在水产养殖中检测和预测致病微生物 (中国江省)
Tong Zhao1,2, Zhencai Shen3,2,4,5, Ping Zhong1,3,2,4,5
1College of Information and Electrical Engineering, China Agricultural University, 17 Tsinghua East Road, Beijing, 100083, China.
Environmental science and pollution research international
|January 4, 2024
概括
这项研究引入了一种使用定量聚合酶连锁反应 (qPCR) 来检测和预测水产养殖中的Cryptocaryon irritans (Cri) 的新方法. 开发的模型显著提高了鱼类疾病的早期预警准确性.
科学领域:
- 水产养殖是水产养殖的一种方式.
- 海洋生物学 海洋生物学
- 疾病检测 疾病检测
背景情况:
- 可持续的水产养殖依赖于检测致病微生物.
- 目前的早期预警系统专注于水质,而不是直接检测病原体.
- 早期发现Cryptocaryon irritans (Cri) 对黄鱼水产养殖至关重要.
研究的目的:
- 开发一种用于检测和预测黄色鱼水产养殖中的致病微生物的创新方法.
- 直接从致病源提供早期警告.
- 提高水产养殖疾病预测模型的准确性和可靠性.
主要方法:
- 量化聚合酶连锁反应 (qPCR) 用于检测Cryptocaryon刺激物 (Cri).
- 波形分析用于数据无效化,随后进行数据增强.
- 开发了一个融合预测模型,将BP神经网络 (BPNN) 与增强数据结合起来.
- 重复性和灵敏性测试验证了qPCR方法.
主要成果:
- 在qPCR方法准确量化了Cri病原性微生物.
- 与LSTM方法相比,核聚变预测模型显示出更高的性能.
- 包括MAE,回忆和准确率在内的评估指标显示出更好的预测.
- 提前预警的准确性提高了54.02%.
结论:
- 开发的qPCR方法对于Cri检测是稳定的和准确的.
- 融合预测模型有效地预测了水产养殖中的Cri病原微生物.
- 这种方法为水产养殖疾病管理的早期预警系统提供了重大进展.
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