367

  • Internet ҳавола
  • DOI
  • UzSCI тизимида яратилган сана 09-02-2022
  • Ўқишлар сони 367
  • Нашр санаси 03-11-2021
  • Мақола тилиO'zbek
  • Саҳифалар сони12-14
Калит сўзлар
English

This article presents the data studied and analyzed in order to create an intelligent system for measuring and controlling the physiological state of the wheat plant during the growing season. The classification of factors influencing the physiological state of the wheat plant and the causes of their origin are analyzed. The fundamental basis for the detection of early-stage symptoms of the disease has been studied.

Калит сўзлар
№ Муаллифнинг исми Лавозими Ташкилот номи
1 Baratov R.. “Электротехника ва мехатроника” кафедраси доценти ТИҚХММИ МТУ
2 Valixonova H.. “Электротехника ва мехатроника” кафедраси 1-курс таянч докторанти ТИҚХММИ МТУ
№ Ҳавола номи
1 1. Дувелиллер Е, Сингх П.К, Меццалам М. Болезни и вредители пшеницы. Анкара-2018. 19 стр.
2 2. Прескотт Дж. М, Бурнетт П. А, Сари Е.Е, Рансом Дж, Боуман Дж, Миллиано В, Сингх Дж, Бекеле Г. Болезни и вредители пшеницы.25-ст
3 3. Suresh Mr.V, Gopinath D, M Hemavarthini. Plant Disease Detection using Image Processing. International Journal of Engineering Research & Technology.
4 4. Gittaly Dhingra, Vinay Kumar, Hem Dutt Joshi. Study of digital image processing techniques for leaf disease detection and classification. Multimedia Tools and Applications · August 2018
5 5. https://review.uz/post/rnok-pshenic-stabilnost-nevziraya-na-pandemiyu
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