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Issue title: Fuzzy model for human autonomous computing in extreme surveillance and it’s applications
Guest editors: Varatharajan Ramachandran
Article type: Research Article
Authors: Tang, Hongyuana; b | Liao, Guipinga; *
Affiliations: [a] Agricultural College, Hunan Agricultural University, Changsha, Hunan, China | [b] Basic Course Teaching Department, Changsha Vocational and Technical College, Changsha, Hunan, China
Correspondence: [*] Corresponding author. Guiping Liao, Agricultural College, Hunan Agricultural University, Changsha, Hunan, China. E-mail: liaoguiping_135@163.com.
Abstract: At present, people’s living standard and consumption level are increasing day by day, the demand for edible oil crops is increasing. As the main source of oil crops, rape needs to use more accurate management and cultivation techniques, change backward technology, increase overall yield, and ensure the supply of oil crops. By means of artificial intelligence, the spectral segments of plants were analyzed to determine the species of light and the nutrients produced by plants, the monitoring of development and the prediction of crop yield. According to the spectral information of plant absorption and reflection, the chlorophyll level contained in plants can provide data support for rape planting and management, and monitor the real-time status of its growth and development. Mastering the nutrition and demand of rape in the whole process of growth and reproduction is very beneficial to the management and yield improvement of rape. And can adjust the cultivation method in time, play the advantage of hyperspectral technology.
Keywords: Artificial intelligence, Rape, Agronomic parameters, Spectral vegetation index
DOI: 10.3233/JIFS-189513
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6803-6813, 2021
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