Near Infrared Spectroscopy (NIRS) Model-Based Prediction for Protein Content in Cowpea

Cowpea (Vigna unguiculata L. Walp) is a multi-purpose legume with high quality protein for human consumption and livestock. The objective of this work was to develop near-infrared spectroscopy (NIRS) prediction models to estimate protein content in cowpea. A total of 116 cowpea breeding lines with a wide range of protein contents (19.28 % to 32.04%) were selected to build the model using whole seed and ground seed samples. Partial least-squares discriminant analysis (PLS-DA) regression technique with different pre-treatments (derivatives, standard normal variate, and multiplicative scatter correction) were carried out to develop the protein prediction model. Results showed: 1) spectral plots of both the whole seed and ground seed showed higher spectral scatter at higher wavelengths (>1450 nm), 2) data pre-processing affects prediction accuracy for bot whole seed and ground seed samples, 3) prediction using ground seed samples (0.64 R2 0.85) is better than the whole seed (0.33 R2 0.78), and 4) the data pre-processing second derivative with standard normal variate has the best prediction (R2_whole seed = 0.78, R2_ground seed = 0.85). The results will be of interest in cowpea breeding programs aimed at improving total seed protein content.

miR⁃138⁃5p靶向Nir1调控胶质瘤细胞的侵袭

目的 探讨miR-138-5p与PYK2 N端结构域相互作用受体1(PYK2 N-terminal domain-interacting receptor 1,Nir1)之间的关系并判断其是否通过与Nir1结合影响胶质瘤的侵袭。方法 比较不同胶质瘤细胞系中miR-138-5p表达水平及其对胶质瘤细胞U251和H4中Nir1蛋白的影响、转染后胶质瘤细胞侵袭能力,检测miR-138-5p能否与Nir1靶向结合。结果 低侵袭人胶质瘤H4细胞中miR-138-5p的水平显著高于高侵袭性的胶质瘤U251、LN229和U87细胞(P<0.05);在U251、H4细胞中,miR-138-5p过表达组Nir1蛋白表达量较其对照组(miR-negative control,miR-NC)降低;miR-138-5p抑制组中Nir1蛋白表达量较其对照组(inhibitor NC)升高。然而,miR-138-5p过表达组中Nir1的mRNA水平较其对照组无明显改变(P>0.05)。miR-138-5p过表达组穿过基底膜小孔的U251、H4细胞数明显少于其对照组(P<0.05)。miR-138-5p过表达显著降低Nir1-3’-UTR的荧光素酶活性。结论 胶质瘤细胞中miR-138-5p与Nir1结合,可通过降低Nir1的翻译、减少Nir1蛋白的表达抑制胶质瘤细胞的侵袭能力。

Noninvasive Detection of Cerebral Blood Flow and Blood Oxygen Based on Inductive Sensing Technology and Near Infrared Spectroscopy

The synchronous monitoring of cerebral blood flow and blood oxygen levels plays a pivotal role in the prevention,diagnosis,and treatment of cerebrovascular diseases.This study introduces a novel noninvasive device utilizing inductive sensing and near-infrared spectroscopy technology to facilitate simultaneous monitoring of cerebral blood flow and blood oxygen levels.The device consists of modules for cerebral blood flow monitoring,cerebral blood oxygen monitoring,control,communication,and a host machine.Through experiments conducted on healthy subjects,it was confirmed that the device can effectively achieve synchronous monitoring and recording of cerebral blood flow and blood oxygen signals.The results demonstrate the device’s capability to accurately measure these signals simultaneously.This technology enables dynamic monitoring of cerebral blood flow and blood oxygen signals with potential clinical applications in preventing,diagnosing,treating cerebrovascular diseases while reducing their associated harm.

