Clare R. Elliott
Oregon State University, Department of Botany and Plant Pathology, Corvallis, OR
Figures available on request
Disease forecasting systems are becoming increasingly important tools in agriculture. Particularly as scientific methods for monitoring the environmental conditions in the field have become more reliable, communications systems more efficient and modeling software more accurate. However, their utility is often limited due to a lack of understanding of, and/or ability to model the pathogen biology and its relationship to disease development.
Hop powdery mildew (Podosphaera macularis), is an economically important disease of hops (Humulus lupulus L.) worldwide which can result in 100% crop loss if not controlled. It is a polycyclic disease that can have as many as 50 generations in a growing season (7). Current management is accomplished using protectant fungicides applied based on a calendar program or an infection risk forecaster (4) that was adapted from the Gubler/Thomas infection risk forecaster for grape powdery mildew (3). Its’ use has resulted in the reduction of fungicide applications used to manage hop powdery mildew (HPM) but it still appears to call for unnecessary applications (Mahaffee, unpublished).
Current HPM models assume that the secondary spores are always present during the asexual phase of the epidemic (4). This assumption may not always be true. It is likely that conditions for sporulation and dissemination do not always precede conditions conducive to infection. Thus the model would incorrectly classify periods as high risk for infection even when there are no viable spores available, potentially resulting in excessive fungicide applications.
Exposure to temperature above optimum has been shown to reduce lesion size (7) and preliminary investigations have shown that sporulating colonies exposed to temperatures >30ºC for 6h result in spores with reduced infection potential 15h after exposure (Mahaffee, unpublished). Field surveys also indicate that the rate of disease development also decreases during July and August when temperatures routinely exceed 30ºC for more than 6h continuously (1,4). The magnitude, length and time of exposure to supraconducive temperatures in relation to time of inoculation has been observed to significantly affect disease development of HPM (5) and it is likely that temperature impacts spore availability in a similar manner.
There have been no studies on the temperature effect of sporulation for P. macularis but there has been some similar work on other genera of powdery mildew. Experiments on grape powdery mildew (Uncinula necator) by Chellemi and Marois (1, 2) found that sporulation was reduced with increasing temperatures above 26ºC. Similarly, experiments on begonia powdery mildew (Oidium begoniae) by Quinn and Powell (6) showed that temperatures above 28ºC caused inhibition of sporulation. These data indicate that accounting for the effects of temperature on sporulation may enhance accuracy of disease or infection risk models.
The aim of this study was to assess the effect of temperature on the sporulation of Podosphaera macularis. It will then be possible to consider the usefulness of this information in developing a forecasting model for hop powdery mildew and to suggest further investigation to lead to the development of an improved forecasting technique.
Materials and Methods
Plant preparation. Greenwood cuttings of the Symphony variety were propagated, from clonal mother plants, into 4” pots of Sunshine mix #1 (SunGro Horticulture, Bellevue, WA) with Soil Moist granules (JRM Cleveland, OH) added to the soil and APEX nursery fertilizer 14-14-14 pellets (JR Simplot Company, Lathrop, CA) on the soil surface. Plants were fertigated with Sunshine Technigro 16-17-17 (SunGro Horticulture, Bellevue, WA) when watered. Sulphur was vaporized for 4h each night to keep the plants free of powdery mildew. Plants were pruned to maintain one bine which was trained clockwise around stakes. Plants were grown under greenhouse conditions (15-26ºC) where light was supplemented with high pressure sodium lamps to achieve a photoperiod of at least a 15h.
Inoculation. A field population of P. macularis, isolated from Oregon hop yards, maintained on successive transfers of potted symphony plants incubated in growth chambers at 13ºC with a 15h photoperiod (~300µmol/m2/s) was used for all inoculations. Inoculum was prepared by selecting infected hop leaves and rubbing the spores from the lesions into a solution of 0.01% (w/v) TWEEN 20. Plants with 4 to 6 unfurled leaves were inoculated with a spore suspension of 60,000 conidia/ml using a hand held atomizer (Nalgene, Rochester, NY) after the apical bud was removed. Plants were air dried at 25ºC within an hour of immersing leaves in the TWEEN solution (to prevent lysis of the conidia). Plants were then incubated at 18ºC in a growth chamber with a 15h day length until mature, sporulating lesions had developed (typically 9-10 days after inoculation).
