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.

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.

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.

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.

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.

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。

Electronic structure and infrared spectrum of a W_n C^(0,±) (n = 1-6) cluster

WnC0＇± （n= 1-6） clusters are investigated by using the density functional theory （DFT） at the B3LYP/LANL2DZ level. We find that the neutral, anionic and cationic ground state structures are similar within the same size, and constituted by substituting a C atom for one W atom in the structures of Wn＋1 clusters. The natural bond orbital （NBO） charge analyses indicate that the direction of electron transfer is from the W atom to the 2p orbital of the C atom. In addition, the calculated infrared spectra of the WnC0＇± （n= 2-6） clusters manifest that the vibrational frequencies of neutral, anionic and cationic clusters are similar in a range of 80 cm-1-864 cm-1. The high frequency, strong peak modes are found to be an almost stretched deformation of the carbide atom. Finally, the polarizabilities of WnC0＇± （n= 1-6） clusters are also discussed.

MODIFICATION OF ABSORPTION SPECTRUM OF GaAs/AlGaAs QUANTUM WELL INFRARED PHOTODETECTOR BY POSTGROWTH ADJUSTMENT

Quantum well intermixing techniques modify the geometric shape of quantum wells to allow postgrowth adjustments.The tuning effect on the optical response property of a GaAs/AlGaAs quantum well infrared photodetector(QWIP) induced by the interdifussion of Al atoms was studied theoretically.By assuming an improvement of the heterointerface quality and an enhanced Al interdiffusion caused by postgrowth intermixings,the photoluminescence spectrum shows a blue-shifted,narrower and enhanced photoluminescence peak.The infrared optical absorption spectrum also shows the expected redshift of the response wavelength.However,the variation in the absorption peak intensity depends on the boundary conditions of the photo generated carriers.For high-quality QWIP samples,the mean free path of photocarriers is long so that the photocarriers are largely coherent when they transport across quantum wells.In this case,the enhanced Al interdiffusion can significantly degrade the infrared absorption property of the QWIP.Special effects are therefore needed to maintain and/or improve the optical properties of the QWIP device during postgrowth treatments.

Evaluation of Expression Recognition Function in Autism Spectrum Disorder Using Near-Infrared Spectroscopy

One of the characteristics of Autism Spectrum Disorder (ASD) is social disorder. The specificity of facial and expression recognition for people with ASD is gathering attention as a factor of this social disorder. The study examined the hemodynamic activities in the prefrontal cortex using near-infrared spectroscopy (NIRS) when a person with ASD performed an expression recognition task. The subjects were twenty males (18 - 22 years old) with ASD and without intellectual disabilities. Forty-five healthy males matched for age and sex were included as a control group. In both groups, the degree of autistic tendencies was evaluated using the Autism-Spectrum Quotient (AQ). Using eight standard emotional expressions of Japanese people, two expression recognition tasks were set. An NIRS was used to measure the prefrontal cortex blood mobilization during the expression-processing process. The AQ was significantly higher in the ASD group, while the rate of overall correct expression response was significantly lower (p &rho;= &minus;0.40 p < 0.001). In the automatic expression-processing task, no activation in the prefrontal cortex was found in either the ASD or the control group. In the conscious expression-processing task, the activation of the left and right lateral prefrontal cortex was weaker in the ASD group compared to the control group. Unlike in the control group, a mild activation of posterior prefrontal cortex was found in the ASD group. The expression-processing process of the ASD group was found to be different from that of the control group. NIRS was effective in detecting a brain function disorder in people with ASD during an expression-processing process.

Detection of Chlorpyrifos Residues in Akesu Red Fuji Apple based on Near Infrared Spectrum

[Objective] The paper was to explore a method for detecting chlorpyrifos residues in red Fuji apple. [Method] The original spectral data of apple samples sprayed with different volume fractions of chlorpyrifos were collected using near infrared spectrometer at the band of 4 000-10 000 cm^（-1）. The original spectra were pre-treated by a variety of methods, and partial least squares（PLS） model was established for predictive analysis. [Result] Near infrared spectrum showed sensitivity to apple samples sprayed with different volume fractions of chlorpyrifos, but had low precision on pesticide-free samples. Data of blank control group were further eliminated for modeling prediction. The results showed that the results were the best when pre-treated with first derivative（FD）： R=0.987 9; the square error of prediction（SEP） was 0.173 6; the root-mean-square error of cross-validation（RMSECV） was 0.120 5; and the precision was 0.923 4. [Conclusion] Near infrared spectrum can better predict chlorpyrifos residue, providing a new method for detecting chlorpyrifos residues in Akesu red Fuji apple.

