In situ determination of growing stages and harvest time of tomato (Lycopersicon esculentum ) fruits using fiber-optic visible-near-infrared (Vis-NIR) spectroscopy

Nondestructive in situ measurement of tomato fruits is essential to determine growing stages and to assist in automatic picking of fruits. This study evaluates the applicability of visible and near-infrared (Vis-NIR) spectroscopy for in situ determination of growing stages and harvest time of three cultivars of tomato fruits. A mobile fiber-type AgroSpec Vis-NIR spectrophotometer (Tec5 Co., Germany) with a spectral range of 350-2200 nm was used to measure tomato spectra in reflection mode. A new growing stage (GS) index defined as the ratio of the current growing age in days to the on-vine duration before harvest in days was proposed. After dividing spectra into a calibration set (70%) and an independent prediction set (30%), spectra in the calibration set were subjected to a partial least squares regression (PLSR) with leave-one-out cross-validation to establish calibration models relating GS to the spectra of tomato fruits. Separate models were developed for each tomato cultivar and compared with a general model that used combined spectra of all three cultivars. The results show that PLSR based on the new GS is successful and robust in predicting the growing stages and harvest time of tomato fruits. Validation of calibration models on the independent prediction set indicates that successful prediction of GS can be achieved using the three models developed separately for each cultivar with a coefficient of determination (R(2)) of 0.91-0.92, root mean square error of prediction (RMSEP) of 0.081-0.097, and residual prediction deviation (RPD) of 3.29-3.70. General calibration using the combined spectra produces good prediction performance, although less accurate than that for the three individual cultivar models. The analysis of regression coefficient plots resulting from PLSR analysis indicates consistent assignment of important wavelengths for individual cultivar spectra and combined spectra. It is concluded that the Vis-NIR PLSR based on GS index can be adopted successfully for in situ determination of growing stages and harvest time of on-vine tomato fruits, which allows for automatic picking of fruits by a horticultural robot.     

基于近红外光谱分析技术的液态水性油墨印刷品 颜色预测模型

针对印刷品颜色离线检测存在滞后、检测不精准等问题,提出基于近红外光谱分析技术的液态水性油墨印刷品颜色预测模型。用多元散射校正（MSC） 、标准正态变换（SNV）和卷积平滑滤波器（SG）对原始光谱数据进行预处理,将原始光谱数据及预处理后的光谱数据分别与印刷品的Lab值建立偏最小二乘回归（PLSR）和主成分回归（PCR）两种预测模型。结果表明,基于MSC预处理的PLSR预测模型的预测精度最高,L、a、b值的R2分别高达0.9885, 0.9879和0.9938,预测颜色的平均色差约为0.71。液态水性油墨的近红外光谱可以精确预测印刷品颜色,为印刷品的在线检测提供了新思路。     

Multiplexed spectral signature detection for microfluidic color-coded bioparticle flow

Here, we report a high-speed photospectral detection technique capable of discriminating subtle variations of spectral signature among fluorescently labeled cells and microspheres flowing in a microfluidic channel. The key component used in our study is a strain-tunable nanoimprinted grating microdevice coupled with a photomultiplier tube (PMT). The microdevice permits acquisition of the continuous spectral profiles of multiple fluorescent emission sources at 1 kHz. Optically connected to a microfluidic flow chamber via a multimode optical fiber, our multiwavelength detection platform allows for cytometric measurement of cell groups emitting nearly identical fluorescence signals with a maximum emission wavelength difference as small as 5 nm. The same platform also allows us to demonstrate microfluidic flow cytometry of four different microsphere types in a wavelength bandwidth as narrow as 40 nm at a high (>85%) confidence level. Our study shows that detection of fluorescent spectral signatures at high speed and high resolution can expand specificity of multicolor flow cytometry. The enhanced capability enables multiplexed analysis of color-coded bioparticles based on single-laser excitation and single-detector spectroscopy in a microfluidic setting. The fluorescence signal discrimination power achieved by the optofluidic technology holds great promise to enable quantification of cellular parameters with higher accuracy as well as enumeration of a larger number of cell types than conventional flow cytometric methods.     

