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Journal of Geoscience and Environment Protection 2021年第3期9卷 75-83页

作者： Xiaowen Shi Lijun Yao Tao Pan Department of Optoelectronic Engineering Jinan University Guangzhou China

Using visible and near-infrared (Vis-NIR) spectroscopy combined with partial least squares (PLS) regression, the rapid reagent-free analysis model for chromium (Cr) content in tideland reclamation soil in the Pearl River Delta, China was established. Based on Savitzky-Golay (SG) smoothing and PLS regression, a multi-parameters optimization platform (SG-PLS) covering 264 modes was constructed to select the appropriately spectral preprocessing mode. The optimal SG-PLS model was determined according to the prediction effect. The selected optimal parameters d, p, m and LV were 2, 6, 23 and 8, respectively. Using the validation samples that were not involved in modeling, the root mean square error (SEPV), relative root mean square error (R-SEPV) and correlation coefficients (RP, V) of prediction were 11.66 mg·kg-1, 10.7% and 0.722, respectively. The results indicated that the feasibility of using Vis-NIR spectroscopy combined with SG-PLS method to analyze soil Cr content. The constructed multi-parameters optimization platform with SG-PLS is expected to be applied to a wider field of analysis. The rapid detection method has important application values to large-scale agricultural production.

关键词： Soil Heavy Metal Chromium visible and near-infrared spectroscopy Rapid Reagent-Free Analysis Savitzky-Golay Smoothing

Mineralogy of Chang'e-4 landing site:preliminary results of visible and near-infrared imaging spectrometer

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Science China(Information Sciences) 2020年第4期63卷 195-206页

作者： Jian CHEN Zongcheng LING Le QIAO Zhiping HE Rui XU Lingzhi SUN Jiang ZHANG Bo LI Xiaohui FU Changqing LIU Xiaobin QI Shandong Key Laboratory of Optical Astronomy and Solar-Terrestrial Environment School of Space Science and PhysicsInstitute of Space Sciences Shandong University Key Laboratory of Space Active Opto-Electronics Technology Shanghai Institute of Technical PhysicsChinese Academy of Sciences Hawai'i Institute of Geophysics and Planetology Department of Earth Sciences University of Hawai'i at Manoa

The exploration of mafic anomaly in South Pole-Aitken(SPA, the largest confirmed) basin on the Moon provides important insights into lunar interior. The landing of Chang’e-4(CE-4) and deployment of Yutu-2 rover on the discontinuous ejecta from Finsen crater enabled in-situ measurements of the unusual mineralogy in the central portion of SPA basin with visible and near-infrared imaging spectrometer(VNIS).Here we present detailed processing procedures based on the level 2B data of CE-4 VNIS and preliminary mineralogical results at the exploration area of Yutu-2 rover. A systematic processing pipeline is developed to derive credible reflectance spectra, based on which several spectral and mineral indices are calculated to constrain the mafic mineralogy. The mafic components in the soils and boulder around CE-4 landing site are concluded as clinopyroxene-bearing with intermediate composition and probably dominated by pigeonite although the possibility of mixing orthopyroxen(OPX) and calcic clinopyroxene(CPX) also exists. These mineralogical results are more consistent with a petrogenesis that the CE-4 regolith and rock fragment are derived from rapid-cooling magmatic systems and we interpret that the materials at the CE-4 landing site ejected from Finsen crater are probably recrystallized from impact melt settings.

关键词： Chang’e-4 visible and near-infrared spectroscopy mineralogy impact melt the Moon

Establishment of a comprehensive indicator to nondestructively analyze watermelon quality at different ripening stages

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Journal of Innovative Optical Health Sciences 2014年第4期7卷 1-11页

作者： Shuye Qi Shuhui Song Shengnan Jiang Yingrui Chen Wu Li Donghai Han College of Food Science and Nutritional Engineering China Agricultural University 17 Qinghua East Road Haidian District BeijingP.R.China National Engineering Research Center for Vegetables 50 Zhanghua Street Haidian District BeijingP.R.China

Two nondestructive methods based on visible and near-infrared(VIS-NIR)spectroscopy and X-ray image have been used for the evaluation of watermelon *** prediction perform-ance based on partial least squares(PLS)by diffuse transmittance measurement(500-1010 nm)was evaluated for_chemical quality attributes SSC(Rc=0.903;RMSEC=0.572%Brix;Rp=0.862;RMSEP=0.717%Brix;RPD=1.83),lycopene(Rc=0.845;RMSEC=0.266 mg/100 gFW;Rp=0.751;RMSEP=0.439 mg/100 gFW;RPD=1.13)and moisture(Rc=0.917;RMSEC=0.280%;Rp=0.937;RMSEP=0.276%;RPD=2.79).The X-ray calibration linearequations developed by extracting the appropriate gray threshold were sufficiently precise forvolume(R?=0.986)and weight(R?=0.993).In order to optimize prediction model of water-melon quality in growth period,multivariate multi-block technique factor analysis enabled in-tegration of these traits:chemical information is related to physical *** component analysis to extract common factors and varimax with Kaiser normalizationto improve explanatory,the comprehensive indicator based on variances was established *** with Rc=0.94,RMSEC=0.244,Rp=0.93,RMSEP=0.344 and RPD=*** of these models indicates that the comprehensive indicator determined only by portable VIS-NIR spectrometer appears as a suitable method for appraising watermelon qualitynondestructively on the plant at diferent ripen *** method contributes to infer the picking date of watermelon with higher accuracy and bigger economic benefits than that byexperience.

