Articles
Remote monitoring of currant shoot borer (Lampronia capitella) moths in blackcurrant in Finland
Article number
1444_13
Pages
91 – 98
Language
English
Abstract
One of the principles in integrated pest management is pest monitoring and identification.
The primary method of detecting common currant pests is laborious visual observation using manual pheromone traps.
Pheromone-based monitoring has been in use in Finnish currant orchards since 1990, whereas there is no experience with technology-assisted remote monitoring.
Two pheromone trap models, the manual delta trap and the remote imaging trap, were tested for the currant shoot borer moth (Lampronia capitella) in 2021 and 2022. The study was conducted in close collaboration with berry growers in three blackcurrant production fields.
The remotely readable technology performed effectively in field conditions, and the machine vision algorithm accurately identified caught currant shoot borers.
However, attention must be paid to selecting the network operator required for data transfer, ensuring that the signal strength is adequate and images can be viewed in the cloud service without delay.
The currant shoot borer had a more dense population in 2022 than in 2021. The currant shoot borer was on the flight for about three weeks in June.
The flight peak took place within one week.
The comparison with the manual trap revealed the need to develop the trap housing, its color, and the size of the flight hole, as the manual trap gathered more moths.
The primary method of detecting common currant pests is laborious visual observation using manual pheromone traps.
Pheromone-based monitoring has been in use in Finnish currant orchards since 1990, whereas there is no experience with technology-assisted remote monitoring.
Two pheromone trap models, the manual delta trap and the remote imaging trap, were tested for the currant shoot borer moth (Lampronia capitella) in 2021 and 2022. The study was conducted in close collaboration with berry growers in three blackcurrant production fields.
The remotely readable technology performed effectively in field conditions, and the machine vision algorithm accurately identified caught currant shoot borers.
However, attention must be paid to selecting the network operator required for data transfer, ensuring that the signal strength is adequate and images can be viewed in the cloud service without delay.
The currant shoot borer had a more dense population in 2022 than in 2021. The currant shoot borer was on the flight for about three weeks in June.
The flight peak took place within one week.
The comparison with the manual trap revealed the need to develop the trap housing, its color, and the size of the flight hole, as the manual trap gathered more moths.
Authors
S. Tuohimetsä, M. Rantanen
Keywords
artificial intelligence (AI), berry production, digitalization, integrated pest management (IPM), pheromones, remote sensing, Ribes nigrum
Groups involved
- Division Vine and Berry Fruits
- Division Plant-Environment Interactions in Field Systems
- Division Horticulture for Human Health
- Working Group Vaccinium Species and Management
- Working Group Rubus and Ribes Species and Management
- Working Group Kiwifruit Culture and Management
- Working Group Strawberry Culture and Management
Online Articles (43)