Disease Warning System Research Articles

Evaluation of a Penman–Monteith approach to provide “reference” and crop canopy leaf wetness duration estimates

Leaf wetness duration (LWD) is a key parameter for plant disease-warning systems since the risk of outbreaks of many plant diseases is directly proportional to this environmental variable. However, LWD is not widely measured so several methods have been developed to estimate it from weather data. Methods based on the physical principles of dew deposition and dew or rain evaporation have shown good portability and sufficiently accurate results for operational use. A Penman–Monteith approach to modeling LWD on a “reference” wetness sensor located at a weather station was investigated as well as the use of an empirical wetness coefficient ( W) to convert “reference” LWD into crop LWD. This study was undertaken because recent observations revealed that an LWD sensor located about 30 cm above a turfgrass surface provided useful estimates of LWD in various nearby crops, suggesting that modeling such a sensor and location may be a simpler “reference” alternative to modeling LWD in a crop canopy. LWD was measured over mowed turfgrass at different heights (30, 110, and 190 cm above the ground) and at the top of the canopy of eight crops – apple, coffee, cotton, maize, muskmelon, grape, soybean, and tomato – using painted flat-plate sensors. At the same times and places, automatic weather stations measured air temperature, relative humidity, wind speed, and net radiation over turfgrass. A Penman–Monteith approach estimated sensor LWD over turfgrass with very good accuracy and precision, using an additional aerodynamic resistance based on wind speed to estimate LWD at 110 and 30 cm. The model overestimated LWD by 3.3% at 190 cm ( R 2 = 0.92), 1.5% at 110 cm ( R 2 = 0.87), and 5.7% at 30 cm ( R 2 = 0.89). When modeled LWD for a 30-cm height over turfgrass was correlated with LWD measured at the top of crop canopies, strong agreement was observed, with an average overestimation of 6.3% and a coefficient of determination of 0.92 for five crops combined. The use of both general and specific W coefficients reduced the average overestimation and the mean absolute error in LWD to less than 1 h/day. When independent data from four crops were use to evaluate crop LWD estimates by this two-step Penman–Monteith approach, mean absolute error was <1.6 h when both general and specific W coefficients were used. We concluded that a Penman–Monteith model for a fixed sensor size, albedo and exposure over turfgrass may be a very useful “reference” index to estimate crop LWD for use in plant disease management schemes.

Evaluation of a Disease Warning System for Phomopsis Cane and Leaf Spot of Grape: A Field Study.

A field evaluation of a warning system for Phomopsis cane and leaf spot of grape (Vitis spp.), caused by Phomopsis viticola, was conducted in Ohio over 3 years (2002 to 2004) by applying fungicides and fungicide-adjuvant combinations based on predicted infection events. Three different criteria for risk-light, moderate, and high-were evaluated with the warning system. The warning system is based on measured weather conditions (temperature and wetness duration following rain) and a model for risk of leaf and internode infection. Vines were sprayed with fungicides based on either the warning system or a calendar-based 7-day protectant program, from 2.5-cm shoot growth (Eichhorn-Lorenz [E-L] stage 7) to the end of the broom (E-L stage 27). Fungicides were tested with or without an adjuvant (JMS Stylet-Oil or Regulaid). In the controls, the mean percentage of leaves and internodes with infections ranged from 36 to 100%, the number of lesions per leaf ranged from 1 to 28, and percentage of internodes covered by lesions ranged from 1 to 12%. Both the calendar-based protectant treatment (based on use of mancozeb) and the warning system treatment based on spraying in response to light or moderate predicted infection events (especially with mancozeb + Regulaid) resulted in significantly less disease incidence and severity compared with the controls. The mean percent control (relative difference in disease between a treatment and the control) was higher for the protectant schedule (˜55% and ˜80% for incidence and severity, respectively, based on application of mancozeb) than for the warning system (˜36% and ˜60% for incidence and severity, respectively, based on application of mancozeb + Regulaid), but there were two to three times more fungicide applications with the protectant schedule than with the warning system.

Forecasting Site-Specific Leaf Wetness Duration for Input to Disease-Warning Systems.

