The relationship of leaf wetness duration and disease progress of glume blotch, caused byStagonospora nodorum, in winter wheat to standard weather data

1996 ◽  
Vol 102 (1) ◽  
pp. 9-20 ◽  
Author(s):  
A. Djurle ◽  
B. Ekbom ◽  
J. E. Yuen
Keyword(s):  
Winter Wheat ◽  
Weather Data ◽  
Leaf Wetness ◽  
Leaf Wetness Duration ◽  
Disease Progress ◽  
Glume Blotch ◽  
Relationship Of ◽  
The Relationship

Effects of temperature and leaf wetness duration on infection of pear leaves by Venturia pirina

2000 ◽  
Vol 51 (1) ◽  
pp. 97 ◽  
Author(s):  
O. N. Villalta ◽  
W. S. Washington ◽  
G. M. Rimmington ◽  
P. A. Taylor
Keyword(s):  
Disease Severity ◽  
Field Experiments ◽  
Leaf Wetness ◽  
Leaf Wetness Duration ◽  
Controlled Conditions ◽  
Pyrus Communis L ◽  
Venturia Pirina ◽  
Effects Of Temperature ◽  
Relationship Of ◽  
The Relationship

The effects of temperature and wetness duration on the infection of pear leaves (Pyrus communis L.) by Venturia pirina were studied by inoculating plants with ascospores and conidia under controlled conditions and in the field. Under controlled inoculations, minimum wetness durations that lead to leaf infections by ascospores were 27, 15, 13, 11, 10, 9, and 9 h at 4, 8, 10, 12, 15, 20, and 25°C, respectively. In parallel inoculations with conidia, the minimum wetness durations that lead to leaf infections were similar to ascospores at temperatures between 12°C and 25°C, but at lower temperatures (4, 8, 10°C), conidia infected leaves only after an additional 2 h of leaf wetness. The relationship between minimum wetness times and temperature was best described using an exponential regression. In field experiments, leaf infection on plants inoculated with ascospores and conidia under various naturally occurring wetness and temperature conditions was in close agreement with those under controlled conditions. Disease severity (percent of leaf area infected) increased with increasing leaf wetness duration at all temperatures. The optimum temperature for infection was 20°C. Analysis of variance with orthogonal polynomial contrasts was used to define the relationship of the angular transformation of disease severity to temperature and leaf wetness duration.

scholarly journals A Model Defining the Relationship Between Temperature and Leaf Wetness Duration, and Infection of Watermelon by Colletotrichum orbiculare

Plant Disease ◽  
1997 ◽  
Vol 81 (7) ◽  
pp. 739-742 ◽  
Author(s):  
J. S. Monroe ◽  
J. B. Santini ◽  
R. Latin
Keyword(s):  
Experimental Design ◽  
Orthogonal Polynomial ◽  
Analysis Of Variance ◽  
Leaf Wetness ◽  
Controlled Environment ◽  
Optimum Temperature ◽  
Colletotrichum Orbiculare ◽  
Leaf Wetness Duration ◽  
Relationship Of ◽  
The Relationship

Controlled environment experiments were conducted to determine the relationship between temperature, leaf wetness duration, and infection of watermelon by Colletotrichum orbiculare. Flats of watermelon seedlings were inoculated and exposed to various combinations of temperature (12, 15, 18, 21, 24, 27, and 30°C) and leaf wetness duration (2, 4, 8, 12, 16, and 24 h). The experimental design was a split-plot, with whole units represented by temperature and subunits represented by leaf wetness duration. Anthracnose incidence, defined as the percentage of symptomatic seedlings in each flat 10 days after inoculation, increased with increasing leaf wetness duration at all levels of temperature. The optimum temperature for infection ranged from 21 to 24°C. At most temperatures, as little as 2 h of leaf wetness was required for infection. Analysis of variance with orthogonal polynomial contrasts and multiple regression procedures was used to define the relationship of anthracnose incidence to temperature and leaf wetness duration.

scholarly journals Pre-anthesis development of winter wheat and barley and relationships with grain yield

2018 ◽  
Vol 64 (No. 7) ◽  
pp. 310-316 ◽  
Author(s):  
Mirosavljevic Milan ◽  
Momcolovic Vojislava ◽  
Maksimovic Ivana ◽  
Putnik-Delic Marina ◽  
Pržulj Novo ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Grain Yield ◽  
Sowing Date ◽  
Wheat Cultivars ◽  
Growing Seasons ◽  
Sowing Dates ◽  
Winter Wheat Cultivars ◽  
Leaf Appearance ◽  
Relationship Of ◽  
The Relationship