复合垂直流人工湿地基质理化性质对nirS和nirK型反硝化菌多样性的影响

深入研究复合垂直流人工湿地基质理化性质及其对相关脱氮反硝化微生物的影响,可为解析人工湿地污水处理及提高脱氮效率提供理论依据。2020年12月采集贵州喀斯特地区复合垂直流人工湿地4口池(一级垂直流下行池、一级垂直流上行池、二级垂直流下行池、二级垂直流上行池)的基质样品,用Illumina高通量测序技术获得反硝化功能基因序列,分析其种群组成和多样性特征,并采用冗余分析揭示反硝化菌群落与基质理化性质之间的相关性。结果表明,复合垂直流人工湿地中4口池的基质理化性质存在显著差异;pH在4口池中均呈中性,溶解氧(DO)呈先下降后升高趋势,下行池的基质电导率(EC)均比上行池要高;总氮(TN)、总磷(TP)含量随着人工湿地梯级呈显著下降趋势,未出现厌氧现象;NO_(3)^(-)-N和NH_(4)^(+)-N含量在二级垂直流下行池中大量积累并达到峰值。在多样性分析中,nirS、nirK型反硝化菌丰度随着人工湿地梯级呈先降低后升高的趋势,多样性随人工湿地级数逐渐降低,且下行池丰度多样性显著高于上行池。基质中nirS型反硝化菌共5门9属,nirS型为6门14属,变形菌门是nirS、nirK型反硝化菌群的共同优势菌门,相对丰度为55.36%~65.72%、30.06%~45.66%。nirS、nirK型反硝化菌共有OTUs数分别为392、245,并与反硝化菌群OTUs数目趋势一致,从多角度表明nirS型反硝化菌群丰度明显高于nirK型,且共有OTUs占有率高达41.6%和41.7%,表明各级池中反硝化菌群相似度较高。冗余分析表明基质中nirS和nirK反硝化菌群的构建主要受pH、NH4+-N、DO、TP、TN影响,且nirS型对pH、nirK型对NH4+-N的响应更为强烈。

Millet Origin Identification Model Based on Near-infrared Spectroscopy

[Objectives]This study was conducted to clarify the difference of millet from different producing areas in near-infrared spectroscopy(NIRS)modeling.[Methods]Millet samples from six different regions were collected for NIRS analysis,and an origin identification model based on BP neural network was established.The competitive adaptive reweighted sampling(CARS)algorithm was used to extract characteristic wavelength variables,and a CARS-BP model was established on this basis.Finally,the CARS-BP model was compared with support vector machine(SVM),partial least squares discriminant analysis(PLS)and KNN models.[Results]The characteristic wavelengths were extracted by CARS,and the number of variables was reduced from 1845 to 130.The discrimination accuracy of the CARS-BP model for the samples from six producing areas reached 98.1%,which was better than SVM,PSL and KNN models.[Conclusions]NIRS can quickly and accurately identify the origin of millet,providing a new method and way for the origin identification and quality evaluation of millet.

Near-infrared spectroscopy(NIRS) evaluation and regional analysis of Chinese faba bean(Vicia faba L.)

To analyze the nutritional composition of faba bean(Vicia faba L.) seed, estimation models were developed for protein, starch, oil, and total polyphenol using near infrared spectroscopy(NIRS). Two hundred and forty-four samples from twelve producing regions were measured in both milled powder and intact seed forms. Partial least squares(PLS) regression was applied for model development. The model based on ground seed powder was generally superior to that based on the intact seed. The optimal seed powder-based models for protein, starch, and total polyphenol had coefficients of correlation(r2) of 0.97, 0.93 and 0.89, respectively. The relationship between nutrient contents and twelve producing areas was determined by two-step cluster analysis. Three distinct groupings were obtained with region-constituent features, i.e., Group 1 of high oil, Group 2 of high protein, and Group 3 of high starch as well as total polyphenol. The clustering accuracy was 79.5%. Moreover, the nutrition contents were affected by seeding date, longitude, latitude, and altitude of plant location. Cluster analysis revealed that the differences in the seed were strongly influenced by geographical factors.

Prediction of Fiber Composition and Silicificationfor Rice Straw with Near Infrared ReflectanceSpectroscopy (NIRS) Technique

The silicification of rice straw is a factor that affects the grain production and straw nutritive quality. The procedure of chemical analysis for silicon in straw is, however, time and labor consuming, and slightly poor in accuracy. The study has attempted to apply near infrared reflectance spectroscopy (NIRS) technique as an advanced alternative to predict the fiber composition and silicification in rice straw. Ninety-two samples from different seasons and varieties were collected over the Fujian Province. Their chemical analyses were carried on the aspects of hemicellulose, cellulose, lignin, extractable and non-extractable silicon, and the results were used as a database for NIRS analyses. The prediction model was developed through modified partial least square regression (MPLS) for a calibration program. The factors that may affect the calibration, cross-validation and the prediction for the application of NIRS on rice straw were also discussed.