Empirical models based on classification and regression tree analysis (CART model) or fuzzy logic (FL model) were used to forecast leaf wetness duration (LWD) 24 h into the future, using site-specific weather data estimates as inputs. Forecasted LWD and air temperature then were used as inputs to simulate performance of the Melcast and TOM-CAST disease-warning systems. Overall, the CART and FL models underpredicted LWD with a mean error (ME) of 2.3 and 3.9 h day-1, respectively. The CFL model, a corrected version of the FL model using a weight value, reduced ME in LWD forecasts to -1.1 h day-1. In the Melcast and TOM-CAST simulations, the CART and CFL models predicted timing of occurrence of action thresholds similarly to thresholds derived from on-site weather data measurements. Both models forecasted the exact spray dates for approximately 45% of advisories derived from measurements. When hindcast and forecast estimates derived from site-specific estimates provided by SkyBit Inc. were used as inputs, the CART and CFL models forecasted spray advisories within 3 days for approximately 70% of simulation periods for the Melcast and TOM-CAST disease-warning systems. The results demonstrate that these models substantially enhance the accuracy of commercial site-specific LWD estimates and, therefore, can enhance performance of disease-warning systems using LWD as an input.

Analyses of the Relationships Between Lettuce Downy Mildew and Weather Variables Using Geographic Information System Techniques.

Previous studies in coastal California suggested that morning leaf wetness duration and temperature immediately after the prolonged leaf wetness period affect infection of lettuce by the downy mildew pathogen, Bremia lactucae. In this study, spatial analysis tools in a geographic information system were used to interpolate disease assessment data and then relate them to weather variables measured in 1995 and 1997 at weather stations in the Salinas Valley. Among the variables monitored at these weather stations, midday temperature (10:00 A.M. to 2:00 P.M.) was related most strongly to the interpolated downy mildew incidence in a circular area (radius = 5 km) around each station (r = 0.52, P < 0.0001); the higher the midday temperature, the lower the disease incidence. High humidity and prolonged morning leaf wetness duration also were associated with high downy mildew incidence. Cluster analysis resulted in distinct regions with different midday temperatures, which overlapped well (92.2% of the total area) with regions distinguished in previous cluster analyses of downy mildew incidence. Clusters of morning relative humidity showed similar patterns, although they overlapped less well with clusters of disease incidence. These results confirmed that midday temperature is an important determining factor for lettuce downy mildew, and its effects should be incorporated into a disease warning system for coastal California. Cluster analyses based on the effects of temperature have great potential for use in regional downy mildew risk assessment.

Operational exposure of leaf wetness sensors

Leaf wetness duration (LWD) is a key factor in plant disease occurrence in many phytopathosystems and, consequently, an important variable in disease warning systems. Measurement of LWD is often problematic because of the lack of a standard sensor, and lack of a standard exposure protocol. Accordingly, operational aspects of LWD exposure were evaluated using data from experiments in three different locations: Elora, Ontario, Canada; Ames, IA, USA; and Piracicaba, SP, Brazil. LWD sensors (flat, printed-circuit) were installed at different heights and angles, and above or inside different crops: turfgrass and corn in Elora; turfgrass and muskmelon in Ames; and turfgrass and cotton in Piracicaba. Visual observations of dew onset and dry-off were made for comparison with the different sensor positions. At Elora and Piracicaba, sensors deployed 30 cm above turfgrass and between 15° and 45° to horizontal showed the smallest errors in relation to visual observations of turfgrass wetness, for both dew onset and dry-off. Assuming the sensor at 30 cm and 30° as a reference for LWD measurements over turfgrass it was possible to identify significant differences among the different sensor heights and angles, showing that the position of the sensor had a strong effect on LWD measurements. Sensors at 190 cm measured shorter average LWD – 97 min for Elora and 54 min for Piracicaba – than sensors at 30 cm. No significant difference was observed between the sensors at 30 and 70 cm in both places. In Ames, the average difference in LWD between the sensors at 30 and 150 cm (both deployed at 45°) was 33 min. In relation to the angle of deployment, sensors at 0° and 15° measured longer average LWD – 38 min for Elora and 56 min for Piracicaba – than sensors at 30° and 45°. LWD measured by sensors near the standard screen height over turfgrass differed considerably from LWD measured by sensors in the canopy, especially during periods with less than 15 h of wetness. In contrast, sensors at 30 cm over the turfgrass showed potential for use in operational plant disease management systems because they provided much more accurate estimates of crop LWD despite large differences in crop height and structure.

