数字农药：面向人工智能应用的综合农药信息库和动态web平台

IF 3.8 1区农林科学 Q1 AGRONOMY

Pest Management Science Pub Date : 2025-05-28 DOI:10.1002/ps.8894

Ziling Zhu, Xingxing Shi, Zicong Zhu, Shuhua Yang, Fan Wang, Guangfu Yang

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引用次数: 0

摘要

农药对于保护作物免受病虫害侵害以满足日益增长的全球粮食需求至关重要。在人工智能（AI）时代，计算机辅助方法有可能显著提高农药设计的效率和安全性。这些方法的应用依赖于全面准确的农药数据，这是开发有效农药的必要条件。然而，仍然缺乏综合和用户友好的数据库来显示有关农药的完整信息。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Digital pesticide: a comprehensive pesticide information database with dynamic web platform for artificial intelligence applications

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Digital pesticide: a comprehensive pesticide information database with dynamic web platform for artificial intelligence applications

Pesticides are crucial for protecting crops from pests and diseases to meet the growing global food demand. In the era of artificial intelligence (AI), computer-aided approaches have the potential to significantly enhance the efficiency and safety of pesticide design. The application of these methods depends on comprehensive and accurate pesticide data, essential for developing effective pesticides. However, there remains a lack of integrated and user-friendly databases to display complete information on pesticides.

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来源期刊

Pest Management Science 农林科学-昆虫学

CiteScore

7.90

自引率

9.80%

发文量

553

审稿时长

4.8 months

期刊介绍： Pest Management Science is the international journal of research and development in crop protection and pest control. Since its launch in 1970, the journal has become the premier forum for papers on the discovery, application, and impact on the environment of products and strategies designed for pest management. Published for SCI by John Wiley & Sons Ltd.