NIRS快速测定管花肉苁蓉提取物中四种苯乙醇苷的含量

建立管花肉苁蓉提取物中四种苯乙醇苷(松果菊苷、管花苷A、毛蕊花糖苷、异毛蕊花糖苷)的近红外光谱定量分析模型,以快速评价管花肉苁蓉提取物的质量。以HPLC法测定管花肉苁蓉提取物中四种苯乙醇苷的含量作为参考值,采用近红外光谱法(NIRS)结合偏最小二乘法(PLS)建立管花肉苁蓉提取物中四种苯乙醇苷成分的定量分析模型,并对模型进行验证。结果表明:松果菊苷、管花苷A、毛蕊花糖苷、异毛蕊花糖苷定量分析模型的最佳光谱预处理方法分别为:SNV+SG+FD、MSC+FD、SNV+SD、MSC+SD,校正相关系数(R2c)分别为0.9937、0.9945、0.9954、0.9948;预测相关系数(R2p)分别为0.9094、0.9222、0.8812、0.8529;校正均方根偏差(RMSEC)分别为0.3681、0.0376、0.1944、0.0524;预测均方根偏差(RMSEP)分别为1.426、0.1448、1.002、0.2821。近红外模型预测值与真实值(HPLC测定)无显著性差异。该方法操作简便、准确、分析速度快、无污染,可用于管花肉苁蓉提取物中四种苯乙醇苷含量的快速测定。

NIRS-XRF联用的煤炭发热量高稳定检测

实时获知煤炭发热量对于及时调整电站锅炉风粉配比和提高煤炭燃烧效率具有重要意义,为了实现电力生产中发热量的稳定快速检测,提出了一种近红外光谱(Near Infrared Spectroscopy, NIRS)与X射线荧光光谱(X-ray Fluorescence, XRF)联用的煤炭发热量高稳定检测方法,它结合了NIRS能高稳定检测煤中与发热量正相关的有机基团的优势与XRF能高稳定检测与发热量负相关的成灰元素的特点,大大提高了对煤炭发热量的测量重复性。在光谱预处理中,先将两套光谱融合作为偏最小二乘回归的输入变量进行全谱初步建模,依据回归系数选择NIRS光谱中的有效波段,再将它与XRF光谱中的成灰元素谱线一并融合进行归一化处理。建模时将预处理后的融合光谱数据作为输入变量,利用偏最小二乘回归对煤炭发热量进行建模。实验结果表明,NIRS-XRF联用方法对定标集煤样发热量预测的线性相关度系数(R^(2))为0.995,对验证集煤样发热量预测的最小均方根误差、平均相对误差和标准偏差分别为0.24 MJ/kg,0.61%和0.05 MJ/kg,测量重复性满足小于0.12 MJ/kg的国家标准。NIRS-XRF联用的煤炭发热量高稳定检测方法有望推广应用于火力发电、煤化工、冶金、水泥和焦化等“高碳”行业,助力我国按期实现碳中和目标。

Functional Nonparametric Predictions in Food Industry Using Near-Infrared Spectroscopy Measurement

Functional statistics is a new technique for dealing with data thatcan be viewed as curves or images. Parallel to this approach, the Near-InfraredReflectance (NIR) spectroscopymethodology has been used in modern chemistryas a rapid, low-cost, and exact means of assessing an object’s chemicalproperties. In this research, we investigate the quality of corn and cookiedough by analyzing the spectroscopic technique using certain cutting-edgestatistical models. By analyzing spectral data and applying functional modelsto it, we could predict the chemical components of corn and cookie dough.Kernel Functional Classical Estimation (KFCE), Kernel Functional QuantileEstimation (KFQE), Kernel Functional Expectile Estimation (KFEE),Semi-Partial Linear Functional Classical Estimation (SPLFCE), Semi-PartialLinear Functional Quantile Estimation (SPLFQE), and Semi-Partial LinearFunctional Expectile Estimation (SPLFEE) are models used to accuratelyestimate the different quantities present in Corn and Cookie dough. Theselection of these functional models is based on their ability to constructa forecast region with a high level of confidence. We demonstrate that theconsidered models outperform traditional models such as the partial leastsquaresregression and the principal component regression in terms of predictionaccuracy. Furthermore, we show that the proposed models are morerobust than competing models such as SPLFQE and SPLFEE in the sensethat data heterogeneity has no effect on their efficiency.

