基于理化指标预测龙井茶的感官品质
Sensory evaluation can provide integrated, direct measurements of the perceivedquality of food products. However, a sensory panel is subjective and suffers frominconsistency and inaccuracy. In this paper, we propose a sensory evaluation simulationmodel for Longjing tea (a Chinese brand of green tea). The physiochemical qualityindicators of Longjing tea were determined by instrumental analysis, including color,aroma, and taste. Meanwhile, the sensory quality of the tea was evaluated by an expertsensory panel. An artificial neural network was conducted to approximately predictsensory evaluation scores on the basis of physiochemical data. The results showedthat physiochemical factors, including hue, fluorescence peak 5, hue chromascale, b,L, 3-(methylthio) propionaldehyde, α-terpineol, linalool, dimethyl sulfide, total aromavalue, caffeine, quinic acid, theanin, gallic acid and total catechins were best correlatedwith sensory evaluation scores. Furthermore, physiochemical features that were chosenaccording to important factor weights were used to classify Longjing tea into two grades.Experimental results demonstrated that instrumental analysis could be complementarilyused in the evaluation and control of sensory quality by establishing a reasonablesensory-instrument correlation and human-simulated predictive model.