Variable-rate fungicide spraying in real time by combining a plant cover sensor and a decision support system

Variable-rate fungicide spraying in real time by combining a plant cover sensor and a decision... In recent years, real-time technology has been introduced into the practice of spraying variable fungicide rates in cereal fields. Plant parameters for characterising heterogeneous plant growth such as biomass or plant surface area can be indirectly detected by the sensor CROP-Meter. The sensor signal is correlated with the Leaf Area Index, which can be used to adapt the application rate. However, this relatively simple method of controlling variable-rate fungicide application does not take into account the differences in disease distribution. In practice, decision support systems such as proPlant expert.classic can provide information about disease infection probabilities, application time, fungicide products and application rates for uniform spraying. A prototype of the system proPlant expert.precise was developed to estimate infection risks from fungal diseases using weather and field-specific data for up to three management areas with different yield expectations. The system also considers economic factors such as expected yield and costs of the fungicide products in generating a spraying map with different fungicide dosages. The information from the CROP-Meter (sensor) and from the decision support system proPlant expert.precise (map) was combined to provide a real-time spraying system with map overlay. The system was tested in 2007 in three winter wheat fields. Compared with conventional uniform spraying the CROP-Meter with map overlay treatment resulted in up to 32.6% fungicide savings (CROP-Meter versus uniform: up to 20.3%). There was no yield reduction on average when the sensor-controlled spraying technologies were used. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Precision Agriculture Springer Journals

Variable-rate fungicide spraying in real time by combining a plant cover sensor and a decision support system

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Publisher
Springer US
Copyright
Copyright © 2008 by Springer Science+Business Media, LLC
Subject
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
ISSN
1385-2256
eISSN
1573-1618
D.O.I.
10.1007/s11119-008-9088-7
Publisher site
See Article on Publisher Site

Abstract

In recent years, real-time technology has been introduced into the practice of spraying variable fungicide rates in cereal fields. Plant parameters for characterising heterogeneous plant growth such as biomass or plant surface area can be indirectly detected by the sensor CROP-Meter. The sensor signal is correlated with the Leaf Area Index, which can be used to adapt the application rate. However, this relatively simple method of controlling variable-rate fungicide application does not take into account the differences in disease distribution. In practice, decision support systems such as proPlant expert.classic can provide information about disease infection probabilities, application time, fungicide products and application rates for uniform spraying. A prototype of the system proPlant expert.precise was developed to estimate infection risks from fungal diseases using weather and field-specific data for up to three management areas with different yield expectations. The system also considers economic factors such as expected yield and costs of the fungicide products in generating a spraying map with different fungicide dosages. The information from the CROP-Meter (sensor) and from the decision support system proPlant expert.precise (map) was combined to provide a real-time spraying system with map overlay. The system was tested in 2007 in three winter wheat fields. Compared with conventional uniform spraying the CROP-Meter with map overlay treatment resulted in up to 32.6% fungicide savings (CROP-Meter versus uniform: up to 20.3%). There was no yield reduction on average when the sensor-controlled spraying technologies were used.

Journal

Precision AgricultureSpringer Journals

Published: Nov 19, 2008

References

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