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometric analysis of cellular glycerophospholipids enabled by multiplexed solvent dependent analyte-matrix interactions

A matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) based approach was developed for the rapid analyses of cellular glycerophospholipids. Through multiplexed solvent-enabled optimization of analyte-matrix interactions during the crystallization process, over a 30-fold increase in S/N was achieved using 9-aminoacridine as the matrix. The linearity of response (r(2) = 0.99) and dynamic range of this method (over 2 orders of magnitude) were excellent. Moreover, through multiplexing ionization conditions by generating suites of different analyte-matrix interactions in the absence or presence of different alkali metal cations in the matrix, discrete lipid classes were highly and selectively ionized under different conditions resulting in the de facto resolution of lipid classes without chromatography. The resultant decreases in spectral complexity facilitated tandem mass spectrometric analysis through high energy fragmentation of lithiated molecular ions that typically resulted in informative fragment ions. Anionic phospholipids were also detected as singly negatively charged species that could be fragmented using MALDI tandem mass spectrometry leading to structural assignments. Collectively, these results identify a rapid, sensitive, and highly informative MALDI-TOF MS approach for analysis of cellular glycerophospholipids directly from extracts of mammalian tissues without the need for prior chromatographic separation.     

非ARMA随机信号谱估计的数字滤波算法及性能分析

为克服传统的周期图谱估计方法存在的分辨率低及非一致估计等缺点而迅速发展的各种近代谱估计法只能适用于ＡＲＭＡ（Ａｕｔｏｒｅｇｒｅｓｓｉｖｅ－ｍｏｖｉｎｇａｖｅｒａｇｅ）信号的谱估计。为解决存在于各种物理过程中的非ＡＲＭＡ随机过程（包括１／ｆ过程）的谱估计，本文提出了一种对非ＡＲＭＡ随机信号的非递归数字滤波算法，重点研究了算法主要参数（滤波器长度、数据长度）的选择原则及对谱估计准确度和精度的影响。理论分析及实际测量证明，此方法具有分辨率高、谱估计精确较好及一致估计等优点，特别适用于对非ＡＲＭＡ信号的某些特征频率点的谱估计。     

基于可见/近红外光谱分析技术的水性油墨黏度预测模型

针对水性油墨黏度测量方法存在操作复杂、主观性强等问题,利用可见/近红外光谱分析技术结合化学计量学方法,建立水性油墨黏度预测模型,实现水性油墨黏度的快速无损检测。首先,利用微型光纤光谱仪采集水性油墨样本的反射光谱;再通过比较不同预处理方法对原始光谱数据的预处理效果,分别基于原始全光谱及预处理后的光谱数据构建水性油墨黏度的偏最小二乘回归(PLSR)和主成分回归(PCR)预测模型;最后,将预处理后的光谱数据采用连续投影算法(SPA)和竞争性自适应重加权算法(CARS)提取特征波长,并基于特征波长的光谱数据建立水性油墨黏度的PLS预测回归模型。结果表明,采用SPA算法从全光谱中只提取了4个特征波长,不仅显著简化了模型,提升了模型的运算效率,建立的SNV-SPA-PLS模型还具有最佳的预测性能(R_p²=0.9992,RMSEP=0.0732)。该研究结果表明应用光谱分析技术实现对水性油墨黏度检测是有效可行的,为进一步通过光谱分析技术进行水性油墨在线黏度检测提供了新方法,为提高印刷品质量稳定性提供了技术基础。     

Solid-state digital micro-mirror array spectrometer for Hadamard transform measurements of glucose and lactate in aqueous solutions

