nondestructive detection of kiwifruit textural characteristic based on near infrared hyperspectral imaging technology

Figures & data

Figure 1. Hyperspectral online grading system.

Figure 2. Sample preparation of three textural test methods of (a) TPA (b) puncture (c) shear.

Figure 3. The characteristic curves kiwifruit texture properties by (a) TPA test (b) puncture test and (c) shear test.

Table 1. Statistical results of kiwifruit texture characteristics in the calibration and prediction.

Texture parameter	Sample set	Sample number	Range	Average	Standard error
H1 /N	Calibration	83	12.3677–673.4229	194.7869	192.1352
	Prediction	27	14.6021–673.4229	205.2451	200.3212
Chewiness /mj	Calibration	83	0.8407–815.0776	169.2926	209.9263
	Prediction	27	1.2311–815.0776	179.7656	224.8917
Resilience	Calibration	83	0.0411–0.3949	0.1700	0.1204
	Prediction	27	0.0450–0.3949	0.1752	0.1231
PH /N	Calibration	80	4.2990–67.9393	29.7421	24.6647
	Prediction	25	4.5901–64.2644	29.2404	24.2814
AH /N	Calibration	80	0.7227–38.5664	14.0574	13.2055
	Prediction	25	0.9849–35.0694	13.7748	12.7952
CH /(N/mm)	Calibration	80	0.8670–25.3618	7.5300	6.3564
	Prediction	25	1.1089–20.3669	7.1012	5.5408
SF /N	Calibration	83	0.4626–89.3205	17.4770	22.3009
	Prediction	26	0.7126–70.6971	16.2350	20.3904
ASF /N	Calibration	83	0.3065–47.1129	7.1789	10.0586
	Prediction	26	0.4630–32.4712	6.3409	8.2654

Figure 4. Average spectra of kiwifruit samples.

Table 2. Prediction results of kiwifruit texture characteristics by PLS.

Texture parameters	Pretreatment methods	Calibration sets		Prediction sets			Bias	Slope
		rc	RMSEC	rp	RMSEP	RPD
H1	NONE	0.9480	60.79	0.9352	72.54	2.72	17.7834	0.9226
	MC	0.9405	64.88	0.9302	74.73	2.57	18.6119	0.8910
	SNV	0.9253	72.44	0.9085	86.39	2.15	–	–
	MSC	0.9454	62.25	0.9289	75.84	2.59	–	–
Chewiness	NONE	0.9800	41.54	0.8972	115.35	2.29	3.4967	1.0553
	MC	0.9768	44.66	0.9025	111.32	2.35	10.3142	1.0477
	SNV	0.8944	93.32	0.8558	114.72	1.69	–	–
	MSC	0.9750	46.32	0.8821	124.10	2.15	–	–
Resilience	NONE	0.9452	0.039	0.9243	0.050	2.65	−0.0053	0.9865
	MC	0.9480	0.038	0.9128	0.053	2.48	−0.0051	0.9689
	SNV	0.9273	0.045	0.9216	0.050	2.62	–	–
	MSC	0.9491	0.038	0.9058	0.055	2.40	–	–
PH	NONE	0.9642	6.50	0.9267	9.39	2.19	2.0881	0.7829
	MC	0.9625	6.65	0.9241	9.48	2.14	1.7395	0.7735
	SNV	0.9763	5.30	0.8893	10.88	2.01	–	–
	MSC	0.9719	5.77	0.9174	9.65	2.17	–	–
AH	NONE	0.9587	3.73	0.8818	6.03	2.06	0.4282	0.8542
	MC	0.9572	3.80	0.8833	6.00	2.07	–	–
	SNV	0.9208	5.12	0.8838	5.97	2.05	–	–
	MSC	0.9504	4.08	0.9111	5.20	2.35	0.0087	0.8709
CH	NONE	0.9695	1.55	0.9503	1.72	3.11	−0.3192	0.9191
	MC	0.9705	1.52	0.9532	1.66	3.23	−0.2587	0.9237
	SNV	0.9615	1.73	0.9487	1.74	2.93	–	–
	MSC	0.9714	1.50	0.9361	1.93	2.78	–	–
SF	NONE	0.7901	13.59	0.8212	12.08	1.16	2.9053	0.5632
	MC	0.8040	13.18	0.8572	11.33	1.21	2.9360	0.5759
	SNV	0.7910	13.56	0.8539	11.56	1.19	–	–
	MSC	0.7975	13.37	0.7794	13.10	1.06	–	–
ASF	NONE	0.9901	1.40	0.7960	6.26	1.68	0.4767	1.0133
	MC	0.9880	1.54	0.7815	6.46	1.63	0.6432	0.9926
	SNV	0.9595	2.82	0.7423	7.05	1.52	–	–
	MSC	0.9893	1.46	0.7917	6.04	1.64	–	–

NONE method means that there is no preprocessing, that is, the original spectrum.

Figure 5. Correlation between predicted and measured values of (a) H1 (b) Chewiness (c) Resilience (d) PH (e) AH (f) CH (g) SF (h) ASF.