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基于微生物组的分类模型用于新鲜产品的安全性和质量评估.

Chao Liao1, Luxin Wang1, Gerald Quon2

  • 1Department of Food Science and Technology, University of California Davis, Davis, California, USA.

Microbiology spectrum
|March 6, 2024
PubMed
概括

使用k-mer哈希分析的机器学习提高了产品安全性和质量分类,优于片序列变体 (ASV). 基于ASV的分类学在食品微生物组研究中更有效地识别关键细菌指标.

关键词:
安普利康序列变异的变体k-mer 哈希哈希哈希哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈机器学习是机器学习.产品质量,生产质量的产品.生产安全生产安全随机的森林随机的森林

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