very diverse, they can be classified readily into three major groups: opportunistic, unspecialized pathogens causing necrotic symptoms such as blossom blights (group 1), and specialist flower pathogens which infect inflorescences either through the gynoecium (group 2) or systemically through the apical meristem (group 3). This three-tier system is supported by life history attributes such as host range, mode of spore transmission, degree of host sterilization as a result of infection, and whether or not the fungus undergoes an obligate sexual cycle, produces resting spores in affected inflorescences, and is r- or K-selected. Across the three groups, the flower as an infection court poses important challenges for disease management. Ecologically and evolutionarily, terms and concepts borrowed from the study of venereal (sexually transmitted) diseases of animals do not adequately capture the range of strategies employed by fungi that infect flowers.

Mimicry in plant-parasitic fungi.

Mimicry is the close resemblance of one living organism (the mimic) to another (the model), leading to misidentification by a third organism (the operator). Similar to other organism groups, certain species of plant-parasitic fungi are known to engage in mimetic relationships, thereby increasing their fitness. In some cases, fungal infection can lead to the formation of flower mimics (pseudo flowers) that attract insect pollinators via visual and/or olfactory cues; these insects then either transmit fungal gametes to accomplish outcrossing (e.g. in some heterothallic rust fungi belonging to the genera Puccinia and Uromyces) or vector infectious spores to healthy plants, thereby spreading disease (e.g. in the anther smut fungus Microbotryum violaceum and the mummy berry pathogen Monilinia vaccinii-corymbosi). In what is termed aggressive mimicry, some specialized plant-parasitic fungi are able to mimic host structures or host molecules to gain access to resources. An example is M. vaccinii-corymbosi, whose conidia and germ tubes, respectively, mimic host pollen grains and pollen tubes anatomically and physiologically, allowing the pathogen to gain entry into the host's ovary via stigma and style. We review these and other examples of mimicry by plant-parasitic fungi and some of the mechanisms, signals, and evolutionary implications.