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<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" article-type="research-article" dtd-version="1.2" xml:lang="en"><front><journal-meta><journal-id journal-id-type="publisher-id">RUDN Journal of Agronomy and Animal Industries</journal-id><journal-title-group><journal-title xml:lang="en">RUDN Journal of Agronomy and Animal Industries</journal-title><trans-title-group xml:lang="ru"><trans-title>Вестник Российского университета дружбы народов. Серия: Агрономия и животноводство</trans-title></trans-title-group></journal-title-group><issn publication-format="print">2312-797X</issn><issn publication-format="electronic">2312-7988</issn><publisher><publisher-name xml:lang="en">Peoples’ Friendship University of Russia named after Patrice Lumumba</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">19901</article-id><article-id pub-id-type="doi">10.22363/2312-797X-2023-18-2-197-212</article-id><article-id pub-id-type="edn">KRIQXB</article-id><article-categories><subj-group subj-group-type="toc-heading" xml:lang="en"><subject>Soil science and agrochemistry</subject></subj-group><subj-group subj-group-type="toc-heading" xml:lang="ru"><subject>Почвоведение и агрохимия</subject></subj-group><subj-group subj-group-type="article-type"><subject>Research Article</subject></subj-group></article-categories><title-group><article-title xml:lang="en">Informative value of infrared survey data for detecting properties of arable soils</article-title><trans-title-group xml:lang="ru"><trans-title>Информативность данных инфракрасного диапазона съемки для детектирования свойств пахотных почв</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-6325-4604</contrib-id><contrib-id contrib-id-type="spin">8805-9813</contrib-id><name-alternatives><name xml:lang="en"><surname>Grubina</surname><given-names>Praskovya G.</given-names></name><name xml:lang="ru"><surname>Грубина</surname><given-names>Прасковья Георгиевна</given-names></name></name-alternatives><bio xml:lang="en"><p>Junior Researcher</p></bio><bio xml:lang="ru"><p>младший научный сотрудник</p></bio><email>grubina_pg@esoil.ru</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-8739-5441</contrib-id><contrib-id contrib-id-type="spin">5132-0631</contrib-id><name-alternatives><name xml:lang="en"><surname>Savin</surname><given-names>Igor Y.</given-names></name><name xml:lang="ru"><surname>Савин</surname><given-names>Игорь Юрьевич</given-names></name></name-alternatives><bio xml:lang="en"><p>Doctor of Agricultural Sciences, Academician of the Russian Academy of Sciences, Professor, Institute of Ecology, RUDN University; Chief Researcher, Dokuchaev Soil Sciense Institute</p></bio><bio xml:lang="ru"><p>доктор сельскохозяйственных наук, академик РАН, профессор Института экологии, Российский университет дружбы народов; главный научный сотрудник, ФИЦ «Почвенный институт имени В.В. Докучаева»</p></bio><email>savin_iyu@esoil.ru</email><xref ref-type="aff" rid="aff1"/><xref ref-type="aff" rid="aff2"/></contrib></contrib-group><aff-alternatives id="aff1"><aff><institution xml:lang="en">V.V. Dokuchaev Soil Science Institute</institution></aff><aff><institution xml:lang="ru">ФИЦ «Почвенный институт им. В.В. Докучаева»</institution></aff></aff-alternatives><aff-alternatives id="aff2"><aff><institution xml:lang="en">RUDN University</institution></aff><aff><institution xml:lang="ru">Российский университет дружбы народов</institution></aff></aff-alternatives><pub-date date-type="pub" iso-8601-date="2023-06-30" publication-format="electronic"><day>30</day><month>06</month><year>2023</year></pub-date><volume>18</volume><issue>2</issue><issue-title xml:lang="en">VOL 18, NO2 (2023)</issue-title><issue-title xml:lang="ru">ТОМ 18, №2 (2023)</issue-title><fpage>197</fpage><lpage>212</lpage><history><date date-type="received" iso-8601-date="2023-07-09"><day>09</day><month>07</month><year>2023</year></date></history><permissions><copyright-statement xml:lang="en">Copyright ©; 2023, Grubina P.G., Savin I.Y.</copyright-statement><copyright-statement xml:lang="ru">Copyright ©; 2023, Грубина П.Г., Савин И.Ю.</copyright-statement><copyright-year>2023</copyright-year><copyright-holder xml:lang="en">Grubina P.G., Savin I.Y.</copyright-holder><copyright-holder xml:lang="ru">Грубина П.Г., Савин И.Ю.