{"id":1948,"date":"2025-05-12T07:39:39","date_gmt":"2025-05-12T06:39:39","guid":{"rendered":"http:\/\/newskbncran.ru\/?page_id=1948"},"modified":"2026-03-26T10:57:10","modified_gmt":"2026-03-26T10:57:10","slug":"26-2-7-en","status":"publish","type":"page","link":"https:\/\/izvestiyakbncran.ru\/index.php\/en\/26-2-7-en\/","title":{"rendered":"26.2.7 en"},"content":{"rendered":"\n

Computer vision for monitoring and accounting Pyrenophora teres<\/em> of winter barley<\/strong><\/h1>\n\n\n\n

I.V. Arinicheva, G.V. Volkova, Ya.V. Yakhnik, I.V. Arinichev<\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/p>\n\n\n\n

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Upload the full text<\/strong><\/p>\n\n\n\n

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Abstract<\/em>. <\/strong>The traditional practice of diagnosing a disease and determining the economic threshold of harmfulness is based on visual assessment. But it is difficult and requires highly qualified specialists, whose timely departure is not always possible, especially to small farms. A fundamentally new and extremely promising approach to diagnose the development of net leaf spot of barley is an approach based on automatic (without the participation of a human expert) recognition of the pathogen and the degree of its development from an image or series of images. The article proposes the use of an innovative approach to diagnosing the development of net blotch (Pyrenophora teres)<\/em> of winter barley, based on advanced computer vision technologies. This approach involves a two-step image analysis process designed to improve the efficiency and accuracy of plant disease diagnosis. The first step uses two convolutional neural networks to perform two key tasks: separating barley leaf blades from the image background and segmenting net spot lesions. This allows for precise identification of affected areas, which is critical for subsequent analysis. At the second stage, a quantitative assessment of the degree of damage occurs, based on counting the pixels of affected and healthy areas of the leaf. The ratio of the areas of the affected areas to the total leaf area is determined, which provides an accurate and objective assessment of the degree of disease development. This method demonstrates significant advantages over traditional visual diagnostic methods, including increased accuracy and objectivity, as well as an accelerated analysis process. Field and laboratory studies were carried out in 2021\u20132023 at the sites of the Federal State Budgetary Institution Federal Research Center for Biological Plant Protection.<\/p>\n\n\n\n

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Keywords<\/em>: <\/strong>winter barley, barley diseases, diagnosis of disease development, net spot, pathogen, protection of grain crops, phytosanitary monitoring, computer vision, artificial intelligence<\/p>\n\n\n\n

For citation<\/strong>. Arinicheva I.V., Volkova G.V., Yakhnik Y\u0430.V., Arinichev I.V. Computer vision for monitoring and accounting Pyrenophora teres<\/em> of winter barley. News of the Kabardino-Balkarian Scientific Center of RAS.<\/em> <\/strong>2024. Vol. 26. No. 2. Pp. 72\u201379.  DOI: 10.35330\/1991-6639-2024-26-2-72-79<\/p>\n\n\n\n

References<\/strong><\/summary>\n
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  1. Arinichev I.V., Polyanskikh S.V., Arinicheva I.V. Semantic segmentation of rusts and spots of wheat. Computer Optics. 2023. T. 47. No. 1. Pp. 118\u2013125. DOI: 10.18287\/2412-6179-CO-1130. (In Russian)<\/li>\n\n\n\n
  2. Volkova G.V., Yakhnik Ya.V., Merzlikina E.N. et al. Sensitivity of barley net spot to triazole class fungicides. Advanced Research of Kuban. Sbornik materialov Yezhegodnoy otchetnoy konferentsii grantoderzhateley Kubanskogo nauchnogo fonda <\/em>[Collection of materials from the Annual Reporting Conference of Grant Holders of the Kuban Science Foundation]. Krasnodar, 2022. Pp. 51\u201355. (In Russian)<\/li>\n\n\n\n
  3. Veretelnikova N.A., Kuznetsova T.E., Nesterenko V.V. et al. Source material for the selection of winter barley for resistance to leaf diseases. Materialy IV mezhdunarodnoy nauchnoprakticheskoy konferentsii \u00abSovremennoe sostoyanie, problemy i perspektivy razvitiya agrarnoy nauki\u00bb<\/em> [Materials of the IV international scientific and practical conference \u201cCurrent state, problems and prospects for the development of agricultural science\u201d]. 2019. Pp. 144\u2013146. (In Russian)<\/li>\n\n\n\n
  4. Bilay V.I. Mikroorganizmy \u2013 vozbuditeli bolezney rasteniy <\/em>[Microorganisms \u2013 pathogens of plant diseases]: handbook. Kyiv: Naukova Dumka, 1988. 549 p. (In Russian)<\/li>\n\n\n\n
  5. Khasanov B.A. Opredelitel’ gribov-vozbuditeley \u00abgel’mintosporiozov\u00bb rasteniy iz rodov Bipolaris, Drechslera i Exserohilum<\/em> [Identify to fungi that cause \u201chelminthosporiosis\u201d of plants from the genera Bipolaris, Drechslera and Exserohilum]. Tashkent: Fan, 1992. 180 p. (In Russian)<\/li>\n\n\n\n
  6. Lashina N.M., Mironenko N.V., Zubkovich A.A., Afanasenko O.S. Juvenile resistance of barley varieties and samples to net-, spot- and hybrid (net \u00d7 spot) forms of Pyrenophora teres. Mycology and Phytopathology. 2023. Vol. 57. No. 1. Pp. 48\u201359. DOI: 10.31857\/S0026364823010099. (In Russian)<\/li>\n\n\n\n
  7. Koyshibaev M. Bolezni pshenitsy.<\/em> [Wheat diseases]. Ankara: Prodovol’stvennaya i sel’skokhozyaystvennaya organizatsiya Ob»yedinonnykh natsiy. 2018. 394 p. (In Russian)<\/li>\n\n\n\n
  8. Arinichev I.V., Volkova G.V. Arinicheva I.V. Diagnosis of the development of net blight of winter barley based on digital intelligent technologies. Trudy Kubanskogo gosudarstvennogo agrarnogo universiteta<\/em> [Proceedings of the Kuban State Agrarian University]. 2023. No. 106. Pp. 81\u201385. DOI: 10.21515\/1999-1703-106-81-85. (In Russian)<\/li>\n\n\n\n
  9. Arinichev I., Arinicheva I., Foshchan G., Saybel N. Digital monitoring of crops in grain ecosystems. BIO Web of Conferences (Agri Science2023), 2023. No. 66. P. 14016. DOI: 10.1051\/bioconf\/20236614016.<\/li>\n\n\n\n
  10. Arinichev I., Sidorov V., Arinicheva I. Digital solutions in the system of intelligent crop monitoring. In the collection: II International conference on current issues of breeding, technology and processing of agricultural crops, and environment (CIBTA-II- 2023). Les Ulis Cedex A, France, 2023. P. 1112. DOI: 10.1051\/bioconf\/20237101112.<\/li>\n<\/ol>\n\n\n\n

