CPD Powdery Mildew Project Annual Report March 2008
Project Title:
Development of a disease prediction model for pepper powdery mildew
Principal Investigator:
Mike Coffey, Professor
Dept. of Plant Pathology and Microbiology
UC Riverside
CA 92521
coffey@ucr.edu
Collaborators:
Oleg Daugovich,
Farm Advisor,
UC Cooperative Extension
Ventura
odaugovish@ucdavis.edu
David Holden
Holden Research and Consulting
P.O. Box 1437
Camarillo, CA 93011-1437
calcropdoc@yahoo.com
Maren Mochizuki
Staff Research Associate,
UC Cooperative Extension
Ventura
mmochizuki@ucdavis.edu
Remigio A. Guzm·n Plazola
Chairman, Plant Pathology Dept
Colegio de Postgraduados
Montecillo 56230, Texcoco
Estado de MÈxico, Mexico
rguzmanp@colpos.mx
Budget Total: $32,756
Project Year: March 1, 2007 to February 28, 2008
Statement of the Problem and Its Significance: California pepper production in California is regularly threatened by the powdery mildew pathogen Leveillula taurica. Growers can reduce application costs and expect to see increased quality by use of an effective predictive risk assessment model. Numerous powdery mildew models exist including improved versions of the Guzman Plazola model developed for powdery mildew of tomatoes in California. Control options that employ practices amenable to growers' production regimes can be improved by disease risk modeling to identify periods when the risk of loss is higher, so as to increase efficacy of registered fungicides. The goals of our proposed research include development and/or refinement of developed disease risk models to encourage their adoption by growers, ultimately resulting in lower production costs with decreased disease losses. If unwilling to deviate from a calendar schedule of fungicide application, at least advised delay (when possible) of the initial application can benefit both grower and the environment. The efficacy of a mildew control program is based upon prevention, rather than eradication. Powdery mildew occurs sporadically and unpredictably in California pepper fields and as such is obviously subject to environmental parameters that can either affect disease expression and development in a positive or negative way. Identification of the factors leading to disease onset and increase can help the grower both time and target the initial fungicide application. Should positive influences not occur then spray applications for control of pepper powdery mildew would not be recommended.
Objectives and Background: A disease risk prediction model for Leveillula taurica on tomatoes has been developed at UC Davis, applied, and partially validated by Dr. Remigio Guzman-Plazola, in tomato/pepper growing regions of Mexico. Like many such models, efficacy alone has not been enough to encourage grower adoption, as calendar spray schedules, though costly, offer a sense of security. Additional field validation could encourage growers to use fungicides in a more thrifty and effective manner, with economic and environmental benefits. A modified version of the Guzman-Plazola forecasting model is currently available to growers through the University of California Integrated Pest Management (UC IPM) website, and offers the ability to enter the growersí own local data. The model on the UC IPM site was further modified with respect to some very important parameters notably leaf wetness without any validation. A more recent version of the Guzman Plazola Model developed by the originator is available for this research (Guzman-Plazola, unpublished). However, this model was developed specifically for tomatoes. In our research we will attempt to develop a similar model for peppers. We are looking very carefully at leaf wetness and other parameters including relative humidity and temperature as useful environmental measures of environmental conditions affecting both mildew onset and development. The aim is to determine how their readouts relate to the trigger events in the predictive model. Additionally, other modeling approaches are still to be investigated.
A second model to be evaluated will be the Gubler/Thomas model originally developed from grape powdery mildew and later modified for other powdery mildews (Spectrum).
Data conversion is tedious and time-consuming but in the last 2 years we developed PERL-based software (Feliciano, unpublished) that will convert the weather station data logger databases into formats compatible with the requirements of the UC IPM website. This software can be placed on a website and made available to growers to allow conversion of their data. Ultimately, the entire system can be made automatic through additional software making input and forecasting extremely fast and user friendly.
The Guzman-Plazola model is premised upon infinite inoculum availability. The disease triangle helps us understand the three interrelated factors required for disease onset; susceptible host, conducive environmental conditions, and the presence of the pathogen. The latter factor is presumed present in most disease modeling. But this assumption is often unfounded.
Our lab has been working with this pathogen for some time now, both in pepper and tomato. We have not determined the racial structure within the pathogen population, though we have found that pepper and nightshades are far more susceptible to this disease than is tomato. It is likely that the pepper powdery mildew pathogen is different from that infecting tomatoes. We have determined that the effects of temperature and humidity on disease development are similar for both tomato and pepper.
Plans and Procedures: Similar predictive models have already been developed and demonstrated as valid in grape, hops and strawberry, and we wish to extend our efforts to pepper, to encourage adoption of proven research, in our long term efforts to reduce overall pesticide use. Two different disease prediction systems will be evaluated Guzman-Plazola and Gubler/Thomas as adapted by Mahaffee.
