vetpressАграрная наукаAgrarian science0869-81552686-701XРедакция журнала "Аграрная наука"10.32634/0869-8155-2024-388-11-139-144vetpress-3349Research ArticleАГРОНОМИЯAGRONOMYЦифровые технологии в оценке качества семян овощных культурDigital technologies in vegetable seed quality assessmenthttps://orcid.org/0000-0001-9323-7741МусаевФ. Б.MusaevF. B.

Мусаев Фархад Багадыр оглы - доктор сельскохозяйственных наук, ведущий научный сотрудник.

ул. Селекционная, 14, пос. ВНИИССОК, Одинцовский р-н, Московская обл., 143080

Farkhad B. Musaev - Doctor of Agricultural Science, Leading Researcher.

14 Selectionskaya Str., VNIISSOK village, Odintsovo district, Moscow region, 143080

musayev@bk.ruhttps://orcid.org/0000-0001-7326-2157ИвановаМ. И.IvanovaM. I.

Иванова Мария Ивановна - доктор сельскохозяйственных наук, профессор РАН.

дер. Верея, стр. 500, Раменский р-н, Московская обл., 140153

Maria I. Ivanova - Doctor of Agricultural Science, Рrofessor RAS.

Vereya village, 500 building, Ramenskoye district, Moscow region, 140153

ivanova_170@mail.ruhttps://orcid.org/0000-0002-5974-4288ПрияткинН. С.PriyatkinN. S.

Прияткин Николай Сергеевич - кандидат технических наук, старший научный сотрудник.

Гражданский пр-т, 14, Санкт-Петербург, 195220

Nikolay S. Priyatkin - Candidate of Technical Sciences, Senior Researcher.

14 Grazhdansky Аve., St. Petersburg, 195220

prini@mail.ruФедеральный научный центр овощеводстваРоссияFederal scientific vegetable center, VNIISSOKRussian FederationВсероссийский научно-исследовательский институт овощеводства — филиал Федерального научного центра овощеводстваРоссияAll-Russian Scientific Research Institute of Vegetable Growing — branch of FSBSI “Federal Scientific Vegetable Center”Russian FederationАгрофизический научно-исследовательский институтРоссияAgrophysical Research InstituteRussian Federation202421112024011139144Copyright © Мусаев Ф.Б., Иванова М.И., Прияткин Н.С., 20242024Мусаев Ф.Б., Иванова М.И., Прияткин Н.С.Musaev F.B., Ivanova M.I., Priyatkin N.S.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.vetpress.ru/jour/article/view/3349Актуальность

Актуальность. Форма, определенная его линейными параметрами, цвет поверхности — важнейшие характеристики качества семян. Метод оптической визуализации в сочетании с автоматическим анализом цифровых сканированных изображений позволяет статистически достоверно различать семена овощных культур по размерным и цветовым параметрам. В Федеральном научном центре овощеводства совместно с сотрудниками Агрофизического научно-исследовательского института и ООО «АргусСофт» проводится разработка современного инструментального метода цифровой морфометрии семян.

Цели работы — определить морфометрические параметры семян трех овощных культур путем цифрового анализа сканированных изображений и установить их связь с жизнеспособностью и качественными показателями.

Методы

Методы. Цифровые изображения семян были получены с использованием планшетного сканера HP Sсanjet 200, формат сохраняемых файлов JPG, разрешение 600 DPI. Морфометрический анализ цифровых сканированных изображений семян выполнен на базе Агрофизического НИИ с использованием программного обеспечения Argus-BIO производства ООО «АргусСофт», г. Санкт-Петербург.

Результаты

Результаты. Показано, что путем отбора семян лука репчатого и редиса по размеру и плотности можно значительно улучшить их качественные показатели: до 75,5% всхожести у лука, до 100% — у редиса при максимальной выровненности партии, оцененной методом цифровой морфометрии. Определена идеальная форма для семян капусты: у полноценных семян капусты индекс округлости должен составить больше 0,9. Дальнейшее развитие методики позволит определить оптимальные параметры размера и формы семян для различных видов овощных культур и увязать их с качественными показателями.

Relevance

Relevance. The shape determined by its linear parameters, the color of the surface are the most important characteristics of seed quality. The optical imaging method combined with the automatic analysis of digital scanned images allows statistically reliable differentiation of vegetable seeds by size and color parameters. The Federal Scientific Center of Vegetable Growing, together with employees of the Agrophysical Research Institute and “ArgusSoft” LLC, is developing a modern instrumental method of digital morphometry of seeds.

The purpose of the work is to determine the morphometric parameters of the seeds of three vegetable crops by digitally analyzing scanned images and establish their relationship with viability and quality indicators.

Methods

Methods. Digital images of the seeds were obtained using an HP Sasanjet 200 flatbed scanner, JPG file format, 600 DPI resolution. Morphometric analysis of digital scanned images of seeds was performed on the basis of the Agrophysical Research Institute using Argus-BIO software manufactured by “ArgusSoft” LLC, St. Petersburg.

Results

Results. It is shown that by selecting onion and radish seeds in size and density, their quality indicators can be significantly improved: up to 75.5% germination in onions, up to 100% in radishes with maximum batch alignment estimated by digital morphometry. The ideal shape for cabbage seeds has been determined: for full-fledged cabbage seeds, the roundness index should be more than 0.9. Further development of the technique will allow determining the optimal parameters of the size and shape of seeds for various types of vegetable crops and linking them with qualitative indicators.

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The authors declare that there are no conflicts of interest present.