Discrimination of Transgenic Rice Based on Near Infrared Reflectance Spectroscopy and Partial Least Squares Regression Discriminant Analysis

Near infrared reflectance spectroscopy （NIRS）, a non-destructive measurement technique, was combined with partial least squares regression discrimiant analysis （PLS-DA） to discriminate the transgenic （TCTP and mi166） and wild type （Zhonghua 11） rice. Furthermore, rice lines transformed with protein gene （OsTCTP） and regulation gene （Osmi166） were also discriminated by the NIRS method. The performances of PLS-DA in spectral ranges of 4 000-8 000 cm-1 and 4 000-10 000 cm-1 were compared to obtain the optimal spectral range. As a result, the transgenic and wild type rice were distinguished from each other in the range of 4 000-10 000 cm-1, and the correct classification rate was 100.0% in the validation test. The transgenic rice TCTP and mi166 were also distinguished from each other in the range of 4 000-10 000 cm-1, and the correct classification rate was also 100.0%. In conclusion, NIRS combined with PLS-DA can be used for the discrimination of transgenic rice.

Qualitative and Quantitative Analysis for the Quality Control of Rhizoma Coptidis by HPLC-DAD and HPLC-ESI-MS

For quality control purpose, an approach of fingerprinting and simultaneous quantification of five major bioactive constituents of Rhizoma Coptidis was established via a high-performance liquid chromatograph coupled with a photodiode array UV detector（HPLC-DAD） and an electrospray ionization mass spectrometer（HPLC-ESI/MS） The compounds were identified on the basis of the comparison of their mass spectra with literature data and those of standard samples and quantified by the HPLC-DAD method. Baseline separation was achieved on an XTerra C18 column（5 μm, 250 mm×4.6 mm i. d.） with linear gradient elution of formate buffer（consisting of 0.5% formic acid, adjusted to pH=4.5 with ammonia） and acetonitrile（consisting of 0.2% formic acid and 0.2% triethylamine）. The me- thod was validated for linearity（r^2〉0.9995）, repeatability（RSD〈3.1%）, intra- and inter-day precision（RSD〈1.8%） with recovery（99.9%-105.1%）, limits of detection（0.15-0.35 μg/mL）, and limits of quantification（0.53-0.82 μg/mL）. The similarities of 32 batches of Rhizoma Coptidis and their classification according to their manufacturers were based on the retention time and peak areas of the characteristic compounds. The five compounds were selected for quality assessment ofRhizoma coptidis via partial least squares analysis（PLS）.

Comprehensive Evaluation and Prediction of the Effectiveness of H_(2)O_(2)- assisted Na_(2)CO_(3)Pretreatment of Corn Stover Using Multivariate Analysis

In this study,multivariate analysis methods,including a principal component analysis(PCA)and partial least square(PLS)analysis,were applied to reveal the inner relationship of the key variables in the process of H_(2)O_(2)-assisted Na_(2)CO_(3)(HSC)pretreatment of corn stover.A total of 120 pretreatment experiments were implemented at the lab scale under different conditions by varying the particle size of the corn stover and process variables.The results showed that the Na_(2)CO_(3) dosage and pretreatment temperature had a strong influence on lignin removal,whereas pulp refining instrument(PFI)refining and Na_(2)CO_(3) dosage played positive roles in the final total sugar yield.Furthermore,it was found that pretreatment conditions had a more significant impact on the amelioration of pretreatment effectiveness compared with the properties of raw corn stover.In addition,a prediction of the effectiveness of the corn stover HSC pretreatment based on a PLS analysis was conducted for the first time,and the test results of the predictability based on additional pretreatment experiments proved that the developed PLS model achieved a good predictive performance(particularly for the final total sugar yield),indicating that the developed PLS model can be used to predict the effectiveness of HSC pretreatment.Therefore,multivariate analysis can be potentially used to monitor and control the pretreatment process in future large-scale biorefinery applications.

Visible and Near-Infrared Spectroscopic Discriminant Analysis Applied to Identification of Soy Sauce Adulteration

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.

