对DNA条形码,几何形态测量和机器学习的综合方法,用于对Culex蚊子 (Diptera: Culicidae) 的现场识别,这对载体传播疾病监测有影响
Sedthapong Laojun1, Tanasak Changbunjong2, Thavatchai Kamoltham3
1Department of Public Health and Health Promotion, College of Allied Health Sciences, Suan Sunandha Rajabhat University, Samut Songkhram, Thailand.
Acta tropica
|October 28, 2025
概括
精确识别Culex蚊子,关键的疾病载体,是通过使用DNA条形码和翅膀几何形态学改进. 这种综合方法可以加强对蚊子的监测和对抗树虫病毒和 filarial 寄生虫的控制工作.
科学领域:
- 医学昆虫学 医学昆虫学
- 分子生物学分子生物学
- 生物信息学是一种生物信息学.
背景情况:
- 虫蚊子会传播大量的树虫病毒和细菌寄生虫.
- 正确的物种识别受到形态相似性和分类学专业知识限制的挑战.
研究的目的:
- 在泰国开发和验证一个完整的框架,用于准确识别Culex蚊子物种.
- 评估DNA条形码,翅膀几何形态学 (GM) 和随机森林 (RF) 蚊子识别的有效性.
主要方法:
- 使用核酸序列进行DNA条形编码.
- 机翼几何形态测量 (GM) 使用Mahalanobis距离分析.
- 随机森林 (RF) 机器学习用于分类.
主要成果:
- 通过DNA条形码确认了形态识别,与数据库一致≥96%.
- 机翼转基因显示出显著的物种差异化 (p < 0.05) 和80%的交叉验证准确性.
- 综合方法在现场识别中实现了八种Culex物种80%-100%的准确性.
结论:
- 结合DNA条形码,机翼转基因和机器学习,为Culex物种识别提供了强大的方法.
- 该框架支持加强蚊媒疾病监测和控制战略.
- 方法的应用应根据特定的流行病学和运营环境量身定制.
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