Evaluating a Wetness-based Warning System and Reduced-risk Fungicides to Manage Sooty Blotch and Flyspeck of Apple

The effectiveness of a disease-warning system and efficacy of reduced-risk fungicides for management of sooty blotch (Peltaster fructicola, Leptodontium elatius, Geastrumia polystigmatis) and flyspeck (Schizothyrium pomi) (SBFS) of apple (Malus × domestica) were evaluated in Illinois, Iowa, and Wisconsin in 2001 and 2002. Warning system-timed applications of the second-cover fungicide spray occurred when 175 h of leaf wetness had accumulated; wetness data were derived either from a sensor placed beneath the canopy of apple trees (on-site) or according to remotely sensed estimates. In replicated experiments, using sensor measurements as inputs to the warning system saved one to three (mean 1.8) and zero to four (mean 2.3) fungicide sprays per season in 2001 and 2002, respectively. Because remotely estimated wetness hours accumulated more rapidly than did on-site measurements, the warning system using remotely sensed wetness data saved only zero to one (mean 0.3) and zero to two (mean 0.7) sprays per season in 2001 and 2002, respectively. SBFS incidence in the integrated pest management (IPM) plots did not differ significantly from that of conventional calendar-based fungicide sprays plots in 11 of 12 site-years. When on-site wetness measurements were used in demonstration trials at 14 cooperating commercial orchards in 2001 and 2002, the SBFS warning system saved one to six (mean 2.6) and two to seven (mean 3.1) sprays per season, respectively. Incidence of SBFS in IPM plots did not differ significantly from trees managed with cooperating growers' conventional fungicide schedules in 16 of 28 siteyears. The on-site warning system was more consistently successful in Illinois and Iowa than it was in Wisconsin in both replicated experiments and in cooperating commercial orchards. The reduced-risk fungicides kresoximmethyl and trifloxystrobin provided control of SBFS equal to conventional fungicides (benomyl or thiophanatemethyl) in all trials. Potassium bicarbonate controlled SBFS less effectively than either conventional fungicides on a calendar-based or disease-warning schedule, or treatments incorporating reduced-risk fungicides.

Managing apple scab (Venturia inaequalis) and powdery mildew (Podosphaera leucotricha) using Adem™

Current control of scab and mildew of apple in the UK requires the routine application of fungicides at 7 - 14-day intervals to achieve the blemish-free fruit required by the market. Such practices are generally effective, but with increased public concern about pesticides and rising costs to the grower, they are now less acceptable. The use of disease-warning systems offers scope for optimizing fungicide use by better timing of sprays. Adem™ is a PC-based system that warns of the risk of scab, mildew, Nectria fruit rot and canker and fireblight. In a 'key stage' strategy, warnings by Adem™ for scab and mildew integrated with practical pest and disease control resulted in similar or better control than a routine programme, with the additional benefit of reduced fungicide inputs and costs even in seasons exceptionally favourable for these diseases. Maximum savings in fungicide use were made by applying sprays curatively in response to scab warnings. However, this approach resulted in increased disease incidence to the crop and scab infection of fruit even in seasons unfavourable for scab attack.