A novel solid-state near-infrared spectrometer is presented based on a digital micro-mirror array device (DMD) that is well designed for Hadamard transform spectroscopy. This spectrometer is designed for the collection of transmission spectra over the C-H first overtone region of the near-infrared spectrum (6500-5500 cm(-1)). A spectral resolution of 2.2 nm (~11 cm(-1)) is realized by using a 25 μm diameter linear tungsten filament as the source. Such a thin filament reduces imaging aberrations into the micro-mirror array, thereby enhancing spectral resolution. After passing through the sample, the transmitted radiation is dispersed with a grating before being imaged onto the surface of the DMD. Hadamard transform masks are implemented through the DMD and the reflected light is monitored by a single-element photodiode detector. The analytical utility of this approach is demonstrated through the multivariate quantification of glucose and lactate in binary mixtures composed in an aqueous buffer solution. A signal-to-noise ratio of 35,000 is achieved through these aqueous samples, and the resulting quantitative measurements provide a standard error of prediction of 1.4 and 0.9 mM for glucose and lactate, respectively. The selectivity of the resulting calibration models is established by using both a pure component selectivity analysis as well as analysis of the net analyte signal for each component. These quantitative results from the DMD Hadamard transform spectrometer compare favorably to similar measurements performed with a commercial Fourier transform spectrometer.     

Calibration of multiplexed fiber-optic spectroscopy

Large-scale commercial bioprocesses that manufacture biopharmaceutical products such as monoclonal antibodies generally involve multiple bioreactors operated in parallel. Spectra recorded during in situ monitoring of multiple bioreactors by multiplexed fiber-optic spectroscopies contain not only spectral information of the chemical constituents but also contributions resulting from differences in the optical properties of the probes. Spectra with variations induced by probe differences cannot be efficiently modeled by the commonly used multivariate linear calibration models or effectively removed by popular empirical preprocessing methods. In this study, for the first time, a calibration model is proposed for the analysis of complex spectral data sets arising from multiplexed probes. In the proposed calibration model, the spectral variations introduced by probe differences are explicitly modeled by introducing a multiplicative parameter for each optical probe, and then their detrimental effects are effectively mitigated through a "dual calibration" strategy. The performance of the proposed multiplex calibration model has been tested on two multiplexed spectral data sets (i.e., MIR data of ternary mixtures and NIR data of bioprocesses). Experimental results suggest that the proposed calibration model can effectively mitigate the detrimental effects of probe differences and hence provide much more accurate predictions than commonly used multivariate linear calibration models (such as PLS) with and without empirical data preprocessing methods such as orthogonal signal correction, standard normal variate, or multiplicative signal correction.     

Photonic crystal fibre based all-optical modulation format conversions between NRZ and RZ with hybrid clock recovery from a PRZ signal

Several all-optical modulation format-converting schemes are described for non-return-to-zero (NRZ) and return-to-zero (RZ) modulation formats that make use of spectral filtering of either self-phase modulation (SPM) or cross-phase modulation (XPM) broadened signal spectrum in a highly-nonlinear dispersion-flattened photonic-crystal fibre. Format conversions have been performed between the most widely used modulation formats - NRZ and RZ. In addition, a hybrid clock recovery scheme is proposed to obtain the data rate of the NRZ signal for NRZ-to-RZ format conversion. All format-converting schemes are based on the extraction of the spectral components in a nonlinear phase modulation broadened signal spectrum. In NRZ-to-RZ format conversion, a periodic pulse train, at a repetition rate similar to the NRZ data rate, is used as a control that induces a nonlinear phase shift to the NRZ probe signal and broadens its spectrum. The spectral components, contributed by different time instances of the control pulse, can be extracted as the converted RZ signal output. In RZ-to-NRZ format conversion, the RZ signal serves as a control that induces a nonlinear phase shift to a continuous wave probe light, where a logic-inverted NRZ signal can be extracted by filtering out the chirped components. Format conversions between NRZ and RZ signals at 9.95328 GB/s (OC-192) are demonstrated. As the proposed optical signal-processing schemes make use of the fibre nonlinearity (SPM/XPM), it is possible to extend it to a high-speed operation <160 Gb/s. Therefore the proposed format-converting schemes can serve as a format converter between the optical time-division multiplexed networks and the wavelength division multiplexed networks     

Use of Raman microscopy and band-target entropy minimization analysis to identify dyes in a commercial stamp. Implications for authentication and counterfeit detection

