Factsheet DSS CPO model for barley net blotch
The CPO net blotch model is recommending treatments in barley when thresholds are exceeded. The risk of attack is based on visual monitoring using frequency of plants attacked. The disease observation is the percentage of plants showing any infection. For example, if 25 plants out of 100 show even a very small amount of disease and the remaining 75 plants are completely healthy, then the observation is 25%. In susceptible cultivars treatments are recommended at lower incidence levels than in resistant cultivars. If treatments are recommended specific fungicides known to be effective against net blotch should be chosen. When running the net blotch model, the risk for yield losses from other diseases is not considered. If no action is recommended it is advised to revisit the crop after approximately one week to make a new evaluation of the risk. To obtain accurate risk predictions it is essential to click on the ‘Edit parameters’ button and enter information on the cultivar’s susceptibility to net blotch. The model does not automatically adjust risk for the effect of previous fungicide sprays. If a fungicide effective against net blotch has been applied in the last 10 days, the risk can be interpreted as low. Created by Aarhus University and SEGES and released in Denmark in 2000. The whole CPO model has been tested in the Nordic and Baltic countries previously, but this might not have included testing of the specific barley net blotch part. This model may be of use in other countries in Northern Europe, it is important to first test in practice before using the DSS for decision support.
Detail beschrijving
1/1
Details bijdrage
- Locatie
- Europe
- Denmark
- Auteurs
- L. Langner
- Doel
- Decision-making support
- Soort bestand
- Document
- Bestandsgrootte
- 819 kB
- Gepubliceerd op
- 14-04-2024
- Taal van herkomst
- English
- Officiële project website
- IPM Decisions
- Licensie
- CC BY
Gerelateerde inhoud
A Bio-inspired Multilayer Drainage System
Agricultural run-off and subsurface drainage tiles transport a significant amount of nitrogen and phosphorus leached after fertilization. alchemia-nova GmbH in collaboration with University of Natural Resources and Life Sciences, Vienna developed two multi-layer vertical filter systems to address the agricultural run-off issue, which has been installed on the slope of an agricultural field in Mistelbach, Austria. While another multi-layer addressing subsurface drainage water is implemented in Gleisdorf, Austria. The goal is to develop a drainage filter system to retain water and nutrients. Both multi-layer filter systems contain biochar and other substrates with adsorption properties of nutrients (nitrogen, phosphorus). The filter system can be of practical use if an excess of nutrients being washed out is of concern in the fields of the practitioner by keeping the surrounding waters clean. This approach may result in economic value by re-using the saturated biochar as fertilizer and improving the soil structure, thus increasing long-term soil fertility. Link: https://wateragri.eu/a-bio-inspired-multilayer-drainage-system/
NANOCELLULOSE MEMBRANES FOR NUTRIENT RECOVERY
This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 858735This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 858735. FACTSHEET NANOCELLULOSE MEMBRANES FOR NUTRIENT RECOVERY Key information Functionalized nanocellulose membranes can take up nitrate and phosphate. These membranes can be put in a water treatment unit. As the membranes are biobased, degradable materials, they can after use be added to the soil, thus returning the leached nutrients back for their original purpose providing fertilizers (nutrient recycling).
Environmental monitoring within greenhouse crops using wireless sensors
Because variables such as temperature and humidity have a profound effect on the activity of crop pests, diseases and natural enemies, the ability to monitor environmental conditions within a crop has always been important for crop protection.