Detection of Taste Change of Bovine and Goat Milk in Room Ambient Using Electronic Tongue

Imam Tazi(1), Anis Choiriyah(2), Dwi Siswanta(3), Kuwat Triyana(4*)

(1) Department of Physics, Universitas Islam Negeri Maulana Malik Ibrahim, Jl. Gajayana No. 50, Dinoyo, Lowokwaru, Malang 65144, East Jawa, Indonesia
(2) Department of Physics, Universitas Islam Negeri Maulana Malik Ibrahim, Jl. Gajayana No. 50, Dinoyo, Lowokwaru, Malang 65144, East Jawa, Indonesia
(3) Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara, Yogyakarta 55281, Indonesia
(4) Department of Physics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara, Yogyakarta 55281, Indonesia
(*) Corresponding Author


An electronic tongue (e-tongue) based on an array of lipid/polymer membranes has been successfully developed for measuring the taste evolution of natural milk. The e-tongue consisted of 16 different lipid/polymer membranes combined with or without a pH sensor. The natural milk of bovine and goat were purchased from the local farming store in Malang-Indonesia. The taste measurement was carried out, from fresh (0 h) to stale (12 h), every two hours under room ambient without any treatment. The responses of the e-tongue were evaluated using a Principal Component Analysis (PCA) and a Linear Discriminant Analysis (LDA). From PCA results, the taste of both milk samples tends to change by time although some groups show a partial overlapping. LDA results show the high precision of the e-tongue in clustering taste evolution. The correctly classified groups after the cross-validation procedure were achieved 95.7 and 87.1% for bovine and goat milk, respectively. The improvement of the classification using LDA was obtained by adding data from a pH sensor of each measurement as 100 and 98.6% for bovine and goat milk, respectively. This work indicates that the lab-made e-tongue may be useful to predict the quality of natural milk for the food industry.


electronic tongue; taste; linear discriminant analysis; principal component analysis

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