Local tangent space alignment and relevance vector machine as nonlinear methods for estimating sensory quality of tea using NIR spectroscopy
作者： Peng Liu , Xiaoyu Zhu , Xiao Hu , Aihua Xiong , Jianping Wen
DOI: 10.1016/J.VIBSPEC.2019.05.005
关键词: Principal component analysis 、 Approximation error 、 Local tangent space alignment 、 Mathematics 、 Pattern recognition 、 Calibration 、 Reduction (complexity) 、 Relevance vector machine 、 Kernel principal component analysis 、 Dimension (vector space) 、 Artificial intelligence
摘要: … Traditionally, the quality of tea is mainly evaluated through the … Tea Tasters on the basis of the appearance of dry tea and infused tea leaves, aroma, liquor color and taste of brewed tea …
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