Risk Assessment Models for Wheat Fusarium Head Blight Epidemics Based on Within-Season Weather Data

ABSTRACT Logistic regression models for wheat Fusarium head blight were developed using information collected at 50 location-years, including four states, representing three different U.S. wheat-production regions. Non-parametric correlation analysis and stepwise logistic regression analysis identified combinations of temperature, relative humidity, and rainfall or durations of specified weather conditions, for 7 days prior to anthesis, and 10 days beginning at crop anthesis, as potential predictor variables. Prediction accuracy of developed logistic regression models ranged from 62 to 85%. Models suitable for application as a disease warning system were identified based on model prediction accuracy, sensitivity, specificity, and availability of weather variables at crop anthesis. Four of the identified models correctly classified 84% of the 50 location-years. A fifth model that used only pre-anthesis weather conditions correctly classified 70% of the location-years. The most useful predictor variables were the duration (h) of precipitation 7 days prior to anthesis, duration (h) that temperature was between 15 and 30 degrees C 7 days prior to anthesis, and the duration (h) that temperature was between 15 and 30 degrees C and relative humidity was greater than or equal to 90%. When model performance was evaluated with an independent validation set (n = 9), prediction accuracy was only 6% lower than the accuracy for the original data sets. These results indicate that narrow time periods around crop anthesis can be used to predict Fusarium head blight epidemics.

Integrated Botrytis cinerea Management in Southeastern Spanish Greenhouses

AbstractA strategy for integrated biological and chemical control of Botrytis cinerea in unheated tomato greenhouses in southeastern Spain was tested. The biocontrol agent used was a commercial preparation developed from an isolate of Trichoderma harzianum T39 (Trichodex®). Decisions concerning whether to spray the biocontrol agent or a fungicide were made based on a future weather disease warning system called BOTMAN implemented as follows: no spraying when slow or no disease progress was expected; use of a chemical fungicide when an outbreak of epidemics was expected; in all other cases, application of Trichoderma harzianum T39 was recommended. A 4‐day weather forecast provided by the Eastern Andalusian Weather Forecast Service was used for predictions. The integrated strategy was compared with weekly applications of fungicides in two experiments conducted over 1998–99 and 1999–2000. Reduction of disease incidence was obtained only with the fungicide‐only treatment in the 1998–99 experiment (55%, P &lt; 0.05). Application of BOTMAN gave high disease risk only in 2 dates or times in that experiment, so fungicides were only applied twice. For the remaining 12 dates or times, Trichodex® was sprayed. In the second experiment, application of BOTMAN gave moderate risk all the weeks and Trichodex® was applied nine times. In this experiment, disease level did not differ significantly (P &lt; 0.05) from untreated plot. The reasons for failure of BOTMAN in Spanish conditions were discussed.

Incorporation of Temperature and Solar Radiation Thresholds to Modify a Lettuce Downy Mildew Warning System

ABSTRACT The effect of temperature on infection of lettuce by Bremia lactucae was investigated in controlled environment studies and in the field. In controlled conditions, lettuce seedlings inoculated with B. lactucae were incubated at 15, 20, 25, or 30 degrees C during a 4-h wet period immediately after inoculation or at the same temperatures during an 8-h dry period after the 4-h postinoculation wet period at 15 degrees C. High temperatures during wet and dry periods reduced subsequent disease incidence. Historical data from field studies in 1991 and 1992, in which days with or without infection had been identified, were analyzed by comparing average air temperatures during 0600 to 1000 and 1000 to 1400 Pacific standard time (PST) between the two groups of days. Days without infection had significantly higher temperatures (mean 21.4 degrees C) than days with infection (20.3 degrees C) during 1000 to 1400 PST (P < 0.01) but not during 0600 to 1000 PST. Therefore, temperature thresholds of 20 and 22 degrees C for the 3-h wet period after sunrise and the subsequent 4-h postpenetration period, respectively, were added to a previously developed disease warning system that predicts infection when morning leaf wetness lasts >/=4 h from 0600 PST. No infection was assumed to occur if average temperature during these periods exceeded the thresholds. Based on nonlinear regression and receiver operating characteristic curve analysis, the leaf wetness threshold of the previous warning system was also modified to >/=3-h leaf wetness (>/=0900 PST). Furthermore, by comparing solar radiation on days with infection and without infection, we determined that high solar radiation during 0500 to 0600 PST in conjunction with leaf wetness ending between 0900 and 1000 PST was associated with downy mildew infection. Therefore, instead of starting at 0600 PST, the calculation of the 3-h morning leaf wetness period was modified to start after sunrise, defined as the hour when measured solar radiation exceeded 8 W m(-2) (or 41 mumol m(-2) s(-1) for photon flux density). The modified warning system was compared with the previously developed system using historical weather and downy mildew data collected in coastal California. The modified system was more conservative when disease potential was high and recommended fewer fungicide applications when conditions were not conducive to downy mildew development.