关键词： visible and near-infrared spectroscopy X-ray imaging maturity process factoranalysis comprehensive indicator.

Application of swarm intelligence algorithms to the characteristic wavelength selection of soil moisture content

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International Journal of Agricultural and Biological Engineering 2021年第6期14卷 153-161页

作者： Dongxing Zhang Jiang Liu Li Yang Tao Cui Xiantao He Tiancheng Yu Abdalla N.O.Kheiry College of Engineering China Agricultural UniversityBeijing 100083China The Soil-Machine-Plant key laboratory of the Ministry of Agriculture of China Beijing 100083China Department of Agricultural Engineering College of Agricultural StudiesSudan University of Science and TechnologyKhartoum 999129Sudan

Swarm intelligence algorithms own superior performance in solving high-dimensional and multi-objective optimization *** application of the swarm intelligence algorithms to visible and near-infrared(VIS-NIR)spectral analysis of soil moisture can contribute to the optimization of the soil moisture prediction model and the development of the real-time soil moisture *** this study,a high-resolution spectrometer was used to obtain spectral data of different levels of soil moisture which were manually *** Forest algorithm(iForest)was used to eliminate outliers from the *** on the root mean square error of prediction RMSEP of Back Propagation Neural Network(BPNN)model results,a series of new swarm intelligence algorithms,including Manta Ray Foraging Optimization(MRFO),Slime Mould Algorithm(SMA),etc.,were used to select the characteristic wavelengths of soil *** analysis results showed that MRFO owned the best performance if only from the predictive capability perspective and SMA had a better performance when considering the proportion of the selecting wavelengths and the results of the model *** comparing and analyzing the modeling results of traditional intelligence algorithms Genetic Algorithm(GA)and Particle Swarm Optimization(PSO),it was found that the new swarm intelligence had a better performance in selecting the characteristic wavelengths of soil *** the results of all intelligence algorithms used,soil moisture sensitive wavelengths were selected as 490 nm,513 nm,543 nm,900 nm and 926 nm,which provide the basis for the design of real-time soil moisture sensor based on VIS-NIR.

关键词： soil moisture content swarm intelligence characteristic wavelength selection application visible and near-infrared spectroscopy

visible and near-infrared Spectroscopic Discriminant Analysis Applied to Identification of Soy Sauce Adulteration

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American Journal of Analytical Chemistry 2022年第2期13卷 51-62页

作者： Chunli Fu Jiemei Chen Lifang Fang Tao Pan Department of Biological Engineering Jinan University Guangzhou China Guangdong Langtao Science and Technology Co. Ltd. Dongguan China Department of Optoelectronic Engineering Jinan University Guangzhou China

The identification of soy sauce adulteration can avoid fraud, and protect the rights and interests of producers and consumers. Based on two measurement models (1 mm, 10 mm), the visible and near-infrared (Vis-NIR) spectroscopy combined with standard normal variate-partial least squares-discriminant analysis (SNV-PLS-DA) was used to establish the discriminant analysis models for adulterated and brewed soy sauces. Chubang soy sauce was selected as an identification brand (negative, 70). The adulteration samples (positive, 72) were prepared by mixing Chubang soy sauce and blended soy sauce with different adulteration rates. Among them, the “blended soy sauce” sample was concocted of salt water (NaCl), monosodium glutamate (C5H10NNaO5) and caramel color (C6H8O3). The rigorous calibration-prediction-validation sample design was adopted. For the case of 1 mm, five waveband models (visible, short-NIR, long-NIR, whole NIR and whole scanning regions) were established respectively;in the case of 10 mm, three waveband models (visible, short-NIR and visible-short-NIR regions) for unsaturated absorption were also established respectively. In independent validation, the models of all wavebands in the cases of 1 mm and 10 mm have achieved good discrimination effects. For the case of 1 mm, the visible model achieved the optimal validation effect, the validation recognition-accuracy rate (RARV) was 99.6%;while in the case of 10 mm, both the visible and visible-short-NIR models achieved the optimal validation effect (RARV = 100%). The detection method does not require reagents and is fast and simple, which is easy to promote the application. The results can provide valuable reference for designing small dedicated spectrometers with different measurement modals and different spectral regions.

关键词： visible and near-infrared spectroscopy Soy Sauce Adulteration Identification Partial Least Squares-Discriminant Analysis Standard Normal Variate

Spectral Pretreatment and Wavelength Selection for Soluble Solids Content in Gannan Navel Orange

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Spectral Pretreatment and Wavelength Selection for Soluble S...