Optimization of wavelength range and data interval in chemometric analysis of complex pharmaceutical mixtures

The performance of different chemometric approaches was evaluated in the spectrophotometric determination of pharmaceutical mixtures characterized by having the amount of components with a very high ratio. Principal component regression （PCR）, partial least squares with one dependent variable （PLS1） or multi-dependent variables （PLS2）, and multivariate curve resolution （MCR） were applied to the spectral data of a ternary mixture containing paracetamol, sodium ascorbate and chlorpheniramine （150：140：1, m/m/m）, and a quaternary mixture containing paracetamol, caffeine, phenylephrine and chlorpheniramine （125：6. 25：1.25：1, m/m/m/m）. The UV spectra of the calibration samples in the range of 200-320 nm were pre-treated by removing noise and useless data, and the wavelength regions having the most useful analytical information were selected using the regression coefficients calculated in the multivariate modeling. All the defined chemometric models were validated on external sample sets and then applied to commercial pharmaceutical formulations. Different data intervals, fixed at 0.5, 1.0, and 2.0 point/nm, were tested to optimize the prediction ability of the models. The best results were obtained using the PLSlcalibration models and the quantification of the species of a lower amount was sig- nificantly improved by adopting 0.5 data interval, which showed accuracy between 94.24% and 107.76%.

Trade-offs and Synergies of Ecosystem Services in Karst Area of China Driven by Grain-for-Green Program

As an important means regulating the relationship between human and natural ecosystem,ecological restoration program plays a key role in restoring ecosystem functions.The Grain-for-Green Program(GFGP,One of the world’s most ambitious ecosystem conservation set-aside programs aims to transfer farmland on steep slopes to forestland or grassland to increase vegetation coverage)has been widely implemented from 1999 to 2015 and exerted significant influence on land use and ecosystem services(ESs).In this study,three ecological models(In VEST,RUSLE,and CASA)were used to accurately calculate the three key types of ESs,water yield(WY),soil conservation(SC),and net primary production(NPP)in Karst area of southwestern China from 1982 to 2015.The impact of GFGP on ESs and trade-offs was analyzed.It provides practical guidance in carrying out ecological regulation in Karst area of China under global climate change.Results showed that ESs and trade-offs had changed dramatically driven by GFGP.In detail,temporally,SC and NPP exhibited an increasing trend,while WY exhibited a decreasing trend.Spatially,SC basically decreased from west to east;NPP basically increased from north to south;WY basically increased from west to east;NPP and SC,SC and WY developed in the direction of trade-offs driven by the GFGP,while NPP and WY developed in the direction of synergy.Therefore,future ecosystem management and restoration policy-making should consider trade-offs of ESs so as to achieve sustainable provision of ESs.

Rock and Soil Classification Using PLS-DA and SVM Combined with a Laser-Induced Breakdown Spectroscopy Library

Laser-induced breakdown spectroscopy （LIBS） has become a powerful technology in geological applications. The correct identification of rocks and soils is critical to many geological projects. In this study, LIBS database software with a user-friendly and intuitive interface is developed based on Windows, consisting of a database module and a sample identification module. The database module includes a basic database containing LIBS persistent lines for elements and a dedicated geological database containing LIBS emission lines for several rock and soil reference standards. The module allows easy use of the data. A sample identification module based on partial least squares discriminant analysis （PLS-DA） or support vector machine （SVM） algorithms enables users to classify groups of unknown spectra. The developed system was used to classify rock and soil data sets in a dedicated database and the results demonstrate that the system is capable of fast and accurate classification of rocks and soils, and is thus useful for the detection of geological materials.

Rapid recognition of Chinese herbal pieces of Areca catechu by different concocted processes using Fourier transform mid-infrared and near-infrared spectroscopy combined with partial least-squares discriminant analysis

Rapid and sensitive recognition of herbal pieces according to different concocted processing is crucial to quality control and pharmaceutical effect. Near-infrared （NIR） and mid-infrared （MIR） technology combined with supervised pattern recognition based on partial least-squares discriminant analysis （PLSDA） was attempted to classify and recognize six different concocted processing pieces of 600 Areca catechu L. samples and the influence of fingerprint information preprocessing methods on recognition performance was also investigated in this work. Recognition rates of 99.24%, 100% and 99.49% for original fingerprint, multiple scatter correct （MSC） fingerprint and second derivative （2nd derivative） fingerprint of NIR spectra were achieved by PLSDA models, respectively. Meanwhile, a perfect recognition rate of 100% was obtained for the above three fingerprint models of MIR spectra. In conclusion, PLSDA can rapidly and effectively extract otherness of fingerprint information from NIR and MIR spectra to identify different concocted herbal pieces ofA. catechu.