The detection of Tomato spotted wilt virus (TSWV) in individual thrips using real time fluorescent RT-PCR (TaqMan)

Tomato spotted wilt virus (TSWV) is an important virus, economically in the UK, causing damaging disease in ornamental and vegetable crops. The virus is vectored by several species of thrips, most importantly the western flower thrips ( Frankliniella occidentalis Pergande [ Thysanoptera: Thripidae]). The vector thrips themselves constitute a damaging pest and are difficult to control completely. Monitoring thrips numbers is an important part of the control of virus, but does not give information on how many of the thrips are viruliferous. Monitoring the presence of viruliferous thrips at an early stage of an epidemic may lead to improved disease control, since virus can be spread effectively whilst vector pressure is low and symptoms may take several weeks to appear on some hosts. This paper describes the development of a sensitive and robust, high-throughput method for the detection of TSWV in individual insects based on TaqMan chemistry. The method incorporates a novel RNA specific internal control to increase the reliability of the results. Results are also presented on comparisons of different extraction methods, including insects taken from sticky traps, for high-throughout testing. Implementation of a method such as this for the reliable detection of TSWV in individual thrips would aid the understanding of the progress of TSWV epidemics, and offer an early disease warning system for growers.

Evaluation of BSPcast Disease Warning System in Reduced Fungicide Use Programs for Management of Brown Spot of Pear.

A forecasting model (BSPcast) developed for prediction of brown spot (Stemphylium vesicarium) of pear was evaluated as an advisory system for reduced fungicide use in disease management programs. Eleven trials were performed during 1995, 1996, and 1997 in five orchards in two different climatic areas in Catalunya (Spain) and Emilia-Romagna (Italy). Values of 3-day cumulative daily infection risk (CR) provided by the model were used to determine risk periods during the growing season of pear and were taken as thresholds to schedule fungicide sprays. The fungicide application programs tested using the model consisted of guided schedules with CR action thresholds of 0.4, 0.5, or 0.6, and fixed sprays following a standard commercial schedule. In nine out of 10 trials, no significant differences were observed in disease incidence on fruit at harvest between the fixed-spray commercial schedule and guided sprays using thresholds of 0.4 or 0.5. The average savings in number of fungicide sprays applied using BSPcast compared with the fixed-spray schedule were 20 to 70% when using fungicides with a 15-day protection period (kresoxim-methyl or procymidone) and ranged from 20 to 50% when using a fungicide with a 7-day protection period (thiram).

Evaluation of a Disease Warning System for Downy Mildew of Grapes.

An electronic warning system for grape downy mildew- based on models for the infection of leaves of Vitis lambrusca, production of sporangia by Plasmopara viticola in lesions, and sporangial survival-was tested over 7 years in Ohio. Grapevines were sprayed with metalaxyl plus mancozeb (Ridomil MZ58) when the warning system indicated that environmental conditions were favorable for sporulation and subsequent infection. Over the 7 years, plots were sprayed from one to four times according to the warning system, and from four to 10 times according to the standard calendar-based schedule (depending on the date of the initiation of the experiment). The warning system resulted in yearly reductions of one to six sprays (with median of three sprays). Disease incidence (i.e., proportion of leaves with symptoms) in unsprayed plots at the end of the season ranged from 0 to 86%, with a median of 68%. Incidence generally was very similar for the warning-system and standard-schedule treatments (median of 7% of the leaves with symptoms), and both of these incidence values were significantly lower (P < 0.05) than that found for the unsprayed control, based on a generalized-linear-model analysis. Simplifications of the disease warning system, where sprays were applied based only on the infection or sporulation components of the system, were also effective in controlling the disease, although more fungicide applications sometimes were applied. Effective control of downy mildew, therefore, can be achieved with the use of the warning system with fewer sprays than a with a standard schedule.