Preparation of Ultrafine SiO2 Powder from Rice Husk and Properties of Its Infrared Spectrum

This paper discussed impact of temperature on the size distribution in preparing ultrafine silica from rice husk.The samples prepared were analyzed with infrared spectrum,and the relation between the particle size and intensity of characteristic absorption peak of IR at center around 1 100 cm-1 was disscussed with the baseline method.Results show that when the temperature is 650 ℃ and roasting time is 11 h,at optimal reaction conditions,the size distribution of the ultrafine silica powder prepared is relatively concentrated,and the average particle size is 199.5 nm.Moreover,the characteristic absorption band of IR is broadening gradually along with particle size decreasing.

Signature of symmetry of laterally coupled quantum dots in far-infrared spectrum

We study the effect of structure asymmetry on the energy spectrum and the far-infrared spectrum （FIR） of a lateral coupled quantum dot. The calculated spectrum shows that the parity break of coupled quantum dot results in more coherent superpositions in the low-lying states and exhibits unique anti-crossing in the two-electron FIR spectrum modulated by a magnetic field. We also find that the Coulomb correlation effect can make the FIR spectrum of coupled quantum dot without strict parity deviate greatly from Kohn theorem, which is just contrary to the symmetric case. Our results therefore suggest that FIR spectrum may be used to determine the symmetry of coupled quantum dot and to evaluate the degree of Coulomb interaction.

玉米秸秆组分近红外漫反射光谱(NIRS)测定方法的建立

玉米秸秆是我国产量最大的秸秆生物质资源，但目前还没有快速高效的组分分析方法，本研究利用傅里叶变换近红外漫反射光谱（NIRS）技术，采用偏最小二乘法（PLS），在国内首次建立了NIRS测定玉米秸秆中灰分、半纤维素、纤维素、Klason木质素、酸不溶灰分和水分含量的校正模型，该模型稳定，适合不同地区、不同品种的玉米秸秆及其不同部位。实验结果表明，采用一阶导数＋KarlNorris滤波预处理，谱区在4100-7500cm^-1，能得到理想的预测模型。该模型对玉米秸秆各组分的交叉验证均方差（RMSECV）范围为0．0903～1．45，预测误差（RMSEP）范围为0．2569％～2．5819％，预测相关系数≥0．8711。该研究对加速我国秸秆生物质的工业转化具有重要意义。

近红外光谱技术(NIRS)在草地生态学研究中的应用

近红外光谱技术(NIRS)是一种快速、高效、无损的现代检测技术,已经在许多领域广泛应用。文章阐述了NIRS应用于草地生态学研究的意义,介绍了NIRS用于测定牧草营养成分、矿物质、土壤养分含量,分析了牧草混合物的组成、动物对所采食牧草的反应、牧草病虫害抗性等一些复杂特性,以及进行生化标记、同位素鉴别研究。综合这些研究可以看出,NIRS能够作为一种整体研究工具应用于草地生态学的许多研究领域中,可以检测各种常规化学成分、分析草地生态系统的各种动态指标和系统运行的多项整体特性。希望通过本文的总结分析,推动NIRS在中国草地生态学研究中的应用,加速该领域研究手段的现代化。

近红外光谱技术(NIRS)在干草品质检测中的研究与应用

干草品质对动物的生产性能、牧草价值和最终盈利有着最直接的影响,检测干草品质的方法也在不断改进,近红外光谱技术(NIRS)这种快速、高效而无破坏性的现代检测技术已在饲草料中广泛应用。文章阐述了应用NIRS分析干草品质的可行性和高效性,详细介绍了NIRS用于检测牧草营养成分、真菌侵染程度、内生真菌产生的有毒物质以及一些难于用化学方法检测的微量成分等重要指标的研究成果。指出NIRS用于分析干草品质突破了过去常规化学方法的复杂、耗时、成本高等缺陷,是干草品质分析方法的一个重大进步,并期待着NIRS在牧草品质中的应用研究工作继续完善和发展,建立更精确的定标模型以及更系统的分析软件,促进畜牧业的快速发展。

近红外光谱技术(NIRS)在检测牧草霉菌毒素中的应用

具有快速、高效、无损、在线等优势的近红外光谱技术(nearinfrared reflectance spectroscopy technique,NIRS)已经在农业、食品、化工、医学等领域获得广泛应用。牧草在加工贮藏过程中,受多种真菌的侵染,引起霉菌毒素在牧草中积累。霉菌毒素会通过动植物产品进入人畜的食物链,引起人畜中毒。牧草中霉菌毒素的常规检测不但需要粉碎、浸提、层析等繁琐的样品前处理过程,还需要酶联免疫吸附法、高效液相色谱法、溥层色谱法等后续检测过程。通过发展高精度、低检出限的光谱仪器,建立相应霉菌毒素检测的软件技术与校正模型,能够在牧草利用中达到快速准确检测霉菌毒素的含量和性质,从而为牧草的合理加工与利用提供依据,促进NIRS技术在健康畜产品生产领域的应用。

