2023
DOI: 10.1016/j.jfca.2023.105216
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Combination of near-infrared spectroscopy and key wavelength-based screening algorithm for rapid determination of rice protein content

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Cited by 26 publications
(3 citation statements)
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“…After the spectrum was acquired, original spectral curves (Figure 2a) and aver spectral curves (Figure 2b) were obtained. Overall, the original spectral curves reflec similarity in the reflectance spectral data of all samples, with small differences from s ple to sample, indicating that the mineral content in the samples was generally sim The reflectance spectral data reached the maximum and minimum values at waveleng of approximately 900 nm and 1450 nm, respectively, and there were obvious cu troughs near 980 nm, 1200 nm, 1440 nm, and 1660 nm and obvious peaks at 1050 nm, 1 nm, and 1680 nm, which may be related to compounds in pear fruit [33,34]. The prim peaks of water absorption, according to the literature, are 980 nm and 1450 nm.…”
Section: Raw Spectral Data Analysismentioning
confidence: 81%
“…After the spectrum was acquired, original spectral curves (Figure 2a) and aver spectral curves (Figure 2b) were obtained. Overall, the original spectral curves reflec similarity in the reflectance spectral data of all samples, with small differences from s ple to sample, indicating that the mineral content in the samples was generally sim The reflectance spectral data reached the maximum and minimum values at waveleng of approximately 900 nm and 1450 nm, respectively, and there were obvious cu troughs near 980 nm, 1200 nm, 1440 nm, and 1660 nm and obvious peaks at 1050 nm, 1 nm, and 1680 nm, which may be related to compounds in pear fruit [33,34]. The prim peaks of water absorption, according to the literature, are 980 nm and 1450 nm.…”
Section: Raw Spectral Data Analysismentioning
confidence: 81%
“…Wavelength screening is typically used to eliminate redundant information in the THz spectrum to extract effective features, thereby improving the modeling efficiency and reducing the amount of calculation. In this study, four spectral band screening methods—uninformative variable elimination (UVE) [ 20 ], successive projections algorithm (SPA) [ 21 ], competitive adaptive reweighted sampling (CARS) [ 22 ] and random frog (RF) [ 23 ]—were used to extract the characteristic wave of the THz absorption coefficient of three PE pipes.…”
Section: Resultsmentioning
confidence: 99%
“…Under the assumption that selection can enhance model prediction, the process of identifying wavelength variables within a speci c range or the entire spectrum range of near-infrared characteristics to improve model performance is termed wavelength selection. Presently, based on different selection strategies, wavelength selection algorithms are broadly categorized into two types: those based on regression models, such as Forward Interval Partial Least Squares (FiPLS), and those rooted in data feature analysis, such as Random Frog Jumping (RFR) [20], Monte Carlo Uninformative Variable Elimination (MC-UVE) [21][22][23], and Whale Optimization Algorithm (WOA) [24]. Studies have demonstrated the effectiveness of combining various wavelength selection algorithms in speci c elds [25,26].…”
Section: Introductionmentioning
confidence: 99%