Variable rate air-assisted spray based on real-time disease spot identification.
Pest Manag Sci
; 79(1): 402-414, 2023 Jan.
Article
em En
| MEDLINE
| ID: mdl-36175385
ABSTRACT
BACKGROUND:
Currently, the variable-rate application (VA) of agrochemicals on fruit trees is based on canopy volume and biomass. The canopy volume has a significant relationship with disease resistance and degree of disease incidence. Therefore, this study proposes a VA method that uses deep convolutional neural networks for real-time recognition of disease spots on pear trees. Furthermore, it specifies the limitations and application scenarios of the disease spot recognition. Field performance tests were conducted to verify the performance of the proposed VA system.RESULTS:
The results showed a mean average precision, precision, and recall of 87.42%, 83.76%, and 87.23%, respectively. The spot recognition rate was 81.3% when the canopy sampling distance, spot diameter, and canopy porosity were 1.2 m, 4-8 mm, and 55.76%, respectively. The results indicate that the proposed VA system saved 51.9% spray volume compared to conventional methods while ensuring quality.CONCLUSION:
Compared to the traditional constant rate model, the proposed VA technology based on real-time disease spot identification can reduce spraying in nondiseased areas, thereby abandoning the previous saturation application practice and significantly reducing pesticide use. © 2022 Society of Chemical Industry.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Idioma:
En
Revista:
Pest Manag Sci
Assunto da revista:
TOXICOLOGIA
Ano de publicação:
2023
Tipo de documento:
Article
País de afiliação:
China