The classification of plants by laser-induced breakdown spectroscopy based on two chemometric methods

The applications of laser-induced breakdown spectroscopy(LIBS) on classifying complex natural organics are relatively limited and their accuracy still requires improvement.In this work,to study the methods on classification of complex organics,three kinds of fresh leaves were measured by LIBS.100 spectra from 100 samples of each kind of leaves were measured and then they were divided into a training set and a test set in a ratio of 7:3.Two algorithms of chemometric methods including the partial least squares discriminant analysis(PLS-DA) and principal component analysis Mahalanobis distance(PCA-MD) were used to identify these leaves.By using 23 lines from 16 elements or molecules as input data,these two methods can both classify these three kinds of leaves successfully.The classification accuracies of training sets are both up to 100% by PCA-MD and PLS-DA.The classification accuracies of the test set are 93.3% by PCA-MD and 97.8% by PLS-DA.It means that PLS-DA is better than PCA-MD in classifying plant leaves.Because the components in PLS-DA process are more suitable for classification than those in PCA-MD process.We think that this work can provide a reference for plant traceability using LIBS.

Partial wave analysis of ψ' →γχ_(c0) →γpK-Λ used for searching for baryon resonance

Abundant ψ＇ events have been collected at the Beijing Electron Positron Collider-Ⅱ （BEPCⅡ） that could undoubtedly provide us with a great opportunity to study the more attractive charmonium decays. As has been noticed before, in the process of J/ψ＇ decaying to the baryonic final states, pK-Λ, the evident Λ＊ and N＊ bands have been observed. Similarly, by using the product of χcJ from ψ＇ radiative decay, we may confirm this or find some extra new resonances. χc0＇s data samples will be more than χc1,2, taking into account the larger branching ratio of ψ＇ →γχc0. Here, we provide explicit partial wave analysis formulae for the very interesting channel ψ＇ →γχc0 →γpK-Λ.

Spatio-temporal variation of Fraction of Photosynthetically Active Radiation absorbed by vegetation in the Hengduan Mountains, China

The Fraction of Absorbed Photosynthetically Active Radiation(FPAR) is an important indicator of the primary productivity of vegetation. FPAR is often used to estimate the assimilation of carbon dioxide in vegetation. Based on MOD15 A2 H/FPAR data product, the temporal and spatial variation characteristics and variation trend of FPAR in different vegetation types in 2001 to 2018 were analyzed in the Hengduan Mountains. The response of FPAR to climate change was investigated by using Pearson correlation analytical method and partial least squares regression analysis. Results showed that the FPAR in Hengduan Mountains presented an increasing trend with time. Spatially, it was high in the south and low in the north, and it also showed obvious vertical zonality by elevation gradient.The vegetation FPAR was found to be positively correlated with air temperature and sunshine duration but negatively correlated with precipitation. Partial least squares regression analysis showed that the influence of sunshine duration on vegetation FPAR in Hengduan Mountains was stronger than that of air temperature and precipitation.

Harvesting Age and Time Effect of Andrographis paniculata Leaf on Its Anti-Inflammatory Activity

In this study, Fourier Transform Infrared (FTIR)-, 1H Nuclear Magnetic Resonance (NMR)-spectroscopy and multivariate statistical analysis were used for the screening of in vitro anti-inflammatory activity on three different germplasm accessions namely 11,341 (P), 11,248 (T) and 11,265 (H) of Malaysian Andrographis paniculata (A. paniculata) leaf. The anti-inflammatory activity by nitric oxide (NO) inhibition assay in relation to the different harvesting ages and times of A. paniculata leaf was determined through comparison by partial least-squares analysis (PLS) using SIMCA-P. The PLS allowed the separation and correlation between the NO assay with the phytochemical present due to the effects of different harvesting ages and times. From the PLS plots, conclusions were drawn with respect to the correlation between A. paniculata leaf metabolites with the anti-inflammatory results which showed that 180 days after transplanting (DAT) of morning session for accessions T and H, and evening for P gave the highest anti-inflammatory activity.

Comparative study on identi¯cation of healthy and osteoarthritic articular cartilages by fourier transform infrared imaging and chemometrics methods

Two discriminant methods,partial least squares-discriminant analysis(PLS-DA)and Fisher's discriminant analysis(FDA),were combined with Fourier transform infrared imaging(FTIRI)to differentiate healthy and osteoarthritic articular cartilage in a canine model.Osteoarthritic cartilage had been developed for up to two years after the anterior cruciate ligament(ACL)transection in one knee.Cartilage specimens were sectioned into 10μm thickness for FTIRI.A PLS-DA model was developed after spectral pre-processing.All IR spectra extracted from FTIR images were calculated by PLS-DA with the discriminant accuracy of 90%.Prior to FDA,principal component analysis(PCA)was performed to decompose the IR spectral matrix into informative princi pal component matrices.Based on the different discriminant mechanism,the discriminant accuracy(96%)of PCA-FDA with high convenience was higher than that of PLS-DA.No healthy cartilage sample was mis assigned by these two methods.The above mentioned suggested that both integrated technologies of FTIRI-PLS-DA and,especially,FTIRI-PCA-FDA could become a promising tool for the discrimination of healthy and osteoarthritic cartilage specimen as well as the diagnosis of cartilage lesion at microscopic level.The results of the study would be helpful for better understanding the pathology of osteoarthritics.

