Research Article
Detection of Adulteration in Food Using Recurrent Neural Network with Internet of Things
Table 1
Fitting parameters of the FOE13 sensor dipped in urea adulterated milk.
| | Test sample | pH value | Exp. Q × 102 | Exp. α | R2 | R1 (kΩ) | CP (nF) | RD (kΩ) | Q1 × 102 | α1 |
| | Milk (250 ml) | 6.62 | 1.89 | 0.53 | 0.999 | 0.166 | 3.84 | 0.48 | 2.01 | 0.681 | | Milk + 0.6 mg/ml urea | 6.58 | 1.86 | 0.51 | 0.998 | 0.153 | 3.52 | 0.35 | 1.79 | 0.659 | | Milk + 0.8 mg/ml urea | 6.55 | 1.82 | 0.49 | 0.997 | 0.150 | 3.36 | 0.31 | 1.33 | 0.626 | | Milk + 1.0 mg/ml urea | 6.52 | 1.80 | 0.47 | 0.998 | 0.148 | 3.33 | 0.28 | 1.11 | 0.618 | | Milk + 1.4 mg/ml urea | 6.44 | 1.78 | 0.44 | 0.995 | 0.145 | 3.21 | 0.25 | 1.08 | 0.608 |
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