Infield sensing of cotton insects using automated image analysis of crop symptoms: CSP2203
Technical report
Heimoana, Simone, Blankley, S. and McCarthy, Alison. 2022. Infield sensing of cotton insects using automated image analysis of crop symptoms: CSP2203. Australia. Cotton Research and Development Corporation.
| Title | Infield sensing of cotton insects using automated image analysis of crop symptoms: CSP2203 |
|---|---|
| Report Type | Technical report |
| Research Report Category | Industry |
| Authors | Heimoana, Simone, Blankley, S. and McCarthy, Alison |
| Institution of Origin | University of Southern Queensland |
| Number of Pages | 6 |
| Year | 2022 |
| Publisher | Cotton Research and Development Corporation |
| Place of Publication | Australia |
| Abstract | There is potential to use image analysis and machine vision technology to improve the timeliness and accuracy of sensing target insects for cotton. Insects that are currently difficult to assess include wireworm, thrips, mirids and green vegetable bugs (GVB). A study will be conducted to evaluate the potential to use image analysis to detect multiple features, including reduced plant stand and leaf area, leaf damage and boll damage, that could diagnose presence of cotton insects. |
| Keywords | cotton insects; green vegetable bugs |
| ANZSRC Field of Research 2020 | 300206. Agricultural spatial analysis and modelling |
| 460304. Computer vision | |
| 410404. Environmental management | |
| Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
| Byline Affiliations | No affiliation |
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