المؤلفون: Fatemeh Farsi, Mehrdad Ahmadi, Shiva Osouli

المصدر: Journal of Crop Protection, Vol 11, Iss 3, Pp 401-411 (2022)

مصطلحات موضوعية: geometric morphometric, outline approach, landmark approach, sterile insect technique, c. capitata, Agriculture

وصف الملف: electronic resource

Relation: http://jcp.modares.ac.ir/article-3-60833-en.html; https://doaj.org/toc/2251-9041; https://doaj.org/toc/2251-905X

URL الوصول: https://doaj.org/article/309e9ddc160d4340ba96dcb16aa3dd9f

المؤلفون: Tannous, Michael, Stefanini, Cesare, Romano, Donato

المساهمون: Tannous, Michael, Stefanini, Cesare, Romano, Donato

مصطلحات موضوعية: Artificial Intelligence (AI) and automation are fostering more sustainable and effective solutions for a wide spectrum of agricultural problems. Pest management is a major challenge for crop production that can benefit from machine learning techniques to detect and monitor specific pests and diseases. Traditional monitoring is labor intensive, time demanding, and expensive, while machine learning paradigms may support cost-effective crop protection decisions. However, previous studies mainly relied on morphological images of stationary or immobilized animals. Other features related to living animals behaving in the environment (e.g., walking trajectories, different postures, etc.) have been overlooked so far. In this study, we developed a detection method based on convolutional neural network (CNN) that can accurately classify in real-time two tephritid species (Ceratitis capitata and Bactrocera oleae) free to move and change their posture. Results showed a successful automatic detection (i.e., precision rate about 93%) in real-time of C. capitata and B. oleae adults using a camera sensor at a fixed height. In addition, the similar shape and movement patterns of the two insects did not interfere with the network precision. The proposed method can be extended to other pest species, needing minimal data pre-processing and similar architecture

Relation: volume:14; issue:2; firstpage:148; numberofpages:14; journal:INSECTS; https://hdl.handle.net/11382/552211

الاتاحة: https://hdl.handle.net/11382/552211
https://doi.org/10.3390/insects14020148

المؤلفون: Hannou Zerkani, Loubna Kharchoufa, Imane Tagnaout, Jamila Fakchich, Mohamed Bouhrim, Smail Amalich, Mohamed Addi, Christophe Hano, Natália Cruz-Martins, Rachid Bouharroud, Touria Zair

المصدر: Plants; Volume 11; Issue 22; Pages: 3084

مصطلحات موضوعية: T. absoluta, C. capitata, essential oil, chemical analysis, toxicity, LD 50, bioinsecticides

