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

Duttweiler, K. B.; Batzer, Jean C.; Taylor, S. Elwynn; Sentelhas, Paulo César; Monteiro, J. M. G.; Gillespie, T. J.

doi:10.1590/s0103-90162008000700013

Cited by 46 publications

(37 citation statements)

References 38 publications

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“…Climate data are also relevant for agricultural and ecological research [2,3], becoming critical inputs to forecast crop growth and development rates, as well as to model population dynamics of pest and diseases [4]. In addition, the data represent a baseline to assess global and local climate change effects [5].…”

Section: Introductionmentioning

confidence: 99%

Improving Stochastic Modelling of Daily Rainfall Using the ENSO Index: Model Development and Application in Chile

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Meza

Gironás

et al. 2018

Water

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Stochastic weather simulation, or weather generators (WGs), have gained a wide acceptance and been used for a variety of purposes, including climate change studies and the evaluation of climate variability and uncertainty effects. The two major challenges in WGs are improving the estimation of interannual variability and reducing overdispersion in the synthetic series of simulated weather. The objective of this work is to develop a WG model of daily rainfall, incorporating a covariable that accounts for interannual variability, and apply it in three climate regions (arid, Mediterranean, and temperate) of Chile. Precipitation occurrence was modeled using a two-stage, first-order Markov chain, whose parameters are fitted with a generalized lineal model (GLM) using a logistic function. This function considers monthly values of the observed Sea Surface Temperature Anomalies of the Region 3.4 of El Niño-Southern Oscillation (ENSO index) as a covariable. Precipitation intensity was simulated with a mixed exponential distribution, fitted using a maximum likelihood approach. The stochastic simulation shows that the application of the approach to Mediterranean and arid climates largely eliminates the overdispersion problem, resulting in a much improved interannual variability in the simulated values.

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Section: Introductionmentioning

confidence: 99%

Improving Stochastic Modelling of Daily Rainfall Using the ENSO Index: Model Development and Application in Chile

Urdiales

Meza

Gironás

et al. 2018

Water

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“…Numerous factors within the canopy, such as temperature, humidity, periods of wetness, or velocity of air movement can influence disease establishment and progression and are often used as indicators for disease prediction models to guide chemical applications (Gleason et al 2008). In studies with cucumber we observed that modified cucumber canopy structure, achieved either by cultural practices or by genetic factors such as leaf size, branching habit, vine length or determinacy, can result in variable environmental conditions under the canopy.…”

Section: Discussionmentioning

confidence: 93%

Modified plant architecture to enhance crop disease control: genetic control and possible value of upright fruit position in cucumber

et al. 2012

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Plant architectural features can facilitate disease control by creating unfavourable environments for pathogen growth or limiting pathogen contact with the host. In the case of Phytophthora capsici infection of cucumber (Cucumis sativus), the susceptible fruit typically lie in contact with soil under warm, moist conditions of a full canopy, an ideal location for exposure to inoculum and disease development. We have shown that increased row spacing, trellising and architectural variants that allow for more open canopies, such as shorter vines, reduced branching, or smaller leaves, can modify microclimate as assessed by temperature at the location of developing fruits. However, only trellising reduced infection rates (<3 % infection vs. 22 % for control). A cucumber accession PI308916, with extremely short internodes and resulting upright position of young fruit, also exhibited reduced disease. Fruit of PI308916 were susceptible when inoculated with P. capsici, indicating that reduced infection likely resulted from decreased soil contact. The compact trait is inherited as a single recessive gene, cp. Like many architectural traits, cp may be pleiotropic; PI308916-derived breeding lines were reported to have poor seedling emergence. PI308916 exhibited inconsistent apical hook formation that cosegregated with short internodes in F 2 and backcross generations, and disorganized internodal cortical cell arrangement. The combined phenotypes suggest either pleiotropy or very tight linkage of genes affecting hormone balance or cell division. The narrow chromosome region recently defined by QTL analysis includes candidate gene homologs of meristem related genes modulating cell division or spacing of lateral shoot organs and genes associated with brassinosteroid signaling or cytokinin content.