近红外反射光谱法(NIRS)测定棉仁粉中蛋白质和棉酚含量的研究

选用49份不同蛋白质和棉酚含量的陆地棉种质资源和188份陆地棉重组近交系为材料,以多年份、多地点种植收获的种子材料组成原始样品集,分别对棉仁粉中蛋白质含量和棉酚含量进行化学测定,采用改进的偏最小二乘法(Modified PLS)和(2,4,4,1)的数学转换方法建立近红外反射光谱(NIRS)定标模型,以寻找棉籽蛋白质含量和棉酚含量的快速测定方法。结果表明,蛋白质含量的定标决定系数(RSQ=0.933)和交叉检验决定系数(1-VR=0.929)较高,定标标准误差(SEC=0.623)和交互校验标准误差(SECV=0.638)较小,预测模型的建模效果较好,可替代化学分析。棉酚含量预测模型的RSQ,1-VR,SEC和SECV分别为0.836,0.811,0.074和0.079,模型预测效果略差于蛋白质模型,但仍可用于棉仁粉中棉酚含量的测定。

近红外光谱技术(NIRS)在反刍动物营养研究中的应用现状

近红外光谱技术（NIRS）分析样品时以其方便、快捷和准确等诸多优点在动物营养研究中得到了广泛的应用；用NIRS技术预测家畜日粮中有机物消化率时所产生的标准偏差（SECV）在1．6％～2．8％之间，而预测干物质的消化率时所产生的SECV在1．6％～3．5％之间。NIRS能够准确地预测饲料中的化学成分和生物学组分以及反刍家畜十二指肠微生物蛋白的流量，但对于预测饲料在瘤胃降解率的动态特性时与实际相差很大。NIRS技术预测舍饲家畜采食量与体内法得到的结果相似，但在预测放牧家畜采食量时其预测误差为14％左右。上述结果表明，NIRS技术在预测反刍家畜消化代谢、日粮营养评价、采食量等方面已取得了很大的进展，并在反刍动物营养研究领域中有着广阔的应用空间。

糙米蛋白质含量与矿质元素含量的相关分析及NIRS模型的建立

利用162份不同类型水稻种质,采用微量凯氏定氮法测定蛋白质含量,原子吸收分光光度法(atomic absorption spec-trophotometry,AAS)测定Mg、Ca、Fe、Zn、Cu和Mn等6种矿质元素含量,火焰光度法测定K含量,分光光度法测定P含量。对糙米蛋白质与矿质元素、矿质元素间进行相关分析;并利用测定的蛋白质含量的化学值,采用偏最小二乘法(partial leastsquares,PLS)建立糙米蛋白质预测的校正模型。结果表明,糙米矿质元素含量大小顺序为P>K>Mg>Ca>Zn>Fe>Cu>Mn,蛋白质与P、K、Cu和Mn等矿质元素极显著或显著正相关;通过比较光谱预处理方法在不同谱区的处理效果:采用一阶导数预处理、谱区为11995.7～7498.3/cm和6102～4597.7/cm建立校正模型的检验和预测效果最佳,糙米蛋白质的近红外测定值和化学测定值之间有较高的相关性,其校正决定系数为92.89,外部验证决定系数为89.91;筛选到小黑谷、小红米和紫糯米等高蛋白、富矿质营养的种质材料,可作为富营养稻米品种创新的亲本材料;通过利用蛋白质和矿质元素间的相关性,借助近红外分析技术(Near-infrared Reflectance Spectroscopy,NIRS)辅助测定蛋白质含量,并间接选择富矿质营养水稻种质,聚合高蛋白和富2种以上矿质元素,可能是水稻营养品质育种的一条有效途径。

棉籽17种氨基酸含量的NIRS定标模型构建与测定方法研究

选用氨基酸含量差异较大的多年份、多品种、多地点种植的445份棉花种子为材料，分别对其进行近红外光谱扫描。用一阶导数的数学处理（1，4，4，1）、标准正态变换和去趋势（SNV＋D）最佳组合的预处理方法，结合改良的偏最小二乘法（MPLS）构建棉籽17种氨基酸成分的近红外定标模型。定标结果表明，天冬氨酸、苏氨酸、谷氨酸、甘氨酸、丙氨酸、缬氨酸、异亮氨酸、亮氨酸、苯丙氨酸、赖氨酸、组氨酸和精氨酸等12种氨基酸含量的定标模型较好，其RPDc为3．735-7．132，外部检验，上为0．910-0．979，近红外光谱分析完全可以替代化学测定；而丝氨酸、蛋氨酸、酪氨酸和脯氨酸等四种氨基酸的定标模型次之，其RP—Dc为2．205-2．814，外部检验r^2为0．800-0．830，近红外分析技术虽不能完全替代化学测定的结果，但仍可用于大量样品的筛选。半胱氨酸定标方程的RPDc较小（RPDc=1．358），因此，棉籽中半胱氨酸含量不能用近红外分析方法进行检测。