Pregled bibliografske jedinice broj: 1241899
Monitoring System for Leucoptera malifoliella (O. Costa, 1836) and Its Damage Based on Artificial Neural Networks
Monitoring System for Leucoptera malifoliella (O. Costa, 1836) and Its Damage Based on Artificial Neural Networks // Agriculture, 13(1) (2023), 67; 1-19 doi:10.3390/agriculture13010067 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1241899 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Monitoring System for Leucoptera malifoliella (O.
Costa, 1836) and Its Damage Based on Artificial
Neural Networks
Autori
Čirjak, Dana ; Aleksi, Ivan ; Miklečić, Ivana ; Antolković, Ana Marija ; Vrtodušić, Rea ; Viduka, Antonio ; Lemic, Darija ; Kos, Tomislav ; Pajač Živković, Ivana
Izvornik
Agriculture (2077-0472) 13(1)
(2023), 67;
1-19
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
apple pests ; automatic monitoring systems ; deep learning models ; site-specific crop management ; sustainable agriculture
Sažetak
The pear leaf blister moth is a significant pest in apple orchards. It causes damage to apple leaves by forming circular mines. Its control depends on monitoring two events: the flight of the first generation and the development of mines up to 2 mm in size. Therefore, the aim of this study was to develop two models using artificial neural networks (ANNs) and two monitoring devices with cameras for the early detection of L. malifoliella (Pest Monitoring Device) and its mines on apple leaves (Vegetation Monitoring Device). To train the ANNs, 400 photos were collected and processed. There were 4700 annotations of L. malifoliella and 1880 annotations of mines. The results were processed using a confusion matrix. The accuracy of the model for the Pest Monitoring Device (camera in trap) was more than 98%, while the accuracy of the model for the Vegetation Monitoring Device (camera for damage) was more than 94%, all other parameters of the model were also satisfactory. The use of this comprehensive system allows reliable monitoring of pests and their damage in real-time, leading to targeted pest control, reduction in pesticide residues, and a lower ecological footprint. Furthermore, it could be adopted for monitoring other Lepidopteran pests in crop production.
Izvorni jezik
Engleski
Znanstvena područja
Poljoprivreda (agronomija)
Napomena
Objavu rada podržao je Fond za otvoreni pristup
publikacijama Sveučilišta u Zagrebu Agronomskog
fakulteta i Europski fond za regionalni razvoj
kroz projekt AgriART sveobuhvatni upravljački
sustav u području precizne poljoprivrede
(KK.01.2.1.02.0290).
POVEZANOST RADA
Projekti:
--KK.01.2.1.02.0290 - AgriART sveobuhvatni upravljački sustav u području precizne poljoprivrede (AgriART) (Fruk, Goran) ( CroRIS)
Profili:
Darija Lemić (autor)
Ivana Miklečić (autor)
Ana Marija Antolković (autor)
Antonio Viduka (autor)
Dana Čirjak (autor)
Ivana Pajač Živković (autor)
Ivan Aleksi (autor)
Tomislav Kos (autor)
Rea Vrtodušić (autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus