Design, construction and evaluation of an automatic sprayer system online weed-plant detection in sugar beet fields

Document Type : Scientific - Research

Authors

1 Master of Science in Biosystems engineering of Department of Mechanics of Biosystems Engineering, Faculty of Agricultural Engineering and Rural Development, Agricultural Sciences and Resources University of Khuzestan, Ahvaz, Iran.

2 Associate Professor, Department of Mechanics of Biosystems Engineering, Faculty of Agricultural Engineering and Rural Development, Agricultural Sciences and Resources University of Khuzestan, Ahvaz, Iran.

3 Professor of Department of Mechanics of Biosystems Engineering, Faculty of Agricultural Engineering and Rural Development, Agricultural Sciences and Resources University of Khuzestan, Ahvaz, Iran.

4 Assistant Professor, Department of Agronomy, Faculty of Agricultural, Agricultural Sciences and Resources University of Khuzestan, Ahvaz, Iran.

Abstract

Weed control during the growth period of plantsis of great importance and various methods have been developed for this purpose. In the fight against these unwanted plants with the conventional method, the entire field as well as the main plant are covered by herbicides, which also causes excessive application of herbicide. In this study, a smart sprayer system was used to detect weed and reduce the amount of herbicide application in sugar beet field based on machine vision technology. For this purpose, 49 phenotype and color characteristics of beet and weed images were extracted and analyzed. By implementing Genetic Algorithm (GA), 11 characteristics that were most accurate in diagnosis were selected, and in order to increase the speed and improve performance, five characteristics (area ratio of convex hull, sphericity coefficient, moment 6, I1I2I3 and Lch_c) with had the most replication number in characteristic selection were selected. The developed algorithm to distinguish weed from sugar beet had an accuracy of more than 98%, which shows the high detection power of this smart system. To evaluate the reduction of herbicide usage, the smart sprayer system was compared with the Buferagri sprayer. The movement speed of 8 km hr-1 with John Deere tractor and 27 m travelled distance were considered to be fixed for both sprayers. In a certain distance, the amount of herbicide used was measured and it could be observed that the amount of herbicide used in the Buferagri sprayer was 77% higher than the smart sprayer system. This shows the efficiency of this system compared with conventional sprayers in reducing herbicides application. These results indicate the feasibility of using the presented system as a smart sprayer system in sugar beet fields.

Keywords

References

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Journal of Sugar Beet
Volume 37, Issue 2
September 2022
Pages 223-238

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