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“…In addition, users may obtain weather data for use with the models in several ways, including on-site mechanical recorders, electronic weather stations, or web-based remote weather services (39.53). Leaf wetness (LW), in particular, varies widely depending on which weather-monitoring method is used and how it is employed (22), yet little attention has been given to matching weather monitoring methods to particular models, which may lead to inappropriate use of SBFS models. In this review, our purpose is to outline the extent of variation between various SBFS models, demonstrate how this variability may impact management decisions, and suggest ways that the models may be improved and more effectively used.…”

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confidence: 99%

“…Using proprietary algorithms, SkyBit estimates weather at a resolution of 1 km^ (31). Users supply SkyBit with the precise latitude, longitude, and elevation of a site and, for a subscription fee, receive information on past weather, weather forecasts, and risk evaluations for various pests based on models, SkyBit does not require maintenance of a weather station on site, and generally performs as well as on-site equipment (22,38), The SkyBit SBFS model is based on the Hartman/Smigell model. For purposes of the SBFS model, SkyBit uses a 350-LWD threshold rather than 175 LWD, suggesting that either LWD is overestimated or that the model is designed to allow a longer spray interval after PF on the assumption that SBFS infections that may occur between 175 and 350 LWD from PF will be suppressed by subsequent fungicide applications.…”

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confidence: 99%

“…The SB model in RIMpro is being tested in European trials (21), Problems associated with measuring LW. The problem of measuring LW has been extensively studied (22,28,34,48,53), However, LW has never been quantitatively defined, and its measurement is problematic (37). In the descriptions above, it is obvious that measurement of LW can be highly variable, depending on the type of instrument used, if any, and where sensors are placed.…”

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confidence: 99%

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Variability Among Forecast Models for the Apple Sooty Blotch/Flyspeck Disease Complex

et al. 2011

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2011. Variability among forecast models for (he apple sooty blotch/flyspeck disease complex. Plant Dis. 95:1179-1186.Several disease forecast models have been developed to guide treatment of the sooty blotch and flyspeck (SBFS) disease complex of apple. Generally, these empirical models are based on the accumulation of hours of leaf wetness (leaf wetness duration [LWD]) from a biofix at or near the phenological growth stage petal fall, when apple fiower petals senesce and drop. The models recommend timing of the initial fungicide application targeting SBFS. However, there are significant differences among SBFS forecast models in terms of biofix and the length of LWD thresholds. A comparison of models using a single input data set generated recommendations for the first SBFS fungicide application that differed by up to 5 weeks. In an attempt to improve consistency among models, potential sources for differences were examined. Leaf wetness (LW) is a particularly variable parameter among models, depending on whether on-site or remote weather data were used, the types of sensors and their placement for on-site monitors, and the models used to estimate LW remotely. When SBFS models are applied in the field, recommended treatment thresholds do not always match the method of data acquisition, leading to potential failures. Horticultural factors, such as tree size, canopy density, and cultivar, and orchard site factors such as the distance to potential inoculum sources can impact risk of SBFS and should also be considered in forecast models. The number of fungal species identified as contributors to the SBFS disease complex has expanded tremendously in recent years. A lack of understanding of key epidemiological factors for different fungi in the complex, and which fungi represent the most challenging management problems, are obvious issues in the development of improved SBFS models. If SBFS forecast models are to be adopted, researchers will need to address these issues.Sooty blotch and flyspeck (SBFS). a disease complex caused by numerous fungal species, impacts pome fruit production in humid regions worldwide (4,5.18,21.35.58,60). Although the disea.se is limited to waxy cuticles and does little damage to trees or fruit, the blemishes it causes can substantially decrease apple fruit quality and. therefore, value. In the eastern production regions of the United States, growers generally apply from 30 to 50% of a season's fungicides, usually from four to eight applications, to manage a set of summer diseases, including SBFS, black rot {Botryosphae-ria obtusa (Schwein.) Shoemaker), bitter rot {Glomerella cingutata (Stoneman) Spauld. & H. Schrenk), white rot or bot rot {B. dothidea (Moug.) Ces. & De Not.). Brooks fruit spot {Mycosphae-rella potni (Pass.) Lindau), and Alternaria blotch {Alternarla niali Roberts) ( 54). SBFS is the only consistent summer disease problem in northem regions such as New England but the other diseases become increasingly important going from north to south.Calendar-based management programs of ...

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

Cited by 46 publications

References 38 publications

Improving Stochastic Modelling of Daily Rainfall Using the ENSO Index: Model Development and Application in Chile

Improving Stochastic Modelling of Daily Rainfall Using the ENSO Index: Model Development and Application in Chile

Modified plant architecture to enhance crop disease control: genetic control and possible value of upright fruit position in cucumber

Variability Among Forecast Models for the Apple Sooty Blotch/Flyspeck Disease Complex

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