Agriculture applications contribution to improve precise pest management in China

The rapid proliferation of agricultural applications (apps) in China's digital village initiative necessitates systematic evaluation of their functionality and accessibility. Regarding the agricultural pest control apps that can be searched in the Chinese market, this study collected and analyzed information using 18 variables, involving developers, languages, application systems, identified objects and functions. There were 158 apps that met the 11 mandatory features, and most of the applications were developed for Android and iOS systems. The functions, accuracy, response time and goals of agricultural apps are all important factors affecting the download and application of agricultural apps. Identification apps are in the initial stage, while comprehensive application apps are gradually increasing. Regional or National, even of crop-specific pest management apps are becoming mainstream. Case studies of prominent Chinese apps provide critical services such as disease diagnosis, pest control recommendations, and farm management solutions, leading to quantifiable benefits including reduced pesticide use, decreased crop losses, and increased farmer income in China. Agricultural applications accessible via smartphones have great potential in preventing crop losses and reducing pesticide use. The development of agricultural pest and disease control applications still has a long way to go, including precise assessment and potential risks during the implementation process. There is no doubt that against the backdrop of the continuous growth of the global population, these applications will facilitate the digital prevention and control of agricultural pests.

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Publication Details

Journal
Scientific Reports
Published
2025-11-24
DOI
https://doi.org/10.1038/s41598-025-25619-8
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00

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article

Agriculture applications contribution to improve precise pest management in China

Mariam Kadzamira, Feng Zhang, Undarmaa Davaasambuu, Yuanyuan Cheng et al.
Scientific Reports
Smart Agriculture and AI
article

Agriculture applications contribution to improve precise pest management in China

Mariam Kadzamira, Feng Zhang, Undarmaa Davaasambuu, Yuanyuan Cheng, Tao Zhang, Hongmei Li, Min Wan, Guangjun Wang
article en

Abstract

The rapid proliferation of agricultural applications (apps) in China's digital village initiative necessitates systematic evaluation of their functionality and accessibility. Regarding the agricultural pest control apps that can be searched in the Chinese market, this study collected and analyzed information using 18 variables, involving developers, languages, application systems, identified objects and functions. There were 158 apps that met the 11 mandatory features, and most of the applications were developed for Android and iOS systems. The functions, accuracy, response time and goals of agricultural apps are all important factors affecting the download and application of agricultural apps. Identification apps are in the initial stage, while comprehensive application apps are gradually increasing. Regional or National, even of crop-specific pest management apps are becoming mainstream. Case studies of prominent Chinese apps provide critical services such as disease diagnosis, pest control recommendations, and farm management solutions, leading to quantifiable benefits including reduced pesticide use, decreased crop losses, and increased farmer income in China. Agricultural applications accessible via smartphones have great potential in preventing crop losses and reducing pesticide use. The development of agricultural pest and disease control applications still has a long way to go, including precise assessment and potential risks during the implementation process. There is no doubt that against the backdrop of the continuous growth of the global population, these applications will facilitate the digital prevention and control of agricultural pests.

Scientific ReportsVol. 15(1)
Gansu Agricultural University (CN), Mongolian University of Life Sciences (MN), Chinese Academy of Agricultural Sciences (CN), East Asia Research (SG), Steel Construction Institute (GB)
Ministry of Agriculture of the People's Republic of China, Foreign, Commonwealth and Development Office, Agriculture and Agri-Food Canada, Australian Centre for International Agricultural Research
Openalex Percentile: Top 74%
Smart Agriculture and AI
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