Determination of nutritive constituents in Chinese cabbage by near infrared spectroscopy(NIRS)

This paper describes using NIRS to determine CP,NDF,RS,VC in Chinese cabbage (Brassica campestris L. ssp pekinensis). Two hundred and forty-two samples of Chinese cabbage were collected from the main producing areas in China for calibration and prediction of the four constituents above. The results of calibration showed that the multiple correlation coefficients between NIRS and chemical methods were 0. 9958,0. 9852,0. 9821 and 0. 9814,and the standard errors were 0. 398,0. 134,0. 098 and 0. 51 ,respectively. The correlation coefficients of prediction were 0. 994,0. 978,0. 974 and 0. 981 ,and standard errors were 0. 353,0. 127, 0. 108 and 0. 548,respectively. These results indicate that NIRS can be used to determine the four constituents of Chinese cabbage as accurately as chemical methods.

WIRELESS DISTRIBUTED ACQUISITION SYSTEM FOR NEAR INFRARED SPECTROSCOPY-WDA-NIRS

The wireless distributed acquisition system for near infrared spectrosecopy(WDA-NIRS)is a portable,ultra-compact,contimuous wave(CW)NIRS system.Its main advantage is that it allows continuous synchronized multi-site hemodynarnic monitoring.The WDA-NIRS syster calculates online changes in hemoglobin concentration based on modifed Beer-Lambert law and the tissue oxy genation index based on the spatial resolved spectroscopy method.It consists of up to seven signal acquisition units,sufficiently small to be easily attached to any part of the body.These units are remotely synchronized by a PC base station for independent acquisition of NIRS signals.Each acquisition module can be freely adapted to individual requirements such as local skin properties and the microcirculation of interest,e.g,different muscles,brain,skin,etc.For this purpose,the light emitted by each LED can be individually,interactively or automatically adjusted to local needs.Furthermore,the user can freely create an emitter time multiplexing protocol and choose the detector sensitivity most suitable to a particular situation.The potential diagnostic value of this advanced device is demonstrated by three typical applications.

Investigation of Prefrontal Cortex Activity in University Students with Presenteeism: A Near-Infrared Spectroscopy (NIRS) Study

Presenteeism refers to impaired performance attributed to attending work with health problems. There has been no study examining the state of presenteeism with objective measures. We compared cerebral hemodynamic changes, measured by near-infrared spectroscopy (NIRS), during neuropsychological tests conducted by university students with presenteeism and healthy controls. Twenty-two university students participated in the study;11 of them with impaired performance caused by mental health problem were allocated to the presenteeism group and 11 without health problems to the control group. Presenteeism was assessed by the Presenteeism Scale for Students. To evoke hemodynamics changes, the participants completed a Word Fluency Test (WFT) and a Trail Making Test (TMT). The NIRS probes were located over the bilateral prefrontal area. Students with presenteeism had significantly higher incidences of depression than controls. However, there was no significant difference in behavioral performance examinations between the two groups. With regard to hemodynamics changes, the repeated measures analysis of covariance of the NIRS signals revealed significant interactions between group and task activation. Although we observed a significant increase in oxygenated hemoglobin concentration during the WFT among controls (simple main effect;left channel, F(1, 19) = 27.34, P F(1, 19) = 22.05, P < 0.001), no changes were found in students with presenteeism during either the WFT (simple main effect;left channel, F(1, 19) = 0.12, P F(1, 19) = 0.08, P t = ﹣0.94, P with Bonferroni correction = 0.745;right channel, t = ﹣2.19, P with Bonferroni correction < 0.113). This is the first study to reveal differences in activity in the cerebral cortex associated with presenteeism. The fact that students with presenteeism have prefrontal dysfunction might reinforce the concept of presenteeism.

