The Influence of Xanthan and Balangu Seed Gums Coats on the Kinetics of Infrared Drying of Apricot Slices: GA-ANN and ANFIS Modeling

Figures & data

Figure 1. Laboratory infrared dryer

Figure 2. The genetic algorithm–artificial neural network model structures for prediction of the drying time (a) and moisture content (b) of apricot slices

Figure 3. The adaptive neuro-fuzzy inference system model structures for prediction of the drying time and moisture content of apricot slices

Figure 4. Variations of moisture content of coated apricot slices at different (a) coating type (250 W and 7.5 cm distance); (b) infrared power (7.5 cm distance, balangu coating); and (c) sample distance (150 W, balangu coating)

Table 1. Error values calculated by optimized GA-ANN approach for estimation of drying time and moisture content of apricot slices in an infrared dryer

Performance	Drying time (min)	Moisture content (%)
Mean squared error (MSE)	255.650	1.022
Normalized mean squared error (NMSE)	0.099	0.001
Mean absolute error (MAE)	14.026	0.597
Minimum absolute error	2.334	0.001
Maximum absolute error	28.935	6.561
Correlation coefficient (r)	0.970	0.999

Figure 5. Experimental versus predicted values of drying time (a) and moisture content (b) of coated apricot slices by balangu seed gum (using genetic algorithm–artificial neural network model)

Table 2. The weight and bias data of the best GA-ANN structure for estimation of drying time

Hidden neurons	Bias	Input neurons		Output neurons
		IR power (W)	Distance (cm)	Drying time (min)
1	−3.1719	−4.5824	2.2269	4.8364
2	0.0294	5.2334	−2.4190	2.1567
3	0.4459	−1.8244	8.08478	3.8164
4	0.1711	2.4330	−0.8300	−5.8180
5	0.5634	3.0550	−4.2096	1.7674
6	0.3495	0.0691	0.0494	−0.1046
7	−0.4798	0.8986	−2.9915	−4.1123
Bias				0.4341

Table 3. The weight and bias data of the best GA-ANN structure for estimation of moisture content

Hidden neurons	Bias	Input neurons			Output neurons
		Time (min)	IR power (W)	Distance (cm)	Moisture content (%)
1	−7.65881	0.2055	4.8498	−0.1587	−1.2315
2	−1.7180	−0.1959	0.4632	−0.2791	0.3877
3	3.4212	−5.0499	−0.1245	−6.4245	−6.5917
4	−9.3933	0.2362	4.3960	−1.6527	0.1044
5	5.4833	−9.0474	0.1290	−0.0684	−6.3634
6	3.1218	−7.0728	−1.0790	1.2472	8.4614
7	−3.2855	5.4046	−0.2416	9.9198	−5.4550
8	0.1022	−0.2558	−5.2601	1.7688	8.8721
9	2.1864	−2.3271	−9.1299	−0.2419	8.5731
Bias					−0.1080

Figure 6. Sensitivity analysis results of apricot slices infrared drying by the best genetic algorithm–artificial neural network structure; drying time (a) and moisture content (b)

Figure 7. Response surface diagram for infrared radiation intensity and distance of apricot slices from lamp surface (coated by balangu seed gum) versus drying time (a). Fuzzy process for prediction of drying time (b)

Figure 8. Experimental versus predicted values of drying time (a) and moisture content (b) of coated apricot slices by balangu seed gum (using adaptive neuro-fuzzy inference system model)