Full Article: PDF
Scientific Object Identifier: http://s-o-i.org/1.1/TAS-11-139-23
DOI: https://dx.doi.org/10.15863/TAS.2024.11.139.23
Language: English
Citation: Chorshanbiev, N.E. (2024). Cotton pest control and cotton yield improvement using convolutional neural network. ISJ Theoretical & Applied Science, 11 (139), 190-195. Soi: http://s-o-i.org/1.1/TAS-11-139-23 Doi: https://dx.doi.org/10.15863/TAS.2024.11.139.23 |
Pages: 190-195
Published: 30.11.2024
Abstract: This article presents data on the observation of plant development periods during cotton cultivation and the study of changes in its condition, timely assessment, analysis of the biology of pests and diseases of cotton, as well as the impact of the comprehensive use of various biostimulants on growth and yield. In cotton cultivation, the development periods of diseases and pests were determined, and the combined use of insecticides, fungicides against diseases, and biostimulants against them was 10.6 centners per hectare or 33.7% higher for the medium-fiber “Buxoro-8” variety and 11.3 centners per hectare or 35.0% higher for the fine-fibered variety “Marvarid”.
Key words: Convolutional neural network, cotton, disease, pest, fungicide, insecticide, yield, fiber quality.
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