Raman microscopy was used in mapping mode to collect more than 1000 spectra in a 100 microm x 100 microm area from a commercial stamp. Band-target entropy minimization (BTEM) was then employed to unmix the mixture spectra in order to extract the pure component spectra of the samples. Three pure component spectral patterns with good signal-to-noise ratios were recovered, and their spatial distributions were determined. The three pure component spectral patterns were then identified as copper phthalocyanine blue, calcite-like material, and yellow organic dye material by comparison to known spectral libraries. The present investigation, consisting of (1) advanced curve resolution (blind-source separation) followed by (2) spectral data base matching, readily suggests extensions to authenticity and counterfeit studies of other types of commercial objects. The presence or absence of specific observable components form the basis for assessment. The present spectral analysis (BTEM) is applicable to highly overlapping spectral information. Since a priori information such as the number of components present and spectral libraries are not needed in BTEM, and since minor signals arising from trace components can be reconstructed, this analysis offers a robust approach to a wide variety of material problems involving authenticity and counterfeit issues.     

Charger: combination of signal processing and statistical learning algorithms for precursor charge-state determination from electron-transfer dissociation spectra

Tandem mass spectrometry in combination with liquid chromatography has emerged as a powerful tool for characterization of complex protein mixtures in a high-throughput manner. One of the bioinformatics challenges posed by the mass spectral data analysis is the determination of precursor charge when unit mass resolution is used for detecting fragment ions. The charge-state information is used to filter database sequences before they are correlated to experimental data. In the absence of the accurate charge state, several charge states are assumed. This dramatically increases database search times. To address this problem, we have developed an approach for charge-state determination of peptides from their tandem mass spectra obtained in fragmentations via electron-transfer dissociation (ETD) reactions. Protein analysis by ETD is thought to enhance the range of amino acid sequences that can be analyzed by mass spectrometry-based proteomics. One example is the improved capability to characterize phosphorylated peptides. Our approach to charge-state determination uses a combination of signal processing and statistical machine learning. The signal processing employs correlation and convolution analyses to determine precursor masses and charge states of peptides. We discuss applicability of these methods to spectra of different charge states. We note that in our applications correlation analysis outperforms the convolution in determining peptide charge states. The correlation analysis is best suited for spectra with prevalence of complementary ions. It is highly specific but is dependent on quality of spectra. The linear discriminant analysis (LDA) approach uses a number of other spectral features to predict charge states. We train LDA classifier on a set of manually curated spectral data from a mixture of proteins of known identity. There are over 5000 spectra in the training set. A number of features, pertinent to spectra of peptides obtained via ETD reactions, have been used in the training. The loading coefficients of LDA indicate the relative importance of different features for charge-state determination. We have applied our model to a test data set generated from a mixture of 49 proteins. We search the spectra with and without use of the charge-state determination. The charge-state determination helps to significantly save the database search times. We discuss the cost associated with the possible misclassification of charge states.     

Optical design in beam steering environments with emphasis on laser transmission measurements

Optical sensors applied to practical devices often encounter beam steering: the wander and/or diffusion of laser light. Here we provide a framework for minimizing the sensitivity of transmission-based sensors to beam steering without quantitative prediction of the severity of the beam-steering field. Typical goals are increased transmission and/or minimized fluctuations in transmission; such features can improve optical sensor performance (e.g., improved signal-to-noise ratio, response time, or spectral resolution). In our framework, we introduce a parameter for characterizing beam-steering severity. We then compare two approaches for absorption spectroscopy and show that the preferred approach depends on the total spectral range monitored, the spectral resolution desired, and the severity of the beam steering.     

Multiplexed ion mobility spectrometry-orthogonal time-of-flight mass spectrometry

Ion mobility spectrometry (IMS) coupled to orthogonal time-of-flight mass spectrometry (TOF) has shown significant promise for the characterization of complex biological mixtures. The enormous complexity of biological samples (e.g., from proteomics) and the need for both biological and technical analysis replicates imposes major challenges for multidimensional separation platforms with regard to both sensitivity and sample throughput. A major potential attraction of the IMS-TOF MS platform is separation speeds exceeding that of conventional condensed-phase separations by orders of magnitude. Known limitations of the IMS-TOF MS platforms that presently mitigate this attraction include the need for extensive signal averaging due to factors that include significant ion losses in the IMS-TOF interface and an ion utilization efficiency of less than approximately 1% with continuous ion sources (e.g., ESI). We have developed a new multiplexed ESI-IMS-TOF mass spectrometer that enables lossless ion transmission through the IMS-TOF as well as a utilization efficiency of >50% for ions from the ESI source. Initial results with a mixture of peptides show a approximately 10-fold increase in signal-to-noise ratio with the multiplexed approach compared to a signal averaging approach, with no reduction in either IMS or TOF MS resolution.     

