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Updated: Sep 17, 2025

Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements
10:25

Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements

Published on: June 28, 2016

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一个新的基于受约束优化的无参数模型更新策略,用于增强跨多个生物变异性的水果质量评估.

Penghui Liu1, Yingjie Zheng1, Hao Tian2

  • 1College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, PR China; Zhejiang Key Laboratory of Intelligent Sensing and Robotics for Agriculture, Hangzhou 310058, PR China; The National Key Laboratory of Agricultural Equipment Technology, Beijing 100083, PR China.

Food chemistry
|June 27, 2025
PubMed
概括

这项研究引入了一种新的校准方法,即修改后的半监督无参数校准增强 (MSS-PFCE),以显著改善水果质量评估. 该方法通过最小的新数据提高了预测准确性,确保了可靠的现场应用.

关键词:
生物变异性 生物变异性有限制的优化受限优化果实质量评估 果实质量评估在MSS-PFCE中使用.更新模型的更新.

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