Comment on the paper “An analysis of Chinese Super League partial results”, by David R Brillinger

This paper gives a nice analysis of an interesting data set, and develops a method that can be applied to a variety of round-robin sports competitions. The paper models the result of a

Lepton mass correction in partial wave analyses of charmed meson semi-leptonic decays

We derive a parameterization formula for the partial wave analyses of charmed meson semi-leptonic decays while considering the effects of lepton mass.Because the proposed super-tau-charm factory will reach a significantly enhanced luminosity and BESIII is collecting newψ(3770)→DD data,our results will help improve the measurement precision of future partial wave analyses of charmed meson semi-muonic decays.

Learning models for colorectal cancer signature reconstruction and classification in patients with chronic inflammatory bowel disease

BACKGROUND In their everyday life,clinicians face an overabundance of biological indicators potentially helpful during a disease therapy.In this context,to be able to reliably identify a reduced number of those markers showing the ability of optimising the classification of treatment outcomes becomes a factor of vital importance to medical prognosis.In this work,we focus our interest in inflammatory bowel disease(IBD),a long-life threaten with a continuous increasing prevalence worldwide.In particular,IBD can be described as a set of autoimmune conditions affecting the gastrointestinal tract whose two main types are Crohn’s disease and ulcerative colitis.AIM To identify the minimal signature of microRNA(miRNA)associated with colorectal cancer(CRC)in patients with one chronic IBD.METHODS We provide a framework of well-established statistical and computational learning methods wisely adapted to reconstructing a CRC network leveraged to stratify these patients.RESULTS Our strategy resulted in an adjusted signature of 5 miRNAs out of approximately 2600 in Crohn’s Disease(resp.8 in Ulcerative Colitis)with a percentage of success in patient classification of 82%(resp.81%).CONCLUSION Importantly,these two signatures optimally balance the proportion between the number of significant miRNAs and their percentage of success in patients’stratification.

Vibrational power flow analysis on combined plates partially covered layer of discontinuous material

Vibrational power flow on combined plates with a change in mass and stiffness or with viscoelastic damping layer used widely in engineering is studied. The expressions of flexural displacement and other physical quantities are obtained using Laplace transformation and transfer matrix approach, then influences of changes in mass and stiffness of discontinuous material and the free damping layer on the input power flow and the transmitted power flow are discussed. The conclusions provide theory basis for structural optimization design and reducing noise and vibration

Analysis of Serum Metabolic Profile by Ultra-performance Liquid Chromatography-mass Spectrometry for Biomarkers Discovery： Application in a Pilot Study to Discriminate Patients with Tuberculosis

Background：Tuberculosis （TB） is a chronic wasting inflammatory disease characterized by multisystem involvement,which can cause metabolic derangements in afflicted patients.Metabolic signatures have been exploited in the study of several diseases.However,the serum that is successfully used in TB diagnosis on the basis of metabolic profiling is not by much.Methods：Orthogonal partial least-squares discriminant analysis was capable of distinguishing TB patients from both healthy subjects and patients with conditions other than TB.Therefore,TB-specific metabolic profiling was established.Clusters of potential biomarkers for differentiating TB active from non-TB diseases were identified using Mann-Whitney U-test.Multiple logistic regression analysis of metabolites was calculated to determine the suitable biomarker group that allows the efficient differentiation of patients with TB active from the control subjects.Results：From among 271 participants,12 metabolites were found to contribute to the distinction between the TB active group and the control groups.These metabolites were mainly involved in the metabolic pathways of the following three biomolecules：Fatty acids,amino acids,and lipids.The receiver operating characteristic curves of3D,7D,and 11D-phytanic acid,behenic acid,and threoninyl-γ-glutamate exhibited excellent efficiency with area under the curve （AUC） values of 0.904 （95% confidence interval [CI]：0.863-0.944）,0.93 （95% CI：0.893-0.966）,and 0.964 （95% CI：0.941-0.988）,respectively.The largest and smallest resulting AUCs were 0.964 and 0.720,indicating that these biomarkers may be involved in the disease mechanisms.The combination of lysophosphatidylcholine （18∶0）,behenic acid,threoninyl-γ-glutamate,and presqualene diphosphate was used to represent the most suitable biomarker group for the differentiation of patients with TB active from the control subjects,with an AUC value of 0.991.Conclusion：The metabolic analysis results identified new serum biomarkers that can distinguish TB from non-TB diseases.The metabolomics-based analysis provides specific insights into the biology of TB and may offer new avenues for TB diagnosis.