The aim of this study was to improve understanding of (1) the effect of genotypic and environmental factors on pre-anthesis development and leaf appearance traits of barley and wheat; (2) the relationship of these factors with grain yield, and (3) the differences between these two crops across different environments/sowing dates. Therefore, trials with six two-row winter barley and six winter wheat cultivars were carried out in two successive growing seasons on four sowing dates. Our study showed that the observed traits varied between species, cultivars and sowing dates. In both growing seasons, biomass at anthesis and grain yield declined almost linearly by delaying the sowing date. There was no clear advantage in grain yield of wheat over barley under conditions of later sowing dates. Generally, barley produced more leaf and had shorter phyllochron than wheat. Both wheat and barley showed a similar relationship between grain yield and different pre-anthesis traits.

scholarly journals Influence of Leaf Wetness Duration and Temperature on Infection of Grape Leaves by Elsinoë ampelina under Controlled and Vineyard Conditions

Plant Disease ◽  
2020 ◽  
Vol 104 (11) ◽  
pp. 2817-2822
Author(s):  
Odile Carisse ◽  
Audrey Levasseur ◽  
Caroline Provost
Keyword(s):  
Leaf Area ◽  
Weather Conditions ◽  
Leaf Wetness ◽  
Predictive Capacity ◽  
Leaf Wetness Duration ◽  
Infection Period ◽  
Richards Model ◽  
Elsinoe Ampelina ◽  
Independent Observations ◽  
The Relationship

On susceptible varieties, indirect damage to vines infected by Elsinoë ampelina range from reduced vigor to complete defoliation while, on berries, damage ranges from reduced quality to complete yield loss. Limited knowledge about the relationship between weather conditions and infection makes anthracnose management difficult and favors routine application of fungicides. The influence of leaf wetness duration and temperature on infection of grape leaves by E. ampelina was studied under both controlled and vineyard conditions. For the controlled conditions experiments, the five youngest leaves of potted vines (Vidal) were inoculated with a conidia suspension and exposed to combinations of six leaf wetness durations (from 0 to 24 h) and six constant temperatures (from 5 to 30°C). A week after each preset infection period, the percent leaf area diseased (PLAD) was assessed. At 5°C, regardless of the leaf wetness duration, no disease developed. At 10 and at 15 to 30°C, the minimum leaf wetness durations were 4 and 6 h, respectively. Above the minimum wetness duration, at temperatures from 10 to 30°C, PLAD increased linearly, with increasing leaf wetness up to 12 h, and then at a lower rate from 12 to 24 h. The optimal temperature for infection was 25°C. Relative infection was modeled as a function of both temperature and wetness duration using a Richards model (R2 = 0.93). The predictive capacity of the model was evaluated with data collected in experimental vineyard plots exposed to natural wetness durations or artificial wetness durations created using sprinklers. In total, 264 vineyard infection events were used to validate the controlled experiments model. There was a linear relationship between the risk of infection estimated with the model and the observed severity of anthracnose (R2 = 90); however, the model underestimated disease severity. A risk chart was constructed using the model corrected for vineyard observations and three levels of risk, with light, moderate, and severe risks corresponding to ≤5, >5% to ≤25, and >25% leaf area diseased, respectively. Overall, 93.9% of 132 independent observations were correctly classified, with 100, 29.4, and 9.4% of the light, moderate, and severe risks, respectively.

scholarly journals Use of an Empirical Model to Estimate Leaf Wetness Duration for Operation of a Disease Warning System Under a Shade in a Ginseng Field

Plant Disease ◽  
2016 ◽  
Vol 100 (1) ◽  
pp. 25-31 ◽  
Author(s):  
Kyu Jong Lee ◽  
Je Yong Kang ◽  
Dong Yun Lee ◽  
Soo Won Jang ◽  
Semi Lee ◽  
...  
Keyword(s):  
Empirical Model ◽  
Disease Risk ◽  
Fuzzy Model ◽  
Warning System ◽  
Weather Data ◽  
Effective Control ◽  
Leaf Wetness ◽  
Spray Application ◽  
Leaf Wetness Duration ◽  
Foliar Diseases