RAPID DETERMINATION OF PROTEIN IN MILLET BY FOURIER TRANSFORM NEAR-INFRARED(FTNIR)DIFFUSE REFLECTANCE SPECTROSCOPY

In this paper,the Fourier transform near-infrared(FTNIR)diffuse reflectance spectroscopy is applied for the rapid determination of protein in millet.The partial least-squares(PLS)regression is successfully used as an effective multivariate calibration technique.The calibration set is composed of 20 standard millet samples that the protein contents were determined by the traditional Kjeldahl method.The optimal model dimension is found to be 5 by cross-validation.22 millet samples were determined by the proposed FTNIR-PLS method.The correlation coefficient between the concentration values obtained by the FTNIR-PLS method and the traditional Kjeldahl method is 0.9805.The standard error of prediction(SEP)is 0.28% and the mean recovery is 100.2%.The proposed method has been successfully applied for the routine analysis of protein in about 10,000 grain samples.

Correlation of prefrontal activity measured by near-infrared spectroscopy (NIRS) with mood, BDNF genotype and serum BDNF level in healthy individuals

Depression has been known to reduce the prefrontal activity associated with the execution of certain cognitive tasks, although whether a temporarily depressed or anxious mood in healthy individuals affects the prefrontal blood oxygen level during cognitive tasks is unknown. Combining the measurement of prefrontal activity with near-infrared spectroscopy (NIRS) and the two cognitive tasks, namely the letter version of the verbal fluency test (VFT-l) and the Stroop test, we measured the effect of a depressed or anxious mood and gender on the changes in the prefrontal oxygenated hemoglobin (Oxy-Hb) levels during those cognitive tests in healthy individuals. Depressed mood or anxious mood was assessed by the Hospital Anxiety and Depression Scale (HADS). Thereby we aimed to explore the possibility of NIRS measurement for detecting the early subclinical manifestation of major depression. Moreover, we examined the possible relationships between prefrontal activation and the functional Val66Met polymorphisms of the brain derived neurotropic factor (BDNF) gene and serum BDNF level. As a result, the increased prefrontal Oxy-Hb levels during cognitive tasks were significantly correlated with the severity of depressed mood in males. The course of the prefrontal Oxy-Hb increase was different depending on the cognitive tasks, i.e., the VFT-l or the Stroop test, in both genders. Correlations of BDNF genotype and serum BDNF level with the prefrontal Oxy-Hb levels during those cognitive tasks were negative. Our results suggest that the early subclinical manifestation of depressed mood in males might be detected by the NIRS measurement, which is not correlated with the individual properties of BDNF.

Simulation and Modelling of near Infrared Spectroscopy (NIRS) as Brain Monitor

Near infrared spectroscopy (NIRS) is a method for non-invasive monitoring of cerebral oxygenation and haemodynamics. Different devices provide information on changes of oxygenated (HbO2) and deoxygenated haemoglobin (HHb), oxidized cytochrome aa3 (CytOx) or regional oxygen saturation (rSO2). NIRS has been used during adult and paediatric cardiac surgery.

Study on the secondary structure and hydration effect of human serum albumin under acidic pH and ethanol perturbation with IR/NIR spectroscopy

Human serum albumin(HSA)is the most abundant protein in plasma and plays an essential physiological role in the human body.Ethanol precipitation is the most widely used way to obtain HSA,and pH and ethanol are crucial factors affecting the process.In this study,infrared(IR)spectroscopy and near-infrared(NIR)spectroscopy in combination with chemometrics were used to investigate the changes in the secondary structure and hydration of HSA at acidic pH(5.6-3.2)and isoelectric pH when ethanol concentration was varied from 0%to 40%as a perturbation.IR spectroscopy combined with the two-dimensional correlation spectroscopy(2DCOS)analysis for acid pH system proved that the secondary structure of HSA changed significantly when pH was around 4.5.What's more,the IR spectroscopy and 2DCOS analysis showed different secondary structure forms under different ethanol concentrations at the isoelectric pH.For the hydration effect analysis,NIR spectroscopy combined with the McCabe-Fisher method and aquaphotomics showed that the free hydrogen-bonded water fluctuates dynamically,with ethanol at 0-20%enhancing the hydrogen-bonded water clusters,while weak hydrogen-bonded water clusters were formed when the ethanol concentration increased continuously from 20%to 30%.These measurements provide new insights into the structural changes and changes in the hydration behavior of HSA,revealing the dynamic process of protein purification,and providing a theoretical basis for the selection of HSA alcoholic precipitation process parameters,as well as for further studies of complex biological systems.

