Detection of Gelatinization Properties of Millet Using Visible/Near Infrared Reflectance Spectroscopy

Fig. 1. Gelatinization characteristic curve and main characteristic parameters of typical millet
1: Variation curve of viscosity value with temperature; 2: Instrumentation temperature control curve

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Fig. 2. Technology roadmap

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Fig. 3. Reflectance spectra of millet samples
(a): S-G spectra; (b): MSC spectra; (c): 1-D spectra

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Fig. 4. Key wavelength variables of peak viscosity selection by SPA
(a): Optimal number of wavelength variables; (b): Optimal wavelengths

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Table 1. Statistics of pasting viscosity properties value of millet flour samples

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Table 1. Statistics of pasting viscosity properties value of millet flour samples

糊化参数	最小值	最大值	均值	均方差
PV/cp	717	2 305	1 347.30	429.28
TV/cp	63	390	226.01	94.01
BD/cp	581	2 006	1 122.23	375.66
FV/cp	171	946	528.03	203.33
SB/cp	104	604	303.18	114.83
GT/℃	75.10	79.93	76.89	0.91
PT/min	3.97	4.80	4.23	0.17

Table 2. The partition of sample sets based on different spectral preprocessing and SPXY

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Table 2. The partition of sample sets based on different spectral preprocessing and SPXY

糊化特性参数	光谱处理	校正集			验证集
糊化特性参数	光谱处理	范围	均值	标准偏差	范围	均值	标准偏差
	S-G	717~2 305	1 345.3	440.44	843~2 069	1 353.2	408.54
PV/cp	MSC	717~2 305	1 320.5	424.10	726~2 069	1 427.7	449.57
	1-D	717~2 305	1 820.1	420.82	795~2 069	1 548.9	402.50
	S-G	64~390	233.62	92.20	63~342	203.40	98.96
TV/cp	MSC	63~390	226.29	95.02	66~344	225.40	94.17
	1-D	63~390	222.67	95.92	66~342	236.27	90.44
	S-G	581~2 006	1 120.80	385.47	670~1 685	1 126.3	357.32
BD/cp	MSC	581~2 006	1 082.80	370.39	670~1 811	1 240.4	378.92
	1-D	581~2 006	1 089.12	375.88	670~1 811	1 219	370.51
	S-G	171~946	541.20	208.79	177~717	488.53	187.08
FV/cp	MSC	171~946	526.20	216.75	188~732	533.53	162.93
	1-D	177~946	543.84	205.65	171~680	480.60	195.20
	S-G	104~604	313.89	116.78	113~419	271.07	105.97
SB/cp	MSC	105~604	305.98	118.53	104~409	294.80	106.36
	1-D	104~604	302.82	121.83	121~406	304.27	94.42
	S-G	75.10~79.93	76.98	0.99	75.53~77.50	76.646	0.59
GT/℃	MSC	75.10~79.93	76.95	0.99	75.85~77.50	76.7153	0.65
	1-D	75.10~79.93	76.94	0.99	75.80~77.50	76.7553	0.62
	S-G	3.97~4.80	4.259 6	0.186 8	4.07~4.27	4.174 0	0.053 6
PT/min	MSC	3.97~4.80	4.234 2	0.170 1	4.07~4.60	4.220 0	0.161 1
	1-D	3.97~4.80	4.247 3	0.175 1	4.07~4.60	4.180 7	0.131 1

Table 3. Key wavelength variables selection by SPA based on different spectral preprocessing and SPXY

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Table 3. Key wavelength variables selection by SPA based on different spectral preprocessing and SPXY