A privatized crop warning system in the USA*

Over 1000 weather stations are operating in the western USA in a multistate disease warning system. They are operated by several private service‐oriented companies, including Western Farm Service, Wilbur Ellis, Terra Spase and Ag Unlimited. These companies work cooperatively with the universities to develop, validate and implement algorithms. The weather stations, manufactured by Adcon Telemetry, collect meteorological information in many crops, for many types of disease and insect warnings. The data is reported by radio from the weather stations automatically. At central data collection facilities, data is analysed to determine disease and insect risk as well as information for irrigation, planting, harvesting and nutrient timing. Information is then distributed daily to hundreds of farming operations by Internet, fax, proprietary Adcon server software or personal visit. This information is combined with remote sensing, GPS, GIS, weather forecasting and scouting technologies to make crop management decisions at the farmer or consultant level. Farmers pay a fee for a service‐oriented information subscription. This technology usually reduces at least one fungicide application and/or improves crop quality or yield by 10–50%.

An Assessment of Fungicide Benefits for the Control of Fungal Diseases of Processing Tomatoes in New York and New Jersey.

Concurrent studies on the benefits of fungicide use for control of fungal diseases of processing tomatoes were conducted in New York and New Jersey in 1993 and 1994. Fungicides (chlorothalonil at 2.5 kg/ha or mancozeb at 1.68 kg/ha) were applied at 7-, 10-, or 14-day intervals to processing tomatoes for control of anthracnose caused by Colletotrichum coccodes, early blight caused by Alternaria solani, and Septoria leaf spot caused by Septoria lycopersici. The New Jersey trial included an additional treatment using the disease-warning system TOM-CAST. All fungicide treatments significantly reduced foliar disease severity (in New York) and anthracnose incidence (New York and New Jersey) in the 2 years of study. Yield of usable fruit was significantly increased by all fungicide treatments with the exception of the TOM-CAST treatment using the cultivar Brigade in 1994 in New Jersey. In New York, usable yield and financial benefit were consistently the highest in plots treated with chlorothalonil on a 7-day interval. In New Jersey, the highest usable yields and the greatest financial benefits occurred in the chlorothalonil 7- and 10-day interval treatments in 1993. At both locations, the yield and financial benefit associated with the fungicide treatments was primarily due to suppression of anthracnose and other fruit rots. Suppression of foliar diseases was less important.

Incorporation of Weather Forecasting in Integrated, Biological-Chemical Management ofBotrytis cinerea

ABSTRACT A strategy for integrated biological and chemical control of Botrytis cinerea in nonheated greenhouse vegetables was developed. The biocontrol agent used was a commercial preparation developed from an isolate of Trichoderma harzianum, T39 (Trichodex). Decisions concerning whether to spray the biocontrol agent or a fungicide were made based on a weather-based disease warning system. The integrated strategy (BOTMAN [short for Botrytis manager]) was implemented as follows: when slow or no disease progress was expected, no spraying was needed; when an outbreak of epidemics was expected, use of a chemical fungicide was recommended; in all other cases, application of T. harzianum T39 was recommended. Future weather information (a 4-day weather forecast provided by the Israel Weather Forecast Service) was more useful for disease warnings than immediate past weather. The integrated strategy was compared with weekly applications of fungicide in 11 experiments conducted over 3 years in greenhouse-grown tomato and cucumber. Disease reduction in the integrated strategy (63.9 +/- 3.0%) did not differ significantly (P < 0.05) from the fungicide-only treatment (70.1 +/- 3.6%). The number of fungicide sprays in the integrated strategy ranged from 2 to 7 (mean 4.2) compared to 7 to 13 (mean 10.5) in the fungicide treatment. The integrated strategy averaged 5.9 sprays of T. harzianum T39. For the integrated strategy, one treatment omitted use of T. harzianum T39 to estimate the contribution of this agent to disease control. Disease reduction in that treatment (49.1 +/- 4.8%) was significantly (P < 0.05) inferior to the combined chemical and biological strategy, indicating that the T. harzianum T39 sprays had a measurable effect on disease control.