Detection of the adulteration in pure cow ghee by electronic nose method (case study: sunflower oil and cow body fat)

Figures & data

Figure 1. The used e-nose system.

Table 1. The used sensors in electronic nose.

Sensor number	Sensor type	Main applications	Typical detection ranges (ppm)
1	MQ3	Alcohol	10–300
4	MQ-9	CO and combustible gas	Co 10–1000, Cg 100–10000
6	MQ135	Steam ammonia, benzene, sulfide	10–10000
3	MQ-136	Sulfur dioxide (SO2)	1–200
5	TGS813	CH4, C3H8, C4H10	500–10000
2	TGS822	Steam organic solvents	50–5000
7	TGS2602	Sulfide Hydrogen sulfide, ammonia, toluene	1–30
8	TGS2620	Alcohol, Steam organic solvents	50–5000

Figure 2. Radar graph response of the sensors for pure cow ghee (a), pure sunflower oil (b) and pure cow body fat (c).

Figure 3. Loading plot (a) and score plot (b) of PCA analysis in the diagnosis of cow ghee mixed with sunflower oil.

Figure 4. Loading plot (a) and score plot (b) of PCA analysis in the diagnosis of cow ghee mixed with cow body fat.

Table 2. Confusion matrix obtained to identify cow ghee from adulterated with sunflower oil.

Groups	1	2	3	4	5	6	7
1	14	0	0	0	0	0	0
2	0	14	1	0	0	0	0
3	2	0	13	0	0	0	0
4	0	1	0	14	0	0	0
5	0	0	0	2	11	2	0
6	0	0	0	0	1	14	0
7	0	0	0	0	0	0	15
Correct classification rate: 91.3%

(1) Pure cow ghee; (2) 10%; (3) 20% ; (4) 30% ; (5) 40% and (6) 50% fake; (7) pure vegetable oil.

Table 3. Artificial neural network results for adulteration with sunflower oil.

Row	Structure	MSE*	r*	CCR*
1	8–13-7	0.09534	0.81073	88.5
2	8–14-7	0.097782	0.76783	88.5
3	8–15-7	0.086222	0.87747	91.3
4	8–16-7	0.087933	0.85295	88.5
5	8–17-7	0.082726	0.85295	88.5

* MSE: Mean Square Error

* r: Correlation coefficient

* CCR: Correct Classification Rate

Table 4. Confusion matrix obtained to identify cow ghee from adulterated with cow body fat.

Groups	1	2	3	4	5	6	7
1	11	0	2	0	0	0	0
2	1	11	1	0	0	0	0
3	1	0	13	1	0	0	0
4	0	1	0	14	0	0	0
5	0	0	0	1	11	0	3
6	1	0	0	0	1	12	1
7	0	0	0	0	0	1	13
Correct classification rate: 82.5%

(1) Cow ghee; (2) 10%; (3) 20%; (4) 30%; (5) 40% and (6) 50% fake; (7) pure animal fat.

Table 5. Artificial neural network results for adulteration with cow body fat.

Row	Structure	MSE*	r*	CCR*
1	8–15-7	0.089305	0.7627	75.7
2	8–16-7	0.094881	0.78826	77.7
3	8–17-7	0.094352	0.81238	82.5
4	8–18-7	0.11907	0.71413	75.7
5	8–19-7	0.092439	0.79907	80.6

* MSE: Mean Square Error

* r: Correlation coefficient

* CCR: Correct Classification Rate