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TACO: An Ontology in Turkish for Identifying and Controlling Plant Pests, Weeds and Diseases

Year 2024, Volume: 26 Issue: 77, 242 - 247, 27.05.2024
https://doi.org/10.21205/deufmd.2024267707

Abstract

While ensuring a more sustainable production, because of reduced chemical usage it is more complicated to control plant pests, diseases and weeds in smart agriculture. For this reason, it is of great importance to detect pests, diseases and weeds at the earliest stage. It is important that both farmers and the artificial intelligence applications developed for agricultural control should be able to detect these organisms and to know the agricultural control methods. Semantic technologies and ontologies provide machine interpretable information and solutions for heterogeneity. This study presents the Turkish Agricultural Control Ontology (TACO), which is built in Turkish and contains information about plant pests, diseases and weeds common in Turkey. The contributions of the study are that it is the first Turkish ontology built in this field and that the methods of agricultural control are included within the scope of the ontology. According to the commonly used ontology evaluation metrics, TACO is predominantly characterized as a deep classification taxonomy. In addition, it was concluded that the classes in the ontology have an evenly distributed and sufficient number of class individuals.

References

  • Tarım ve Orman Bakanlığı, 2019. Akıllı Tarım Platformu.http://www.akillitarim.org/tr/ (Date Of Access: 22.02.2023)
  • Jonquet, C., Toulet, A., Arnaud, E., Aubin, S., Yeumo, E.D., Emonet, V., Graybeal, J., Laporte, M.A., Musen, M.A., Pesce, V., Larmande, P. 2018. AgroPortal: A vocabulary and ontology repository for agronomy: Computers and Electronics in Agriculture, Vol. 144, p. 126-143. DOI:10.1016/j.compag.2017.10.012
  • Jaiswal, P., Avraham, S., Ilic, K., Kellogg, E.A., McCouch, S., Pujar, A., Reiser, L., Rhee, S.Y., Sachs, M.M., Schaeffer, M., Stein, L., Stevens, P., Vincent, L., Ware, D., Zapata, F. 2005. Plant Ontology (PO): a Controlled Vocabulary of Plant Structures and Growth Stages: Comparative and Functional Genomics, Vol. 6(7-8), p. 388-397. DOI: 10.1002/cfg.496
  • Arnaud, E., Cooper, L., Shrestha, R., Menda, N., Nelson, R.T., Matteis, L., Skofic, M., Bastow, R., Jaiswal, P., Mueller, L., McLaren, G. 2012. Towards a reference Plant Trait Ontology for modeling knowledge of plant traits and phenotypes. International Conference on Knowledge Engineering and Ontology Development, 4-7 October, Barcelona, 220–225.
  • European Bioinformatics Institute, 2017. Plant Experimental Conditions Ontology. https://bioportal.bioontology.org/ontologies/PECO (Date Of Access: 22.02.2023)
  • European Bioinformatics Institute, 2020. Plant Stress Ontology. 2020.https://bioportal.bioontology.org/ontologies/PLANTSO (Date Of Access: 22.02.2023)
  • Walls, R.L., Smith, B., Elser, J., Goldfain, A., Stevenson, D.W., Jaiswal, P. 2012. A plant disease extension of the infectious disease ontology. International Conference on Biomedical Ontology, 21-25 July, Graz, 1-5.
  • Aubert, C., Buttigieg, P.L., Laporte, M.A., Devare, M., Arnaud, E. 2017.Agronomy Ontology. http://purl.obolibrary.org/obo/agro.owl (Date Of Access: 22.02.2023)
  • Caracciolo, C., Stellato, A., Morshed, A., Johannsen, G., Rajbahndari, S., Jaques, Y., Keizer J. 2013. The AGROVOC Linked Dataset: Semantic Web Journal, Vol. 4(3), p. 341-348. DOI: 10.5555/2786071.2786087
  • Rodriguez-Garcia, M.A., Garcia-Sanchez, F. 2020. CropPestO: An Ontology Model for Identifying and Managing Plant Pests and Diseases: Communications in Computer and Information Science, Vol. 1309, p. 18-29. DOI: 10.1007/978-3-030-62015-8_2
  • Onkov, K. 2020. Ontology of Crop Pest Control. 3rd International Conference on Information Science and Systems, 19–22 March, Cambridge, 8–12.
  • Iglesias, A.R., Aranguren, M. E., González, A.R., Wilkinson, M.D. 2013. Plant Pathogen Interactions Ontology (PPIO). International WorkConference on Bioinformatics and Biomedical Engineering, 18-20 March, Gradana, 695-702.
  • Lacasta, J., Lopez-Pellicer, F.J., Espejo-García, B., Nogueras-Iso, J., Zarazaga-Soria, F.J. 2018. Agricultural recommendation system for crop protection: Computers and Electronics in Agriculture, Vol. 152, p. 82-89. DOI: 10.1016/j.compag.2018.06.049246 DEU FMD 26(77) (2024) 242-247
  • Medici, M., Dooley, D., Canavari, M. 2022. PestOn: An Ontology to Make Pesticides Information Easily Accessible and Interoperable: Sustainability, Vol. 14, p. 66-73. DOI: 10.3390/su14116673
  • TAGEM, 2018. Zirai Mücadele Teknik Talimatları Kitapları Cilt 1-Cilt 6.T.C. Tarım Orman ve Hayvancılık Bakanlığı, Ankara, 1841 p.
  • Noy, N., Fergerson, R., Musen, M. 2000. The knowledge model of Protégé2000: combining interoperability and flexibility, 12th International Conference on Knowledge Engineering and Knowledge Management, 26 October, French Riviera, 17-32.
  • Bizer, C., Vidal, M.E., Skaf-Molli, H. 2018. Linked Open Data. p 2096-2101.Liu, L., Özsu, M.T., ed. 2018. Encyclopedia of Database Systems, Springer Nature, Berlin, 4866 p.
  • Welty, C., McGuinness, D.L., Smith, M.K. 2004. OWL Web ontology language guide. https://www.w3.org/TR/owl-guide/ (Date Of Access:22.02.2023)
  • Tartır, S., Arpınar, I.B., Moore, M., Sheth, A.P., Aleman-Meza, B. 2005. OntoQA: Metric-based ontology quality analysis. IEEE Workshop on Knowledge Acquisition from Distributed, Autonomous, Semantically Heterogeneous Data and Knowledge Sources, 27 November, New Orleans, 45-53.
  • Ebietomer, E.P., Ekuobase, G.O. 2013. Evaluation of Ontology for Nigerian Case Laws: Computing, Information Systems, Development Informatics & Allied Research Journal, Vol. 4(3), p. 1-6.