Analysis of Phytochemical Constituents of Zuogui Wan in Rat Serum and its Effects on Early Embryonic Development of Mice

Objective:Zuogui Wan(ZGW)has been used as a typical prescription for tonifying kidney essence in traditional Chinese medicine.The objective of this study is to elucidate the phytochemical constituents of ZGW-treated rat serum(ZGWRS)using ultra-performance liquid chromatography-electrospray ionization/quadrupole-time-of-flight high-definition mass spectrometry(UPLC-ESI-Q-TOF-MS).Methods:ZGW was administered to rats,and the phytochemical constituents in rat serum were determined using UPLC-ESI-Q-TOF-MS.MetaboLynx analysis in negative ion mode was adopted to characterize the chemical constituents of ZGWRS.Orthogonal partial least squares discriminant analysis was applied for the discovery of constituents of ZGW that entered the serum of rats.The fertilized eggs collected from the same experiment were randomly divided into four groups,including the normal,40 mmol/L glucose,40 mmol/L glucose 5%control rat serum,and 40 mmol/L glucose 5%ZGWRS groups.They were cultivated at 37°C and 5%CO2 in a saturated humidity CO2 incubator.The blastocyst rate and two-cell rate were used to evaluate the effects of ZGWRS on embryonic development.Results:Thirteen constituents were identified in the ZGWRS,among which sweroside,loganin,morroniside,loganic acid,and 8-epiloganic acid were from Fructus Corni(Shan Zhu Yu).5-Hydroxymethyl-2-furfural-glucuronide,2-H-5-hydroxymethyl-2-furfural-glucuronide,3-hydroxy-2,6,6-trimethyl-1-cyclohexene-1-carboxylic acid,andβ-D-ribofuranuronic acid methyl ester triacetate were from Radix Rehmanniae Preparata(Shu Di Huang).Coumaric acid was from Fructus Lycii(Gou Qi Zi).Kaempferol-3-beta-O-glucuronide and cuscutamine were from Semen Cuscutae(Tu Si Zi).The embryonic development was significantly inhibited using 40 mmol/L glucose.Compared with the normal group,the blastocyst rate of the glucose group was decreased.The blastocyst rate of the 40 mmol/L glucose 5%ZGWRS group was significantly higher than that of the glucose group,indicating that ZGWRS negates the effect of glucose on mouse embryonic development.Conclusion:The results verified that a rapid and robust UPLC-ESI-Q-TOF-MS-based platform had been successful for identifying multiple constituents of ZGW.ZGWRS is rich in active constituents of iridoid glycosides.The results of this study also showed that ZGWRS could negate the effect of glucose on mouse embryonic development.

Climate change and its effect on reference crop evapotranspiration in central and western Inner Mongolia during 1961-2009

Water resource is one of the major constraints to agricultural production in central and western Inner Mongolia, where are characteristic by arid and semi-arid climate. Reference crop evapotranspiration （ETo） is an important part of water cycle in agricultural ecosystem, which has a direct effect on crop growth and yield. The implications of climate change on ETo are of high importance for agriculture regarding water management and irrigation scheduling. The aim of this study was to analyze the variations in climate and its effect on ETo in central and western Inner Mongolia over the period 1961 to 2009 For this purpose, data in ten meteorological stations across study area were collected and the FAO Penman-Monteith 56 method was used. Results showed that the average temperature, maximum temperature and minimum temperature increased by 0.49~C, 0.31~C and 0.70~C per decade during 1961-2009, respectively. In comparison, the daily temperature range decreased by 0.38~C per decade. The air relative humidity, sunshine hour, and 10-m wind speed decreased generally by 0.58%, 40.11 h, and 0.35 rrds per decade, respectively. Annual mean ETo decreased significantly at a rate of 12.2 mm per decade over the periods, this was mainly due to the decrease in wind speed in the study area. The decrease in wind speed may balance the effect of the increase in air temperature on ETo. Variations in spatial distribution of ETo and its main controlling factor were also detected among ten stations. Our results suggested that spatial and temporal distribution of ETo should be considered regarding the optimization of water resource management for agriculture in central and western Inner Mongolia under foreseen climate change.