    <\/p>\n<\/details>\n\n\n\n

    Information about the authors<\/strong><\/summary>\n

    Irina V. Arinicheva<\/strong>, Doctor of Biology Sciences, Professor of the Department of Higher Mathematics, Kuban State Agrarian University named after I.T. Trubilin;
    350044, Russia, Krasnodar, 13 Kalinina street;
    loukianova7@mail.ru, ORCID: https\/\/orcid.org\/0000-0002-3331-8731, SPIN-code: 6169-1334
    Galina V. Volkova<\/strong>, Doctor of Biology Sciences, Corresponding Member of the Russian Academy of Sciences, Deputy Director for Research, Federal Scientific Center for Biological Plant Protection;
    350039, Russia, Krasnodar, 1 VNIIBZR street;
    galvol.bpp@yandex.ru, ORCID: https\/\/orcid.org\/0000-0002-3696-2610, SPIN-code: 1949-6965
    Yana V. Yakhnik<\/strong>, Researcher at the Laboratory of Plant Immunity to Diseases, Federal Scientific Center for Biological Plant Protection;
    350039, Russia, Krasnodar, 1 VNIIBZR street;
    yahnik1@mail.ru, ORCID: https\/\/orcid.org\/0000-0002-3410-7928, SPIN-code: 7453-5768
    Igor V. Arinichev<\/strong>, Candidate of Economic Sciences, Associate Professor of the Department of Theoretical Economics, Kuban State University;
    350040, Russia, Krasnodar, 149 Stavropolskaya street;
    iarinichev@gmail.com, SPIN-code: 7555-6470<\/p>\n\n\n\n

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    Computer vision for monitoring and accounting Pyrenophora teres of winter barley I.V. Arinicheva, G.V. Volkova, Ya.V. Yakhnik, I.V. Arinichev Upload the full text Abstract. The traditional practice of diagnosing a disease and determining the economic threshold of harmfulness is based on visual assessment. But it is difficult and requires highly qualified specialists, whose timely departure […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-1948","page","type-page","status-publish","hentry"],"yoast_head":"\n26.2.7 en - \u0418\u0417\u0412\u0415\u0421\u0422\u0418\u042f \u041a\u0410\u0411\u0410\u0420\u0414\u0418\u041d\u041e-\u0411\u0410\u041b\u041a\u0410\u0420\u0421\u041a\u041e\u0413\u041e \u041d\u0410\u0423\u0427\u041d\u041e\u0413\u041e \u0426\u0415\u041d\u0422\u0420\u0410 \u0420\u0410\u041d\u00bb<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/izvestiyakbncran.ru\/index.php\/en\/26-2-7-en\/\" \/>\n<meta property=\"og:locale\" content=\"ru_RU\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"26.2.7 en - \u0418\u0417\u0412\u0415\u0421\u0422\u0418\u042f \u041a\u0410\u0411\u0410\u0420\u0414\u0418\u041d\u041e-\u0411\u0410\u041b\u041a\u0410\u0420\u0421\u041a\u041e\u0413\u041e \u041d\u0410\u0423\u0427\u041d\u041e\u0413\u041e \u0426\u0415\u041d\u0422\u0420\u0410 \u0420\u0410\u041d\u00bb\" \/>\n<meta property=\"og:description\" content=\"Computer vision for monitoring and accounting Pyrenophora teres of winter barley I.V. 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