Ginseng foliar diseases are typically controlled by spray application using periodic schedules. Few disease warning systems have been used for effective control of ginseng foliar diseases because ginseng is grown under shade nettings, which makes it difficult to obtain weather data for operation of the disease warning system. Using weather data measured outside the shade as inputs to an empirical leaf wetness duration (LWD) model, LWD was estimated to examine if operation of a disease warning system would be feasible for control of ginseng foliar diseases. An empirical model based on a fuzzy logic system (fuzzy model) was used to estimate LWD at two commercial ginseng fields located in Gochang-gun and Jeongeup-si, Korea, in 2011 and 2012. Accuracy of LWD estimates was assessed in terms of mean error (ME) and mean absolute error (MAE). The fuzzy model tended to overestimate LWD during dew eligible days whereas it tended to underestimate LWD during rainfall eligible days. Still, daily disease risk ratings of the TOM-CAST disease warning system, which are derived from estimates of wetness duration and temperature, had a tendency to coincide with that derived from measurements of weather variables. As a result, spray advisory dates for the TOM-CAST disease warning system were predicted within ±3 days for about 78% of time windows during which the action threshold for spray application was reached. This result suggested that estimates of LWD using an empirical model would be helpful in control of a foliar disease in a ginseng field. It was also found that a spray application time model using meteorological observations may prove successful without the requirement of leaf wetness sensors within the field. Development of empirical correction schemes to the fuzzy model and a physical model for LWD estimation in a ginseng field could improve accuracy of LWD estimates and, as a result, spray advisory date prediction, which merits further studies.

The relationship of LT50 to prolonged freezing survival in winter wheat

2008 ◽  
Vol 88 (5) ◽  
pp. 885-889 ◽  
Author(s):  
D. Z. Skinner ◽  
K. A. Garland-Campbell
Keyword(s):  
Winter Wheat ◽  
Freezing Tolerance ◽  
Linear Regression Analysis ◽  
Triticum Aestivum L ◽  
The Other ◽  
Freezing Injury ◽  
Tolerance Mechanism ◽  
Relationship Of ◽  
The Relationship

Twenty-six wheat (Triticum aestivum L.) lines were tested for their ability to withstand remaining frozen for extended periods of time. Survival of acclimated seedlings was evaluated after remaining frozen at -5°C for 15 or 20 wk. Survival after 15 wk ranged from 0 to 100% and after 20 wk ranged from 0 to 33%. The relationship of survival and LT50 scores, the temperatures at which 50% of the plants were predicted to die, was examined with linear regression analysis. The linear relationship was highly statistically significant after 15 wk and after 20 wk. The cultivars Norstar and Froid survived being frozen for 20 wk nearly twice as well as the other cultivars; about 33% vs. 17% for the next best cultivar. These results indicated that the LT50 score, which can be estimated in about 8 wk, reliably predicts the ability to survive in the frozen state for as long as 20 wk, and that Norstar and Froid possess a long-term freezing tolerance mechanism that is far superior to the other cultivars tested. Key words: Winter wheat, freezing tolerance, freezing injury

scholarly journals Environmental Factors Affecting the Severity of Alternaria Brown Spot of Citrus and Their Potential Use in Timing Fungicide Applications

Plant Disease ◽  
2000 ◽  
Vol 84 (6) ◽  
pp. 638-643 ◽  
Author(s):  
L. W. Timmer ◽  
H. M. Darhower ◽  
S. E. Zitko ◽  
T. L. Peever ◽  
A. M. Ibáñez ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Disease Severity ◽  
Environmental Data ◽  
Brown Spot ◽  
Weather Data ◽  
Leaf Wetness ◽  
Point System ◽  
Leaf Wetness Duration ◽  
Alternaria Brown Spot ◽  
Trap Plants

Alternaria brown spot affects many tangerines and their hybrids, causing lesions on leaves, twigs, and fruit resulting in reduced yield and fruit quality. Field studies were conducted in a severely affected Minneola tangelo grove in central Florida from 1996 to 1998 to determine the environmental factors associated with infection of field trees and potted trap plants. Conidial production peaked following large flushes of new leaves, which were heavily infected. Most infections occurred during the summer rainy season, but trap plants became infected nearly every week of the year. When plants were exposed for 1-week periods, linear regression analysis indicated that disease severity on trap plants was positively related to the amount of rainfall, duration of leaf wetness, and average daily temperatures, and negatively related to the number of conidia trapped. Similar relationships occurred with trap plants exposed for 24-h periods on 141 different dates, except that temperature was not a significant factor. Nevertheless, these factors individually or combined in stepwise multiple regressions explained only a low percentage of the variability in disease severity with both weekly and daily trap plant sampling. When daily environmental data were categorized as: (i) rain versus no rain, (ii) <10 h or >10 h leaf wetness duration, and (iii) average temperature <20°C, 20 to 28°C, and >28°C, relationships to disease severity on trap plants were clearer. Disease severity on days with rain was nearly double that of days without rain, but considerable infection occurred on days with >10 h leaf wetness duration and no rain. Infection was greatest on days with temperatures of 20 to 28°C and slightly less at lower or higher temperatures. A point system, called the ALTER-RATER, was designed whereby each day would be assigned a severity value according to the prevailing environmental conditions. A fungicide application would be made after a predetermined number of points had accumulated. Simulated spray programs based on accumulation of 50, 75, 100, and 150 points from historical weather data at several locations indicated that from 8 to 15, 6 to 8, 5 to 6, or 3 to 4 sprays, respectively, would be needed depending on year and location in Florida. Such a weather-based control system could reduce the number of fungicide applications and improve control of Alternaria brown spot of tangerine.