جغرافية الموضوع: agris

وصف الملف: application/pdf

Relation: Phytochemistry; https://dx.doi.org/10.3390/plants11223084

الاتاحة: https://doi.org/10.3390/plants11223084

المؤلفون: Michael Tannous, Cesare Stefanini, Donato Romano

المصدر: Insects
Volume 14
Issue 2
Pages: 148

مصطلحات موضوعية: Mediterranean fruit fly, the similar shape and movement patterns of the two insects did not interfere with the network precision. The proposed method can be extended to other pest species, Artificial Intelligence (AI) and automation are fostering more sustainable and effective solutions for a wide spectrum of agricultural problems. Pest management is a major challenge for crop production that can benefit from machine learning techniques to detect and monitor specific pests and diseases. Traditional monitoring is labor intensive, time demanding, and expensive, while machine learning paradigms may support cost-effective crop protection decisions. However, previous studies mainly relied on morphological images of stationary or immobilized animals. Other features related to living animals behaving in the environment (e.g., walking trajectories, different postures, etc.) have been overlooked so far. In this study, we developed a detection method based on convolutional neural network (CNN) that can accurately classify in real-time two tephritid species (Ceratitis capitata and Bactrocera oleae) free to move and change their posture. Results showed a successful automatic detection (i.e., precision rate about 93%) in real-time of C. capitata and B. oleae adults using a camera sensor at a fixed height. In addition, the similar shape and movement patterns of the two insects did not interfere with the network precision. The proposed method can be extended to other pest species, needing minimal data pre-processing and similar architecture, Artificial Intelligence (AI) and automation are fostering more sustainable and effective solutions for a wide spectrum of agricultural problems. Pest management is a major challenge for crop production that can benefit from machine learning techniques to detect and monitor specific pests and diseases. Traditional monitoring is labor intensive, deep learning, etc.) have been overlooked so far. In this study, we developed a detection method based on convolutional neural network (CNN) that can accurately classify in real-time two tephritid species (Ceratitis capitata and Bactrocera oleae) free to move and change their posture. Results showed a successful automatic detection (i.e, integrate pest management, tephritid, monitoring, machine learning, AI, Insect Science, olive fruit fly, and expensive, while machine learning paradigms may support cost-effective crop protection decisions. However, walking trajectories, precision rate about 93%) in real-time of C. capitata and B. oleae adults using a camera sensor at a fixed height. In addition, previous studies mainly relied on morphological images of stationary or immobilized animals. Other features related to living animals behaving in the environment (e.g, agtech, time demanding, needing minimal data pre-processing and similar architecture, real-time classification, different postures

وصف الملف: application/pdf

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2cf7b1ffc97dd9dea8a97b4c549bf9f3
https://hdl.handle.net/11382/552211

المؤلفون: Zanoni, S., Baldessari, M., De Cristofaro, A., Angeli, G., Bosch, D., Escudero Colomar, L. A., Ioriatti, C.

المساهمون: Zanoni, S., Baldessari, M., De Cristofaro, A., Angeli, G., Bosch, D., Escudero Colomar, L.A., Ioriatti, C.

مصطلحات موضوعية: C. capitata, Laboratory bioassay, Insecticide efficacy, Settore AGR/11 - ENTOMOLOGIA GENERALE E APPLICATA

Relation: ispartofbook:X Congreso nacional de entomología aplicada: XVI jornadas científicas de la SEEA, Logroño, 16-20 octubre 2017; X Congreso nacional de entomología aplicada: XVI jornadas científicas de la SEEA; firstpage:131; http://hdl.handle.net/10449/51668

الاتاحة: http://hdl.handle.net/10449/51668

المؤلفون: Davi, Mateus Caetano Costa

المساهمون: Godoy, Maurício Sekiguchi de, http://lattes.cnpq.br/, Gomes, Jessé Malveira, Silva, Daniel Gonçalves da

مصطلحات موضوعية: Fruticultura, Índice MAD, C. capitata, Fruit produciton, FTP index, Anastrepha spp, CNPQ::CIENCIAS AGRARIAS::AGRONOMIA

وصف الملف: application/pdf

Relation: DAVI, Mateus Caetano Costa . Monitoramento de mosca-das-frutas em áreas produtoras de mamão (Carica papaya l.) no Município de Baraúna, RN. 2018. 37 f. Monografia (Graduação em Agronomia), Centro de Ciências Agronômicas e Florestais, Universidade Federal Rural do Semi-Árido, Mossoró, 2018.; https://repositorio.ufersa.edu.br/handle/prefix/1038; https://repositorio.ufersa.edu.br/handle/prefix/3260

الاتاحة: https://repositorio.ufersa.edu.br/handle/prefix/1038
https://repositorio.ufersa.edu.br/handle/prefix/3260

المؤلفون: Mahmoud, M.F., Osman, M.A.M., El-Hussiny, M.A.M., Elsebae, A.A., Hassan, S.A., Said, M.

