Quantitative Evaluation of Orange Juice Sensory Quality using Electronic Tongue
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Abstract:
The sensory quality of three kinds of commercial available juice samples (20 brands) was evaluated by sensory evaluation combined with fuzzy mathematics. The samples were also analyzed by using the electronic tongue to obtain the corresponding electronic tongue data. The weight of each sensory indicator of the orange juice was determined using factor analysis method. The total score of the sensory quality was derived based on the weight of each sensory indicator. Subsequently, partial least squares (PLS) and back propagation neural network(BPNN) methods were contradistinctively used to establish the quantitative prediction model between sensor signals and the total score of sensory quality. The results showed that, sensory indicators of different types of orange juice could be effectively analyzed through factor analysis which accurately reflected the quality of the orange juice by the sensory evaluation results. The weights of color, aroma, acidity, sweetness, bitterness, body were 0.15, 0.06, 0.20, 0.24, 0.15 and 0.20, respectively. When the number of principal component was 3, the performance of BPNN model was better than PLS. The correlation coefficient (Rp) between the value predicted by the BPNN model and the reference value in the prediction set was 0.93 and the root mean square error of prediction (RMSEP) was 0.20. The results could provide a reference for intelligently evaluation of the sensory quality of orange juice.
