The Influence of Temperature and Leaf Wetness Duration on Infection of Perennial Ryegrass by Rhizoctonia solani

The functions of foliar nyctinasty: a review and hypothesis

Foliar nyctinasty is a plant behaviour characterised by a pronounced daily oscillation in leaf orientation. During the day, the blades of nyctinastic plant leaves (or leaflets) assume a more or less horizontal position that optimises their ability to capture sunlight for photosynthesis. At night, the positions that the leaf blades assume, regardless of whether they arise by rising, falling or twisting, are essentially vertical. Among the ideas put forth to explain the raison d'être of foliar nyctinasty are that it: (i) improves the temperature relations of plants; (ii) helps remove surface water from foliage; (iii) prevents the disruption of photoperiodism by moonlight; and (iv) directly discourages insect herbivory. After discussing these previous hypotheses, a novel tritrophic hypothesis is introduced that proposes that foliar nyctinasty constitutes an indirect plant defence against nocturnal herbivores. It is suggested that the reduction in physical clutter that follows from nocturnal leaf closure may increase the foraging success of many types of animals that prey upon or parasitise herbivores. Predators and parasitoids generally use some combination of visual, auditory or olfactory cues to detect prey. In terrestrial environments, it is hypothesised that the vertical orientation of the blades of nyctinastic plants at night would be especially beneficial to flying nocturnal predators (e.g. bats and owls) and parasitoids whose modus operandi is death from above. The movements of prey beneath a plant with vertically oriented foliage would be visually more obvious to gleaning or swooping predators under nocturnal or crepuscular conditions. Such predators could also detect sounds made by prey better without baffling layers of foliage overhead to damp and disperse the signal. Moreover, any volatiles released by the prey would diffuse more directly to the awaiting olfactory apparatus of the predators or parasitoids. In addition to facilitating the demise of herbivores by carnivores and parasitoids, foliar nyctinasty, much like the enhanced illumination of the full moon, may mitigate feeding by nocturnal herbivores by altering their foraging behaviour. Foliar nyctinasty could also provide a competitive advantage by encouraging herbivores, seeking more cover, to forage on or around non-nyctinastic species. As an added advantage, foliar nyctinasty, by decreasing the temperature between plants through its effects on re-radiation, may slow certain types of ectothermic herbivores making them more vulnerable to predation. Foliar nyctinasty also may not solely be a behavioural adaptation against folivores; by discouraging foraging by granivores, the inclusive fitness of nyctinastic plants may be increased.

Effects of leaf wetness duration and temperature on infection of Prunus by Xanthomonas arboricola pv. pruni

Xanthomonas arboricola pv. pruni is the causal agent of bacterial spot disease of stone fruits and almond. The bacterium is distributed throughout the major stone-fruit-producing areas of the World and is considered a quarantine organism in the European Union according to the Council Directive 2000/29/EC, and by the European and Mediterranean Plant Protection Organization. The effect of leaf wetness duration and temperature on infection of Prunus by X. arboricola pv. pruni was determined in controlled environment experiments. Potted plants of the peach-almond hybrid GF-677 were inoculated with bacterial suspensions and exposed to combinations of six leaf wetness durations (from 0 to 24 h) and seven fixed temperatures (from 5 to 35°C) during the infection period. Then, plants were transferred to a biosafety greenhouse, removed from bags, and incubated at optimal conditions for disease development. Although leaf wetness was required for infection of Prunus by X. arboricola pv. pruni, temperature had a greater effect than leaf wetness duration on disease severity. The combined effect of wetness duration and temperature on disease severity was quantified using a modification of the Weibull equation proposed by Duthie. The reduced-form of Duthie’s model obtained by nonlinear regression analysis fitted well to data (R = 0.87 and R²_adj = 0.85), and all parameters were significantly different from 0. The estimated optimal temperature for infection by X. arboricola pv. pruni was 28.9°C. Wetness periods longer than 10 h at temperatures close to 20°C, or 5 h at temperatures between 25 and 35°C were necessary to cause high disease severity. The predictive capacity of the model was evaluated using an additional set of data obtained from new wetness duration-temperature combinations. In 92% of the events the observed severity agreed with the predicted level of infection risk. The risk chart derived from the reduced form of Duthie’s model can be used to estimate the potential risk for infection of Prunus by X. arboricola pv. pruni based on observed or forecasted temperature and wetness duration.

Weather-Based Forecasting of Rhizoctonia Web Blight Development on Container-Grown Azalea

The most reliable approach for timing fungicides to control Rhizoctonia web blight on container-grown azalea has been a fixed calendar date. The purpose of this study was to model periods when a preventive control could be applied in advance of significant increases in leaf blight intensity (LBI) in response to a daily accumulated risk value indicating conducive conditions of temperature (18 or more hours between 20 and 30°C when maximum temperature is less than 35°C), leaf wetness (16 or more hours), and/or rainfall (greater than 6.7 mm above the maximum daily irrigation). Analysis used weather measurements taken every 30 minutes from 11 site-year datasets from 2006 to 2011, and weekly or biweekly LBI assessments. Six developmental site-year datasets were analyzed using receiver operating characteristic (ROC) curve procedures to evaluate models. Only a single model predicted true positives and negatives significantly greater than a 50:50 probability. Subsequently, five site-year validation datasets were evaluated. Similar results were obtained from both the developmental and validation datasets, which produced ROC areas of 0.7715 (P = 0.0120) and 0.8393 (P = 0.0034), respectively. The practical application of weather-based forecasting for management of web blight in nurseries is discussed.