Our experience has shown that on-site telemetry is essential to monitor site-specific weather. This equipment consists of electronic sensors of weather variables, a transmitter to a receiver in the area, and relay to our computers via carrier. We have numerous software analytical packages, but the intention in this project would be to feed the data collected to the UC IPM free interface to the disease risk model. From this, conducive weather would alert us to the disease risk. Combined with the inoculum bellwether, we would decide whether or not to make the initial application.
Work Plan 2007:
- Established 4 cooperators willing to compare application management decision methods to their own standard practices.
- Replicated across 5 sites. The sites are representative of pepper-growing areas in Ventura County Oxnard, Santa Paula), the Coachella Valley (Oasis), Salinas Valley (Hollister) and the Central Valley (Woodland).
- Monitored model and feed data regularly. Data was collected at 5-15 minute intervals and included temperature, relative humidity and leaf wetness (measured by an artificial leaf wetness monitor).
- Compared two systems for collecting environmental data (Hobo Weather station and Spectrum Watchdog Data loggers). Calibrated the two different types of leaf wetness monitor to be compatible with the prediction model.
Mildew Forecasting using the Disease Prediction Model
A disease risk prediction model for Leveillula taurica has been developed by Dr. Remigio Guzman-Plazola, while working at UC Davis with Dr. Mike Davis. For pepper growers, field validation at sufficient locations and through several mildew years might encourage growers to use fungicides in a more effective manner, with economic and environmental benefits. In particular, such disease prediction technologies could be used to determine if and when to apply the first fungicide spray. Such field-based analysis and research would permit modifications and fine-tuning of prediction programs to make them more robust. One version of the Guzman-Plazola forecasting model is currently available to growers through the University of California Integrated Pest Management (UC IPM) website, and allows the grower to enter their own local data. Several other versions of this model are also available and they need to be compared for their abilities to forecast disease. In collaboration with Dr. Remigio Guzman-Plazola who is involved in developing a similar system for Mexican tomato and pepper growers we are in the process of analyzing and improving the available models.
Practical problems for the California pepper grower include the collection, collation and conversion of the weather data to a format compatible with the UC IPM site. This is currently an extremely time-consuming process and it is highly desirable to develop the software to make data analysis straightforward and rapid. In fact the ideal system would be one where telemetry data is ëgrabbedí automatically and is then ëfedí into the prediction model and a disease forecast again automatically sent to the grower. This year we developed PERL-based software that can be used as an interface on a Linux-driven (Max OS X) server in my UCR office to instantly convert field data into a format compatible with the disease prediction program.
Another issue for growers will be the cost of the equipment for monitoring weather. Ultimately, it might be possible to obtain regional data from a network of telemetry stations. The validity of using regional weather data to forecast powdery mildew also needs to be assessed. In the short-term the monitoring of weather data over several ëmildewí years from a small number of well-maintained telemetry stations will provide the needed databases to validate or modify different powdery mildew forecasting models including those of Guzman-Plazola and Gubler/Thomas.
The Guzman-Plazola model is premised upon infinite inoculum availability. The disease triangle helps us understand the three interrelated factors required for disease onset: susceptible host, conducive environmental conditions, and the presence of the pathogen. The latter factor is presumed present in most disease modeling. But this assumption is often unfounded.
One desirable objective will be to determine the key factors in triggering mildew epidemics and, if possible simplify the database requirements.
Our lab has been working with this pathogen for some time now, both in pepper and tomato. Although we have not determined the racial structure within the pathogen population, we have found that pepper and nightshades are far more susceptible to this disease than is tomato. Placement of highly susceptible pepper varieties such as ëFooled Youí in growersí plantings might serve as a bellwether of inoculum presence. Combined with usage of the forecasting model, our objective would be to demonstrate the utility of our and othersí research to reduce grower costs while assuring harvest.
We have numerous software analytical packages, but the intention in this project would be to feed the data collected to the UC IPM free interface to two versions of the disease risk model that use different leaf wetness scales. A third and original version, which is SAS-based and ëformattedí in an Excel-based program will also be tested with the assistance of Dr. Remigio Guzman-Plazola. From this, conducive weather would alert us to the disease risk. Combined with the inoculum bellwether, we would decide whether or not to make the initial application.
UC IPM Collaboration (Joyce Strand):
UC IPM will develop and make available a second version of the model for our project, so that he can compare model results based on the two different ways of determining wet hours. In addition, we will submit data files to Guzman so that he can run them against the original SAS model to make sure that UC IPM 's model generates the same results as the original.
