Combine Hyperspectral Imaging and Machine Learning to Identify the Age of Cotton Seeds

Table 1. Sample classification
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Table 1. Sample classification
2016年
棉种/粒 2017年
棉种/粒 2018年
棉种/粒 2019年
棉种/粒
训练集 208 208 208 208
验证集 77 77 77 77
测试集 75 75 75 75

Table 2. Instrument information

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Table 2. Instrument information

模块	设备信息
成像模块	Surface Optics Corporation(SOC)710 SWIR摄像机(Surface Optics Corporation, San Diego, California, USA)
照明模块	卤素灯, 单盏卤素灯功率为50 W, 共使用4盏卤素灯
软件模块	HyperScanner V2, 用于采集数据

Table 3. Identification results of different models

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Table 3. Identification results of different models

	全光谱			特征光谱
	训练集	验证集	测试集	训练集	验证集	测试集
LR	0.967 4	0.979 0	0.962 7	0.931 3	0.930 1	0.935 6
PLS-DA	0.990 7	1.000 0	0.989 8	0.987 2	0.993 0	0.972 9
SVM	0.996 5	0.986 0	0.993 2	0.988 4	0.979 0	0.983 0
RNN	0.967 4	0.961 5	0.969 5	0.956 9	0.954 5	0.952 5
LSTM	0.980 2	0.968 5	0.976 3	0.966 2	0.965 0	0.942 4
CNN	1.000 0	1.000 0	1.000 0	1.000 0	0.986 0	0.996 6

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Long DUAN, Tian-ying YAN, Jiang-li WANG, Wei-xin YE, Wei CHEN, Pan GAO, Xin LÜ. Combine Hyperspectral Imaging and Machine Learning to Identify the Age of Cotton Seeds[J]. Spectroscopy and Spectral Analysis, 2021, 41(12): 3857

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