scholarly journals Obtaining weather data for input to crop disease-warning systems: leaf wetness duration as a case study

2008 ◽  
Vol 65 (spe) ◽  
pp. 76-87 ◽  
Author(s):  
Mark L. Gleason ◽  
Katrina B. Duttweiler ◽  
Jean C. Batzer ◽  
S. Elwynn Taylor ◽  
Paulo Cesar Sentelhas ◽  
...  
Keyword(s):  
Control Measures ◽  
Weather Data ◽  
Leaf Wetness ◽  
Warning Systems ◽  
Leaf Wetness Duration ◽  
Advantages And Disadvantages ◽  
Support Tools ◽  
Crop Disease ◽  
Weather Stations

Disease-warning systems are decision support tools designed to help growers determine when to apply control measures to suppress crop diseases. Weather data are nearly ubiquitous inputs to warning systems. This contribution reviews ways in which weather data are gathered for use as inputs to disease-warning systems, and the associated logistical challenges. Grower-operated weather monitoring is contrasted with obtaining data from networks of weather stations, and the advantages and disadvantages of measuring vs. estimating weather data are discussed. Special emphasis is given to leaf wetness duration (LWD), not only because LWD data are inputs to many disease-warning systems but also because accurate data are uniquely challenging to obtain. It is concluded that there is no single " best" method to acquire weather data for use in disease-warning systems; instead, local, regional, and national circumstances are likely to influence which strategy is most successful.

scholarly journals Spatial variability of leaf wetness duration in a 'Niagara Rosada' vineyard

2008 ◽  
Vol 28 (1) ◽  
pp. 104-114
Author(s):  
Jorge Lulu ◽  
Paulo C. Sentelhas ◽  
Mário J. Pedro Júnior ◽  
José R. M. Pezzopane ◽  
Gabriel C. Blain
Keyword(s):  
Spatial Variability ◽  
Leaf Wetness ◽  
Crop Canopy ◽  
Vitis Labrusca ◽  
Leaf Wetness Duration ◽  
Canopy Position ◽  
Significant Difference ◽  
The Relationship ◽  
Electronic Sensors ◽  
Niagara Rosada

Despite considerable efforts to develop accurate electronic sensors to measure leaf wetness duration (LWD), little attention has been given to studies about how is LWD variability in different positions of the crop canopy. In order to evaluate the influence of 'Niagara Rosada' (Vitis labrusca) grapevine structure on the spatial variability of LWD, the objective of this study was to determine the canopy position of the ‘Niagara RosadaÂ’ table grape with longer LWD and its correlation with measured standard LWD over turfgrass. LWD was measured in four different canopy positions of the vineyard (sensors deployed at 45º with the horizontal): at the top of the plants, with sensors facing southwest and northeast (Top-SW and Top-NE), and at the grape bunches height, with sensors facing southwest and northeast (Bottom-SW and Bottom-NE). No significant difference was observed between the top (1.6 m) and the bottom (1.0 m) of the canopy and also between the southwest and northeast face of the plants. The relationship between standard LWD over turfgrass and crop LWD in different positions of the grape canopy showed a define correlation, with R² ranging from 0.86 to 0.89 for all period, from 0.72 to 0.77 for days without rain, and from 0.89 to 0.91 for days with rain.

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

Plant Disease ◽  
2006 ◽  
Vol 90 (5) ◽  
pp. 650-656 ◽  
Author(s):  
K. S. Kim ◽  
M. L. Gleason ◽  
S. E. Taylor
Keyword(s):  
Regression Tree ◽  
Empirical Models ◽  
Classification And Regression Tree ◽  
Weather Data ◽  
Leaf Wetness ◽  
Warning Systems ◽  
Site Specific ◽  
Leaf Wetness Duration ◽  
Regression Tree Analysis ◽  
Cart Model

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.

Sign in / Sign up

Export Citation Format

Share Document