Frequency-estimation-based signal-processing algorithm for white-light optical fiber Fabry-Perot interferometers

A novel signal-processing algorithm based on frequency estimation of the spectrogram of single-mode optical fiber Fabry-Perot interferometric sensors under white-light illumination is described. The frequency-estimation approach is based on linear regression of the instantaneous phase of an analytical signal, which can be obtained by preprocessing the original spectrogram with a bandpass filter. This method can be used for a relatively large cavity length without the need for spectrogram normalization to the spectrum of the light source and can be extended directly to a multiplexed sensor system. Experimental results show that the method can yield both absolute measurement with high resolution and a large dynamic range. Performance analysis shows that the method is tolerant of background noise and variations of the source spectrum.     

MALDI MS analysis of oligonucleotides: desalting by functional magnetite beads using microwave-assisted extraction

The presence of alkali cation adductions of oligonucleotides commonly deteriorates matrix-assisted laser desorption/ionization (MALDI) mass spectra. Thus, desalting is required for oligonucleotide samples prior to MALDI MS analysis in order to prevent the mass spectra from developing poor quality. In this paper, we demonstrate a new approach to extract traces of oligonucleotides from aqueous solutions containing high concentrations of salts using microwave-assisted extraction. The C18-presenting magnetite beads, capable of absorbing microwave irradiation, are used as affinity probes for oligonucleotides with the addition of triethylammonium acetate as the counterions. This new microwave-assisted extraction approach using magnetite beads as the trapping agents and as microwave-absorbers has been demonstrated to be very effective in the selective binding of oligonucleotides from aqueous solutions. The extraction of oligonucleotides from solutions onto the C18-presenting magnetite beads takes only 30 s to enrich oligonucleotides in sufficient quantities for MALDI MS analysis. After using this desalting approach, alkali cation adductions of oligonucleotides are dramatically reduced in the MALDI mass spectra. The presence of saturated NaCl (approximately 6 M) in the oligonucleotide sample is tolerated without degrading the mass spectra. The detection limit for d(A)6 is approximately 2.8 fmol.     

Spectral Doppler estimation utilizing 2-D spatial information and adaptive signal processing

The trade-off between temporal and spectral resolution in conventional pulsed wave (PW) Doppler may limit duplex/triplex quality and the depiction of rapid flow events. It is therefore desirable to reduce the required observation window (OW) of the Doppler signal while preserving the frequency resolution. This work investigates how the required observation time can be reduced by adaptive spectral estimation utilizing 2-D spatial information obtained by parallel receive beamforming. Four adaptive estimation techniques were investigated, the power spectral Capon (PSC) method, the amplitude and phase estimation (APES) technique, multiple signal classification (MUSIC), and a projection-based version of the Capon technique. By averaging radially and laterally, the required covariance matrix could successfully be estimated without temporal averaging. Useful PW spectra of high resolution and contrast could be generated from ensembles corresponding to those used in color flow imaging (CFI; OW = 10). For a given OW, the frequency resolution could be increased compared with the Welch approach, in cases in which the transit time was higher or comparable to the observation time. In such cases, using short or long pulses with unfocused or focused transmit, an increase in temporal resolution of up to 4 to 6 times could be obtained in in vivo examples. It was further shown that by using adaptive signal processing, velocity spectra may be generated without high-pass filtering the Doppler signal. With the proposed approach, spectra retrospectively calculated from CFI may become useful for unfocused as well as focused imaging. This application may provide new clinical information by inspection of velocity spectra simultaneously from several spatial locations.     

An integrated ten-pump, eight-channel parallel LC/MS system for automated high-throughput analysis of proteins.