TACO: Bitki Zararlıları, Yabani Otlar ve Hastalıkların Tespiti ve Kontrolü İçin Türkçe Bir Ontoloji

Year 2024, Volume: 26 Issue: 77, 242 - 247, 27.05.2024
https://doi.org/10.21205/deufmd.2024267707

Abstract

Akıllı tarımda daha sürdürülebilir bir üretim sağlanırken, kimyasal kullanımının azalması nedeniyle bitki zararlıları, hastalıkları ve yabancı ot kontrolü daha karmaşık hale gelmektedir. Bu nedenle zararlı, hastalık ve yabancı otların erken aşamada tespit edilmesi büyük önem taşımaktadır. Hem çiftçilerin hem de tarımsal mücadele için geliştirilen yapay zeka uygulamalarının bu organizmaları tespit edebilmesi ve tarımsal mücadele yöntemlerini bilmesi önemlidir. Semantik teknolojiler ve ontolojiler, makine tarafından yorumlanabilir bilgiler ve heterojenlik için çözümler sağlar. Bu çalışmada Türkiye'de yaygın olarak görülen bitki zararlıları, hastalıkları ve yabancı otlar hakkında bilgiler içeren Türkçe olarak oluşturulmuş Türk Tarımsal Kontrol Ontolojisi (TACO) sunulmaktadır. Çalışmanın katkıları, bu alanda yapılan ilk Türk ontolojisi olması ve tarımsal mücadele yöntemlerinin ontoloji kapsamında yer almasıdır. Sıkça kullanılan ontoloji değerlendirme metriklerine göre TACO, ağırlıklı olarak derin bir sınıflandırma taksonomisi olarak nitelendirilmiştir. Ayrıca ontolojideki sınıfların eşit olarak dağılım gösteren, yeterli sayıda sınıf örneğine sahip olduğu sonucuna varılmıştır.

