Experiment Science and Technology, Volume. 22, Issue 5, 53(2024)

Development and Application of Intelligent Identification APP for Plant Disease in the Practical Teaching

Lingguang KONG1... Xiaoqin LI2, Yang LI1, Chongchong LU1, Yongfang JIANG1, Chao ZHANG3 and Xinhua DING1,* |Show fewer author(s)
Author Affiliations
  • 1College of Plant Protection, Shandong Agricultural University, Tai'an 271018, China
  • 2Library, Shandong Agricultural University, Tai'an 271018, China
  • 3Department of Information Science and Engineering, Shandong Agricultural University, Tai'an 271018, China
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    The challenges and limitations associated with traditional methods of the teaching plant pathology are addressed, and an AI-based mobile application (APP) that utilizes the convolutional neural network (CNN) technology for the visualization of plant disease symptoms and pathogens is developed, which is applied to practical teaching scenarios. The APP can be applied to the innovative practical teaching, which enhances the practical teaching effectiveness. Compared with the traditional teaching methods, this AI-based APP demonstrates a notable positive impact on learning efficacy, significantly increases students’ interest in self-directed learning, fosters interdisciplinary innovative thinking, and enhances their application abilities. This tool is particularly beneficial for young talent with diverse skill sets. Furthermore, the APP can be used to improve the quality of education, modernize teaching methodologies, promote interdisciplinary integration, and enhance the evaluation system of practical teaching.

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    Lingguang KONG, Xiaoqin LI, Yang LI, Chongchong LU, Yongfang JIANG, Chao ZHANG, Xinhua DING. Development and Application of Intelligent Identification APP for Plant Disease in the Practical Teaching[J]. Experiment Science and Technology, 2024, 22(5): 53

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    Paper Information

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    Received: Feb. 25, 2024

    Accepted: Jul. 11, 2024

    Published Online: Dec. 13, 2024

    The Author Email: DING Xinhua (丁新华)

    DOI:10.12179/1672-4550.20240073

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