偏最小二乘回归
分光计
多元统计
小波
校准
特征(语言学)
内容(测量理论)
计算机科学
生物系统
材料科学
分析化学(期刊)
数学
光学
统计
化学
人工智能
色谱法
物理
生物
语言学
哲学
数学分析
作者
Kunshan Yao,Jun Sun,Jiehong Cheng,Min Xu,Chen Chen,Xin Zhou
标识
DOI:10.1016/j.infrared.2023.104685
摘要
The study investigated the feasibility of using portable NIR spectrometer coupled with multivariate analysis to monitor the S-ovalbumin content in eggs during storage. The NIR spectra of egg samples were obtained in the spectral range of 900–1700 nm. Savitzky-Golay (SG) smoothing, wavelet threshold denoising (WTD), multiplicative scatter correction (MSC), standard normal variate (SNV) and their combinations were used to pretreat the raw spectral data. In addition, successive projection algorithm (SPA) and iteratively retains informative variables (IRIV) were employed to extract feature related wavelengths from the full spectrum. Finally, the developed partial least squares regression (PLSR) model based on 14 IRIV feature wavelengths preprocessed by WTD-MSC had the best performance (R2P = 0.86, RMSEP = 9.33%). The result indicates that portable NIR device can be used with caution for nondestructive monitoring of S-ovalbumin content in eggs and has the potential to be applied in the supply chain.
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