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Nondestructive Phenolic Compounds Measurement and Origin Discrimination of Peated Barley Malt Using Near-Infrared Hyperspectral Imagery and Machine Learning

机译：非破坏性酚类化合物测量和起源近红外高光谱图像和机器学习的泥土大麦麦芽的辨别

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Yijun Yan; Jinchang Ren; Julius Tschannerl; Huimin Zhao; Barry Harrison; Frances Jack;
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年度 2021
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1. Potential of UV and SWIR hyperspectral imaging for determination of levels of phenolic flavour compounds in peated barley malt [J] . Tschannerl Julius, Ren Jinchang, Jack Frances, Food Chemistry . 2019,第JANa1期

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2. Rapid and Nondestructive Discrimination of Geographical Origins of Longjing Tea using Hyperspectral Imaging at Two Spectral Ranges Coupled with Machine Learning Methods [J] . Zhiqi Hong, Yong He Applied Sciences . 2020,第3期

机译：使用高光谱成像在两种光谱范围内使用Hyperspectral Zone的快速和非破坏性辨别，耦合机器学习方法
3. Recognising weeds in a maize crop using a random forest machine-learning algorithm and near-infrared snapshot mosaic hyperspectral imagery [J] . Biosystems Engineering . 2018,第期

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5. Extraction and Optimization of Phenolic Compounds from Barley Malt Rootlets: A Low-Value Byproduct from Malting Industry [D] . Budaraju, Naga Sravanthi. 2019

机译：大麦麦芽根本的酚类化合物的提取与优化：麦芽工业低价副产品
6. Application of Near-Infrared Hyperspectral Imaging with Machine Learning Methods to Identify Geographical Origins of Dry Narrow-Leaved Oleaster (Elaeagnus angustifolia) Fruits [O] . Pan Gao, Wei Xu, Tianying Yan, 2019

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7. Rapid and Nondestructive Discrimination of Geographical Origins of Longjing Tea using Hyperspectral Imaging at Two Spectral Ranges Coupled with Machine Learning Methods [O] . Zhiqi Hong, Yong He 2020

机译：使用高光谱成像在两种光谱范围内使用Hyperspectral Zone的快速和非破坏性辨别，耦合机器学习方法

Nondestructive Phenolic Compounds Measurement and Origin Discrimination of Peated Barley Malt Using Near-Infrared Hyperspectral Imagery and Machine Learning

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