A critical factor in this epidemiological research will be the accurate monitoring and recording of powdery mildew occurrence and increase during a growing season at the experimental sites. Without this careful evaluation and recording of disease progress the research will be meaningless. We purchased a field-tested a HOBO Weather Station which offers research-grade measurement quality and up to 10 channels that accept plug-in smart sensors that eliminate complicated programming, wiring, and calibration. The entire HOBO Weather Station system, including sensors, is powered for one year using four AA batteries and can log over 500,000 measurements into the non-volatile memory. Leaf Wetness Sensor Data logger We also purchased 2 WatchDog 450 Series Data Loggers featuring four channels with a capacity of 15,000 measurements (3,750 per channel). Data can be downloaded to a PC for analysis. Select measurement intervals are those 1, 10, 15, 30, 60 and 120 minutes. A 30-minute measurement interval will record for 85 days before the logger's memory is full. EEPROM memory keeps data safe in case of power loss. WatchDog Datalogger Leaf Wetness sensor A replicated trial was planted at the Hansen Trust Farm on June 13 (TABLE 1). Compounds to be evaluated included Rally, Cabrio, Quintec and a new material Dpx-LEM17. Two applications of the chemicals were made. Unfortunately powdery mildew did not appear until almost the end of the season. No results were obtained for relative efficacy of the materials. TABLE 1. Powdery Mildew Control of Peppers, Hansen Trust Farm, Ventura County 2007 Treatments: 10, 5 reps Planted June 13, 2007. Hybrid variety Excalibur (gift from Headstart Nursery, Mecca) We collected data at 5 sites this year. At two of them different weather monitoring datalogging systems: Hobo and Spectrum Watchdog were compared. Hobo weather stations are very robust and easy to operate and download usable data. Spectrum Bulldogs are currently used by Guzman-Plazola in Mexico for refining his predictive model. From a user perspective, Watchdog dataloggers proved to be the most reliable. Unnfortunately, powdery mildew appeared either very early before the dataloggers were properly in place or extremely late in the season when observations were no longer taking place. I thank the California Pepper Commission for their generous financial support for this research. Planting material was provided by Headstart Nursery. 1 Laboratory Assistant I @ $24,852 per year (12 months, 80% time) 2 Benefits (22%) for Laboratory Assistant I for 12 months. 3 Cost of university fleet car rental and overnight accommodation — 16 trips to collect data From 4 field sites in pepper growing areas ($200 per trip) 4 Equipment already purchased with CTC funds includes one Hobo Weather Station and two Spectrum Bulldog Data loggers. Additional equipment required includes an additional Hobo Weather station ($2,200), 2 more Bulldogs ($900) and 2 radio telemetry units for the Hobo weather stations ($2,200). Mike Coffey, Professor & Plant Pathologist
Fungicide Research in 2007
Water volume: ~120gal/A, ~1L/treat (first application) 8-23-07
200 gal/, 1740 ml from 2nd application on
Plots: 10 X 2 ft= 20 ft2 Total area/ treat. 100 ft2 (0.00229A)
Spray pressure: 50psi
Treatment Code Rate/A gm or ml/treat (2L) 1. Non treated Control White ------ ------- 2. Dpx-LEM17 20% Blue 8 fl oz (236.58ml) 0.54 ml 3. Dpx-LEM17 20% Red 14 fl oz (414.0ml) 0.95ml 4. Dpx-LEM17 20% Pink 20 fl oz (591.46ml) 1.35ml 5. Rally 40W Green 4 oz (113.5gm) 0. 3gm 6. Cabrio Yellow 16 oz (454gm) 1.03gm 7. Cabrio alt Orange 16 oz (454gm) 1.03gm Rally 4 oz (113.5gm) 0.26gm 8. Milstop Purple 2.5 lb (1135gm) 2.6gm 9. Milstop Lime 3.5 lb (1589gm) 3.64gm 10. Quintec Yellow/Red 8 fl oz (236.58ml) 0.54ml
Rep I 1 2 3 4 5 6 7 8 9 10 Rep II 5 7 6 9 10 4 3 2 1 8 Rep III 2 8 4 1 7 10 5 9 6 3 Rep IV 9 6 1 5 8 2 7 3 10 4 Rep V 4 2 7 8 10 3 1 6 9 5
Excalibur (PSX25785) - Breeder and vendor: Petoseed. Characteristics: Blocky bell, large, green to red; medium plant. Resistance: Tobacco Mosaic Virus. 1989.Research Summary
Acknowledgements:
Detailed Budget: Laboratory Assistant I (salary 80% ) 19,8821 (benefits) 4,3742 Salary and Benefits Total 24,256 Travel /Subsistence 3,2003 Equipment 5,3004 Total: 32,756 Signatures:
March 25, 2008