Moisture content of Panax notoginseng taproot predicted using near infrared spectroscopy

IF 1.6 4区化学 Q3 CHEMISTRY, APPLIED

Journal of Near Infrared Spectroscopy Pub Date : 2024-07-27 DOI:10.1177/09670335241242644

Fujie Zhang, Shanshan Li, Lei Shi, Lixia Li, Xiuming Cui

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引用次数: 0

Abstract

The rapid determination of moisture content in Panax notoginseng taproot (PNT) was determined using a portable near infrared spectrometer (900∼1700 nm). First, to reduce baseline offset of the spectra Savitzky-Golay and standard normal variate transformation were combined to preprocess the original spectral data. Then, competitive adaptive reweighting sampling and bootstrapping soft shrinkage (BOSS) were employed to extract feature wavelengths that could characterize the moisture content information of PNT respectively. Finally, the least square support vector regression (LSSVR) model was established based on feature spectra and full spectra. To improve the prediction accuracy of the model, a LSSVR model based on the arithmetic optimization algorithm (AOA) was proposed, and the optimization results were compared with those of the snake optimizer and particle swarm optimization. The results indicated that the best prediction model was BOSS-AOA-LSSVR, with r2 and RMSEP values of 0.96 and 0.03%, respectively. Thus, it is feasible to predict the moisture content of Panax notoginseng taproot by portable near infrared spectroscopy in combination with BOSS-AOA-LSSVR. The results show that portable near infrared spectroscopy can be used to predict the moisture content of Panax notoginseng taproot, which provides a theoretical basis for the rapid and non-destructive detection of the moisture content of Panax notoginseng taproots.

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利用近红外光谱预测三七直根的水分含量

使用便携式近红外光谱仪（900∼1700 nm）快速测定了三七直根（PNT）中的水分含量。首先，为了减少光谱的基线偏移，将萨维茨基-戈莱变换和标准正态变分变换相结合，对原始光谱数据进行预处理。然后，采用竞争性自适应再加权采样和自引导软收缩（BOSS）方法分别提取能表征 PNT 含水率信息的特征波长。最后，基于特征光谱和全光谱建立了最小平方支持向量回归（LSSVR）模型。为了提高模型的预测精度，提出了基于算术优化算法（AOA）的 LSSVR 模型，并将优化结果与蛇形优化器和粒子群优化的结果进行了比较。结果表明，最佳预测模型是 BOSS-AOA-LSSVR，其 r2 值和 RMSEP 值分别为 0.96% 和 0.03%。因此，利用便携式近红外光谱仪结合 BOSS-AOA-LSSVR 预测三七直根的水分含量是可行的。结果表明，便携式近红外光谱仪可用于预测三七直根的含水量，为快速、无损地检测三七直根的含水量提供了理论依据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Near Infrared Spectroscopy 物理-光谱学

CiteScore

3.30

自引率

5.60%

发文量

审稿时长

6 months

期刊介绍： JNIRS — Journal of Near Infrared Spectroscopy is a peer reviewed journal, publishing original research papers, short communications, review articles and letters concerned with near infrared spectroscopy and technology, its application, new instrumentation and the use of chemometric and data handling techniques within NIR.