Near-infrared spectroscopy method for rapid proximate quantitative analysis of nutrient composition in Pacific oyster Crassostrea gigas

Glycogen,amino acids,fatty acids,and other nutrient components affect the flavor and nutritional quality of oysters.Methods based on near-infrared reflectance spectroscopy(NIRS)were developed to rapidly and proximately determine the nutrient content of the Pacific oyster Crassostreagigas.Samples of C.gigas from 19 costal sites were freeze-dried,ground,and scanned for spectral data collection using a Fourier transform NIR spectrometer(Thermo Fisher Scientific).NIRS models of glycogen and other nutrients were established using partial least squares,multiplication scattering correction first-order derivation,and Norris smoothing.The R_(C) values of the glycogen,fatty acids,amino acids,and taurine NIRS models were 0.9678,0.9312,0.9132,and 0.8928,respectively,and the residual prediction deviation(RPD)values of these components were 3.15,2.16,3.11,and 1.59,respectively,indicating a high correlation between the predicted and observed values,and that the models can be used in practice.The models were used to evaluate the nutrient compositions of 1278 oyster samples.Glycogen content was found to be positively correlated with fatty acids and negatively correlated with amino acids.The glycogen,amino acid,and taurine levels of C.gigas cultured in the subtidal and intertidal zones were also significantly different.This study suggests that C.gigas NIRS models can be a cost-effective alternative to traditional methods for the rapid and proximate analysis of various slaughter traits and may also contribute to future genetic and breeding-related studies in Pacific oysters.

Effect of the Continuum Removal in Predicting Soil Organic Carbon with Near Infrared Spectroscopy (NIRS) in the Senegal Sahelian Soils

Spectroscopy plays a major role in the access of the analytical parameters of the soil. It tends to substitute the conventional laboratory analysis because hyperspectral data were least expensive and easier to obtain. The objective of this study was to evaluate the effect of the continuum removal (CR) in the validation of the accurate prediction model of the soil properties with Vis-NIR spectroscopy data. Few studies using Vis-NIR reflectance spectroscopy have well focused the calculation of the CR method;its effect in the calibration of the accurate models was also not well emphasized. In this study, we used the remote sensing software ENVI 4.7 to compute the CR function where the value of the continuum for each sample and for each spectral wavelength was obtained by dividing the reflectance values of the full spectrum (FS) with those of the continuum curve (CC). The partial least square regression (PLSR) model was applied in the spectral data from the soil of the Senegal Sahelian region. It was calibrated with both data from the full spectrum (FS) and those obtained after the application of the continuum removal. With the application of the CR, ultraviolet wavelengths (350 - 429 nm) and those of near infrared (2491 - 2500 nm) were removed from the explanatory variables of PLSR model. With the FS, all wavelengths between 350 and 2500 nm were taken into account in predicting soil properties. Our findings show a positive effect of the application of CR in the estimation of soil organic carbon. In calibration, the R2 increased up to 10% with the continuum removal in the model of 12 components (CP). In terms of validation, it’s the 15-component model which is the most accurate with the same range in calibration between the FS and the CR. The lowest RMSE ranged from 0.04 with the FS to 0.03 with the application of the CR in calibration and validation. These results show that the interest of this study as soil organic carbon is recognized as a key indicator of fertility of the soil in Sahelian-African regions. For future studies, it’s important to apply the model of neural networks to better evaluate the effect of continuum removal in predicting soil properties from the spectral data and other methods of preprocessing like the multiplicative scatter correction (msc).

近红外光谱技术在食用菌品质检测方面的应用研究进展

食用菌是一类高蛋白、低脂肪且兼具药用价值的大型真菌,因其多营养、鲜风味、低热量、多功效等特点而成为餐桌上常备食材之一。随着消费理念不断转变,食用菌的高品质和高营养需求成为必然。近红外光谱(near-infrared spectroscopy,NIRS)技术因其快捷、无损、多组分同时检测、绿色无污染等优点,被广泛应用于食用菌品质检测研究。本文全面归纳综述了近5年来NIRS技术结合化学计量学方法在食用菌理化组分、活性成分、品种鉴别、产地溯源、病原菌污染、掺假识别等及其他方面的研究及应用进展,同时提出了NIRS技术在食用菌品质检测应用方面的发展策略,以期为完善NIRS技术检测食用菌理论、研发专用食用菌检测设备提供方法参考和思路借鉴。