Resource efficient plant protection based on a data driven multi-scale approach for the process chain - Diseases detection - decision support - demand specific fungicide application.

Publication Type

Contribution to conference

Authors

E. Memic, S. Graeff-Hönninger, W. Claupein, H. Schomburg, A. Brandes

Year of publication

2016

Published in

Mitteilungen Gesellschaft für Pflanzenbauwissenschaften e. V.

Page (from - to)

192-193

Conference name

59. Jahrestagung der Gesellschaft für Pflanzenbauwissenschaften e. V. - Klimawandel und Qualität

Conference location

Gießen

Conference date

27. bis 29. September 2016

The objective of this project is to implement a multi-disciplinary
approach in order to develop a decision mechanism for controlling crop
infestation in wheat and sugar beet, which would be more flexible and
more appealing to the farmers. Combining knowledge about plant
pathology, engineering, information technologies and spectral-imaging
techniques to easier delineate sub-field management zones of crop
infested areas is one goal. After successful delineation of infested
subfield zones, another goal is to use and evaluate a precise sprayer
with separately controllable nozzles to reduce the amount of chemicals
applied in the field. Compared to preventative single rate chemical
application in conventional farming practices, precise application of
chemicals on infested sub-field zones will result in social, economic
and environmental benefits.
The goal of this project is also to upgrade the precision farming
concept to a smart farming by speeding up the whole process of
detection, identification and quantification of leaf diseased areas in
wheat and sugar beet and subsequently apply precise chemical
treatments minimizing the amount of chemicals and yield loses.
Speeding up the decision process depends a lot on the strong spatial
and temporal variability of the field infestation, which is where the
true potential of the smart farming lies in. A crop model will be
developed to incorporate a whole range of information from mentioned
disciplines, which will reproduce different scenarios with different
outcomes enabling farmers to react the most rationally in regard of
social and economic benefits.