Effect of constant temperature on sporulation. Plants with mature, sporulating lesions were prepared for the temperature treatments by removing all but the single most infected leaf, blowing the available spores from the lesions using a 14000kg/m2 (20psi) air supply, and positioning the stem so that the leaf was 8cm above the top of the pot. Plants were then placed in 29.5 cm × 11.8 cm × 12.1 cm plastic vessels (Snapware, Inc, Mira Loma, CA) with an airtight lid. A custom impaction spore sampler was mounted in the lid (figure 1). The trap was capable of sampling 57L/min when using 1.5 mm × 22 mm acrylic rods. Perforated tubing was placed around the stem of the plant and linked to an air source (figure 1). Plants were placed at each temperature, 5, 10, 15, 20, 25, and 30ºC and incubated for 48 h with a 15h photoperiod (~300µmol/m2/s). After transferring two acrylic rods coated with petroleum jelly to each spore trap, the traps were turned on and 30 x 1 sec air blasts (28,000kg/m2) were administered using the perforated tubing. After running the traps for 15 min rods were collected and number of spores on the leading edge enumerated microscopically. Leaf and lesion area was determined using Access image analysis software (APS Press, St. Paul, MN). Data were transformed to trapped spores/cm2 of lesion area for each leaf.
Experimental design and statistical analysis. The experiment was a randomized complete block design with replication in time and 3 sub samples per replication. Between each replication, growth chambers were randomly assigned temperatures and reprogrammed. A control vessel was placed in each growth chamber, which consisted of a plant with mature, sporulating lesions and a thermo coupler inside to monitor temperature.
Figure 1. Custom impaction spore sampler.
1) Motor; 2) Power supply wire; 3) Air tight lid; 4) Plastic vessel; 5) Training stake; 6) Tape to secure leaf; 7) Infected hop plant; 8) Air supply inlet; 9) Perforated tubing; 10) Plant pot.
Effect of constant temperature on sporulation. There was a significant curvilinear relationship between temperature and trapped spores. It shows that there is a lot of variation between the results in each temperature treatment. Figure 2 shows the average of all the repetitions at each temperature treatment. It indicates that there is a steady increase in sporulation with temperature increase up to 20ºC. The graph plateaus around 25ºC which where the maximum average sporulation occurs. The graph then declines as the temperature reaches 30ºC.
Figure 2: Effect of temperature on sporulation. Symbols represent mean number of spores/cm2 from 6 replications. Bars indicate standard deviation from the mean
Effect of constant temperature on sporulation. The results in figure 2 show the expected trend, of increasing sporulation up to 25ºC and then a decline in the level of sporulation.
However there is a wide range of data observed at each temperature treatment and there is not a significant difference between temperature treatment even though figure 2 shows a trend in the data there is too much variation for this to have any significance with such a small sample size.
There are several factors that can be identified as possible sources variation.
Condensation was present in some of the tubes but not others which is indicative of differences in relative humidity. RH has been shown to influence sporulation slightly. Quinn and Powell (6) observed that decreasing relative humidity caused slight decreases in conidial germination and the development of mildew colonies on begonia.
The presence of condensation in the tubes should be included as part of the statistical analysis to see if this had a barring on the sporulation results.
The leaves that were chosen for spore collection and lesion area analysis were not all the same size and there was variation in the maturity and density of the lesions. In some cases lesions were present on the underside of the leaves too. This may cause variation since the conidia will get blown differently here than the lesions on the upper surface of the leaf so spore samples may be higher in the cases where lesions were present on the underside of the leaves.
