VitiMeteo and Agrometeo: Two platforms for plant protection management based on an international collaboration

Abstract

The negative effects of plant protection products on the human health and the environment have become a major concern for consumers and politics in Europe. In the last years new policies for risk mitigation and reduction of use of synthetic pesticides has been enforce in Europe and Switzerland. A possible strategy to reduce the use of plant protection products is to spray according to the epidemic of diseases and pests by following decision support systems (DSS). The platform VitiMeteo offers a wide set of forecasting models for viticulture including downy and powdery mildew, black rot, grape berry moth and rust mite. Two research institutes the Staatliches Weinbauinstitut Freiburg (Germany) and Agroscope (Switzerland) developed VitiMeteo jointly. A consortium was built with the company Geosens (Germany) which is in charge of the programming of the different forecasting software. Each institute is running his own internet website with specific tools and feature for each country but the core of the system is the same. The combination of these different DSS allows a significant reduction of plant protection products used. All these forecasting systems and tools are freely available for the winegrowers on the platform www.vitimeteo.de and www.agrometeo.ch. The use of these platforms helps the winegrowers to meet current society's expectations.

Together for the Better: Improvement of a Model Based Strategy for Grapevine Downy Mildew Control by Addition of Potassium Phosphonates

“…However, in order to provide reliable predictions, DSS depend on accurate and reliable data provided by local and fully maintained weather stations. One well established decision support system in viticulture which combines several models for diseases, pests, and phenology is VitiMeteo (VM) [ 13 ]. VitiMeteo was introduced in 2002 and has now been evaluated in vineyards throughout Baden-Wuerttemberg (Germany) for almost two decades.…”

“…Valuable tools for integrated plant protection and the reduction of treatments are decision support systems (DSS), e.g., Agrometeo.ch [ 10 ], vite.net [ 11 ], or VitiMeteo [ 12 ]. Combining real time weather data, weather forecast models, and specific algorithms, the well-established DSS VitiMeteo provides predictions of the development of the most important diseases and pests in viticulture in several winegrowing countries in Europe [ 13 ]. Based on predicted infection events and the calculated development of plant growth, winegrowers are able to decide whether a treatment is necessary or not.…”

New Aspects of In Situ Measurements for Downy Mildew Forecasting

“…The infection process needs a minimum of 13° C plus 8 mm of rain to occur [ 16 ]. This prerequisite enables precise forecasting, especially for the primary infection [ 11 ]. After primary infection and through the incubation time, germinated sporangia produce many zoospores, which may cause secondary infections on nearby plants.…”

“…Based on the weather station data, the model calculates and predicts the potential infection risk with sporulation and incubation times for specific viticultural regions [ 9 ]. Several studies [ 6 , 10 , 11 ] showed that the prediction of the model is relevant to practice and is highly correlated to real occurrences of infection with accuracy increasing annually. Nevertheless, the precisions of the models have some variations to be minimised.…”

Grapevine Downy Mildew Warning System Based on NB-IoT and Energy Harvesting Technology

“…Some commercial solutions that use modern low-power technologies such as LoRaWAN or NB-IoT, have recently emerged (e.g., Metos [13]). Two examples of a platform-based approach consist of a weather station net, disease models, and the Internet website with specific tools and features [27]. A new line of research suggests using a machine learning approach to downy mildew forecasting [28].…”