References

  • Tarım ve Orman Bakanlığı, 2019. Akıllı Tarım Platformu.http://www.akillitarim.org/tr/ (Date Of Access: 22.02.2023)
  • Jonquet, C., Toulet, A., Arnaud, E., Aubin, S., Yeumo, E.D., Emonet, V., Graybeal, J., Laporte, M.A., Musen, M.A., Pesce, V., Larmande, P. 2018. AgroPortal: A vocabulary and ontology repository for agronomy: Computers and Electronics in Agriculture, Vol. 144, p. 126-143. DOI:10.1016/j.compag.2017.10.012
  • Jaiswal, P., Avraham, S., Ilic, K., Kellogg, E.A., McCouch, S., Pujar, A., Reiser, L., Rhee, S.Y., Sachs, M.M., Schaeffer, M., Stein, L., Stevens, P., Vincent, L., Ware, D., Zapata, F. 2005. Plant Ontology (PO): a Controlled Vocabulary of Plant Structures and Growth Stages: Comparative and Functional Genomics, Vol. 6(7-8), p. 388-397. DOI: 10.1002/cfg.496
  • Arnaud, E., Cooper, L., Shrestha, R., Menda, N., Nelson, R.T., Matteis, L., Skofic, M., Bastow, R., Jaiswal, P., Mueller, L., McLaren, G. 2012. Towards a reference Plant Trait Ontology for modeling knowledge of plant traits and phenotypes. International Conference on Knowledge Engineering and Ontology Development, 4-7 October, Barcelona, 220–225.
  • European Bioinformatics Institute, 2017. Plant Experimental Conditions Ontology. https://bioportal.bioontology.org/ontologies/PECO (Date Of Access: 22.02.2023)
  • European Bioinformatics Institute, 2020. Plant Stress Ontology. 2020.https://bioportal.bioontology.org/ontologies/PLANTSO (Date Of Access: 22.02.2023)
  • Walls, R.L., Smith, B., Elser, J., Goldfain, A., Stevenson, D.W., Jaiswal, P. 2012. A plant disease extension of the infectious disease ontology. International Conference on Biomedical Ontology, 21-25 July, Graz, 1-5.
  • Aubert, C., Buttigieg, P.L., Laporte, M.A., Devare, M., Arnaud, E. 2017.Agronomy Ontology. http://purl.obolibrary.org/obo/agro.owl (Date Of Access: 22.02.2023)
  • Caracciolo, C., Stellato, A., Morshed, A., Johannsen, G., Rajbahndari, S., Jaques, Y., Keizer J. 2013. The AGROVOC Linked Dataset: Semantic Web Journal, Vol. 4(3), p. 341-348. DOI: 10.5555/2786071.2786087
  • Rodriguez-Garcia, M.A., Garcia-Sanchez, F. 2020. CropPestO: An Ontology Model for Identifying and Managing Plant Pests and Diseases: Communications in Computer and Information Science, Vol. 1309, p. 18-29. DOI: 10.1007/978-3-030-62015-8_2
  • Onkov, K. 2020. Ontology of Crop Pest Control. 3rd International Conference on Information Science and Systems, 19–22 March, Cambridge, 8–12.
  • Iglesias, A.R., Aranguren, M. E., González, A.R., Wilkinson, M.D. 2013. Plant Pathogen Interactions Ontology (PPIO). International WorkConference on Bioinformatics and Biomedical Engineering, 18-20 March, Gradana, 695-702.
  • Lacasta, J., Lopez-Pellicer, F.J., Espejo-García, B., Nogueras-Iso, J., Zarazaga-Soria, F.J. 2018. Agricultural recommendation system for crop protection: Computers and Electronics in Agriculture, Vol. 152, p. 82-89. DOI: 10.1016/j.compag.2018.06.049246 DEU FMD 26(77) (2024) 242-247
  • Medici, M., Dooley, D., Canavari, M. 2022. PestOn: An Ontology to Make Pesticides Information Easily Accessible and Interoperable: Sustainability, Vol. 14, p. 66-73. DOI: 10.3390/su14116673
  • TAGEM, 2018. Zirai Mücadele Teknik Talimatları Kitapları Cilt 1-Cilt 6.T.C. Tarım Orman ve Hayvancılık Bakanlığı, Ankara, 1841 p.
  • Noy, N., Fergerson, R., Musen, M. 2000. The knowledge model of Protégé2000: combining interoperability and flexibility, 12th International Conference on Knowledge Engineering and Knowledge Management, 26 October, French Riviera, 17-32.
  • Bizer, C., Vidal, M.E., Skaf-Molli, H. 2018. Linked Open Data. p 2096-2101.Liu, L., Özsu, M.T., ed. 2018. Encyclopedia of Database Systems, Springer Nature, Berlin, 4866 p.
  • Welty, C., McGuinness, D.L., Smith, M.K. 2004. OWL Web ontology language guide. https://www.w3.org/TR/owl-guide/ (Date Of Access:22.02.2023)
  • Tartır, S., Arpınar, I.B., Moore, M., Sheth, A.P., Aleman-Meza, B. 2005. OntoQA: Metric-based ontology quality analysis. IEEE Workshop on Knowledge Acquisition from Distributed, Autonomous, Semantically Heterogeneous Data and Knowledge Sources, 27 November, New Orleans, 45-53.
  • Ebietomer, E.P., Ekuobase, G.O. 2013. Evaluation of Ontology for Nigerian Case Laws: Computing, Information Systems, Development Informatics & Allied Research Journal, Vol. 4(3), p. 1-6.
There are 20 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Övünç Öztürk 0000-0001-7127-7902