</copyright-holder><ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/><license><ali:license_ref xmlns:ali="http://www.niso.org/schemas/ali/1.0/">https://creativecommons.org/licenses/by-nc/4.0</ali:license_ref></license></permissions><self-uri xlink:href="https://agrojournal.rudn.ru/agronomy/article/view/19901">https://agrojournal.rudn.ru/agronomy/article/view/19901</self-uri><abstract xml:lang="en"><p style="text-align: justify;">Possibility of detecting soil fertility parameters based on the use of thermal survey data was studied on the test area of Yasnogorsky District, Tula region, Russia. The test area has gray forest slightly eroded arable soils located in the flat part of the slope. During the field works, an open soil surface was photographed using a FLIR VUE 512 thermal imager (range 7.5-13.5 mkm), soil samples were also taken from a layer of 0-5 cm and soil moisture was measured in a layer of 15-20 cm. For almost all parameters of soil fertility (pH, humus content, potassium content, exchange cations - Mg++, K+, Na+), a statistically significant correlation was established (r =0.4-0.7) between them and the survey data in the thermal range of the spectrum. For moderate correlations, polynomial regression equations were compiled. Among the studied fertility parameters, the pH of the salt extract, the content of potassium oxide and potassium exchange cations had significant coefficient of determination (R<sup>2</sup> &gt; 0.60) with the thermal range of the spectrum - R<sup>2</sup>= 0.61, R<sup>2</sup> =0.60 and R<sup>2</sup> = 0.63, respectively. The obtained results have shown that thermal imaging can be used to map some parameters of soil fertility for the region. Nevertheless, it turned out to be impossible to reliably detect all the main parameters of soil fertility of the test field on the basis of thermal survey data. However, the thermal soil survey data can be used as auxiliary data when shooting in the visible and nearIR ranges, which helps to improve the accuracy of contactless soil monitoring.</p></abstract><trans-abstract xml:lang="ru"><p style="text-align: justify;">Приведены результаты анализа возможности детектирования параметров почвенного плодородия на основе использования данных тепловой съемки на примере тестового участка в Ясногорском районе Тульской области. На тестовом участке представлены серые лесные слабоэродированные пахотные почвы, расположенные в плоской части склона. Во время полевых работ проводилась съемка открытой поверхности почв с использованием т епловизора FLIR VUE 512 (диапазон 7,5-13,5 мкм), также из слоя 0-5 см производился отбор почвенных образцов и измерение влажности почвы в слое 15-20 см. Практически для всех параметров почвенного плодородия (pH, содержание гумуса, содержание калия, обменные катионы - Mg++, K+, Na+) была установлена статистически значимая корреляция (r =0,4-0,7), между ними и данными съемки в тепловом диапазоне спектра. Для умеренных корреляций были составлены уравнения полиноминальной регрессии. Из исследуемых параметров плодородия значимый коэффициент детерминации (R<sup>2</sup> &gt; 0,60) с тепловым диапазоном спектра имели pH сол. (R<sup>2</sup> = 0,61), содержание оксида калия (R<sup>2</sup> = 0,60) и обменных катионов калия (R<sup>2</sup> = 0,63). Полученные результаты показали, что использование съемки в тепловом диапазоне может применяться для картографирования некоторых параметров почвенного плодородия региона исследования. Для тестового поля оказалось невозможным на основе данных тепловой съемки надежно отдетектировать все основные параметры плодородия почв поля. Однако данные тепловой почвенной съемки можно использовать как вспомогательные при съемке в видимом и ближнем ИК диапазонах, что поможет повысить точность бесконтактного почвенного мониторинга.</p></trans-abstract><kwd-group xml:lang="en"><kwd>thermal infrared imaging</kwd><kwd>soil properties</kwd><kwd>soil fertility parameters</kwd><kwd>Tula region</kwd></kwd-group><kwd-group xml:lang="ru"><kwd>тепловая съемка</kwd><kwd>почвенные свой ства</kwd><kwd>параметры плодородия почв</kwd><kwd>Тульская область</kwd></kwd-group><funding-group><award-group><funding-source><institution-wrap><institution xml:lang="ru">Исследования выполнены при финансовой поддержке проекта РФ в лице Минобрнауки (соглашение № 075-15-2022-321).</institution></institution-wrap><institution-wrap><institution xml:lang="en">The research was carried out with the financial support of the project of the Russian Federation represented by the Ministry of Education and Science (no. 075-15-2022-321).</institution></institution-wrap></funding-source></award-group></funding-group></article-meta></front><body></body><back><ref-list><ref id="B1"><label>1.</label><citation-alternatives><mixed-citation xml:lang="en">Savin IY, Simakova MS. 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