Shi-zhuang WENG, Zhao-jie CHU, Man-qin WANG, Nian WANG. Reflectance Spectroscopy for Accurate and Fast Analysis of Saturated Fatty Acid of Edible Oil Using Spectroscopy-Based 2D Convolution Regression Network[J]. Spectroscopy and Spectral Analysis, 2022, 42(5): 1490
- Spectroscopy and Spectral Analysis
- Vol. 42, Issue 5, 1490 (2022)
Fig. 1. Image of acquisition system of the reflectance spectroscopy on edible oils
Fig. 2. Structure of full convolution network
Fig. 3. Spectral input form of two-dimensional matrix
Fig. 4. Structure of spectroscopy-based two Dimension convolution regression network
Fig. 5. Reflectance spectra for all kinds of oil samples (a) and mean reflectance spectra of esame oil, soybean oil, corn oil, sunflower oil, rapeseed oil, peanut oil and olive oil (b)
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Table 1. Prediction results of palmitic acid content in edible oils by PLSR after different pretreatment methods
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Table 2. Prediction results of palmitic acid content in edible oils after SNV denoising
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Table 3. Important wavelengths selected by different methods
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Table 4. Prediction results of S2DCRN on palmitic acid content in edible oil after important wavelength selection
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Table 5. Prediction results based on S2DCRN for arachidic acid and behenic acid content in edible oils after important wavelength selection
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