Some plants had thrips and/or mites present on the leaf surface which reduced the capacity of the lesions to produce spores.
It is possible to assess all of the leaves for mites or thrips after taking the photographic data so that any sub samples with these pests can be thrown out and thus remove another source of variation.
Post analysis assessment of the photographs may shed light on the quality of the lesions and could indicate other sources of variation in the data.
Although the growth chambers were randomized and set to target temperatures it is possible that there was some fluctuation in the actual temperatures achieved and whether the temperature remained constant.
Extracting the temperature readings from the thermo coupler in the control plants It was found that the chambers didn’t always attain the target temperature. The average temperatures for each chamber were calculated for each treatment. This allowed the data to be plotted against a more accurate temperature scale rather than against the target temperature intervals.
The total area of each leaf in the sub samples should be calculated to see if it is a significant factor causing variation.
All of these are factors which were not properly controlled or accounted for in the data and could have been a cause of the high degree of variation that was observed in the data in figure 2.
After these factors have been accounted for in the existing data further statistical analysis may show more significant trends in the data and less variation or noise.
Improvements for further experiments. The observed variation in the data indicates that further improvement in experimental design is necessary to address the significant uncontrolled experimental error.
It was found that some of the data from the thermo couplers in the control plant tubes gathered inaccurate data and so it is suggested that new, more accurate HOBO’s are purchased to gather both temperature and relative humidity (RH) data from the control plants to allow the sporulation data to be plotted against a more accurate temperature scale. This would smooth out variation caused by fluctuations in the growth chamber temperatures. The inclusion of RH data could also be of benefit in analyzing the data.
When setting up the experiment, where possible all equipment should be assembled on the start date of the temperature treatments to minimize any unnecessary disturbance to the plants on the sampling date.
An improved method of applying the inoculum could be devised to ensure that leaves of similar area are inoculated with a similar number of spores, resulting in a more uniform density of lesions and eliminating the variation of lesions forming on the underside of the leaves.
Application. With this knowledge the current hop powdery mildew forecasting model could be improved (4). Rather than assuming that the inoculum is always present the observed temperature in the field can be used to predict a level of inoculum which when combined with data predicting the conduciveness of conditions for infection will provide more accurate forecasts for the disease development in the field. This will enable fungicide application at the appropriate times for maximum effectiveness and minimum waste.
I would like to thank Walt Mahaffee and Amy Peetz for their patient advice and guidance.
Chellemi, D. O., and Marois, J. J. 1991. Effect of fungicides and water on sporulation of Uncinula necator. Plant Disease 75:455-157.
Chellemi, D. O., and Marois, J. J. 1991. Sporulation of Uncinula necator on grape leaves as influenced by temperature and cultivar. Phytopathology 81:197-201.
Gubler, W. D., Rademacher, M. R., Vasquez, S. J., and Thomas, C. S. 1999. Control of powdery mildew using the UC Davis powdery mildew risk index. Online. APSnet Feature Story, January 1999. American Phytopathological Society, St. Paul, MN.
Mahaffee, W.F., Thomas, C.S., Turechek, W.W., Ocamb, C.M., Nelson, M.E., Fox, A., and Gubler, W. D. 2003. Responding to an introduced pathogen: Podosphaera macularis (hop powdery mildew) in the Pacific Northwest. Online. Plant Health Progress doi: 10.1094/PHP-200301113-07-RV.
Mahaffee, W.F., Turechek, W.W., and Ocamb, C.M. 2003. Effect of variable temperature on infection severity of Podosphaera macularis on hops. Phytopathology 93:1587-1592.
Quinn, J. A., and Powell, C. C., Jr. 1982. Effects of temperature, light, and relative humidity on powdery mildew of begonia. Phytopathology 72:480-484.
Turechek, W.W., Mahaffee, W.F., and Ocamb, C.M. 2001. Development of management strategies for hop powdery mildew in the Pacific Northwest. Online. Plant Health Progress doi: 10.1094/PHP-2001-0313-01-RS.