The overall objective of this project was to develop a combined decision support system for Septoria and aphids in winter wheat by improving the simulation model SeptoriaSim and extending it with an aphid module. The work to fulfill this objective was split into four immediate objectives: 1) Develop new monitoring methods for the two pests, 2) Provide a stronger scientific foundation for warning models against Septoria and aphids, 3) Describe the spatial variation of aphids, and 3) Evaluate the reliability of the warning method/decision support tools in field trials.
Four types of investigations were carried out with the aim of both providing data for calibration of the model and enforcing the scientific background: 1) the background level of Septoria spores causing the initial infestation of winter wheat, 2) the growth of Septoria in the winter wheat leaves, 3) the population development of all three cereal aphids in winter wheat from late May to mid-July, 4) detailed growth analysis of winter wheat under field conditions.
This project has shown that a decision support system based on biological knowledge and projections of economic benefit of treatments may produce net yields equivalent to or better than the well-known empirically based CPO. One important difference between the two decision support systems is that SeptoriaSim gives predictions of the economic benefit of treating, and it is up to the farmer to decide whether to treat or not. This type of decision support system is an innovation that has the capacity to avoid treatments that may be economically beneficial, but not worth the effort for many farmers.
The project also showed that the use of decision support systems can be a tool to reduce the number of treatments against Septoria, and that SeptoriaSim can reduce the number of treatments against aphids.