Early Pub Date May 14, 2024
Publication Date May 27, 2024
Published in Issue Year 2024 Volume: 26 Issue: 77

Cite

APA Öztürk, Ö. (2024). TACO: An Ontology in Turkish for Identifying and Controlling Plant Pests, Weeds and Diseases. Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen Ve Mühendislik Dergisi, 26(77), 242-247. https://doi.org/10.21205/deufmd.2024267707
AMA Öztürk Ö. TACO: An Ontology in Turkish for Identifying and Controlling Plant Pests, Weeds and Diseases. DEUFMD. May 2024;26(77):242-247. doi:10.21205/deufmd.2024267707
Chicago Öztürk, Övünç. “TACO: An Ontology in Turkish for Identifying and Controlling Plant Pests, Weeds and Diseases”. Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen Ve Mühendislik Dergisi 26, no. 77 (May 2024): 242-47. https://doi.org/10.21205/deufmd.2024267707.
EndNote Öztürk Ö (May 1, 2024) TACO: An Ontology in Turkish for Identifying and Controlling Plant Pests, Weeds and Diseases. Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi 26 77 242–247.
IEEE Ö. Öztürk, “TACO: An Ontology in Turkish for Identifying and Controlling Plant Pests, Weeds and Diseases”, DEUFMD, vol. 26, no. 77, pp. 242–247, 2024, doi: 10.21205/deufmd.2024267707.
ISNAD Öztürk, Övünç. “TACO: An Ontology in Turkish for Identifying and Controlling Plant Pests, Weeds and Diseases”. Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi 26/77 (May 2024), 242-247. https://doi.org/10.21205/deufmd.2024267707.
JAMA Öztürk Ö. TACO: An Ontology in Turkish for Identifying and Controlling Plant Pests, Weeds and Diseases. DEUFMD. 2024;26:242–247.
MLA Öztürk, Övünç. “TACO: An Ontology in Turkish for Identifying and Controlling Plant Pests, Weeds and Diseases”. Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen Ve Mühendislik Dergisi, vol. 26, no. 77, 2024, pp. 242-7, doi:10.21205/deufmd.2024267707.
Vancouver Öztürk Ö. TACO: An Ontology in Turkish for Identifying and Controlling Plant Pests, Weeds and Diseases. DEUFMD. 2024;26(77):242-7.

Dokuz Eylül Üniversitesi, Mühendislik Fakültesi Dekanlığı Tınaztepe Yerleşkesi, Adatepe Mah. Doğuş Cad. No: 207-I / 35390 Buca-İZMİR.