糊化特性参数	预处理	特征波长数量	波长/nm
	S-G	5	380, 389, 420, 440, 600
PV/cp	MSC	9	385, 417, 424, 432, 510, 527, 778, 912, 950
	1-D	6	480, 603, 659, 859, 869, 874
	S-G	14	370, 376, 382, 390, 395, 401, 407, 419, 422, 702, 880, 961, 1 001, 1 019
TV/cp	MSC	17	370, 382, 390, 396, 402, 408, 425, 436, 445, 766, 775, 798, 962, 981, 991, 1 006, 1 018
	1-D	13	499, 556, 610, 619, 852, 862, 932, 940, 953, 968, 977, 991, 1 006
	S-G	15	382, 390, 393, 401, 417, 426, 446, 496, 605, 833, 962, 974, 991, 1 003, 1 007
BD/cp	MSC	7	382, 390, 425, 430, 444, 920, 929
	1-D	12	385, 606, 615, 622, 660, 799, 835, 853, 865, 916, 921, 986
	S-G	6	382, 389, 554, 810, 955, 1 020
FV/cp	MSC	10	373, 382, 415, 430, 666, 784, 861, 962, 974, 1 007
	1-D	16	474, 604, 616, 624, 673, 850, 853, 862, 865, 887, 920, 922, 928, 934, 972, 991
	S-G	7	387, 390, 442, 495, 731, 897, 985
SB/cp	MSC	18	373, 382, 389, 396, 401, 410, 425, 429, 442, 450, 776, 789, 964, 970, 975, 982, 999, 1 006
	1-D	14	447, 602, 620, 742, 827, 852, 862, 932, 935, 941, 953, 965, 991, 1 006
	S-G	5	382, 392, 678, 947, 1 006
GT/℃	MSC	2	458, 831
	1-D	3	430, 505, 930
	S-G	5	380, 417, 495, 983, 1 020
PT/min	MSC	4	373, 413, 518, 983
	1-D	2	468, 574

Table 4. Calibration and validation results of MLR models

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Table 4. Calibration and validation results of MLR models

糊化特性参数	预处理	R	SEC	R_p	SEP
	S-G	0.935 3	139.613 3	0.902 0	201.934 2
PV/cp	MSC	0.913 1	177.075 5	0.934 7	174.039 7
	1-D	0.918 8	153.506 4	0.860 5	227.680 5
	S-G	0.857 9	49.118 2	0.757 4	76.969 9
TV/cp	MSC	0.910 5	37.597 1	0.825 5	67.220 3
	1-D	0.915 4	35.154 1	0.784 3	69.436 6
	S-G	0.910 7	142.572 9	0.924 4	178.020 1
BD/cp	MSC	0.943 4	121.433 3	0.888 9	182.608 1
	1-D	0.947 7	114.222 4	0.894 2	194.336 9
	S-G	0.843 8	97.004 1	0.709 0	156.402 3
FV/cp	MSC	0.746 9	101.404 6	0.802 9	144.867 9
	1-D	0.937 6	65.562 3	0.853 1	132.166 7
	S-G	0.736 4	69.256 8	0.686 9	92.549 5
SB/cp	〗MSC	0.845 9	54.788 2	0.874 6	74.251 8
	1-D	0.903 2	39.131 7	0.857 2	76.737 2
	S-G	0.622 1	0.895 1	0.515 3	0.889 4
GT/℃	MSC	0.152 2	-	0.308 7	0.947 9
	1-D	0.733 6	0.503 9	0.493 7	0.882 7
	S-G	0.196 5	-	0.683 2	0.143 2
PT/min	MSC	0.911 8	0.132 9	0.696 5	0.126 5
	1-D	0.823 6	0.111 1	0.551 6	0.147 7

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Jian-hu WU, Gui-feng LI, Yan-kun PENG, Jun-jie DU, Jian-guo XU, Gang GAO. Detection of Gelatinization Properties of Millet Using Visible/Near Infrared Reflectance Spectroscopy[J]. Spectroscopy and Spectral Analysis, 2020, 40(10): 3247

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Paper Information

Category: Research Articles

Received: Aug. 22, 2019

Accepted: --

Published Online: Jun. 18, 2021

The Author Email: WU Jian-hu (287718596@qq.com)

DOI:10.3964/j.issn.1000-0593(2020)10-3247-07

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Statistics of pasting viscosity properties value of millet flour samples

Table 1. Statistics of pasting viscosity properties value of millet flour samples

Table 2. The partition of sample sets based on different spectral preprocessing and SPXY

Table 2. The partition of sample sets based on different spectral preprocessing and SPXY

Table 3. Key wavelength variables selection by SPA based on different spectral preprocessing and SPXY

Table 3. Key wavelength variables selection by SPA based on different spectral preprocessing and SPXY

Table 4. Calibration and validation results of MLR models

Table 4. Calibration and validation results of MLR models

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