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Title: | CASH: CORRELATING, ANALYTICAL, SENSORY AND HEDONIC DATA IN GREEN TEA | Authors: | YU PEIGEN | Keywords: | green tea, design of experiments, artificial neural network, mathematical modelling, sensory evaluation, consumer liking | Issue Date: | 3-Aug-2016 | Citation: | YU PEIGEN (2016-08-03). CASH: CORRELATING, ANALYTICAL, SENSORY AND HEDONIC DATA IN GREEN TEA. ScholarBank@NUS Repository. | Abstract: | Green tea (Camellia sinensis) is one of the world’s most popular beverages, and its consumption is on the rise due to its associated health benefits. In order for manufacturers to keep up and stay relevant with consumer choices, products will have to be designed with consumer acceptability in mind. The study of chemical, sensory, and hedonic properties of ready-to-drink (RTD) green tea is an information gathering process, and can be divided into three main stages: (i) the design of experiment; (ii) the collection of data through chemical analyses, sensory profiling, and consumer acceptance testing; and (iii) analysis and interpretation of data. As such, the objectives of this research were to systematically develop a methodology for collecting, analysing, and utilising data through the use of the design of experiments (DOE) methodology and a suite of modelling techniques. | URI: | http://scholarbank.nus.edu.sg/handle/10635/134911 |
Appears in Collections: | Ph.D Theses (Open) |
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