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.

Effects of Surface Wetness Periods on Development of Soybean Rust Under Field Conditions

Soybean rust (SBR), caused by Phakopsora pachyrhizi, has the potential to be an economic threat to U.S. soybean production after its arrival to the continental United States in 2004. The use of fungicides to control SBR may be problematic due to the large acreage that needs to be protected, the high costs of fungicides, and the cost of application. Cultural practices such as the use of reduced seed rates, increased row widths, and row orientation to the sun have been prescribed as environmental modifications that create a microclimate less conducive to foliar disease development. Therefore, our objective was to determine the influence of different periods of leaf wetness and respective microenvironments on infection and rust development on soybean plants in the field. A misting irrigation system was developed and applied on MGV soybean for 1 min every 30 min for 0-, 6-, 12-, and 18-h periods. This study indicates that extended periods of leaf wetness (18 h) increase disease severity and the rate of spread of the disease in the upper canopy. These results, in combination with spore monitoring, may be used to refine models of pathogen reproduction, prediction, and risk in a certain regions.

A simple generic infection model for foliar fungal plant pathogens

ABSTRACT In this study, a simple generic infection model was developed for predicting infection periods by fungal foliar pathogens. The model is designed primarily for use in forecasting pathogens that do not have extensive epidemiological data. Most existing infection models require a background epidemiological data set, usually including laboratory estimates of infection at multiple temperature and wetness combinations. The model developed in this study can use inputs based on subjective estimates of the cardinal temperatures and the wetness duration requirement. These inputs are available for many pathogens or may be estimated from related pathogens. The model uses a temperature response function which is scaled to the minimum and optimum values of the surface wetness duration requirement. The minimum wetness duration requirement (W(min)) is the number of hours required to produce 20% disease incidence or 5% disease severity on inoculated plant parts at a given temperature. The model was validated with published data from 53 controlled laboratory studies, each with at least four combinations of temperature and wetness. Validation yielded an average correlation coefficient of 0.83 and a root mean square error of 4.9 h, but there was uncertainty about the value of the input parameters for some pathogens. The value of W(min) varied from 1 to 48 h and was relatively uniform for species in the genera Cercospora, Alternaria, and Puccinia but less so for species of Phytophthora, Venturia, and Colletotrichum. Operationally, infection models may use hourly or daily weather inputs. In the case of the former, information also is required to estimate the critical dry-period interruption value, defined as the duration of a dry period at relative humidities <95% that will result in a 50% reduction in disease compared with a continuous wetness period. Pathogens were classified into three groups based on their critical dry-period interruption value. The infection model is being used to create risk maps of exotic pests for the U.S. Department of Agriculture's Animal Plant Health and Inspection Service.

A temperature and leaf wetness duration-based model for prediction of gray leaf spot of perennial ryegrass turf

ABSTRACT Gray leaf spot is a serious disease of perennial ryegrass (Lolium perenne), causing severe epidemics in golf course fairways. The effects of temperature and leaf wetness duration on the development of gray leaf spot of perennial ryegrass turf were evaluated in controlled environment chambers. Six-week-old Legacy II ryegrass plants were inoculated with an aqueous conidial suspension of Pyricularia grisea (approximately 8 x 10(4) conidia per ml of water) and subjected to four different temperatures (20, 24, 28, and 32 degrees C) and 12 leaf wetness durations (3 to 36 h at 3-h intervals). Three days after inoculation, gray leaf spot developed on plants at all temperatures and leaf wetness durations. Disease incidence (percent leaf blades symptomatic) and severity (index 0 to 10; 0 = leaf blades asymptomatic, 10 = >90% leaf area necrotic) were assessed 7 days after inoculation. There were significant effects ( alpha = 0.0001) of temperature and leaf wetness duration on disease incidence and severity, and there were significant interactions ( alpha = 0.0001) between them. Among the four temperatures tested, 28 degrees C was most favorable to gray leaf spot development. Disease incidence and severity increased with increased leaf wetness duration at all temperatures. A shorter leaf wetness duration was required for disease development under warmer temperatures. Analysis of variance with orthogonal polynomial contrasts and regression analyses were used to determine the functional relationships among temperature and leaf wetness duration and gray leaf spot incidence and severity. Significant effects were included in a regression model that described the relationship. The polynomial model included linear, quadratic, and cubic terms for temperature and leaf wetness duration effects. The adjusted coefficients of determination for the fitted model for disease incidence and severity were 0.84 and 0.87, respectively. The predictive model may be used as part of an integrated gray leaf spot forecasting system for perennial ryegrass turf.

The Effects of Temperature and Wetness Period on the Development of Spinach White Rust

Experiments were conducted in controlled environments to determine the influence of temperature and duration of wetness on development of white rust of spinach. Plants of the susceptible cv. Kent were exposed to temperatures of 6 to 28°C and interrupted wetness periods that totaled 3 to 84 h following inoculation. Disease severity was assessed following further incubation in a greenhouse at 20 to 30°C. Disease was observed at all temperatures and increased with wetness duration. The optimum temperature for disease development ranged from 12 to 18°C. Only 3 h of wetness were required for disease development at 12 to 22°C. A minimum wetness period of 6 to 12 h was required for disease development at suboptimal temperatures. A multiple regression model describing the response surface of arcsine square root transformed disease severity was developed that had significant quadratic wetness effects, cubic temperature effects, and interaction between temperature and wetness. The resulting polynomial model provided a good fit to the observed data, accounting for 89% of the variation in transformed disease severity.