Effectiveness of short‐term numerical weather prediction in predicting growing degree days and meteorological conditions for apple scab appearance

Lalić, Branislava; Francia, María Victoria; Eitzinger, Josef; Podraščanin, Zorica; Arsenić, Ilija

doi:10.1002/met.1521

Cited by 7 publications

(6 citation statements)

References 23 publications

(22 reference statements)

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“…The results from previous research on the use of NWP in disease appearance forecasting for apple scab led to the same results as those presented here, i.e., NWP output accuracy was not strictly correlated with good disease prediction [43,44].…”

Section: Discussionsupporting

confidence: 80%

Toward a Weather-Based Forecasting System for Fire Blight and Downy Mildew

et al. 2018

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The aim of this research is to present a weather-based forecasting system for apple fire blight (Erwinia amylovora) and downy mildew of grapevine (Plasmopara viticola) under Serbian agroecological conditions and test its efficacy. The weather-based forecasting system contains Numerical Weather Prediction (NWP) model outputs and a disease occurrence model. The weather forecast used is a product of the high-resolution forecast (HRES) atmospheric model by the European Centre for Medium-Range Weather Forecasts (ECMWF). For disease modelling, we selected a biometeorological system for messages on the occurrence of diseases in fruits and vines (BAHUS) because it contains both diseases with well-known and tested algorithms. Several comparisons were made: (1) forecasted variables for the fifth day are compared against measurements from the agrometeorological network at seven locations for three months (March, April, and May) in the period 2012–2018 to determine forecast efficacy; (2) BAHUS runs driven with observed and forecast meteorology were compared to test the impact of forecasted meteorological data; and (3) BAHUS runs were compared with field disease observations to estimate system efficacy in plant disease forecasts. The BAHUS runs with forecasted and observed meteorology were in good agreement. The results obtained encourage further development, with the goal of fully utilizing this weather-based forecasting system.

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Section: Discussionsupporting

confidence: 80%

Toward a Weather-Based Forecasting System for Fire Blight and Downy Mildew

et al. 2018

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“…Field devices can also create difficulties for agricultural machinery practices. For over 20 years, grids of weather stations and numerical weather models have been used in subfield spatio-temporal projections (Russo, 2000;Olantinwo and Hoogenboom, 2014;Lalic et al, 2016;Kim et al, 2020). Therefore, weather data networks and numerical grid datasets are probably the most cost-effective, reliable strategy to forecast the occurrence and distribution of insects (Merrill et al, 2015;Newlands, 2018;Hu et al, 2019;Wang et al, 2019).…”

Section: Important Questions For Future Researchmentioning

confidence: 99%

How does the digital transformation of agriculture affect the implementation of Integrated Pest Management?

Filho

Pazini

Alves

et al. 2022

Front. Sustain. Food Syst.

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Integrated pest management (IPM) has greatly influenced farming in the past decades. Even though it has been effective, its adoption has not been as large as anticipated. Operational issues regarding crop monitoring are among the reasons for the lack of adoption of the IPM philosophy because control decisions cannot be made unless the crop is effectively and constantly monitored. In this way, recent technologies can provide unique information about plants affected by insects. Such information can be very precise and timely, especially with the use of real-time data to allow decision-making for pest control that can prevent local infestation of insects from spreading to the whole field. Some of the digital tools that are commercially available for growers include drones, automated traps, and satellites. In the future, a variety of other technologies, such as autonomous robots, could be widely available. While the traditional IPM approach is generally carried out with control solutions being delivered throughout the whole field, new approaches involving digital technologies will need to consider adaptations in the concepts of economic thresholds, sampling, population forecast, injury identification, and ultimately the localized use of control tactics. Therefore, in this paper, we reviewed how the traditional IPM concepts could be adapted, considering this ongoing digital transformation in agriculture.

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“…Several software packages are available, such as PESTCLIM, which utilizes the already proven algorithms of ECAMON (Trnka et al, 2007), and CLIMEX (Svobodová et al, 2014), a new efficient data handling and calculation procedure enabling sophisticated optimization and improved performance. BAHUS the biometeorological system for messages on the occurrence of diseases in fruits and vines is calibrated for apple scab (Venturia inaequalis), fire blight (Erwinia amylovora) and grapevine downy mildew (Plasmopara viticola) (Mihailovic et al, 2001, Lalic et al, 2016.…”

Section: Pest and Disease Models Or Algorithmsmentioning

confidence: 99%

“…An increasingly used method is the combination of agrometeorological monitoring and near term to seasonal forecasting (e.g. Lalic et al, 2015Lalic et al, , 2018. These methods can be applied not only for specific sites, but as spatial GIS applications, with spatial resolutions up to only a few meters, which well covers the field scale required by farmers.…”

Section: Adaptation Options For Better Crop Managementmentioning

confidence: 99%

Agricultural Meteorology and Climatology

Lalić

Eitzinger

Marta

et al. 2018

Manuali – Scienze Tecnologiche

Self Cite

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Agricultural Meteorology and Climatology is an introductory textbook for meteorology and climatology courses at faculties of agriculture and for agrometeorology and agroclimatology courses at faculties whose curricula include these subjects. Additionally, this book may be a useful source of information for practicing agronomists and all those interested in different aspects of weather and climate impacts on agriculture. In times when scientific knowledge and practical experience increase exponentially, it is not a simple matter to prepare a textbook. Therefore we decided not to constrain Agricultural Meteorology and Climatology by its binding pages. Only a part of it is a conventional textbook. The other part includes numerical examples (easy-to-edit worksheets) and recommended additional reading available on-line in digital form. To keep the reader's attention, the book is divided into three sections: Basics, Applications and Agrometeorological Measurements with Numerical Examples.

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Effectiveness of short‐term numerical weather prediction in predicting growing degree days and meteorological conditions for apple scab appearance

Cited by 7 publications

References 23 publications

Toward a Weather-Based Forecasting System for Fire Blight and Downy Mildew

Toward a Weather-Based Forecasting System for Fire Blight and Downy Mildew

How does the digital transformation of agriculture affect the implementation of Integrated Pest Management?

Agricultural Meteorology and Climatology

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