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Updated: Jul 15, 2025

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

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基于近红外光谱的PE包装蓝的可溶性固体含量建模与反向传播神经网络和部分最小方形 (BP-PLS) 算法

Ya Chen1, Yaoxiang Li1, Roger A Williams2

  • 1College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin, China.

Journal of food science
|September 27, 2023
PubMed
概括

近红外 (NIR) 谱学与反向传播 (BP) 神经网络和部分最小方形 (PLS) 算法 (BP-PLS) 结合,提供了一种快速,非破坏性的方法来确定包装蓝中的可溶性固体含量 (SSC). 这种先进的技术提高了整个蓝供应链质量控制的准确性.

关键词:
反向传播神经网络的神经网络.接近红外光谱学近红外光谱学正角部分最小平方差分分析.部分最小正方形.包装在聚乙烯中的蓝.可溶性固体含量可溶性固体含量

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