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SIT-ia:一种软硬件系统,用于提高无菌昆虫技术的男性分类效率

Gerardo de la Vega¹, Luciano Smith², Lihuen Soria-Mercier³

¹Instituto de Investigaciones Forestales y Agropecuarias de Bariloche, Instituto Nacional de Tecnología Agropecuaria-Consejo Nacional de Investigaciones Científicas y Técnicas (IFAB, INTA-CONICET), San Carlos de Bariloche 8400, Río Negro, Argentina.

|November 27, 2025

概括

一个新的AI系统SIT-ia,自动化昆虫性别分类用于无菌昆虫技术 (SIT). 这项技术通过精确分离雄性和雌性昆虫来提高害虫管理效率,这对可持续农业至关重要.

科学领域:

农业昆虫学农业昆虫学
生物技术是生物技术.
人工智能的人工智能

背景情况:

侵入性昆虫在全球范围内构成重大经济和健康风险.
传统的杀虫剂使用引发了环境和健康问题,需要可持续的害虫控制.
无菌昆虫技术 (SIT) 为害虫管理提供了一个有希望的环保替代方案.

研究的目的:

开发和评估SIT-ia,这是一种使用人工智能和计算机视觉对昆虫进行性别分类的自动化系统.
提高无菌昆虫技术的效率和可行性,用于害虫防治.
为了证明该系统的有效性,使用果害虫D. suzukii.

主要方法:

开发一个集成人工智能和计算机视觉的软硬件系统,用于自动化性别识别.
应用SIT-ia系统来分类雄性和雌性 *D. suzukii*.
排序速度和精度与专家手动排序的比较.

主要成果:

在SIT-ia系统实现98.6%的准确性区分男性和女性 *D. suzukii*.
自动分类1000只大约需要70分钟,比手动分类所需的112分钟快得多.
该系统在SIT程序中的大规模应用方面表现出高效率.

结论:

SIT-ia为昆虫的性别分类提供了一种高效准确的自动化解决方案.
该系统可以很容易地集成到无菌昆虫技术生产协议中.
这一进步提高了SIT的实用性和有效性,以实现可持续的害虫管理.

关键词:

人工智能的人工智能是人工智能.卷积神经网络架构卷积神经网络架构机器学习是机器学习.男人分类男人分类害虫管理害虫管理害虫管理斑点翅膀的多索菲拉 (Drosophila) 是一个有斑点的翅膀的多索菲拉.

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