An integrated 10-pump eight-channel LC/MS system has been developed for automated high-throughput analysis of intact proteins in recombinant protein purification processes. The key features of the system include (1) a compact 10-pump HPLC module that uses two pumps to generate a binary gradient and 8 pumps to deliver the mixed gradient to eight independent flow channels; (2) a TOF mass spectrometer with an eight-channel multiplexed ESI interface, which records separate data for all eight channels over each HPLC run cycle; and (3) highly automated data processing software that allows unattended calculation of protein molecular weight (in Da) from original mass spectral data (in m/z). This system was used in the routine screening of fractions from preparative scale chromatography to monitor the purification process with the required mass accuracy and throughput. As an example, the production and purification of an acylated protein with a molecular weight of 9 kDa is described. Using this off-line approach, it is practical to fully characterize protein-containing fractions from column chromatography with an overall analytical throughput of 1 min/protein sample with minimum operator involvement.     

Reaction Kinetics‐Mediated Control over Silver Nanogap Shells as Surface‐Enhanced Raman Scattering Nanoprobes for Detection of Alzheimer's Disease Biomarkers

It is very challenging to accurately quantify the amounts of amyloid peptides Aβ40 and Aβ42, which are Alzheimer's disease (AD) biomarkers, in blood owing to their low levels. This has driven the development of sensitive and noninvasive sensing methods for the early diagnosis of AD. Here, an approach for the synthesis of Ag nanogap shells (AgNGSs) is reported as surface‐enhanced Raman scattering (SERS) colloidal nanoprobes for the sensitive, selective, and multiplexed detection of Aβ40 and Aβ42 in blood. Raman label chemicals used for SERS signal generation modulate the reaction rate for AgNGSs production through the formation of an Ag‐thiolate lamella structure, enabling the control of nanogaps at one nanometer resolution. The AgNGSs embedded with the Raman label chemicals emit their unique SERS signals with a huge intensity enhancement of up to 10⁷ and long‐term stability. The AgNGS nanoprobes, conjugated with an antibody specific to Aβ40 or Aβ42, are able to detect these AD biomarkers in a multiplexed manner in human serum based on the AgNGS SERS signals. Detection is possible for amounts as low as 0.25 pg mL^?1. The AgNGS nanoprobe‐based sandwich assay has a detection dynamic range two orders of magnitude wider than that of a conventional enzyme‐linked immunosorbent assay.     

Prediction of molar fractions in two-component gas mixtures using pulse-echo ultrasound and PLS regression

The composition, and thus the energy content and monetary value of natural gas and biogas, vary considerably depending on the source. Present energy measurement techniques are not suitable for online use. We show with experiments on mixtures of ethane (C2H6) and oxygen (O2) how partial least squares regression (PLSR) can be used to predict the molar fraction of ethane in the mixtures, given spectral data from ultrasonic pulse-echo measurements. The PLSR technique is compared with the standard principal component regression (PCR), and we show that PLSR yields better predictive performance.     

Evaluation of surface-enhanced resonance Raman scattering for quantitative DNA analysis

The labeling of biological species using dyes has become common practice to aid in their detection, and immediate positive identification of specific dyes in high dilution is a key requirement. Here the detection by surface-enhanced resonance Raman scattering (SERRS) of eight commercially available dye labels (ROX, rhodamine 6G, HEX, FAM, TET, Cy3, Cy5, TAMRA) attached to oligonucleotide strands is reported. Each of the eight labels was easily detected by using the SERRS from silver nanoparticles to produce a unique, molecularly specific spectrum. The conditions were optimized to obtain the best signal enhancement, and linear concentration graphs at low oligonucleotide concentrations were obtained. At higher concentrations (above approximately 10(-)(8) mol dm(-)(3)), curvature was introduced into the concentration graphs with the exception of rhodamine 6G, TET, and FAM, which gave linearity over the entire concentration range studied. Detection limits as low as 0.5 fmol were obtained, with lower possible if a smaller sample was analyzed. Investigation was also carried out into the effect of a Tris-HCl buffer containing the surfactant Tween 20 to aid in the prevention of surface adhesion of the oligonucleotides to the sample vessels at ultralow concentrations. The Tween 20 allowed lower detection limits to be obtained for each of the labels studied. This study shows that the different dyes commonly used with oligonucleotides can give quantitative SERRS at concentration levels not possible when the same dyes are used with fluorescence detection.