مصطلحات موضوعية: B. zonata, C. capitata, partial - spot spray, efficacy, infestation, monitoring, GF-120, malathion

وصف الملف: application/pdf

Relation: Mahmoud, M.F., M.A.M. Osman, M.A.M. El-Hussiny, A.A. Elsebae, S.A. Hassan, M. Said. 2017. ”Low environmental impact method for controlling the peach fruit fly, Bactrocera zonata (Saunders) and the Mediterranean fruit fly, Ceratitis capitata (Wied.), in mango orchards in Egypt”. Cercetări Agronomice în Moldova 50 (4): 93-108. DOI:10.1515/cerce-2017-0039.; https://repository.uaiasi.ro/xmlui/handle/20.500.12811/1019

الاتاحة: https://repository.uaiasi.ro/xmlui/handle/20.500.12811/1019
https://hdl.handle.net/20.500.12811/1019
https://doi.org/10.1515/cerce-2017-0039

المؤلفون: Σολδάτος, Αναστάσιος

Thesis Advisors: Μαρμάρας, Βασίλειος, Soldatos, Anastasios, Κατσώρης, Παναγιώτης, Γεωργίου, Χρήστος, Δημόπουλος, Νικόλαος, Στεφάνου, Γεωργία, Δερμών, Αικατερίνη, Ροσμαράκη, Ελευθερία

مصطلحات موضوعية: Αιμοκύτταρα, Σηματοδοτικά μονοπάτια, Ανοσοποιητικό σύστημα, Κυτταροφαγία, Ενδοκυττάρωση, Ιντεγκρίνες, 571.915 77, C. capitata, LPS, MAPKs, ERK, Haemocytes, Signaling, Phagocytosis, Endocytosis, Integrins

Relation: Η ΒΚΠ διαθέτει αντίτυπο της διατριβής σε έντυπη μορφή στο βιβλιοστάσιο διδακτορικών διατριβών που βρίσκεται στο ισόγειο του κτιρίου της.

الاتاحة: http://hdl.handle.net/10889/8397

المساهمون: Μαρμάρας, Βασίλειος, Soldatos, Anastasios, Κατσώρης, Παναγιώτης, Γεωργίου, Χρήστος, Δημόπουλος, Νικόλαος, Στεφάνου, Γεωργία, Δερμών, Αικατερίνη, Ροσμαράκη, Ελευθερία

مصطلحات موضوعية: 571.915 77, Ανοσοποιητικό σύστημα, Integrins, LPS, Haemocytes, Ιντεγκρίνες, C. capitata, Αιμοκύτταρα, Σηματοδοτικά μονοπάτια, Signaling, Endocytosis, ERK, MAPKs, Phagocytosis, Ενδοκυττάρωση, Κυτταροφαγία

URL الوصول: https://explore.openaire.eu/search/publication?articleId=od______1047::95dea1f489db9141ea29d5a2e133e0a1
http://hdl.handle.net/10889/8397

المؤلفون: Σολδάτος, Αναστάσιος

المساهمون: Μαρμάρας, Βασίλειος, Soldatos, Anastasios, Κατσώρης, Παναγιώτης, Γεωργίου, Χρήστος, Δημόπουλος, Νικόλαος, Στεφάνου, Γεωργία, Δερμών, Αικατερίνη, Ροσμαράκη, Ελευθερία

مصطلحات موضوعية: Αιμοκύτταρα, Σηματοδοτικά μονοπάτια, Ανοσοποιητικό σύστημα, Κυτταροφαγία, Ενδοκυττάρωση, Ιντεγκρίνες, 571.915 77, C. capitata, LPS, MAPKs, ERK, Haemocytes, Signaling, Phagocytosis, Endocytosis, Integrins

وصف الملف: application/pdf

Relation: Η ΒΚΠ διαθέτει αντίτυπο της διατριβής σε έντυπη μορφή στο βιβλιοστάσιο διδακτορικών διατριβών που βρίσκεται στο ισόγειο του κτιρίου της.; http://hdl.handle.net/10889/8397

الاتاحة: http://hdl.handle.net/10889/8397

المؤلفون: Bustos, María E.¹, Enkerlin, Walther², Reyes, Jesús³, Toledo, Jorge⁴

المصدر: Journal of Economic Entomology 97(2):286-292. 2004

المؤلفون: Niyazi, Nuri^1,2,3,6, Lauzon, Carol R.^4,6, Shelly, Todd E.^5,6

المصدر: Journal of Economic Entomology 97(5):1570-1580. 2004