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Pregled bibliografske jedinice broj: 1241899

Monitoring System for Leucoptera malifoliella (O. Costa, 1836) and Its Damage Based on Artificial Neural Networks


Čirjak, Dana; Aleksi, Ivan; Miklečić, Ivana; Antolković, Ana Marija; Vrtodušić, Rea; Viduka, Antonio; Lemic, Darija; Kos, Tomislav; Pajač Živković, Ivana
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)

Poveznice na cjeloviti tekst rada:

Pristup cjelovitom tekstu rada doi www.mdpi.com

Citiraj ovu publikaciju:

Čirjak, Dana; Aleksi, Ivan; Miklečić, Ivana; Antolković, Ana Marija; Vrtodušić, Rea; Viduka, Antonio; Lemic, Darija; Kos, Tomislav; Pajač Živković, Ivana
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)
Čirjak, D., Aleksi, I., Miklečić, I., Antolković, A., Vrtodušić, R., Viduka, A., Lemic, D., Kos, T. & Pajač Živković, I. (2023) Monitoring System for Leucoptera malifoliella (O. Costa, 1836) and Its Damage Based on Artificial Neural Networks. Agriculture, 13(1) (67), 1-19 doi:10.3390/agriculture13010067.
@article{article, author = {\v{C}irjak, Dana and Aleksi, Ivan and Mikle\v{c}i\'{c}, Ivana and Antolkovi\'{c}, Ana Marija and Vrtodu\v{s}i\'{c}, Rea and Viduka, Antonio and Lemic, Darija and Kos, Tomislav and Paja\v{c} \v{Z}ivkovi\'{c}, Ivana}, year = {2023}, pages = {1-19}, DOI = {10.3390/agriculture13010067}, keywords = {apple pests, automatic monitoring systems, deep learning models, site-specific crop management, sustainable agriculture}, journal = {Agriculture}, doi = {10.3390/agriculture13010067}, volume = {13(1)}, number = {67}, issn = {2077-0472}, title = {Monitoring System for Leucoptera malifoliella (O. Costa, 1836) and Its Damage Based on Artificial Neural Networks}, keyword = {apple pests, automatic monitoring systems, deep learning models, site-specific crop management, sustainable agriculture} }
@article{article, author = {\v{C}irjak, Dana and Aleksi, Ivan and Mikle\v{c}i\'{c}, Ivana and Antolkovi\'{c}, Ana Marija and Vrtodu\v{s}i\'{c}, Rea and Viduka, Antonio and Lemic, Darija and Kos, Tomislav and Paja\v{c} \v{Z}ivkovi\'{c}, Ivana}, year = {2023}, pages = {1-19}, DOI = {10.3390/agriculture13010067}, keywords = {apple pests, automatic monitoring systems, deep learning models, site-specific crop management, sustainable agriculture}, journal = {Agriculture}, doi = {10.3390/agriculture13010067}, volume = {13(1)}, number = {67}, issn = {2077-0472}, title = {Monitoring System for Leucoptera malifoliella (O. Costa, 1836) and Its Damage Based on Artificial Neural Networks}, keyword = {apple pests, automatic monitoring systems, deep learning models, site-specific crop management, sustainable agriculture} }

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


Citati:





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